Methods and systems for predicting treatment outcomes, patient selection and individualized therapy using patient response characteristics to sensory stimuli - Patent Application 20070123333

Abstract

In some aspects, the present disclosure describes a method for predicting a subject's expected treatment outcome, the method comprising administering a gamma oscillation-inducing non-invasive sensory stimulation to the subject, measuring a response from the subject, and predicting the subject's expected treatment outcome based at least in part on the measured response using a machine learning algorithm. In some aspects, the present disclosure also provides a method for individualizing gamma therapy treatment by adjusting parameters associated with the gamma oscillation-inducing non-invasive sensory stimulation based on the subject's response to the gamma oscillation-inducing non-invasive sensory stimulation.

Description

[Technical Field]

[0001] cross reference This application is a continuation of U.S. Provisional Application No. 63 / 321,301, filed March 18, 2022, which is incorporated herein by reference in its entirety.

[0002] Incorporation by Reference Each patent, publication, and non-patent document cited in this application is incorporated herein by reference in its entirety, as if each were individually incorporated by reference. [Background technology]

[0003] Neural oscillations occur in humans or animals and involve rhythmic or repetitive neural activity in the central nervous system. Neural tissue can generate oscillatory activity through mechanisms within individual neurons or through interactions between neurons. Oscillations can manifest as oscillations in membrane potentials or rhythmic patterns of action potentials, which can lead to oscillatory activation of postsynaptic neurons. The synchronized activity of a group of neurons can generate macroscopic oscillations that can be observed noninvasively by electroencephalography (EEG). Neural oscillations can be characterized by their frequency, amplitude, and phase. These signal characteristics can be studied in the time and / or frequency domains to provide information about underlying brain dynamics. Neural oscillations can be externally induced by stimuli or drugs, and the characteristics of a subject's EEG response to stimuli or drugs can also provide information about underlying brain dynamics and, therefore, about the subject's disease.

[0004] Neurological diseases affecting the nervous systems of humans and animals can be difficult to diagnose, evaluate, and treat due to delayed onset of symptoms, frequent overlap or similar symptoms between diseases, lack of accurate quantitative biomarker-based assays, or long presymptomatic and prodromal periods. Summary of the Invention

[0005] In some aspects, the present disclosure discloses a method of predicting the likelihood that a subject will benefit from a treatment, the method comprising: (a) administering neural oscillation-inducing non-invasive sensory stimulation to the subject; and (b) measuring a response from the subject; and (c) predicting a likelihood of an expected treatment outcome for the subject using a statistical algorithm, a machine learning algorithm, or a combination thereof, wherein the prediction is based at least in part on the measurement of the response from the subject, and the expected treatment outcome comprises reducing neurodegeneration, slowing neurodegeneration, reducing or preventing brain atrophy due to aging or neurodegeneration, slowing brain atrophy due to aging or neurodegeneration, improving symptoms of neurodegeneration, slowing cognitive decline and decline in functional ability, improving cognitive function, improving functional ability, improving symptoms of neurological and psychiatric disorders, or a combination thereof.

[0006] In any embodiment of the present disclosure, the gamma oscillation-inducing non-invasive sensory stimulation comprises periodic stimulation. In some embodiments, the periodic stimulation comprises a frequency component between about 20 Hz and about 160 Hz. In some embodiments, the periodic stimulation comprises a frequency component between about 25 Hz and about 80 Hz. In some embodiments, the periodic stimulation comprises a frequency component between about 30 Hz and about 50 Hz. In some embodiments, the periodic stimulation comprises a frequency component between about 35 Hz and about 45 Hz. In some embodiments, the periodic stimulation comprises a frequency component of about 45 Hz. In some embodiments, the periodic stimulation is intermittent. In some embodiments, the non-invasive sensory stimulation further comprises a non-periodic component.

[0007] In some embodiments, the gamma oscillation-inducing non-invasive sensory stimulus is a visual stimulus, an auditory stimulus, a kinesthetic stimulus, or any combination thereof.

[0008] In some embodiments, the subject has been diagnosed with or is at risk of developing a neurodegenerative disorder associated with cognitive decline.

[0009] In some embodiments, the neurodegenerative disorder comprises supranuclear palsy (PSP).

[0010] In some embodiments, the neurodegenerative disorder is a prion disease or a transmissible spongiform encephalopathy.

[0011] In some embodiments, the neurodegenerative disorder is Alzheimer's disease, Creutzfeldt-Jakob disease (CJD), variant CJD, Gerstmann-Straussler-Scheinker syndrome, fatal familial insomnia, kuru, or any combination thereof.

[0012] In some embodiments, the subject has been diagnosed with or is at risk for developing behavioral and psychological symptoms of dementia (BPSD).

[0013] In some embodiments, the subject has been diagnosed with or is at risk of developing a mood disorder, apathy, agitation, depression, bipolar disorder, anxiety, addiction, neurosis, anorexia, bulimia, dementia, mild cognitive impairment, subjective cognitive decline, dementia with Lewy bodies, Parkinson's disease, sleep fragmentation, schizophrenia, or any combination thereof.

[0014] In some embodiments, the expected outcome of treatment is a reduction in the frequency, duration, or severity of symptoms associated with a psychiatric or neurological disorder, hi certain embodiments, the symptoms are symptoms associated with bipolar disorder or schizophrenia.

[0015] In some embodiments, the subject is undergoing treatment for or has been diagnosed with a neurodegenerative disorder.

[0016] In some embodiments, the response is measured using an electroencephalogram (EEG).

[0017] In some embodiments, the EEG measures at least EEG coherence.

[0018] In some embodiments, EEG coherence is correlated with a measure of clinical outcome in the subject.

[0019] In some embodiments, EEG coherence is correlated with multiple measures of clinical outcome in a subject.

[0020] In some embodiments, the scale comprises the Mini-Mental State Examination (MMSE), the Alzheimer's Disease Assessment Scale (ADAS-Cog), the Clinical Dementia Rating Scale (CDR), the Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), the Neuropsychiatric Inventory (NPI), Positron Emission Tomography (PET), or Magnetic Resonance Imaging (MRI) volumetric data assessment. In some embodiments, the scale comprises multiple scales. In some embodiments, the scale comprises a composite scale. In some embodiments, the scale comprises a weighted composite scale, an unweighted composite scale, or a combination thereof. In some embodiments, the scale is mapped using a global statistical test. In some embodiments, the scale comprises a composite scale, a weighted scale, a global statistical test, or a z-score based on one or more scales.

[0021] In some embodiments, the gamma oscillation-inducing non-invasive sensory stimulation is administered continuously for a predetermined period of time, which in some embodiments is between 10 minutes and 2 hours.

[0022] In some embodiments, the gamma oscillation-inducing non-invasive sensory stimulation is administered over multiple discrete periods of time. In some embodiments, the multiple discrete periods of time occur at least once daily. In some embodiments, the multiple discrete periods of time occur at least once every two days. In some embodiments, the multiple discrete periods of time occur at least once weekly. In some embodiments, the multiple discrete periods of time occur at least once every two weeks. In some embodiments, the multiple discrete periods of time occur at least once monthly. In some embodiments, the multiple discrete periods of time occur at least once every other month.

[0023] Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least two days. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least one week. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least two weeks. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least one month. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least three months. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least six months. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least one year. Alternatively or additionally, in some embodiments, the plurality of discrete time periods spans at least five years.

[0024] In some embodiments, the method further comprises selecting the subject as a patient who may benefit from administration of gamma oscillation-induced non-invasive sensory stimulation therapy based at least in part on the expected treatment outcome. In some embodiments, the method further comprises selecting the subject as a patient who is unlikely to benefit from administration of gamma oscillation-induced non-invasive sensory stimulation therapy based at least in part on the expected treatment outcome.

[0025] In some embodiments, the method further includes selecting the subject as a patient for a treatment regimen based at least in part on the expected treatment outcome, hi some embodiments, the treatment regimen is a gamma oscillation-inducing non-invasive sensory stimulation treatment regimen.

[0026] In some embodiments, the machine learning algorithm comprises a neural network, a deep learning algorithm, an ensemble, regularization, a rule system, regression, Bayesian analysis, a decision tree, dimensionality reduction, an example-based algorithm, or a clustering algorithm.

[0027] In some embodiments, the method further comprises predicting an expected treatment outcome for the subject using the subject's network information.

[0028] In some embodiments, the method further comprises predicting an expected treatment outcome for the subject using the subject's biometric data.

[0029] In some embodiments, the biometric data is sleep data.

[0030] In some embodiments, the anticipated treatment outcome is a treatment outcome in sleep fragmentation.

[0031] In some embodiments, the expected treatment outcome comprises a reduction in age-related brain atrophy.

[0032] In some embodiments, the expected treatment outcome includes slowing of age-related brain atrophy.

[0033] In some embodiments, the expected treatment outcome comprises a reduction in neurodegeneration. In some embodiments, the reduction in neurodegeneration comprises a reduction in atrophy of the nervous system. In certain embodiments, the reduction in atrophy of the nervous system comprises a reduction in brain atrophy. In certain embodiments, the reduction in atrophy of the nervous system comprises a reduction in atrophy of the peripheral nervous system.

[0034] In some embodiments, the expected treatment outcome comprises a slowing of neurodegeneration. In some specific embodiments, the slowing of neurodegeneration comprises a slowing of the rate of atrophy of the nervous system. In some more specific embodiments, the slowing of the rate of atrophy of the nervous system comprises a slowing of the rate of brain atrophy. In some more specific embodiments, the slowing of the rate of atrophy of the nervous system comprises a slowing of the rate of atrophy of the peripheral nervous system.

[0035] In some embodiments, the expected treatment outcome comprises an improvement in a symptom of neurodegeneration, hi some embodiments, the improvement in a symptom of neurodegeneration comprises improved sleep, improved cognition, improved memory, improved muscle control, improved balance, improved breathing, improved cardiac function, or a combination thereof.

[0036] In some aspects, the present disclosure discloses a method for identifying a biomarker associated with a discrete clinical outcome, the method comprising: training a machine learning algorithm to identify a statistical relationship between (i) a first dataset comprising a plurality of response measures of a plurality of subjects, the plurality of response measures comprising responses of each subject in the plurality of subjects to a gamma oscillation-inducing non-invasive sensory stimulus; and (ii) a second dataset comprising a plurality of clinical measures of the plurality of subjects; and identifying, using the statistical or machine learning algorithm, the biomarker associated with the discrete clinical outcome.

[0037] In some embodiments, the plurality of response measurements comprises a plurality of bioelectric measurements.

[0038] In some embodiments, the plurality of bioelectrical measurements are a plurality of electroencephalogram (EEG) measurements.

[0039] In some embodiments, the biomarker is a signal pattern in multiple response measurements.

[0040] In some embodiments, the one or more measures of clinical outcome include a Mini-Mental State Examination (MMSE), a Clinical Dementia Rating Scale (CDR), an Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), a Neuropsychiatric Inventory (NPI), a positron emission tomography (PET), or a magnetic resonance imaging (MRI) volumetric data assessment. In some embodiments, the one or more measures of clinical outcome include a measure of daily activities, activity level, apathy measure, actigraphy, or a measure of sleep quality.

[0041] In some aspects, the present disclosure discloses a computer-implemented method of predicting response to treatment in a subject diagnosed with or at risk of developing a neurodegenerative disorder associated with cognitive decline, the computer-implemented method comprising: providing a gamma oscillation-inducing visual stimulus to the subject; and performing electroencephalography on a brain region of the subject to measure a plurality of bioelectrical signals.

[0042] In some embodiments, the gamma oscillation-inducing visual stimulus comprises a periodic stimulus. In some embodiments, the periodic stimulus comprises a frequency component of about 20 Hz to about 160 Hz. In some embodiments, the periodic stimulus comprises a frequency component of about 25 Hz to about 80 Hz. In some embodiments, the periodic stimulus comprises a frequency component of about 30 Hz to about 50 Hz. In some embodiments, the periodic stimulus comprises a frequency component of about 35 Hz to about 45 Hz. In some embodiments, the periodic stimulus comprises a frequency component of about 45 Hz. In some embodiments, the periodic stimulus is intermittent. In some embodiments, the visual stimulus further comprises a non-periodic component.

[0043] In some embodiments, the gamma oscillation-inducing visual stimulus is provided using a display device.

[0044] In some aspects, the present disclosure discloses a method of administering a treatment to a subject diagnosed with Alzheimer's disease and calculating an expected clinical outcome score for the treatment, the computer-implemented method comprising: administering a therapeutic dose of gamma oscillation-inducing non-invasive sensory stimulation to the subject's brain; performing electroencephalography on the subject's brain to measure a plurality of bioelectric signals; calculating an expected clinical outcome score for the subject based on the plurality of bioelectric signals using a statistical or machine learning algorithm; and adjusting the treatment dose based at least in part on the expected clinical outcome score.

[0045] In some embodiments, adjusting the therapeutic dose comprises adjusting parameters of the gamma oscillation-induced non-invasive sensory stimulation. In certain embodiments, adjusting parameters of the gamma oscillation-induced non-invasive sensory stimulation comprises adjusting the duration, frequency, wavelength, duty cycle, phase, amplitude, intensity, spectrum, envelope, inter-stimulus interval, harmonic structure, modulation, or waveform of the stimulation. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a square wave stimulus. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a sine wave stimulus. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a noise stimulus. In some more specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a white noise stimulus. In some more specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a pink noise stimulus. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a chirp stimulus. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of an O-chirp stimulus. In some specific embodiments, adjusting the therapeutic dose comprises adjusting parameters of a click stimulus.

[0046] The present disclosure further provides a method for selecting a patient population responsive to gamma oscillation-inducing non-invasive sensory stimulation, the method comprising: (a) administering gamma oscillation-inducing non-invasive sensory stimulation to subjects of the patient population; (b) measuring responses from the subjects; and (c) predicting an expected treatment outcome for the patient population based at least in part on the measurement of (b) using a statistical algorithm, a machine learning algorithm, or a combination thereof. In some embodiments, the expected treatment outcome comprises a reduction in neurodegeneration, a slowing of neurodegeneration, an improvement in symptoms of neurodegeneration, or a combination thereof.

[0047] Also provided herein is a method for identifying preferred parameter settings for gamma oscillation-induced non-invasive sensory stimulation therapy, the method comprising: (a) administering gamma oscillation-induced non-invasive sensory stimulation to a subject of a patient population; (b) measuring a response from the subject; and (c) modifying parameters of the gamma oscillation-induced non-invasive sensory stimulation, wherein the parameters of the gamma oscillation-induced non-invasive sensory stimulation are modified at least in part based on the measurement of (b), thereby identifying and modifying preferred parameter settings for the gamma oscillation-induced non-invasive sensory stimulation therapy.

[0048] Further provided is a method for selecting parameters that function as a placebo for a treatment using gamma oscillation-inducing non-invasive sensory stimulation, the method comprising: (a) administering the stimulation to a subject in a patient population; (b) measuring a response from the subject; (c) modifying one or more parameters of the stimulation to reduce the response from the subject; and (d) repeating (a)-(c) until the response from the subject is minimized, thereby selecting parameters that function as a placebo for the treatment using gamma oscillation-inducing non-invasive sensory stimulation.

[0049] In some embodiments, the parameter of the stimulation comprises multiple parameters of the stimulation.

[0050] The present disclosure also provides systems and methods for selecting a brain region to target for treatment, the systems including: (a) administering non-invasive sensory stimulation to a subject in a patient population; (b) performing electroencephalography (EEG) on the subject's brain to measure a plurality of bioelectric signals; and (c) selecting a brain region to target for treatment based on the plurality of bioelectric signals. In some cases, the brain region includes multiple brain regions.

[0051] In some cases, a brain region has reduced amplitude of neural oscillations compared to another brain region. In some cases, a brain region has reduced coherence of neural oscillations compared to another brain region.

[0052] The present disclosure further provides a method for determining a unified clinical outcome for the progression of a disease or disorder, the method comprising: (a) administering gamma oscillation-inducing non-invasive sensory stimulation to a plurality of individuals; (b) measuring one or more biological responses of the plurality of individuals to gamma oscillations, wherein the one or more biological responses are associated with the progression of the disease or disorder; (c) normalizing values ​​corresponding to the one or more biological responses, thereby generating normalized data points; and (d) using the normalized data points to determine principal components of the data points.

[0053] In some embodiments, the biological response comprises multiple biological responses.

[0054] In some embodiments, the brain region comprises multiple brain regions.

[0055] Also provided herein is a method including: (a) administering gamma oscillation-inducing non-invasive sensory stimulation to a plurality of individuals; (b) measuring the responses of the plurality of individuals to the gamma oscillation-inducing non-invasive sensory stimulation using electroencephalography; (c) dividing the plurality of individuals into groups based on identified shared characteristics; and (d) preparing a dataset for each group of the plurality of individuals.

[0056] In some cases, the method further includes (e) administering a gamma oscillation-inducing non-invasive sensory stimulus to the subject; (f) characterizing the subject's response to the gamma oscillation-inducing non-invasive sensory stimulus based on the dataset for each group of the plurality of individuals; and (g) diagnosing the subject based on the dataset.

[0057] The present disclosure further provides a method for identifying stimulation parameters that target an aspect of a disease, the method comprising: (a) administering gamma oscillation-inducing non-invasive sensory stimulation to a plurality of individuals; (b) measuring the biological responses of the plurality of individuals to the gamma oscillation-inducing non-invasive sensory stimulation; (c) evaluating the biological responses of the plurality of individuals using a machine-based algorithm; and (d) adjusting one or more parameters of the gamma oscillation-inducing non-invasive sensory stimulation and repeating steps (a) to (c) to identify stimulation parameters that target an aspect of the disease.

[0058] In some embodiments, the disease aspect comprises multiple aspects.

[0059] In some embodiments, the disease is a neurological disorder associated with cognitive decline. In certain embodiments, the neurodegenerative disorder comprises supranuclear palsy (PSP). In certain embodiments, the neurodegenerative disorder is a prion disease or a transmissible spongiform encephalopathy. In certain embodiments, the neurodegenerative disorder is Alzheimer's disease, Creutzfeldt-Jakob disease (CJD), variant CJD, Gerstmann-Straussler-Scheinker syndrome, fatal familial insomnia, kuru, or any combination thereof. In certain embodiments, the subject has been diagnosed with or is at risk for developing behavioral and psychological symptoms of dementia (BPSD).

[0060] In some embodiments, the subject has been diagnosed with or is at risk of developing a mood disorder, apathy, agitation, depression, bipolar disorder, anxiety, addiction, neurosis, anorexia, bulimia, dementia, mild cognitive impairment, subjective cognitive decline, dementia with Lewy bodies, Parkinson's disease, sleep fragmentation, schizophrenia, or any combination thereof.

[0061] Further provided is a non-transitory computer-readable storage medium encoded with instructions executable by one or more processors, the instructions performing any one of the methods or computer-implemented methods disclosed herein. Also provided is a computer-implemented system including at least one processor and at least one digital processing device containing instructions executable by the at least one processor, the instructions performing any one of the methods or computer-implemented methods disclosed herein. [Brief explanation of the drawings]

[0062] [Figure 1] FIG. 1 is a block diagram illustrating a system for neurostimulation via visual stimulation, according to one embodiment. [Figure 2A] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 2B] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 2C] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 2D] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 2E] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 2F] 1 illustrates a visual stimulation signal generating neural stimulation, according to some embodiments. [Figure 3A] 1 illustrates a field of view in which visual signals can be transmitted for visually stimulated induction of gamma oscillations in the brain, according to some embodiments. [Figure 3B] 1 illustrates a field of view in which visual signals can be transmitted for visually stimulated induction of gamma oscillations in the brain, according to some embodiments. [Figure 3C]1 illustrates a field of view in which visual signals can be transmitted for visually stimulated induction of gamma oscillations in the brain, according to some embodiments. [Figure 4A] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 4B] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 4C] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 5A] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 5B] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 5C] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 5D] 1 illustrates a device configured to transmit a visual signal for neural stimulation, according to some embodiments. [Figure 6A] 1 illustrates a device configured to receive feedback to facilitate neural stimulation, according to some embodiments. [Figure 6B] 1 illustrates a device configured to receive feedback to facilitate neural stimulation, according to some embodiments. [Figure 7A] FIG. 1 is a block diagram illustrating an embodiment of a computing device useful in connection with the systems and methods described herein. [Figure 7B] FIG. 1 is a block diagram illustrating an embodiment of a computing device useful in connection with the systems and methods described herein. [Figure 8] FIG. 1 is a flow diagram of a method for performing neurostimulation using visual stimulation, according to one embodiment. [Figure 9]FIG. 1 is a block diagram illustrating a system for neural stimulation via auditory stimulation, according to one embodiment. [Figure 10A] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10B] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10C] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10D] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10E] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10F] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10G] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10H] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 10I] 1 illustrates an audio signal and the type of modulation used to induce neural oscillations through auditory stimulation, according to some embodiments. [Figure 11A] 1 illustrates an audio signal generated using binaural beats, according to one embodiment. [Figure 11B] 1 illustrates an acoustic pulse with isochronic tones, according to one embodiment. [Figure 11C]1 illustrates an audio signal with a modulation technique including an acoustic filter, according to one embodiment. [Figure 12A] 1 illustrates a system configuration for neural stimulation via auditory stimulation, according to some embodiments. [Figure 12B] 1 illustrates a system configuration for neural stimulation via auditory stimulation, according to some embodiments. [Figure 12C] 1 illustrates a system configuration for neural stimulation via auditory stimulation, according to some embodiments. [Figure 13] 1 illustrates the configuration of a room-based auditory stimulation system for neural stimulation, according to one embodiment. [Figure 14] 1 illustrates a device configured to receive feedback to facilitate neural stimulation by auditory stimulation, according to some embodiments. [Figure 15] FIG. 1 is a flow diagram of a method for auditory induction of gamma oscillations in the brain, according to one embodiment. [Figure 16A] FIG. 1 is a block diagram illustrating a system for nerve stimulation with peripheral nerve stimulation, according to one embodiment. [Figure 16B] FIG. 1 is a block diagram illustrating a system for neural stimulation with multiple stimulation modes, according to one embodiment. [Figure 17A] FIG. 1 is a block diagram illustrating a system for neurostimulation with visual and auditory stimuli, according to one embodiment. [Figure 17B] FIG. 1 depicts waveforms used for neural stimulation with visual and auditory stimuli, according to one embodiment. [Figure 18] FIG. 1 is a flow diagram of a method for neurostimulation with visual and auditory stimuli, according to one embodiment. [Figure 19] FIG. 11 is an efficacy summary chart for the modified intention-to-treat (mITT) population, including p-values, differences, confidence intervals (CIs), and standardized estimates of efficacy based on these values. [Figure 20]Individual mean analyses of Alzheimer's Disease Composite Score (ADCOMS) optimized for mild and moderate Alzheimer's disease (MADCOMS) for the sham and active treatment groups are shown on the left, and linear model analyses are shown on the right. [Figure 21] Individual mean analyses of Alzheimer's Disease Assessment Scale-Cognitive Subscale 14 (ADAS-Cog 14) values ​​for the sham control and active treatment groups are shown on the left, and linear model analyses are shown on the right. [Figure 22] Individual mean analyses of Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) values ​​for the sham control and active treatment groups are shown on the left, and linear model analyses are shown on the right. [Figure 23] Individual mean analyses of Alzheimer's Disease Cooperative Study-Activities of Daily Living Scale (ADCS-ADL) scores for the sham control and active treatment groups are shown on the left, and linear model analyses are shown on the right. [Figure 24] Linear model analysis of Mini-Mental State Examination (MMSE) scores measured 6 months after treatment (ie, final time point) is shown. [Figure 25] Linear model analysis of magnetic resonance imaging (MRI) results for whole brain volume (left) and hippocampal volume (right) after 6 months of treatment. [Figure 26] 1 is a table depicting a summary of efficacy findings from human clinical trials, including p-values, treatment differences, CI values, and rates of deceleration of brain atrophy. [Figure 27] Panels a and b show graphs depicting the observed improvement in sleep quality, as measured by a reduction in sleep fragmentation, represented by more frequent and longer periods of rest, over the course of 24 weeks of exemplary gamma oscillation-inducing noninvasive sensory stimulation treatment in subjects with mild to moderate AD, during the first 12-week treatment period (indicated by the line closest to the white arrow) and the second 12-week treatment period (indicated by the line farthest from the white arrow). Panels c and d depict the observed effect of a sham treatment on sleep quality, as measured by a reduction in sleep fragmentation. [Figure 28]Figure 1 shows the change in power values ​​in response to 40 Hz LED stimulation (for 1 hour) in an exemplary embodiment showing 40 Hz steady-state oscillations and enhanced alpha power values ​​during and after stimulation in a young, healthy subject. Both panels illustrate time-frequency domain decomposition of EEG activity recorded over the occipital pole (Oz, channel 64) before, during, and after gamma-stimulation-induced 40 Hz stimulation. The onset and offset of 40 Hz stimulation are indicated by the STIM ON and STIM OFF borders in both panels. The top panel illustrates enhanced 40 Hz power values ​​during stimulation, representing steady-state visual evoked potentials (SSVEPs). The bottom panel shows alpha power dynamics during eyes-open (EYO) and eyes-closed (EYC) states, as well as enhanced alpha power values ​​both during eyes-open 40 Hz stimulation and after 1 hour of gamma oscillation-induced 40 Hz stimulation. [Figure 29] Figure 1 provides a diagram of the composite global cognitive summary score as a function of mean sleep fragmentation (Panel A) and the combined expression of genes enriched in aging microglia (Panel B). Dashed lines indicate the 95% confidence interval of the estimate. [Figure 30] 1 provides oscilloscope captures of the visual signal (upper signal) and auditory signal (lower signal) of an exemplary non-invasive sensory stimulus with fs equal to 40 Hz, vd equal to 50%, VD equal to 50%, ft equal to 7,000 Hz, and AD equal to 0.57%. [Figure 31] 31 shows a schematic diagram of some aspects and parameters characterizing the audio and visual stimulus components of non-invasive stimuli delivered by the audio stimulus module (110, FIG. 33) and the visual stimulus module (120, FIG. 33), respectively, of the stimulus delivery system (170, FIG. 33). The number and relative dimensions of elements in FIG. 31 are adjusted for illustrative purposes and may not represent the number and relative dimensions of elements for an actual embodiment. [Figure 32]

[0023] Figure 1 depicts an overview of enrollment, treatment, and control for an exemplary embodiment of non-invasive stimulation to improve sleep quality in subjects with mild to moderate AD. Treatment was delivered using 40 Hz frequency audio in two-thirds of subjects (12) and at another frequency in one-third of subjects (6, "control"). [Figure 33] A block diagram of an exemplary stimulus delivery system and an analysis and monitoring system is provided, which includes modules specific to sleep-related monitoring and / or analysis. [Figure 34] Actigraphy data from 24-hour activity levels (gray bars, 1501 in FIG. 37 ) over two days for one example patient, centered at 12:00 AM (indicated by a double-sided arrow), are provided, along with a median filtering curve (depicted by a dashed arrow, 1507 in FIG. 37 ). The horizontal axis of FIG. 34 indicates time of day, and the vertical axis is relative activity (arbitrary logarithmic scale) recorded on the wrist-worn actigraphy measurement device. Calculated sleep periods (black horizontal lines, see 1508 in FIG. 37 ) are shown along with individual sample rest periods (yellow horizontal lines, see 1509 in FIG. 37 ), with the top panel (a) showing an exemplary pattern of frequent activity and short rest periods during sleep periods, and the bottom panel (b) showing an exemplary pattern of less frequent activity and long rest periods during sleep periods. [Figure 35] An exemplary pattern (arbitrary units, see FIG. 34) of actigraphy over several days is provided, showing actigraphy (gray, e.g., 1501 in FIG. 37) with a smooth curve superimposed. A cutoff line (black) separates active versus resting periods (e.g., 1505 in FIG. 37). The black square represents the initial estimate of the midnight time point (e.g., 1507 in FIG. 37). The final assessment of the midnight time point is determined by an optimization algorithm (e.g., 1508 in FIG. 37). [Figure 36]An exemplary cumulative distribution of rest periods (e.g., 1511 in FIG. 37) for one patient is shown. Data from a first exemplary 12-week treatment (solid dots, weeks 0-12) and data from a second exemplary 12-week treatment (dashed dots) are shown. In some embodiments, the distribution is characterized by an exponential distribution (e.g., 1512 in FIG. 37). In further embodiments, an increase in the exponential decay constant represents an improvement in sleep quality (e.g., 1513 in FIG. 37). In this example, tau2=45 minutes, tau1=40 minutes, and taudiff=5 minutes>0. [Figure 37] FIG. 37 provides a flow diagram of exemplary analysis steps responsive to actigraphy data, which, in some embodiments, are provided at least in part by actigraphy monitoring module 130 (FIG. 33). In some embodiments, the analysis aims to determine a cumulative distribution of rest periods for one or more subjects over the duration of one or more nocturnal sleep periods (1511). Further, in some embodiments, the analysis aims to fit an exponential distribution to the determined cumulative distribution (1512). Further, in some embodiments, the analysis aims to calculate summary statistics or feature parameters for the fitted exponential distribution. In an exemplary embodiment, an exponential decay constant for the fitted exponential distribution is determined (1512 in FIG. 36). In FIG. 37, italicized terms within parentheses refer to MATLAB® (R2020a) APIs used in the corresponding steps in the exemplary embodiment, e.g., "medfilt1" refers to 1-D median filtering. In some embodiments, alternative APIs, methods, or processes having equivalent functionality may be used (e.g., the Wolfram Language's "ButterworthFilterModel" may be used in place of "butter"). [Figure 38]Sample actigraphy recordings from one patient are provided demonstrating the effect of gamma oscillation-induced noninvasive sensory stimulation therapy on sleep through five consecutive nights of recordings taken before treatment and five consecutive nights of recordings taken after treatment. The dark gray horizontal bars below the x-axis indicate periods of continuous activity that are considered significantly higher in actigraphy recordings taken before treatment than in actigraphy recordings taken after treatment. [Figure 39] Figure 39 provides the cumulative distribution of nighttime rest and activity periods based on pooled data from all participants. Black squares indicate active periods, and gray squares indicate rest periods. Panel A of Figure 39 shows the cumulative distribution using a log-linear scale, and Panel B of Figure 39 shows the cumulative distribution using a log-log scale. [Figure 40] Figure 40 shows a graph comparing relative changes in activity duration, with the Y-axis representing the change from weeks 13-24 compared to weeks 1-12. Figure 40 illustrates a reduction in activity period duration in the treatment group, resulting in reduced sleep fragmentation and improved sleep quality. In contrast, the opposite effect was found in the sham group, represented by the line closest to the gray arrow. Panel A of Figure 40 shows the relative change based on activity period duration, while Panel B of Figure 40 shows normalized nighttime activity duration, calculated by dividing the duration of each activity period by the duration of the matching total nighttime period. [Figure 41] This figure shows the effect of gamma oscillation-induced non-invasive sensory stimulation on maintaining daytime activity, as assessed by the Activities of Daily Living (ADCS-ADL) scope. The graph shows that the change in daytime activity significantly improved in the treatment group and decreased in the sham group. The X-axis compares the period from 1 to 12 weeks with the period from 13 to 24 weeks. The Y-axis shows the change in ADCS-ADL score from 13 to 24 weeks compared to 1 to 12 weeks. [Figure 42]Flowchart showing the proposed relationship between Alzheimer's disease and sleep dysfunction. This diagram is adapted from Wang, C. and D.M. Holtzman (2020). "Bidirectional relationship between sleep and Alzheimer's disease: role of amyloid, tau, and other factors." Neuropsychopharmacology 45(1):104-120. [Figure 43] An exemplary embodiment of a handheld controller for adjusting parameters of stimulation delivered by an operably coupled stimulation device is provided. [Figure 44] Figure 1 shows the results of the change in material volume (%) from baseline for the treatment and control groups who received 40 Hz gamma vibration-induced sensory stimulation therapy and sham sensory stimulation therapy, respectively, for 6 months. Dark gray squares correspond to participants in the treatment group, and light gray squares correspond to participants in the placebo group. Error bars indicate standard error (SE). [Figure 45] Changes in white matter T1-weighted to T2-weighted (T1w / T2w) ratios (% change from baseline) are shown for placebo (light gray) and treatment (dark gray) participants after sham and 40 Hz gamma vibration sensory stimulation, respectively, over a 6-month period. [Figure 46A] Measures of volumetric changes in white matter structures are presented as percent changes compared to baseline. Participants in the treatment group are shown in dark gray, and results for participants in the placebo group are shown in light gray. Figure 46A provides results for the entorhinal region, left cingulate lobe, paratriangular region, cuneus region, lateral occipital region, posterior central region, left occipital lobe, left frontal lobe, left parietal lobe, occipital lobe, left temporal lobe, and caudal midfrontal region (sorted in ascending order by p-value) of the treatment group after 6 months of treatment. [Figure 46B]Measures of volumetric changes in white matter structures are presented as percent changes relative to baseline. Participants in the treatment group are shown in dark gray, and results for participants in the placebo group are shown in light gray. Figure 46B shows results for the precentral region, paracentral region, lingual region, fusiform region, frontal lobe, rostral anterior cingulate region, inferior temporal region, right occipital lobe, parietal lobe, rostral middle frontal lobe, precorneal region, medial orbitofrontal region, and temporal lobe (sorted in ascending order by p-value). [Figure 47A] The changes in T1w / T2w ratios (% change from baseline) of white matter structures in placebo and treatment participants after 6 months of sham and 40 Hz gamma oscillation-induced sensory stimulation therapy are provided in favor of the treatment group. Figure 47A provides results for the entorhinal region, pars triangularis region, posterior central region, left parietal lobe, lateral occipital region, paracentral region, rostral midfrontal region, supramarginal region, precentral region, parietal lobe, right occipital lobe, fusiform region, occipital lobe, left frontal lobe, cuneus region, precorneal region, inferior parietal region, frontal lobe, lingual region, left occipital lobe, left temporal lobe, right parietal lobe, and pars orbitalis region, with white matter structures sorted in ascending order by p-value. [Figure 47B] The changes in T1w / T2w ratios of white matter structures (% change from baseline) for placebo and treatment participants after 6 months of sham and 40 Hz gamma oscillation-induced sensory stimulation therapy, respectively, are provided in favor of the treatment group. Figure 47B shows results for the right frontal lobe, caudal midfrontal region, rostral anterior cingulate region, superior frontal region, temporal lobe, medial orbitofrontal region, posterior cingulate region, superior parietal region, left cingulate lobe, superior temporal region, cingulate lobe, and temporal pole region, with white matter structures sorted in ascending order by p-value. [Figure 48] This example shows a participant using a 40 Hz auditory and visual stimulation device over a 6-month period. The participant selected different visual and audio settings (rows 1 and 2 from the top) while simultaneously setting the device frequency to 40 Hz (row 3 from the top). The device recorded the date and time it was used (row 4 from the top). Independently, the participant recorded treatment time in a diary (row 5 from the top). This participant demonstrated near 100% adherence (bottom row). [Figure 49]Figure 1 shows the change in Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) score as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and ADAS-Cog score. [Figure 50] Figure 1 shows the change in Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) scores as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall positive correlation is observed between baseline coherence and ADCS-ADL. [Figure 51] Figure 1 shows the change in Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) (mindful engagement in conversation score) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall positive correlation is observed between baseline coherence and the ADCS-ADL and mindful engagement in conversation scores. [Figure 52] Figure 1 shows the change in Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL) (Finding Belongings) score as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall positive correlation is observed between baseline coherence and ADCS-ADL (Finding Belongings score). [Figure 53] Figure 1 shows the change in the Clinical Dementia Rating (CDR) scale (memory score) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and CDR (memory score) scores. [Figure 54] Figure 1 shows the change in the Clinical Dementia Rating (CDR) scale (orientation score) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and the CDR (orientation score) score. [Figure 55] Figure 1 shows the change in the Clinical Dementia Rating (CDR) scale (Sum of the Boxes (CDR SB) score) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and CDR(SB) score. [Figure 56] Figure 1 shows the change in Mini-Mental State Examination (MMSE) scores as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall positive correlation is observed between baseline coherence and MMSE scores. [Figure 57] Figure 1 shows the change in magnetic resonance imaging (MRI) lateral ventricle volume as a percentage of total intracranial volume (vMRI-LV as % of TIV) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and lateral ventricle (LV) volume. [Figure 58] Figure 1 shows the change in MRI temporal cortical thickness (mm) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall positive correlation is observed between baseline coherence and temporal cortical thickness. [Figure 59] Figure 1 shows the change in Neuropsychiatric Inventory Questionnaire (NPIQ) severity scores as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and NPIQ severity scores. [Figure 60] Figure 1 shows the change in positron emission tomography (PET) combined amyloid normalized uptake value ratio (SUVR) as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and PET combined SUVR. [Figure 61]Figure 1 shows the change in PET occipital amyloid SUVR as a function of baseline coherence after 6 months of active treatment with a 40 Hz auditory and visual stimulation device. An overall negative correlation is observed between baseline coherence and PET occipital SUVR.

[0063] The features and advantages of this solution will become apparent from the detailed description set forth below when taken in conjunction with the drawings in which like reference numerals generally refer to similar elements and in which: DETAILED DESCRIPTION OF THE INVENTION

[0064] Neurological diseases affecting the nervous systems of humans and animals can be difficult to diagnose, treat, and assess due to delayed onset of symptoms, frequent overlap or similar symptoms between diseases, lack of accurate quantitative biomarker-based assays, or long presymptomatic and prodromal phases.

[0065] Alzheimer's disease (AD) is an example of a neurological disorder in which many of these problems exist. AD can progress for years or even decades before symptoms appear. There are no widely available or recognized biomarker-based quantitative assays that provide diagnostic certainty for AD. Diagnosing AD requires a multifaceted analysis, including patient and family medical history, the patient's subjective symptom report, MRI, clinical testing, and evaluation by multiple medical professionals. AD is still considered to have a high rate of misdiagnosis (10%–20%). Part of the misdiagnosis may be due to various neurodegenerative or psychiatric disorders that are mistaken for AD.

[0066] Some neurodegenerative diseases, such as AD, are associated with long presymptomatic and prodromal stages, which can result in symptoms such as cognitive impairment, behavioral abnormalities, and impairment in activities of daily living. Symptoms resulting from neurodegenerative diseases can develop over a long period of time, and by the time they are detected, the underlying disease may have progressed significantly to a moderate or severe stage, with little hope of improvement. For example, the presymptomatic stage of Alzheimer's disease (before any physical symptoms appear) can last for years or even decades.

[0067] Even when early symptoms begin to appear, the disease may progress slowly, making the symptoms easily ignored or overlooked. There may be several stages of cognitive decline before the onset of clinical dementia. In some cases, one of the first stages may be subjective cognitive decline (SCD). SCD can refer to the self-reported experience of worsening or increasing frequency of confusion or forgetfulness. At this stage, individuals can be identified as "SCD+," referring to patients who have both cognitive complaints and AD-related pathological changes. In some cases, patients classified as "SCD+" may have characteristics that place them at high risk for further cognitive decline, such as subjective memory decline, onset of SCD within the past five years, age under 60 at the time of SCD onset, SCD-related concerns (worries), feelings of performing worse than others in their age group, or informant confirmation of cognitive decline. In some cases, the next stage of cognitive decline following SCD may be mild cognitive impairment (MCI), which is characterized by problems with memory, language, thinking, or judgment. In some cases, it can be difficult to separate out the subjective (eg, "self-report") element in the clinical assessment of AD diagnosis and monitoring of AD progression.

[0068] Prion diseases are another problematic neurological condition. Prion diseases, also known as transmissible spongiform encephalopathies, can refer to a group of fatal neurodegenerative disorders, including Creutzfeldt-Jakob disease (CJD), variant Creutzfeldt-Jakob disease (vCJD), Gerstmann-Straussler-Scheinker syndrome, fatal familial insomnia, and kuru. In some cases, prion diseases can present with symptoms similar to other diseases and / or AD. In some cases, different types of prion diseases can cause brain damage with similar characteristics, such as widespread spongiform degeneration, widespread neuronal loss, synaptic changes, atypical brain inflammation, and accumulation of protein aggregates. In some cases, prion diseases such as CJD, kuru, and Gerstmann-Straussler-Scheinker disease can form amyloid plaques similar to those observed in AD.

[0069] The present invention recognizes the need for quantitative assays to assess neurological diseases. For example, several resting-state EEG markers have been identified as potential biomarkers for monitoring the decline in the integrity of neuronal network activity in AD. EEG biomarkers are considered for detecting the stage of neurological disorders (e.g., pre-symptomatic AD or early AD) and for differentiating between neurological disorders (e.g., AD and prion diseases). The present invention recognizes that neurophysiological responses to gamma oscillation-inducing non-invasive sensory stimulation can predict clinical outcomes in subjects with AD or other neurological disorders.

[0070] In some aspects, the present disclosure describes systems and methods for stimulating at least a portion of a subject's brain region with gamma oscillation-inducing non-invasive sensory stimulation and measuring a response from the brain region. In some cases, the response may be used to differentiate between different neurological diseases, such as neurodegenerative disorders and psychiatric disorders. In some cases, the response may be used to differentiate between neurodegenerative disorders. In some cases, the response may be used to differentiate between psychiatric disorders.

[0071] In some cases, the response may be used to predict an expected treatment outcome. In some cases, the expected treatment outcome may be the rate of disease progression or survival. In some cases, the expected treatment outcome may be improved survival, slowing of disease progression, or recommendation of treatment. A variety of other possible treatment outcomes are disclosed herein.

[0072] In some aspects, the present disclosure describes a method for predicting a subject's expected treatment outcome. Optionally, the method includes administering a gamma oscillation-inducing non-invasive sensory stimulus to the subject. Optionally, the method includes measuring a response from the subject. Optionally, the method includes using a machine learning algorithm to predict the subject's expected treatment outcome based at least in part on the measured response.

[0073] In some embodiments, the present disclosure provides a method for generating multiple datasets based on the responses of multiple individuals, where the individuals are assigned to distinct populations based on shared characteristics. In some embodiments, the responses can be used to predict treatment responses for subjects with one or more of the shared characteristics. For example, the multiple datasets can include EEG response profiles to various stimuli. The distinct populations of individuals can include healthy controls. Another distinct population can include a group of subjects with neurological disorders. The responses of the subjects to gamma oscillation-inducing non-invasive sensory stimulation can be assessed and compared with the responses provided in the datasets. This comparison can reveal, for example, that the subjects are healthy individuals. Alternatively, this comparison can reveal that the subjects share a response characteristic associated with a particular disease or disorder. Thus, this comparison can be used to diagnose whether the subject has a disease or disorder.

[0074] In some aspects, the present disclosure describes a computer-implemented method for predicting a response to treatment in a subject diagnosed with or at risk of developing a neurodegenerative disorder associated with cognitive decline. In some cases, the computer-implemented method includes administering gamma oscillation-inducing non-invasive sensory visual stimulation to the subject. In some cases, the computer-implemented method includes performing electroencephalography on a brain region of the subject to measure a plurality of bioelectric signals.

[0075] In some aspects, the present disclosure describes a computer-implemented method for administering a treatment to a subject diagnosed with or at risk of developing Alzheimer's disease and calculating an expected clinical outcome score for the treatment. In some cases, the computer-implemented method includes administering a therapeutic dose of gamma oscillation-inducing non-invasive sensory stimulation to the subject's brain. In some cases, the computer-implemented method includes performing an electroencephalogram (EEG) on the subject's brain to measure a plurality of bioelectric signals. In some cases, the computer-implemented method includes using a machine learning algorithm to calculate the subject's expected clinical outcome score based on the plurality of bioelectric signals. In some cases, the computer-implemented method includes adjusting the treatment dose based at least in part on the expected clinical outcome score.

[0076] Predicting the expected treatment outcome may include using any one of a variety of methods, qualitative or quantitative. In some cases, the predicting step may include calculating one or more prediction scores using a computer program. In some cases, the prediction score may be a logical value, a categorical value, a probability value, or any combination thereof. In some cases, the predicting step may include comparing the prediction score to a predetermined threshold. In some cases, the predetermined threshold may be a value above which the expected treatment outcome is favorable for the subject. In some cases, the predetermined threshold may be a value below which the expected treatment outcome is unfavorable for the subject. In some cases, the predetermined threshold may be a value above which the expected treatment outcome is classified as a particular type of outcome. In some cases, the predetermined threshold may be a value below which the expected treatment outcome is not classified as a particular type of outcome. In some cases, the predicting step may include prediction by a medical professional.

[0077] Predicting the expected treatment outcome of subject can include predicting at various time points or time ranges in the future.In some cases, predicting the expected treatment outcome of subject can be at least 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes or 60 minutes in advance.In some cases, predicting the expected treatment outcome of subject can be at least 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours or 24 hours in advance. In some cases, the prediction of the subject's expected treatment outcome can be at least 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, or 7 days in advance. In some cases, the prediction of the subject's expected treatment outcome can be at least 1 week, 2 weeks, 3 weeks, or 4 weeks in advance. In some cases, the prediction of the subject's expected treatment outcome can be at least 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, or 12 months in advance. In some cases, the prediction of the subject's expected treatment outcome can be at least 1 year, 2 years, 3 years, 4 years, 5 years, 6 years, 7 years, 8 years, 9 years, or 10 years in advance. In some cases, the subject's expected treatment outcome can be predicted up to 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, or 60 minutes in advance. In some cases, the subject's expected treatment outcome can be predicted up to 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours, or 24 hours in advance.In some cases, the prediction of the subject's expected treatment outcome can be up to 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, or 7 days in advance. In some cases, the prediction of the subject's expected treatment outcome can be up to 1 week, 2 weeks, 3 weeks, or 4 weeks in advance. In some cases, the prediction of the subject's expected treatment outcome can be 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, or 12 months in advance. In some cases, the prediction of the subject's expected treatment outcome can be 1 year, 2 years, 3 years, 4 years, 5 years, 6 years, 7 years, 8 years, 9 years, or 10 years in advance. In some cases, the prediction of the subject's expected treatment outcome can be within a range formed by any combination of the above.

[0078] In some cases, the expected treatment outcome may be an outcome of gamma oscillation-inducing non-invasive sensory stimulation. The expected treatment outcome may be a likelihood of response to treatment. The treatment may be for any one of the diseases or disorders disclosed herein. In some cases, the treatment is for Creutzfeldt-Jakob disease (CJD), variant CJD, Gerstmann-Straussler-Scheinker syndrome, fatal familial insomnia, kuru, or any combination thereof. In some cases, the expected treatment outcome may be an episode associated with a psychiatric or neurological disorder. In some cases, the episode may be a bipolar episode or a schizophrenic episode.

[0079] In some cases, the treatment is for microglia-mediated diseases or disorders.Microglia-mediated diseases or disorders may include tauopathy-related neurodegenerative diseases, including but not limited to Alzheimer's disease, frontotemporal dementia, chronic traumatic encephalopathy (CTE) and corticobasal degeneration.In some cases, the subject may have hereditary ataxia.Hereditary ataxia often causes cerebellar atrophy as a result of the circuit and dysfunction of the cerebellar cortex, which is the result of the neurodegeneration of the cellular afferents and Purkinje cells with long axonal projections, which comprise the only source of output from the cerebellar cortex to the deep cerebellar nuclei.

[0080] In some cases, the treatment is for neuropsychiatric disorders associated with microglial cell-mediated brain atrophy. For example, individuals with schizophrenia often show a decrease in cortical tissue after death. This phenomenon is caused by synaptic pruning and reflects abnormalities in microglia-like cells and synaptic function. In other embodiments, the present disclosure provides methods and systems for alleviating symptoms of depression. Stress, impaired neurogenesis, and defective synaptic plasticity are associated with depression. Chronic stress promotes microglial hyperbranching and astroglial atrophy. Therefore, in some embodiments, the disclosed systems and methods can alleviate symptoms associated with chronic stress or depression by improving synaptic plasticity and stimulating neural networks, along with improving microglia-mediated clearance.

[0081] In some cases, the treatment is for symptoms related to stroke. For example, the stroke may be an ischemic stroke, which causes a neuroinflammatory response and activates microglia to help repair the brain. Ischemic stroke is associated with the loss of synaptic activity. As a result, the brain tissue within the penumbra during ischemic stroke is structurally intact but functionally asymptomatic.

[0082] In some cases, treatment is for demyelinating diseases. Demyelinating diseases can include multiple sclerosis or acute disseminated encephalomyelitis, both of which can cause neuroinflammation and brain atrophy. In multiple sclerosis (MS), brain atrophy is common due to demyelination and destruction of nerve cells. As a result of multiple attacks over time, widespread myelin damage occurs, damaging the brain's myelin-rich white matter. In acute disseminated encephalomyelitis, similar symptoms are seen, but the onset of widespread myelin damage is due to a single episode or attack.

[0083] The outcome can be any one of a variety of clinically relevant outcomes. In some cases, the outcome can be survival. In some cases, the outcome can be extended survival. In some cases, the outcome can be an improvement in symptoms associated with a disease or disorder, such as a neurodegenerative disease. For example, in some cases, the outcome includes an improvement in behavioral and psychological symptoms of dementia (BPSD). For example, symptoms associated with a disease or disorder can include apathy, anxiety, or depression. In some cases, the outcome can include an improved quality of life. In some cases, the outcome can be an improvement in a pathological process, such as improved sleep. In some cases, the outcome can include a decreased quality of life. In some cases, the outcome can be a cure. In some cases, the outcome can be no cure. In some cases, the outcome can be an improvement in cognitive function. In some cases, the outcome can be a deterioration in cognitive function. In some cases, the outcome can be an improvement in memory. In some cases, the outcome can be a deterioration in memory. In some cases, the outcome can be well-being. In some cases, the outcome can be depression. In some cases, the outcome can be death. The outcome may be a quantitatively or qualitatively measurable or determinable value or state for any of the aforementioned examples of clinically relevant outcomes. In some cases, the outcome may be a quantitative or qualitative assessment that can be performed by a medical professional. In some cases, the outcome may be a self-assessment by the subject, a patient report, or a partner report made about the subject. In some cases, the outcome may be the outcome of a sleep fragmentation treatment. In some cases, the outcome may be a quantitative or qualitative assessment that can be performed by a device or computer.

[0084] The subject may be any animal having a nervous system. In some cases, the subject may be a mammal. In some cases, the subject may be a human. The subjects may vary in age, gender, sex, height, weight, or any other clinically relevant biometric.

[0085] The subject may be diagnosed with, suspected of having, or at risk of having any one of the diseases disclosed herein. In some cases, the disease may be a neurodegenerative disorder associated with cognitive decline. In some cases, the subject may have, be suspected of having, or be at risk of having a prion disease or transmissible spongiform encephalopathy. In some cases, the subject may have, be suspected of having, or be at risk of having Alzheimer's disease, Creutzfeldt-Jakob disease (CJD), variant CJD, Gerstmann-Streissler-Scheinker syndrome, fatal familial insomnia, Kuru, or any combination thereof. In some cases, the disease is a psychiatric or neurological disorder associated with cognitive decline. In some cases, the psychiatric or neurological disorder is a mood disorder, depression, bipolar disorder, anxiety, addiction, neurosis, anorexia, bulimia, dementia, mild cognitive impairment, subjective cognitive decline, dementia with Lewy bodies, Parkinson's disease, sleep fragmentation, schizophrenia, or any combination thereof.

[0086] In some cases, administration may be a non-invasive procedure. In some cases, administration may be indirect (e.g., without physical contact) stimulation of the optic nerve. In some cases, administration may use light. In some cases, administration may be indirect stimulation of the auditory nerve. In some cases, administration may be indirect stimulation of any one of the nerves disclosed herein. In some cases, administration may use sound. In some cases, administration may be direct stimulation. In some cases, administration may be electricity delivered to an area of ​​the subject's body. In some cases, administration may be vibration delivered to an area of ​​the subject's body. In some cases, the area of ​​the subject's body may be the skin of the subject's head, the surface of the subject's skull, the surface of the membrane surrounding the subject's brain, a region of the subject's brain, the subject's retinal nerve, or the subject's cochlear nerve. In some cases, the gamma oscillation-induced non-invasive sensory stimulation may be visual stimulation, auditory stimulation, kinesthetic stimulation, or any combination thereof. The gamma oscillation-induced non-invasive sensory stimulation may be provided using any one of the devices or methods disclosed herein.

[0087] In some cases, administration may be continuous for a predetermined period of time. In some cases, the predetermined period of time may be between 10 minutes and 2 hours. In some cases, the predetermined period of time may be at least 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, or 60 minutes. In some cases, the predetermined period of time may be at least 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours, or 24 hours. In some cases, the predetermined period of time may be 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, or 7 days. In some cases, the predetermined period of time may be at most 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, or 60 minutes. In some cases, the predetermined period of time may be at most 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours, or 24 hours. In some cases, the predetermined period of time may be at most 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, or 7 days.

[0088] In some cases, administration may be performed at multiple discrete times. In some cases, administration may be performed about once daily for six months. In some cases, administration may be performed at least about once, twice, three times, four times, five times, six times, seven times, eight times, nine times, or ten times daily. In some cases, administration may be performed up to about once, two times, three times, four times, five times, six times, seven times, eight times, nine times, or ten times daily. In some cases, administration may be performed multiple times over a period of at least about one week, two weeks, three weeks, or four weeks. In some cases, administration may be performed multiple times over a period of at least about one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, or twelve months. In some cases, administration may be performed multiple times over a period of up to one week, two weeks, three weeks, or four weeks. In some cases, administration may be multiple times over a period of up to 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11 months, or 12 months.

[0089] In some cases, the predictive scores may be presented to a medical professional, which in some cases may be a patient, a nurse, a doctor, or an analyst at an insurance company.

[0090] The gamma oscillation-inducing non-invasive stimulation may be any type of non-invasive stimulation that has a component that induces gamma brain waves (also referred to as neural activity). The gamma oscillation-inducing non-invasive sensory stimulation may be any stimulation that can be administered to a subject so as to induce gamma oscillations in the subject's nerves. In some cases, the gamma oscillation-inducing non-invasive sensory stimulation may be a gamma oscillation-inducing non-invasive sensory stimulation. In some cases, the gamma oscillation-inducing non-invasive sensory stimulation may be a non-invasive sensory stimulation. In some embodiments, the gamma oscillation-inducing non-invasive stimulation may induce neural oscillations in a frequency range other than the gamma range. In some embodiments, the gamma oscillation-inducing non-invasive stimulation may induce neural oscillations in the theta frequency range. In some embodiments, the gamma oscillation-inducing non-invasive stimulation may induce neural oscillations in the gamma frequency range that alternate with neural oscillations in other frequency ranges (e.g., the theta, alpha, or beta frequency ranges). The gamma oscillation-inducing non-invasive sensory stimulation may have the characteristics of any stimulation disclosed herein.

[0091] The subject's response may be any clinically relevant response from the subject. In some cases, the response may be correlated with the subject's expected treatment outcome. In some cases, the response may be a change in brain activity. In some cases, the brain activity may be measured by EEG. In some cases, the response may be a change in EEG coherence. In some cases, the EEG coherence may be correlated with one or more measures of the subject's clinical outcome. In some cases, the response may be a change in the subject's ability to perform a task involving cognitive function (e.g., identifying an object, drawing, speaking, hearing, tasting, smelling, counting, playing a game, playing a musical instrument). In some cases, the response may be a change in a biometric signal, including, but not limited to, heart rate, blood pressure, respiratory rate, body temperature, or electrical signals from any region of the subject's body. In some cases, the response may be measured by the Mini-Mental State Examination (MMSE), the Clinical Dementia Rating Scale (CDR), the Alzheimer's Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), magnetic resonance imaging (MRI) volumetric data from the lateral ventricles, or a combination thereof. In some cases, the biometric signal may be sleep data.

[0092] The method may use various machine learning algorithms. In some cases, the machine learning algorithm may use any one of the machine learning elements disclosed herein. In some cases, the machine learning algorithm may be configured to receive a measured response from the subject. In some cases, the machine learning algorithm may be configured to receive one or more EEG signals measured from the subject. In some cases, the machine learning algorithm may be configured to receive one or more signals having a frequency of about 4 Hz to 400 Hz. In some cases, the machine learning algorithm may be configured to receive one or more signals having a frequency of about 20 Hz to 200 Hz. In some cases, the machine learning algorithm may be configured to receive one or more signals having a frequency of about 20 Hz to 80 Hz. In some cases, the machine learning algorithm may be configured to output one or more values ​​for an expected treatment outcome.

[0093] In some cases, the method may further include predicting the expected treatment outcome of the subject based on the subject's network information. In some cases, the network information may include mobile phone data, GPS data, social network data, or any combination thereof. The social network data may be used, for example, to monitor the patient's behavior and predict future behavior. In an exemplary embodiment, for a patient with bipolar disorder, future behavior may include manic episodes or depressive episodes.

[0094] In some cases, subjects may be selected for treatment plans or clinical trials based at least in part on expected treatment outcomes.In some cases, the treatment plan may be a treatment plan for any one of the diseases disclosed herein.In some cases, the treatment plan may be a treatment plan for gamma oscillation-induced non-invasive sensory stimulation.In some cases, the clinical trial may be a test for gamma oscillation-induced non-invasive sensory stimulation.

[0095] In some cases, the method may include adjusting the subject's treatment based at least in part on the subject's expected treatment outcome. In some cases, the adjustment may be an adjustment of the therapeutic dose of the treatment. In some cases, the adjustment of the therapeutic dose may be an adjustment of the amount (e.g., volume or weight) of the drug or pharmaceutical for drug- or pharmaceutical-based treatment.

[0096] In some cases, the therapeutic dose adjustment may be an adjustment of parameters of gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory stimulation. In some cases, the therapeutic dose adjustment may be an adjustment of parameters of gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory periodic stimulation. In some cases, the therapeutic dose adjustment may be an adjustment of parameters of gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory stimulation including a periodic component. In some cases, the therapeutic dose adjustment may be an adjustment of parameters of gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory non-periodic stimulation. In some cases, the therapeutic dose adjustment may be an adjustment of parameters of gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory stimulation including a non-periodic component. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation provided for the periodic or aperiodic component of the gamma oscillation-induced non-invasive sensory stimulation treatment. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the duration of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the intensity of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the amplitude of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the wavelength of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the frequency of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the waveform of the stimulation. In some cases, the adjustment of the parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the duty cycle of the stimulation. In some cases, the adjustment of a parameter of the gamma oscillation-inducing non-invasive sensory stimulation is an adjustment of an inter-stimulus interval of the stimuli. In some cases, the adjustment of the gamma oscillation-inducing non-invasive sensory stimulation is an adjustment of a spectrum of the stimuli. In some cases, the adjustment of the gamma oscillation-inducing non-invasive sensory stimulation is an adjustment of an envelope of the stimuli.In some cases, the adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the modulation of the stimulation. In some cases, the adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the modulation frequency of the stimulation. In some cases, the adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the modulation amplitude of the stimulation. In some cases, the adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the harmonic structure of the stimulation. In some cases, the adjustment of a parameter of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the phase of the stimulation.

[0097] In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a uni-directional wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a bi-directional wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a square wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a rectangular wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a pulsed stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a sine wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a triangular wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a sawtooth wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a ramp wave stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a noise stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a white noise stimulus. In some cases, the adjustment of the therapeutic dose may be an adjustment of a parameter of a pink noise stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a red noise stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a purple noise stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a gray noise stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a sweep stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a chirp stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of an O-chirp stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a linear chirp stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of an exponential chirp stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a hyperbolic chirp stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a click stimulus. In some cases, the therapeutic dose adjustment may be adjustment of a parameter of a frequency modulated wave stimulus.In some cases, the adjustment of the therapeutic dose may be an adjustment of the parameters of the amplitude modulated wave stimulation.

[0098] In some cases, the adjustment of the therapeutic dose may be an adjustment of delivery parameters of the gamma oscillation-induced non-invasive sensory stimulation administered for the treatment of gamma oscillation-induced non-invasive sensory stimulation. In some cases, the adjustment of delivery parameters of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the time course of delivery of the stimulation. In some cases, the adjustment of delivery parameters of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the intensity of delivery of the stimulation. In some cases, the adjustment of delivery parameters of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the delivery time of the stimulation. In some cases, the adjustment of delivery parameters of the gamma oscillation-induced non-invasive sensory stimulation is an adjustment of the mode of delivery of the stimulation.

[0099] In some cases, the therapeutic dose can be any adjustable dose for the treatment of any one of the diseases disclosed herein.

[0100] Method and system for identifying EEG biomarkers In some aspects, the present disclosure describes a method for identifying a biomarker. In some cases, the method includes training a machine learning algorithm to identify a statistical relationship between (i) a first dataset including a plurality of response measures of a plurality of subjects, the plurality of response measures including responses of each subject in the plurality of subjects to a gamma oscillation-inducing non-invasive sensory stimulus, and (ii) a second dataset including a plurality of clinical measures of the plurality of subjects. In some cases, the method includes using the machine learning algorithm to identify a biomarker associated with a distinct clinical outcome.

[0101] In some cases, identifying biomarkers may include discovering one or more patterns in the response data that correlate with clinical measurements. In some cases, the response data may include bioelectrical measurements. In some cases, the response data may be EEG data. In some cases, the one or more features may include a range of amplitudes in the EEG data. In some cases, the one or more features may include a range of frequencies in the EEG data. In some cases, the one or more features may consist of higher-order relationships between two or more different brain regions observed through EEG, such as a particular frequency (coherence) or a preserved phase relationship at a frequency in the frequency domain, or a preserved phase relationship in the time domain (synchronous activity up to a phase delay in the waveforms).

[0102] In some cases, the response measurement value can be any one of the response measurements disclosed herein.In some cases, the clinical measurement value can be any one of the clinical measurement values ​​disclosed herein.In some cases, the measurement value can be obtained from a diverse group of subjects that differ in gender, age, demographics, genetics, or health status.In some cases, the multiple subjects can include subjects that suffer from the diseases disclosed herein and subjects that do not suffer from the diseases.

[0103] In some cases, stimulus-evoked EEG responses may predict one or more clinical outcomes.

[0104] In some cases, stimulus-evoked EEG responses may predict a unified measure of clinical outcome consisting of a combination of multiple outcomes that may be summed in different proportions.

[0105] In some cases, singular value decomposition or principal component analysis of multiple outcomes can yield a unified outcome related to EEG.

[0106] In some cases, the EEG response to a particular stimulus can predict the direction of maximum change, with each axis potentially indicating a different clinical outcome.

[0107] Delivery Methods and Systems The present disclosure provides a method for determining an expected treatment outcome by inducing at least gamma oscillations in a subject, the method comprising delivering a gamma oscillation-inducing non-invasive sensory stimulus and / or inducing gamma oscillations in the subject. In some embodiments, the gamma oscillation-inducing non-invasive sensory stimulus induces a signal indicative of the expected treatment outcome.

[0108] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through one or more of visual, auditory, tactile, olfactory stimulation, or bone conduction. In some embodiments, the combined visual and auditory stimulation is delivered for one hour daily for a period of three to six months or more. In some embodiments, the stimulation is delivered for two hours daily. In some embodiments, the stimulation is delivered for multiple periods throughout the day. In some embodiments, the combined visual and auditory stimulation is delivered for an extended, indefinite period. In some embodiments, the stimulation is delivered for periods of varying duration. In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered, at least in part, through glasses, goggles, a mask, or other wearable device that provides visual stimulation.

[0109] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered at least in part through one or more devices in the user's environment, such as a speaker, a light fixture, a bed attachment, a wall screen, or other home device, hi some embodiments, the one or more devices are controlled by a further device, such as a phone, tablet, or home automation hub, configured to manage the delivery of the gamma oscillation-induced non-invasive sensory stimulation through the one or more devices in the user's environment.

[0110] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through opaque or partially transparent glasses worn by the subject, with lighting elements inside to provide a visual signal. In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through headphones or earphones worn by the subject, which provide an audio signal. In some embodiments, the combined audiovisual signal is provided by headphones and glasses worn together at the same time. In some embodiments, the audiovisual signals are delivered separately by glasses or headphones worn at different times. An exemplary embodiment includes glasses with LEDs inside the glasses that provide a visual stimulus and headphones that provide an audio stimulus.

[0111] In some embodiments, the gamma vibration-induced non-invasive sensory stimulation is delivered through vibrotactile stimulation via clothing or a body attachment, hi some embodiments, the gamma vibration-induced non-invasive sensory stimulation may be delivered through the user's nostrils.

[0112] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through transcranial magnetic stimulation (TMS). In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through transcranial alternating current stimulation (tACS). In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered through transcranial pulsed current stimulation (tPCS).

[0113] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is provided at least in part by a device described in one or more of U.S. Pat. No. 10,307,611 B2, U.S. Pat. No. 10,293,177 B2, or U.S. Pat. No. 10,279,192 B2.

[0114] In some embodiments, the gamma oscillation-induced non-invasive sensory stimulation is delivered to multiple subjects present in a space. In an exemplary embodiment, the gamma oscillation-induced non-invasive sensory stimulation is delivered to multiple subjects in the space through devices present in the space, where such devices deliver the same stimulation to all subjects, or customized stimulation to each subject, or a combination thereof.

[0115] Program parameters and parameter values In some embodiments, the parameters for the gamma oscillation-induced non-invasive sensory stimulation comprise a stimulation frequency (e.g., fs in FIG. 31) of about 30 Hz to about 50 Hz for both the audio and visual signals. In some embodiments, the audio and visual signals are offset from each other by a delay time (e.g., td in FIG. 31). In an exemplary embodiment, the audio and visual signals are synchronized (td=0 s).

[0116] In some embodiments, the parameters of the gamma oscillation-inducing non-invasive sensory stimulation consist of various timing and intensity parameters. In an exemplary embodiment, these parameters include those illustrated in FIG. 31 . In some embodiments, these parameters are pre-configured; in some embodiments, these parameters are adjusted at least in part by a third party, such as a caregiver or healthcare provider; and in some embodiments, one or more parameters are adjusted in response to measurements or analyses of one or more of the following: a user's condition, a measured sleep quality-related parameter associated with the user, or observed or detected use of the stimulation device. In some embodiments, the parameters of the gamma oscillation-inducing non-invasive sensory stimulation are adjusted in response to the progression of detected or analyzed neurodegenerative disease symptoms. Various frequencies and various intensities can be used as parameters of the gamma oscillation-inducing non-invasive sensory stimulation.

[0117] In some embodiments, one or more stimulation parameters are based at least in part on various clinical measures of cognitive treatment outcomes as disclosed herein. In some embodiments, various combinations of stimulation parameters are used during different time periods, with subsequent stimulation parameters selected at least in part based on a comparison of the clinical measures of cognitive treatment outcomes during at least some of those time periods.

[0118] In some embodiments, the present disclosure delivers non-invasive audio, visual, or combined audiovisual stimuli at 40 Hz. In some embodiments, the stimuli are delivered at one or more stimulation frequencies (e.g., fs in FIG. 31). In some embodiments, the stimuli are delivered at one or more stimulation frequencies (e.g., fs in FIG. 31) within a range of approximately 30-50 Hz. In some embodiments, "gamma" refers to a frequency in the range of 30-50 Hz. In some embodiments, the stimuli are periodic. In some embodiments, the stimuli are aperiodic. In some embodiments, the stimuli are periodic with an aperiodic component. In some embodiments, the stimuli are intermittent. In some embodiments, the stimuli are delivered based at least in part on the user's detected, reported, or demographically or individually associated, or dominant alpha wave frequency.

[0119] In some embodiments, the specific visual parameters include one or more of the following: stimulus frequency, intensity (luminance), hue, visual pattern, spatial frequency, contrast, and duty cycle. In an exemplary embodiment, the visual stimulus is presented at a stimulus frequency of 40 Hz, a luminance of 0 μW / cm to 1120 μW / cm, and a visual signal duty cycle of 50%.

[0120] In some embodiments, the non-invasive stimulation is delivered as a combined audiovisual stimulation delivered at a frequency of 40 Hz. In some embodiments, the audiovisual stimulation is synchronized to start each cycle at the same time. In some embodiments, the start of each audiovisual stimulation cycle is offset by a configured time. In some embodiments, the audiovisual signal is delivered at an intensity that is clearly perceived by the subject and adjusted to the subject's tolerance level.

[0121] In some embodiments, at least a portion of the parameters or characteristics of the non-invasive signal administered to the subject correspond to those described in one or more of the following: U.S. Patent No. 10,307,611 B2, U.S. Patent No. 10,293,177 B2, or U.S. Patent No. 10,279,192 B2. In some embodiments, at least a portion of the parameters or characteristics of the non-invasive signal administered to the subject correspond to those described in one or more of U.S. Patent Nos. 10,159,816 B2 or 10,265,497 B2.

[0122] In some embodiments, the specific audio parameters include one or more of stimulus frequency, intensity (volume), and duty cycle. In some embodiments, the audio frequency is adjusted in response to the subject's hearing characteristics, e.g., in response to frequencies that are easier for the subject to hear. In an exemplary embodiment, the audio stimulus is provided at an audio tone frequency of 7,000 Hz, a volume level between 0 dBA and 80 dBA, and an audio signal duty cycle of 0.57%.

[0123] In some embodiments, the non-invasive stimulation parameters are selected for evoking gamma wave oscillations in the brain of the human subject. In some embodiments, the non-invasive stimulation parameters are selected for eliciting alpha waves in the human subject (FIG. 40). In some embodiments, the non-invasive stimulation parameters are intended to elicit beta waves in the human subject. In some embodiments, the non-invasive stimulation parameters are intended to elicit gamma waves in the human subject.

[0124] In some embodiments, the light level and hue are adjusted to avoid tiring the subject. In some embodiments, the light level and hue are adjusted to provide motivation to the subject. In some embodiments, the parameters for each ear or eye are adjusted similarly. In some embodiments, the parameters for each ear or eye are adjusted differently. In exemplary embodiments, audio and visual parameters such as tone and hue are varied to provide engagement or motivation to the subject to continue the stimulation or monitoring.

[0125] Neurostimulation via visual stimulation In some embodiments, the disclosed systems and methods aim to use visual signals to control the frequency of neural oscillations, thereby generating a detectable signal indicative of a predicted treatment outcome. Visual stimulation can modulate, control, or otherwise influence the frequency of neural oscillations to mitigate or prevent adverse consequences to cognitive status or function while simultaneously providing beneficial effects to one or more cognitive status or functions of the brain or immune system. Visual stimulation can produce sensory-evoked neural oscillations that can generate detectable signals that can correlate with potentially beneficial effects on one or more cognitive statuses, brain functions, the immune system, or inflammation in the brain. In some cases, visual stimulation can produce localized effects, such as in the visual cortex and associated regions. In other cases, visual stimulation can produce broader effects, causing physiological changes beyond the nervous system. Sensory-evoked neural oscillations can generate detectable signals that can correlate with predicted treatment outcomes in disorders, stages of disease, disabilities, injuries, or other problems related to cognitive function, cognitive status, the immune system, or inflammation.

[0126] Neural oscillations occur in humans or animals and involve rhythmic or repetitive neural activity in the central nervous system. Neural tissue can generate oscillatory activity through mechanisms within individual neurons or through interactions between neurons. Oscillations can manifest as oscillations in membrane potential or as rhythmic patterns of action potentials, which can lead to oscillatory activation of postsynaptic neurons. Synchronized activity of a group of neurons can produce macroscopic oscillations, which can be observed, for example, by electroencephalography ("EEG"), magnetoencephalography ("MEG"), magnetic resonance imaging ("fMRI"), or electrocorticography ("ECoG"). Neural oscillations can be characterized by their frequency, amplitude, and phase. These signal properties can be observed from neural recordings using time-frequency analysis.

[0127] For example, EEG can measure oscillatory activity between groups of neurons, and the measured oscillatory activity can be classified into frequency bands, such as delta activity corresponding to the 0-4 Hz frequency band, theta activity corresponding to the 4-8 Hz frequency band, alpha activity corresponding to the 8-12 Hz frequency band, beta activity corresponding to the 13-30 Hz frequency band, and gamma activity corresponding to the 30-100 Hz frequency band.

[0128] The frequency and presence or activity of neural oscillations can be associated with cognitive states or cognitive functions, such as information transmission, perception, motor control, and memory. In some cases, the frequency and presence or activity of neural oscillations can be associated with deficits in cognitive states or cognitive functions. The frequency of neural oscillations can vary based on the cognitive state or cognitive function. Furthermore, certain frequencies of neural oscillations can have beneficial or detrimental effects on one or more cognitive states or cognitive functions. In some cases, the characteristics of neural oscillations can indicate expected treatment outcomes.

[0129] Sensory arousal or sensory-evoked neural oscillations occur when an external stimulus of a specific frequency is encoded by neurons, triggering neural activity in the brain, resulting in neuronal oscillations at a frequency corresponding to the specific frequency of the external stimulus. Thus, sensory arousal neural oscillations can refer to the synchronization of neural oscillations in the brain using an external stimulus so that neural oscillations occur at a frequency corresponding to a specific frequency component of the external stimulus. In some cases, sensory arousal neural oscillations may include additional neural oscillations with frequencies different from the frequency of the external stimulus. In some cases, the additional neural oscillations may be correlated with expected treatment outcomes.

[0130] The disclosed systems and methods can provide external visual stimuli to achieve sensory elicitation of neural oscillations. For example, external signals, such as light pulses or high-contrast visual patterns, can be perceived by the brain. The brain can adjust, manage, or control the frequency of neural oscillations in response to the observation or perception of the light pulses. Light pulses generated at a predetermined frequency and perceived by visual means through direct or peripheral vision can trigger neural activity in the brain to induce neural oscillations in a specific frequency range. The frequency of neural oscillations can be at least partially influenced by the frequency of the light pulses. While higher-level cognitive functions can gate or interfere with the sensory elicitation of neural oscillations in some areas, the brain can respond to visual stimuli in the sensory cortex. Thus, the disclosed systems and methods can provide sensory elicitation of neural oscillations using external visual stimuli, such as light pulses emitted at a predetermined frequency to synchronize electrical activity between groups of neurons based on the frequency of the light pulses. Sensory elicitation of neural oscillations in one or more parts or regions of the brain can be observed based on the total frequency of oscillations generated by synchronized electrical activity in populations of cortical neurons. The frequency of the light pulses can cause or tune this synchronous electrical activity in the population of cortical neurons to oscillate at a frequency corresponding to the frequency of the light pulses. In some cases, the brain can generate a detectable signal in response to an external visual stimulus, where the detectable signal has characteristics that correlate with an expected treatment outcome.

[0131] 1 is a block diagram illustrating a system for visually stimulating neural oscillations, according to one embodiment. System 100 may include a neural stimulation system (“NSS”) 105. NSS 105 may be referred to as a visual NSS 105 or NSS 105. Briefly, NSS 105 may include, access, interface with, or otherwise communicate with one or more of a light generation module 110, a light adjustment module 115, an unwanted frequency filtering module 120, a profile manager 125, a side effect management module 130, a feedback monitor 135, a data repository 140, a visual signaling component 150, a filtering component 155, or a feedback component 160. Light generation module 110, light adjustment module 115, unwanted frequency filtering module 120, profile manager 125, side effect management module 130, feedback monitor 135, visual signaling component 150, filtering component 155, or feedback component 160 may each include at least one processing unit or other logic device, such as a programmable logic array engine or a module configured to communicate with database repository 150. Light generation module 110, light adjustment module 115, unwanted frequency filtering module 120, profile manager 125, side effect management module 130, feedback monitor 135, visual signaling component 150, filtering component 155, or feedback component 160 may be separate components, a single component, or part of NSS 105. System 100 and its components, such as NSS 105, may include hardware elements, such as one or more processors, logic devices, or circuits. System 100 and its components, such as NSS 105, may include one or more hardware or interface components depicted in system 700 of Figures 7A and 7B.For example, the components of the system 100 may include or execute on one or more processors 721 , access storage 728 , or memory 722 , and may communicate via a network interface 718 .

[0132] Still referring to FIG. 1 , and in more detail, the NSS 105 may include at least one light-generating module 110. The light-generating module 110 may be designed and configured to interface with the visual signaling component 150 to instruct or otherwise cause or facilitate the generation of a visual signal, such as a light pulse or flash of light, having one or more predetermined parameters. The light-generating module 110 may include hardware or software for receiving and processing instructions or data packets from one or more modules or components of the NSS 105. The light-generating module 110 may generate instructions to cause the visual signaling component 150 to generate a visual signal. The light-generating module 110 may control or enable the visual signaling component 150 to generate a visual signal having one or more predetermined parameters.

[0133] The light-generating module 110 can be communicatively coupled to the visual signaling component 150. The light-generating module 110 can communicate with the visual signaling component 150 via a circuit, a wire, a data port, a network port, a power line, a ground, an electrical contact, or a pin. The light-generating module 110 can wirelessly communicate with the visual signaling component 150 using one or more wireless protocols, such as Bluetooth, Bluetooth Low Energy, Zigbee, Z-wave, IEEE 802.11, WIFI, 3G, 4G, LTE, near field communication (“NFC”), or other short-, medium-, or long-range communication protocols. The light-generating module 110 can include or have access to a network interface 718 for wirelessly or wired communication with the visual signaling component 150.

[0134] The light-generating module 110 can interface with, control, or otherwise manage various types of visual signaling components 150 to cause the visual signaling components 150 to generate, block, control, or otherwise provide a visual signal having one or more predetermined parameters. The light-generating module 110 can include a driver configured to drive a light source of the visual signaling component 150. For example, the light source can include a light-emitting diode ("LED"), and the light-generating module 110 can include an LED driver, chip, microcontroller, operational amplifier, transistor, resistor, or diode configured to drive the LED light source by providing electricity or power having certain voltage and current characteristics.

[0135] In some embodiments, the light-generating module 110 can instruct the visual signaling component 150 to provide a visual signal including a light wave 200, as depicted in FIG. 2A . The light wave 200 can include or be formed of an electromagnetic wave. The electromagnetic waves of the light wave can have respective amplitudes and travel orthogonally to each other, as depicted by the amplitude versus time of the electric field 205 and the amplitude versus time of the magnetic field 210. The light wave 200 can have a wavelength 215. The light wave can also have a frequency. The product of the wavelength 215 and the frequency can be the speed of the light wave. For example, the speed of the light wave can be approximately 299,792,458 meters per second in a vacuum.

[0136] The light-generating module 110 can instruct the visual signaling component 150 to generate light waves having one or more predetermined wavelengths or intensities. The wavelengths of the light waves may correspond to the visible spectrum, the ultraviolet spectrum, the infrared spectrum, or some other wavelength of light. For example, the wavelengths of light waves within the visible spectrum range may range from 390 to 700 nanometers (“nm”). Within the visible spectrum, the light-generating module 110 can further specify one or more wavelengths corresponding to one or more colors. For example, the light-generating module 110 can instruct the visual signaling component 150 to generate a visual signal including one or more light waves having one or more wavelengths corresponding to one or more of ultraviolet (e.g., 10-380 nm), violet (e.g., 380-450 nm), blue (e.g., 450-495 nm), green (e.g., 495-570 nm), yellow (e.g., 570-590 nm), orange (e.g., 590-620 nm), red (e.g., 620-750 nm), or infrared (e.g., 750-1,000,000 nm). The wavelengths can range from 10 nm to 100 micrometers. In some embodiments, the wavelengths can be in the range of 380-750 nm.

[0137] The light-generating module 110 can determine to provide a visual signal including a light pulse. The light-generating module 110 can instruct the visual signaling component 150 to generate or otherwise generate the light pulse. A light pulse may refer to a burst of light waves. For example, FIG. 2B illustrates a burst of light waves. A burst of light waves may refer to a burst of electric field 250 generated by the light waves. A burst of electric field 250 of a light wave may be referred to as a light pulse or a flash of light. For example, a light source that is intermittently turned on and off can generate a burst, flash, or pulse of light.

[0138] 2C illustrates light pulses 235a-c, according to one embodiment. Light pulses 235a-c can be illustrated via a frequency spectrum graph, where the y-axis represents the frequency of the light wave (e.g., the speed of the light wave divided by the wavelength) and the x-axis represents time. A visual signal is generated by F a and the frequency of F a For example, the NSS 105 can modulate light waves between frequencies within the visible spectrum, such as Fa, and frequencies outside the visible spectrum. The NSS 105 can modulate light waves between two or more frequencies, between on and off states, or between high and low power states.

[0139] In some cases, the frequency of the light wave used to generate the light pulse is F a In some embodiments, each of the three pulses 235a-c has the same frequency, F a The light wave may include a light wave having the following characteristics:

[0140] The width of each of the light pulses (e.g., the duration of the burst of light waves) may correspond to a pulse width 230a. The pulse width 230a may refer to the length or duration of the burst. The pulse width 230a may be measured in units of time or distance. In some embodiments, the pulses 235a-c may include light waves having different frequencies from one another. In some embodiments, the pulses 235a-c may have different pulse widths 230a from one another, as illustrated in FIG. 2D. For example, the first pulse 235d in FIG. 2D may have a pulse width 230a, while the second pulse 235e has a second pulse width 230b that is larger than the first pulse width 230a. The third pulse 235f may have a third pulse width 230c that is smaller than the second pulse width 230b. The third pulse width 230c may also be smaller than the first pulse width 230a. Although the pulse widths 230a-c of the pulses 235d-f in the pulse train may vary, the light-generating module 110 is able to maintain a constant pulse rate spacing 240 in the pulse train.

[0141] The pulses 235a-c can form a pulse train having a pulse rate interval 240. The pulse rate interval 240 can be quantified using units of time. The pulse rate interval 240 can be based on the frequency of the pulses in the pulse train 201. The frequency of the pulses in the pulse train 201 can be referred to as the modulation frequency. For example, the light-generating module 110 can provide the pulse train 201 with a predetermined frequency corresponding to gamma radioactivity, such as 40 Hz. To do so, the light-generating module 110 can determine the pulse rate interval 240 by taking the multiplicative inverse (or reciprocal) of the frequency (e.g., dividing 1 by the predetermined frequency of the pulse train). For example, the light-generating module 110 can take the multiplicative inverse of 40 Hz by dividing 1 by 40 Hz to determine the pulse rate interval 240 as 0.25 seconds. The pulse rate interval 240 can remain constant throughout the pulse train. In some embodiments, the pulse rate interval 240 may vary throughout the pulse train or from one pulse train to the next. In some embodiments, the pulse rate interval 240 varies, but the number of pulses transmitted per second may be fixed.

[0142] In some embodiments, the light-generating module 110 can generate light pulses having light waves with varying frequencies. For example, the light-generating module 110 can generate up-chirp pulses, in which the frequency of the light waves of the light pulse increases from the beginning of the pulse to the end of the pulse, as illustrated in FIG. 2E. For example, the frequency of the light waves at the beginning of pulse 235g is F a The frequency of the light wave in pulse 235g can be F a From F b and then may increase to a maximum of Fc at the end of pulse 235g. Thus, the frequency of the light wave used to generate pulse 235g may be F a ~F c The frequency may increase linearly, exponentially, or based on some other rate or curve.

[0143] The light-generating module 110 can generate down-chirp pulses, as illustrated in FIG. 2F, where the frequency of the light wave in the light pulse decreases from the start of the pulse to the end of the pulse. For example, the frequency of the light wave at the start of pulse 235j is F d The frequency of the light wave of pulse 235j can be F d From F e and then at the end of pulse 235j, F f Therefore, the frequency of the light wave used to generate pulse 235j can be reduced to a minimum of F d ~F f The frequency may decrease linearly, exponentially, or based on some other rate or curve.

[0144] The visual signaling component 150 can be designed and configured to generate light pulses in response to instructions from the light generating module 110. The instructions can include parameters of the light pulses, such as the frequency or wavelength of the light waves, intensity, pulse duration, pulse train frequency, pulse rate interval, or pulse train duration (e.g., the number of pulses in a pulse train or the length of time to transmit a pulse train having a predetermined frequency). The light pulses can be perceived, observed, or otherwise identified by the brain through visual means, such as the eye. The light pulses can be transmitted to the eye via the direct visual field or peripheral vision.

[0145] FIG. 3A illustrates a horizontal direct field of view 310 and a horizontal peripheral field of view. FIG. 3B illustrates a vertical direct field of view 320 and a vertical peripheral field of view 325. FIG. 3C illustrates the angles of the direct and peripheral fields of view, including the relative distances at which visual signals can be perceived in various fields of view. The visual signaling component 150 may include a light source 305. The light source 305 may be positioned to transmit light pulses into the direct field of view 310 or 320 of the person's eye. The NSS 105 may be configured to transmit light pulses into the direct field of view 310 or 320 because the person may pay more attention to the light pulses, which may facilitate the sensory elicitation of neural oscillations. The level of attention can be measured directly in the brain, indirectly through the person's eye movements, or quantitatively by active feedback (e.g., mouse tracking).

[0146] The light source 305 can be positioned to transmit light pulses to the peripheral vision 315 or 325 of the person's eye. For example, the NSS 105 can transmit light pulses to the peripheral vision 315 or 325 because these light pulses may be less distracting to a person who may be performing other tasks such as reading, walking, driving, etc. Thus, the NSS 105 can provide subtle, continuous visual brain stimulation by transmitting light pulses through the peripheral vision.

[0147] In some embodiments, the light source 305 is head-mounted, while in other embodiments, the light source 305 can be held by the subject's hand, placed on a stand, suspended from the ceiling, connected to a chair, or otherwise positioned to direct light into the subject's direct or peripheral vision. For example, a chair or externally supported system can include or position the light source 305 to provide visual input while maintaining a fixed / prespecified relationship between the subject's field of view and the visual stimulus. The system can provide an immersive experience. For example, the system can include an opaque or partially opaque dome containing the light source. The dome can be positioned above the subject's head while the subject is sitting or reclining in a chair. The dome can obscure a portion of the subject's field of view, thereby reducing external distractions and facilitating sensory elicitation of neural oscillations in brain regions.

[0148] The light source 305 may include any type of light source or light-emitting device. The light source may include a coherent light source such as a laser. The light source 305 may include a light-emitting diode (LED), an organic LED, a fluorescent light source, an incandescent light, or any other light-emitting device. The light source may include a lamp, a light bulb, or one or more light-emitting diodes of various colors (e.g., white, red, green, blue). In some embodiments, the light source includes a semiconductor light-emitting device, such as a light-emitting diode of any spectrum or wavelength range. In some embodiments, the light source 305 includes a broadband lamp or a broadband light source. In some embodiments, the light source includes a black light. In some embodiments, the light source 305 includes a hollow cathode lamp, a fluorescent tube light source, a neon lamp, an argon lamp, a plasma lamp, a xenon flash lamp, a mercury lamp, a metal halide lamp, or a sulfur lamp. In some embodiments, the light source 305 includes a laser or a laser diode. In some embodiments, the light source 305 includes an OLED, a PHOLED, a QDLED, or any other light source variant that utilizes organic materials. In some embodiments, light source 305 comprises a monochromatic light source. In some embodiments, light source 305 comprises a polychromatic light source. In some embodiments, light source 305 comprises a light source that partially emits light in the ultraviolet spectral range. In some embodiments, light source 305 comprises a device, product, or material that partially emits light in the visible spectral range. In some embodiments, light source 305 is a device, product, or material that partially emits or emits light in the infrared spectral range. In some embodiments, light source 305 comprises a device, product, or material that emits or emits light in the visible spectral range. In some embodiments, light source 305 comprises a light guide, optical fiber, or waveguide through which light is emitted from the light source.

[0149] In some embodiments, the light source 305 includes one or more mirrors to reflect or redirect light. For example, the mirrors can reflect or redirect light toward the direct field of view 310 or 320 or the peripheral field of view 315 or 325. The light source 305 can include or interact with a microelectromechanical device (“MEMS”). The light source 305 can include or interact with a digital light projector (“DLP”). In some embodiments, the light source 305 can include ambient light or sunlight. The ambient light or sunlight is focused by one or more optical lenses and directed toward the direct field of view or the peripheral field of view. The ambient light or sunlight can be directed toward the directed field of view or the peripheral field of view by one or more mirrors.

[0150] If the light source is ambient light, the ambient light is not positioned, but can enter the eye through the direct or peripheral field of view. In some embodiments, the light source 305 can be positioned to direct light pulses into the direct or peripheral field of view. For example, as illustrated in FIG. 4A , one or more light sources 305 can be attached, fixed, coupled, mechanically coupled, or otherwise provided to a frame 400. In some embodiments, the visual signaling component 150 can include the frame 400. Further details of the operation of the NSS 105 in conjunction with the frame 400, including one or more light sources 305, are provided below in the section entitled “NSS Operating with a Frame.” Thus, the light source can include any type of light source, such as an optical light source, a mechanical light source, or a chemical light source. The light source can include any reflective or opaque material or object capable of generating, emitting, or reflecting an oscillating pattern of light, such as a fan or bubble rotating in front of the light. In some embodiments, the light source may include an invisible optical illusion, the internal physiology of the eye (e.g., pressing on the eyeball), or a chemical applied to the eye.

[0151] Systems and devices configured for neural stimulation via visual stimulation - Patents.com Referring now to FIG. 4A , frame 400 can be designed and configured to be placed or positioned on a person's head. Frame 400 can be configured to be worn by a person. Frame 400 can be designed and configured to remain in place. Frame 400 can be configured to be worn and remain in place when a person sits, stands, walks, runs, or lies flat. Light source 305 can be configured on frame 400 to project light pulses toward the person's eyes while in these various positions. In some embodiments, light source 305 can be configured to project light pulses toward the person's eyes when the person's eyelids are closed, so that the light pulses pass through the eyelids and are perceived by the retina. Frame 400 can include a bridge 420. Frame 400 can include one or more eye wires 415 coupled to bridge 420. Bridge 420 can be positioned between eye wires 415. The frame 400 may include one or more temples extending from one or more eye wires 415. In some embodiments, the eye wire 415 may include or hold a lens 425. In some embodiments, the eye wire 415 may include or hold a solid material 425 or a cover 425. The lens, solid material, or cover 425 may be transparent, translucent, opaque, or completely block external light.

[0152] One or more light sources 305 may be positioned on or adjacent to the eye wire 415, lens, or other solid material 425, or bridge 420. For example, the light source 305 may be positioned in the center of the eye wire 415 on the solid material 425 to transmit light pulses directly into the visual field. In some embodiments, the light source 305 may be positioned at a corner of the eye wire 415, such as a corner of the eye wire 415 connected to the temple 410, to transmit light pulses into the peripheral visual field.

[0153] The NSS 105 can provide visual stimulation of neural oscillations via one eye or both eyes. For example, the NSS 105 can direct light pulses to one eye or both eyes. The NSS 105 can interface with a visual signaling component 150, which includes a frame 400 and two eye wires 415. However, the visual signaling component 150 may also include a single light source 305 configured and positioned to direct light pulses to a first eye. The visual signaling component 150 may further include a light blocking component that prevents or blocks light pulses generated from the light source 305 from entering a second eye. The visual signaling component 150 can block or prevent light from entering the second eye during sensory stimulation of neural oscillations.

[0154] In some embodiments, the visual signaling component 150 can alternately transmit or direct light pulses to a first eye and a second eye. For example, the visual signaling component 150 can direct light pulses to a first eye for a first time interval. The visual signaling component 150 can direct light pulses to a second eye for a second time interval. The first time interval and the second time interval can be identical, overlapping, mutually exclusive, or consecutive.

[0155] 4B illustrates a frame 400 including a set of shutters 435 that can block at least a portion of the light entering through the eye wire 415. The set of shutters 435 can intermittently block ambient or sunlight entering through the eye wire 415. The set of shutters 435 can be opened to admit light through the eye wire 415 and can be closed to at least partially block light entering through the eye wire 415. Further details of the operation of the NSS 105 in conjunction with a frame 400 that includes one or more shutters 430 are provided below in the section entitled "NSS Operating with a Frame."

[0156] The set of shutters 435 may include one or more shutters 430 that are opened and closed by one or more actuators. The shutters 430 may be formed from one or more materials. The shutters 430 may include one or more materials. The shutters 430 may include or be formed from a material that can at least partially block or attenuate light.

[0157] The frame 400 may include one or more actuators configured to at least partially open and close the set of shutters 435 or individual shutters 430. The frame 400 may include one or more types of actuators for opening and closing the shutters 435. For example, the actuators may include mechanically driven actuators. The actuators may include magnetically driven actuators. The actuators may include pneumatic actuators. The actuators may include hydraulic actuators. The actuators may include piezoelectric actuators. The actuators may include micro-electromechanical systems ("MEMS").

[0158] The set of shutters 435 may include one or more shutters 430 that are opened and closed via electrical or chemical techniques. For example, the shutter 430 or set of shutters 435 may be formed from one or more chemicals. The shutter 430 or set of shutters may include one or more chemicals. The shutter 430 or set of shutters 435 may include or be formed from a chemical capable of at least partially blocking or attenuating light.

[0159] For example, shutter 430 or set of shutters 435 may include a photochromic lens configured to filter, attenuate, or block light. The photochromic lens may automatically darken upon exposure to sunlight. The photochromic lens may include molecules configured to darken the lens. The molecules may be activated by light waves, such as ultraviolet light or other wavelengths of light. Thus, the photochromic molecules may be configured to darken the lens in response to a predetermined wavelength of light.

[0160] The shutter 430 or set of shutters 435 may comprise electrochromic glass or plastic, which can change from light to dark (e.g., transparent to opaque) in response to a voltage or current. The electrochromic glass or plastic may include a metal oxide coating deposited on the glass or plastic, multiple layers, and lithium ions that migrate between two electrodes between the layers to lighten or darken the glass.

[0161] The shutter 430 or set of shutters 435 may include a micro-shutter. The micro-shutter may include a small window measuring 100 x 200 microns. The micro-shutters may be arranged within the eye frame 415 in a waffle-like grid. Individual micro-shutters may be opened and closed by an actuator. The actuator may include a magnetic arm that passes by the micro-shutter to open and close it. An open micro-shutter may allow light to enter through the eye frame 415, while a closed micro-shutter may block, attenuate, or filter light.

[0162] NSS 105 can drive an actuator to open and close one or more shutters 430 or sets of shutters 435 at a predetermined frequency, such as 40 Hz. By opening and closing shutters 430 at the predetermined frequency, shutters 430 can pass flash light to eyewire 415 at the predetermined frequency. Thus, a frame 400 including sets of shutters 435 may not include or use a separate light source coupled to frame 400, such as light source 305 coupled to frame 400 depicted in FIG. 4A .

[0163] In some embodiments, the visual signaling component 150 or the light source 305 may refer to or be included in a virtual reality headset 401, as depicted in FIG. 4C . For example, the virtual reality headset 401 may be designed and configured to receive the light source 305. The light source 305 may include a computing device with a display device, such as a smartphone or mobile communication device. The virtual reality headset 401 may include a cover 440 that opens to receive the light source 305. The cover 440 may close to lock or hold the light source 305 in place. When closed, the cover 440 and the cases 450 and 445 may form an enclosure for the light source 305. This enclosure may provide an immersive experience that minimizes or eliminates unnecessary visual distractions. The virtual reality headset may provide an environment that maximizes the sensory elicitation of neural oscillations. The virtual reality headset may provide an augmented reality experience. In some embodiments, the light source 305 may form an image on another surface such that the image is reflected from the surface toward the subject's eye (e.g., a heads-up display that overlays flashing objects or augmented parts of reality on the screen). Further details of the operation of the NSS 105 in conjunction with the virtual reality headset 401 are provided below in the section entitled "Systems and Devices Configured for Neurostimulation Via Visual Stimulation."

[0164] Virtual reality headset 401 includes straps 455 and 460 configured to secure virtual reality headset 401 to a person's head. Virtual reality headset 401 is secured via straps 455 and 460, which can minimize movement of headset 401 while worn during physical activities such as walking or running. Virtual reality headset 401 may include a skull cap formed from 460 or 455.

[0165] The feedback sensor 605 may include an electrode, a dry electrode, a gel electrode, a saline-soaked electrode, or an adhesive-based electrode.

[0166] 5A-5D illustrate an embodiment of a visual signaling component 150 that may include a tablet computing device 500 or other computing device 500 having a display screen 305 as a light source 305. The visual signaling component 150 may transmit a light pulse, a light flash, or a pattern of light via the display screen 305 or the light source 305.

[0167] FIG. 5A illustrates a light-transmitting display screen 305 or light source 305. The light source 305 can transmit light including wavelengths within the visible spectrum. The NSS 105 can instruct the visual signaling component 150 to transmit light through the light source 305. The NSS 105 can instruct the visual signaling component 150 to transmit flashes of light or light pulses having a predetermined pulse rate interval. For example, FIG. 5B illustrates the light source 305 turned off or disabled so that the light source emits no light or a minimal or reduced amount of light. The visual signaling component 150 can cause the tablet computing device 500 to enable (e.g., FIG. 5A ) and disable (e.g., FIG. 5B ) the light source 305 so that the flashes of light have a predetermined frequency, such as 40 Hz. The visual signaling component 150 can toggle or switch the light source 305 between two or more states to generate flashes of light or light pulses of a predetermined frequency.

[0168] In some embodiments, as depicted in FIGS. 5C and 5D , the light-generating module 110 can command or cause the visual signaling component 150 to display a light pattern via the display device 305 or light source 305. The light-generating module 110 can cause the visual signaling component 150 to blink, toggle, or switch between two or more patterns to generate flashing lights or light pulses. The patterns can include, for example, alternating checkerboard patterns 510 and 515. The patterns can include symbols, letters, or images that can be toggled or adjusted from one state to another. For example, the color of the letters or text can be inverted relative to the background color to switch between a first state 510 and a second state 515. Inverting the foreground and background colors at a predetermined frequency can generate light pulses as a visual change that can facilitate modulation or management of the frequency of neural oscillations. Further details of the operation of the NSS 105 in conjunction with the tablet 500 are provided below in the section entitled “NSS Operating with a Tablet.”

[0169] In some embodiments, the light-generating module 110 can command or cause the visual signaling component 150 to flash, toggle, or switch between images configured to stimulate specific or predetermined portions of the brain or a particular cortex. The presentation, form, color, movement, and other aspects of the light or image-based stimuli can determine which cortex is recruited to process the stimuli. The visual signaling component 150 can stimulate distinct portions of the cortex by adjusting the presentation of the stimuli to target specific or general regions of interest. The relative position in the visual field, the color of the input, or the movement and speed of the light stimuli may determine which areas of the cortex are stimulated.

[0170] For example, the brain may include at least two portions that process a given type of visual stimulus: the primary visual cortex on the left side of the brain and the calcarine fissure on the right side of the brain. Each of these two portions may have one or more complex subportions that process a given type of visual stimulus. For example, the calcarine fissure may include a subportion called area V5, which may contain neurons that respond strongly to motion but may not register stationary objects. A subject with damage to area V5 may have motion blindness but otherwise normal vision. In another example, the primary visual cortex may include a subportion called area V4, which may contain neurons specialized for color perception. A subject with damage to area V4 may have color blindness and may only be able to perceive objects in shades of gray. In another example, the primary visual cortex may include a subportion called area V1, which contains neurons that respond strongly to contrast edges and help segment an image into separate objects.

[0171] Thus, the light-generation module 110 can command or cause the visual signaling component 150 to generate a type of still image or video, or to flicker or toggle between images configured to stimulate specific or predetermined portions of the brain or a particular cortex. For example, the light-generation module 110 can command or cause the visual signaling component 150 to generate an image of a human face to stimulate the fusiform face region, thereby promoting the sensory elicitation of neural oscillations in a subject with prosopagnosia or face loss. The light-generation module 110 can command or cause the visual signaling component 150 to generate a flickering image of a face to target this region of the subject's brain. In another example, the light-generation module 110 can command the visual signaling component 150 to generate an image containing edges or lines to stimulate neurons in the primary visual cortex that respond strongly to contrasting edges.

[0172] The NSS 105 may include, access, interface with, or otherwise communicate with at least one light adjustment module 115. The light adjustment module 115 may be designed and configured to measure or verify environmental variables (e.g., light intensity, timing, incident light, ambient light, eyelid condition, etc.) to adjust parameters associated with the visual signal, such as the frequency, amplitude, wavelength, intensity pattern, or other parameters of the visual signal. The light adjustment module 115 may automatically modify parameters of the visual signal based on profile information or feedback. The light adjustment module 115 may receive feedback information from a feedback monitor 135. The light adjustment module 115 may receive instructions or information from a side effect management module 130. The light adjustment module 115 may receive profile information from a profile manager 125.

[0173] The NSS 105 may include, access, interface with, or otherwise communicate with at least one unwanted frequency filtering module 120. The unwanted frequency filtering module 120 may be designed and configured to block, attenuate, reduce, or otherwise filter out frequencies of visual signals that are undesirable to prevent or reduce the brain from perceiving a certain amount of such visual signals. The unwanted frequency filtering module 120 may interface with, instruct, control, or otherwise communicate with the filtering component 155 to cause the filtering component 155 to block, attenuate, or otherwise reduce the effect of unwanted frequencies on neural oscillations.

[0174] The NSS 105 may include, access, interface with, or otherwise communicate with at least one profile manager 125. The profile manager 125 may be designed or configured to store, update, retrieve, or otherwise manage information related to one or more subjects associated with visual stimulus-evoked neural oscillations. The profile information may include, for example, past treatment information, past sensory elicitation of neural oscillations information, administration information, light wave parameters, feedback, physiological information, environmental information, or other data related to the systems and methods for sensory elicitation of neural oscillations.

[0175] The NSS 105 may include, access, interface with, or otherwise communicate with at least one side effect management module 130. The side effect management module 130 may be designed and configured to provide information to the light adjustment module 115 or the light generation module 110 to modify one or more parameters of the visual signal to reduce side effects, including, for example, nausea, migraines, fatigue, seizures, eye strain, and vision loss.

[0176] The side effect management module 130 can automatically command components of the NSS 105 to modify or change parameters of the visual signal. The side effect management module 130 can be configured with predetermined thresholds to reduce side effects. For example, the side effect management module 130 can be configured with a maximum duration of a pulse train, a maximum intensity of the light waves, a maximum amplitude, a maximum duty cycle of the pulse train (e.g., pulse width multiplied by the frequency of the pulse train), and a maximum number of treatments for sensory elicitation of neural oscillations over a period of time (e.g., 1 hour, 2 hours, 12 hours, or 24 hours).

[0177] The side effect management module 130 can modify the parameters of the visual signal in response to the feedback information. The side effect management module 130 can receive feedback from a feedback monitor 135. The side effect management module 130 can determine to adjust the parameters of the visual signal based on the feedback. The side effect management module 130 can compare the feedback with a threshold and determine to adjust the parameters of the visual signal.

[0178] The side effect management module 130 may be configured with or include a policy engine that applies policies or rules to the current visual signal or feedback and determines adjustments to the visual signal. For example, if the feedback indicates that the patient receiving the visual signal has a heart rate or pulse rate above a threshold, the side effect management module 130 may turn off the pulse train until the pulse rate stabilizes below the threshold or below a second threshold that is below the threshold.

[0179] The NSS 105 may include, access, interface with, or otherwise communicate with at least one feedback monitor 135. The feedback monitor may be designed and configured to receive feedback information from a feedback component 160. The feedback component 160 may include feedback sensors 605 such as, for example, a temperature sensor, a heart rate or pulse rate monitor, a physiological sensor, an ambient light sensor, an ambient temperature sensor, sleep state via actigraphy, a blood pressure monitor, a respiratory rate monitor, an electroencephalogram sensor, an EEG probe, an electro-oculogram (“EOG”) probe configured to measure corneal retinal standing potentials present between the front and back of a human eye, an accelerometer, a gyroscope, a motion detector, a proximity sensor, a camera, a microphone, or a photodetector.

[0180] In some embodiments, computing device 500 may include feedback component 160 or feedback sensor 605, as depicted in Figures 5C and 5D. For example, the feedback sensor of tablet 500 may include a front-facing camera capable of capturing an image of a person looking at light source 305.

[0181] 6A depicts one or more feedback sensors 605 provided on frame 400. In some embodiments, frame 400 may include one or more feedback sensors 605 provided on a portion of the frame, such as on a portion of bridge 420 or eye wire 415. Feedback sensor 605 may comprise or be coupled to light source 305. Feedback sensor 605 may be separate from light source 305.

[0182] The feedback sensor 605 can interact or communicate with the NSS 105. For example, the feedback sensor 605 can provide detected feedback information or data to the NSS 105 (e.g., to the feedback monitor 135). The feedback sensor 605 can provide data to the NSS 105 in real time, for example, as the feedback sensor 605 detects or senses information. The feedback sensor 605 can provide feedback information to the NSS 105 based on a time interval, such as 1 minute, 2 minutes, 5 minutes, 10 minutes, 1 hour, 2 hours, 4 hours, 12 hours, or 24 hours. The feedback sensor 605 can provide feedback information to the NSS 105 in response to a condition or event, such as a feedback measurement value above or below a threshold. The feedback sensor 605 can provide feedback information in response to a change in a feedback parameter. In some embodiments, the NSS 105 may ping, query, or send a request for information to the feedback sensor 605, and the feedback sensor 605 may provide feedback information in response to the ping, request, or query.

[0183] 6B illustrates a feedback sensor 605 placed or positioned on, on, or near a person's head. The feedback sensor 605 may include, for example, an EEG probe that detects brain wave activity.

[0184] Feedback monitor 135 may detect, receive, acquire, or otherwise determine feedback information from one or more feedback sensors 605. Feedback monitor 135 may provide the feedback information to one or more components of NSS 105 for further processing or storage. For example, profile manager 125 may update profile data structure 145 stored in data repository 140 with the feedback information. Profile manager 125 may associate the feedback information with an identifier of the patient or person receiving visual brain stimulation, as well as a timestamp and datestamp corresponding to the receipt or detection of the feedback information.

[0185] The feedback monitor 135 can determine the attention level. The attention level may refer to the focus provided for the light pulses used for brain stimulation. The feedback monitor 135 can determine the attention level using a variety of hardware and software techniques. The feedback monitor 135 can assign a score to the attention level (e.g., 1 to 10, where 1 is low attention and 10 is high attention, or vice versa, or 1 to 100, where 1 is low attention and 100 is high attention, or vice versa, or 0 to 1, where 0 is low attention and 1 is high attention, or vice versa), categorize the attention level (e.g., low, medium, high), grade the attention (e.g., A, B, C, D, or F), or otherwise provide an indication of the attention level.

[0186] In some cases, the feedback monitor 135 can track the person's eye movements to determine attention levels. The feedback monitor 135 can interface with a feedback component 160 that includes an eye tracker. The feedback monitor 135 can detect and record the person's eye movements (e.g., via the feedback component 160) and analyze the recorded eye movements to determine attention span or attention levels. The feedback monitor 135 can measure gaze, which may indicate or provide information related to potential attention. For example, the feedback monitor 135 can be configured (e.g., via the feedback component 160) using electrooculography (“EOG”) to measure skin potential around the eyes, which can indicate the direction the eyes are pointing relative to the head. In some embodiments, the EOG can include a system or device for stabilizing the head to prevent head movement in order to determine the direction of the eyes relative to the head. In some embodiments, the EOG can include or interface with a head tracker system to determine the position of the head and, in turn, the direction of the eyes relative to the head.

[0187] In some embodiments, feedback monitor 135 and feedback component 160 can determine or track eye direction or eye movement using video detection of pupil or corneal reflexes. For example, feedback component 160 can include one or more cameras or video cameras. Feedback component 160 can include an infrared source that transmits light pulses toward the eye. The light can be reflected by the eye. Feedback component 160 can detect the location of the reflection. Feedback component 160 can capture or record the location of the reflection. Feedback component 160 can perform image processing on the reflection to determine or calculate eye direction or eye gaze direction.

[0188] The feedback monitor 135 can determine the level of attention by comparing the eye direction or movement with the person's past eye direction or movement, nominal eye movement, or other past eye movement information. For example, if the eye is focused on the light pulses during the pulse train, the feedback monitor 135 can determine the level of attention is high. If the feedback monitor 135 determines that the eye is away from the pulse train for 25% of the pulse train, the feedback monitor 135 can determine the level of attention is moderate. If the feedback monitor 135 determines that eye movement occurred for more than 50% of the pulse train or that the eye was not focused on the pulse train for more than 50% of the pulse train, the feedback monitor 135 can determine the level of attention is low.

[0189] In some embodiments, system 100 may include a filter (e.g., filtering component 155) to control the spectral range of light emitted from the light source. In some embodiments, the light source includes a polarizer, filter, prism, or a light-responsive material that affects the emitted light, such as a photochromic material or electrochromic glass or plastic. Filtering component 155 can receive instructions from unwanted frequency filtering module 120 to block or attenuate one or more frequencies of light.

[0190] The filtering component 155 may include an optical filter that can selectively transmit light of a particular range of wavelengths or colors while blocking one or more other ranges of wavelengths or colors. An optical filter can change the magnitude or phase of an incident light wave for a range of wavelengths. The optical filter may include an absorption filter, or an interference filter or a dichroic filter. An absorption filter can capture the energy of photons and convert the electromagnetic energy of the light wave into internal energy of the absorber (e.g., thermal energy). The reduction in intensity of a light wave propagating through a medium due to absorption of some of the photons may be referred to as attenuation.

[0191] Interference or dichroic filters may include optical filters that reflect one or more spectral bands of light while transmitting others. Interference or dichroic filters may have a near-zero absorption coefficient for one or more wavelengths. Interference filters may be high-pass, low-pass, band-pass, or band-stop. Interference filters may include one or more thin layers of dielectric or metallic materials with different refractive indices.

[0192] In an exemplary embodiment, NSS 105 can interface with visual signaling component 150, filtering component 155, and feedback component 160. Visual signaling component 150 can include hardware or devices such as eyeglass frames 400 and one or more light sources 305. Filtering component 155 can include hardware or devices such as feedback sensors 605. Filtering component 155 can include hardware, materials, or chemicals such as polarized lenses, shutters, electrochromic or photochromic materials, etc.

[0193] Computing Environment 7A and 7B depict block diagrams of a computing device 700. As shown in FIGS. 7A and 7B, each computing device 700 includes a central processing unit 721 and a main memory unit 722. As shown in FIG. 7A, the computing device 700 may include a storage device 728, an installation device 716, a network interface 718, an I / O controller 723, display devices 724a-724n, a keyboard 726, and a pointing device 727, such as a mouse. The storage device 728 may include, without limitation, an operating system, software, and software of a neurostimulation system ("NSS") 701. The NSS 701 may include or refer to one or more of the NSS 105, NSS 905, or NSS 1605. Also, as shown in FIG. 7B, each computing device 700 may include additional optional elements, such as a memory port 703, a bridge 770, one or more input / output devices 730a-730n generally referred to using reference numeral 730, and a cache memory 740 in communication with the central processing unit 721.

[0194] Central processing unit 721 is any logic circuitry that responds to and processes instructions retrieved from main memory unit 722. In many embodiments, central processing unit 721 is provided by a microprocessor unit, such as those manufactured by Intel Corporation of Mountain View, California, Motorola Corporation of Schaumburg, Illinois, ARM processors (e.g., from ARM Holdings and those manufactured by ST, TI, ATMEL, etc.), and TEGRA systems-on-chips (SoCs) manufactured by Nvidia of Santa Clara, California, POWER7 processors manufactured by IBM of White Plains, New York, or those manufactured by Advanced Micro Devices of Sunnyvale, California, or field programmable gate arrays ("FPGAs") from Altera of San Jose, California, Intel Corporation of San Jose, California, Xlinix, or MicroSemi of Aliso Viejo, California, etc. Computing device 700 can be based on any of these processors or any other processor capable of operating as described herein. The central processing unit 721 can utilize instruction-level parallelism, thread-level parallelism, different levels of cache, and multi-core processors. Multi-core processors may include two or more processing units on a single computing component. Examples of multi-core processors include the AMD PHENOM IIX2, INTEL CORE i5, and INTEL CORE i7.

[0195] The main memory unit 722 may include one or more memory chips that store data and allow any memory location to be directly accessed by the microprocessor 721. The main memory unit 722 may be volatile and faster than the memory of storage 728. The main memory unit 722 may be dynamic random access memory (DRAM) or any variant including static random access memory (SRAM), burst SRAM or sync burst SRAM (BSRAM), fast page mode DRAM (FPM DRAM), extended DRAM (EDRAM), extended data output RAM (EDO RAM), extended data output DRAM (EDO DRAM), burst extended data output DRAM (BEDO DRAM), Single Data Rate Synchronous DRAM (SDR SDRAM), Double Data Rate SDRAM (DDR SDRAM), Direct Rambus DRAM (DRDRAM), or Extreme Data Rate DRAM (XDR DRAM). In some embodiments, the main memory 722 or storage 728 may be nonvolatile, such as nonvolatile read-access memory (NVRAM), flash memory nonvolatile static RAM (nvSRAM), ferroelectric RAM (FeRAM), magnetoresistive RAM (MRAM), phase-change memory (PRAM), conductive bridge RAM (CBRAM), silicon-oxide-nitride-oxide-silicon (SONOS), resistive RAM (RRAM), racetrack, nanoRAM (NRAM), or millipede memory. The main memory 722 may be based on any of the memory chips described above or any other available memory chips that can operate as described herein. In the embodiment shown in FIG. 7A, the processor 721 communicates with the main memory 722 via a system bus 750 (described in more detail below). FIG. 7B shows an embodiment of a computing device 700 in which the processor communicates directly with the main memory 722 via memory port 703. For example, in FIG. 7B, the main memory 722 may be DRAM.

[0196] FIG. 7B illustrates an embodiment in which the main processor 721 communicates directly with the cache memory 740 via a secondary bus, sometimes referred to as a backside bus. In another embodiment, the main processor 721 communicates with the cache memory 740 using a system bus 750. The cache memory 740 typically has a faster response time than the main memory 722 and is typically provided by SRAM, BSRAM, or EDRAM. In the embodiment illustrated in FIG. 7B, the processor 721 communicates with various I / O devices 730 via a local system bus 750. Various buses, including a PCI bus, a PCI-X bus, or a PCI-Express bus, or NuBus, can be used to connect the central processing unit 721 to any of the I / O devices 730. In an embodiment in which the I / O device is a video display 724, the processor 721 communicates with the display 724 or an I / O controller 723 for the display 724 using an Advanced Graphics Port (AGP). Figure 7B shows an embodiment of a computer 700 in which a main processor 721 communicates directly with an I / O device 730b or another processor 721' via HYPERTRANSPORT, RAPIDIO, or INFINIBAND communication technologies. Figure 7B also shows an embodiment in which local bus and direct communication are mixed, with processor 721 communicating with an I / O device 730a using a local interconnect bus while communicating directly with an I / O device 730b.

[0197] A wide variety of I / O devices 730a-730n may be present in the computing device 700. Input devices may include a keyboard, mouse, trackpad, trackball, touchpad, touch mouse, multi-touch pad and touch mouse, microphone (analog or MEMS), multi-array microphone, drawing tablet, camera, single lens reflex camera (SLR), digital SLR (DSLR), CMOS sensor, CCD, accelerometer, inertial measurement unit, infrared optical sensor, pressure sensor, magnetometer sensor, angular rate sensor, depth sensor, proximity sensor, ambient light sensor, gyroscope sensor, or other sensor. Output devices may include a video display, a graphics display, speakers, headphones, inkjet printer, laser printer, and 3D printer.

[0198] Devices 730a-730n may include a combination of multiple input or output devices, including, for example, Microsoft KINECT, Nintendo Wiimote for the WII, Nintendo WII U GAMEPAD, or Apple IPHONE®. Some devices 730a-730n combine some of their inputs and outputs to allow gesture recognition input. Some devices 730a-730n offer facial recognition, which can be used as input for different purposes, including authentication and other commands. Some devices 730a-730n offer voice recognition and voice input, including, for example, Microsoft KINECT, SIRI for the IPHONE® by Apple, Google Now, or Google Voice Search.

[0199] Additional devices 730a-730n have both input and output capabilities, including, for example, haptic feedback devices, touchscreen displays, or multi-touch displays. Touchscreens, multi-touch displays, touchpads, touch mice, or other touch-sensing devices can sense touch using different technologies, including, for example, capacitive, surface capacitive, projected capacitive touch (PCT), in-cell capacitive, resistive, infrared, waveguide, distributed signal touch (DST), in-cell optical, surface acoustic wave (SAW), bending wave touch (BWT), or force-based sensing technologies. Some multi-touch devices allow for two or more points of contact with the surface, enabling advanced functionality including, for example, pinch, spread, rotate, scroll, or other gestures. Some touchscreen devices, including, for example, the Microsoft PIXELSENSE or Multi-Touch Collaboration Wall, may have larger surfaces, such as tabletops or wall-mounted surfaces, and can also interact with other electronic devices. Some I / O devices 730a-730n, display devices 724a-724n, or devices may be augmented reality devices. The I / O devices may be controlled by an I / O controller 721, as shown in FIG. 7A. The I / O controller 721 may control one or more I / O devices, such as keyboard 126 and a pointing device 727, such as a mouse or optical pen. Additionally, the I / O devices may provide storage and / or installation media 116 for computing device 700. In yet other embodiments, computing device 700 may provide a USB connection (not shown) for accepting a handheld USB storage device. In further embodiments, I / O device 730 may be a bridge between system bus 750 and an external communication bus, such as a USB bus, a SCSI bus, a FireWire bus, an Ethernet bus, a Gigabit Ethernet bus, a Fibre Channel bus, or a Thunderbolt bus.

[0200] In some embodiments, display devices 724a-724n can be connected to the I / O controller 721. The display devices can include, for example, a liquid crystal display (LCD), a thin film transistor LCD (TFT-LCD), a blue phase LCD, an electronic paper (e-ink) display, a flexible display, a light emitting diode display (LED), a digital light processing (DLP) display, a liquid crystal on silicon (LCOS) display, an organic light emitting diode (OLED) display, an active matrix organic light emitting diode (AMOLED) display, a liquid crystal laser display, a time-domain optical shutter (TMOS) display, or a 3D display. Examples of 3D displays can use, for example, stereoscopic vision, polarized filters, active shutters, or autostereoscopy. Additionally, the display devices 724a-724n can be head-mounted displays (HMDs). In some embodiments, the display devices 724a-724n or corresponding I / O controllers 723 may be controlled through an OPENGL or DIRECTX API or other graphics library, or may have hardware support for an OPENGL or DIRECTX API or other graphics library.

[0201] In some embodiments, computing device 700 may include or be connected to multiple display devices 724a-724n, each of which may be the same or different types and / or forms. Accordingly, any of I / O devices 730a-730n and / or I / O controller 723 may include any type and / or form of suitable hardware, software, or combination of hardware and software to support, enable, or provide for the connection and use of multiple display devices 724a-724n by computing device 700. For example, computing device 700 may include any type and / or form of video adapter, video card, driver, and / or library to interface with, communicate with, connect to, or otherwise use display devices 724a-724n. In one embodiment, a video adapter may include multiple connectors for interfacing with multiple display devices 724a-724n. In other embodiments, computing device 700 may include multiple video adapters, each connected to one or more of display devices 724a-724n. In some embodiments, any portion of the operating system of computing device 700 can be configured to use multiple displays 724a-724n. In other embodiments, one or more of display devices 724a-724n may be provided by one or more other computing devices 700a or 700b connected to computing device 700 via network 140. In some embodiments, software can be designed and configured to use a display device of another computer as a second display device 724a for computing device 700. For example, in one embodiment, an Apple iPad® can connect to computing device 700 and use the display of device 700 as an additional display screen that can be used as an extended desktop.

[0202] Referring again to FIG. 7A , the computing device 700 may include a storage device 728 (e.g., one or more hard disk drives or a redundant array of independent disks) for storing an operating system or other related software, and for storing application software programs, such as any programs related to software for the NSS. Examples of the storage device 728 include a hard disk drive (HDD), an optical drive, including a CD drive, DVD drive, or Blu-ray drive, a solid-state drive (SSD), a USB flash drive, or any other device suitable for storing data. Some storage devices may include multiple volatile and non-volatile memories, including, for example, a solid-state hybrid drive that combines a hard disk with a solid-state cache. Some storage devices 728 may be non-volatile, volatile, or read-only. Some storage 728 may be internal and connected to the computing device 700 via a bus 750. Some storage devices 728 may be external and connected to the computing device 700 via an I / O device 730 that provides an external bus. Some storage 728 may be connected to the computing device 700 over a network via the network interface 718, including, for example, a remote disk for the Macbook Air by Apple. Some client devices 700 do not require a non-volatile storage device 728 and may be thin clients or zero clients 202. Some storage devices 728 may also be used as installation devices 716 and may be suitable for installing software and programs. Additionally, operating systems and software may be run from bootable media, such as a bootable CD, for example, a bootable CD for GNU / Linux available as a GNU / Linux distribution from knoppix.net.

[0203] Additionally, the computing device 700 can install software or applications from an application distribution platform. Examples of application distribution platforms include the App Store for iOS provided by Apple, Inc., the Mac App Store provided by Apple, Inc., Google PLAY for Android OS provided by Google Inc., the CHROME Webstore for CHROME OS provided by Google Inc., and the Amazon Appstore for Android OS and Kindle Fire provided by Amazon.com, Inc.

[0204] Additionally, computing device 700 may include a network interface 718 for interfacing to network 140 through various connections, including, but not limited to, standard telephone line LAN or WAN links (e.g., 802.11, T1, T3, Gigabit Ethernet, InfiniBand), broadband connections (e.g., ISDN, Frame Relay, ATM, Gigabit Ethernet, Ethernet-over-SONET, ADSL, VDSL, BPON, GPON, fiber optic including FiOS), wireless connections, or some combination of any or all of the above. Connections can be established using various communication protocols (e.g., TCP / IP, Ethernet, ARCNET, SONET, SDH, Fiber Distributed Data Interface (FDDI), IEEE 802.11a / b / g / n / ac CDMA, GSM, WiMax, and direct asynchronous connections). In one embodiment, computing device 700 communicates with other computing devices 700′ via any type and / or form of gateway or tunneling protocol, such as Secure Sockets Layer (SSL) or Transport Layer Security (TLS), or the Citrix Gateway protocol manufactured by Citrix Systems, Inc. of Fort Lauderdale, Fla. Network interface 118 may include an internal network adapter, a network interface card, a PCMCIA network card, an EXPRESSCARD network card, a card bus network adapter, a wireless network adapter, a USB network adapter, a modem, or any other device suitable for interfacing computing device 700 to any type of network capable of performing the operations described herein.

[0205] 7A type of computing device 700 can operate under the control of an operating system that controls the scheduling of tasks and access to system resources. Computing device 700 can run any operating system, such as any version of the MICROSOFT WINDOWS® operating system, different releases of Unix and Linux® operating systems, any version of MAC OS for Macintosh computers, any embedded operating system, any real-time operating system, any open source operating system, any proprietary operating system, any operating system for mobile computing devices, or any other operating system capable of running on a computing device and performing the operations described herein. Exemplary operating systems include, but are not limited to, WINDOWS® 7000, WINDOWS® Server 2012, WINDOWS® CE, WINDOWS® Phone, WINDOWS® XP, WINDOWS® VISTA, and WINDOWS® 7, WINDOWS® RT, and WINDOWS® 8 (all manufactured by Microsoft Corporation of Raymond, Washington), MAC OS and iOS manufactured by Apple, Inc. of Cupertino, California, as well as freely available operating systems such as the Linux® Mint distribution ("distro") or Ubuntu distributed by Canonical Ltd. of London, United Kingdom, or Unix or other Unix-like derivative operating systems, and Android designed by Google of Mountain View, California, among others.For example, some operating systems, including CHROME OS by Google, can be used on zero clients or thin clients, including, for example, CHROMEBOOKS.

[0206] Computer system 700 may be any workstation, telephone, desktop computer, laptop or notebook computer, netbook, Ultrabook, tablet, server, handheld computer, mobile phone, smartphone or other portable telecommunications device, media playback device, gaming system, mobile computing device, or other type and / or form of computing device, telecommunications device, or media device capable of communications. Computer system 700 has sufficient processor power and memory capacity to perform the operations described herein. In some embodiments, computing device 700 may have different processors, operating systems, and input devices consistent with the device. For example, Samsung GALAXY smartphones operate under the control of the Android operating system developed by Google, Inc. GALAXY smartphones receive input via a touch interface.

[0207] In some embodiments, computing device 700 is a gaming system. For example, computer system 700 may include a PLAYSTATION 3, or PERSONAL PLAYSTATION PORTABLE (PSP), PLAYSTATION VITA device manufactured by Sony Corporation of Tokyo, Japan, a NINTENDO DS, NINTENDO 3DS, NINTENDO WII, or NINTENDO WII U device manufactured by Nintendo Co., Ltd. of Kyoto, Japan, an XBOX® 360 device manufactured by Microsoft Corporation of Redmond, Washington, or an OCULUS RIFT or OCULUS VR device manufactured by OCULUS VR, LLC of Menlo Park, California.

[0208] In some embodiments, computing device 700 is a digital audio player, such as the Apple IPOD, IPOD Touch, and IPOD NANO device lines manufactured by Apple Computer of Cupertino, California. Some digital audio players may have other functionality, including, for example, a gaming system or any functionality made available by applications from a digital application distribution platform. For example, the IPOD Touch has access to the Apple App Store. In some embodiments, computing device 700 is a portable media player or digital audio player that supports file formats, including, but not limited to, MP3, WAV, M4A / AAC, WMA Protected AAC, AIFF, Audible audiobooks, Apple Lossless audio file formats, and .mov, .m4v, and .mp4 MPEG-4 (H.264 / MPEG-4 AVC) video file formats.

[0209] In some embodiments, computing device 700 is a tablet, such as the IPAD® line of devices by Apple, the GALAXY TAB family of devices by Samsung, or a KINDLE FIRE by Amazon.com, Inc. of Seattle, Washington. In other embodiments, computing device 700 is an eBook reader, such as the KINDLE family of devices by Amazon.com, or the NOOK family of devices by Noble, Inc. of New York City, New York.

[0210] In some embodiments, communication device 700 includes a combination of devices, such as, for example, a smartphone combined with a digital audio player or portable media player. For example, one of these embodiments is a smartphone, such as, for example, the IPHONE® family of smartphones manufactured by Apple, Inc., the Samsung GALAXY family of smartphones manufactured by Samsung, Inc., or the Motorola DROID family of smartphones. In yet another embodiment, communication device 700 is a laptop or desktop computer equipped with a web browser and a microphone and speaker system, e.g., a telephone headset. In these embodiments, communication device 700 is web-enabled and can receive and initiate calls. In some embodiments, the laptop or desktop computer also includes a webcam or other video capture device to enable video chat and video calling.

[0211] In some embodiments, the status of one or more machines 700 in a network is monitored, typically as part of network management. In one of these embodiments, the status of a machine may include determining load information (e.g., the number of processes, CPU, and memory utilization on the machine), port information (e.g., the number of available communication ports and port addresses), or session status (e.g., the duration and type of process, and whether the process is active or idle). In another of these embodiments, this information may be determined by multiple metrics that may be applied, at least in part, to determining load distribution, network traffic management, and network failure recovery, as well as any aspect of the operation of the present solution described herein. Aspects of the operating environment and components described above will become apparent in the context of the systems and methods disclosed herein.

[0212] Methods for nerve stimulation FIG. 8 is a flow diagram of a method for eliciting visual stimulation through neural oscillations, according to one embodiment. Method 800 can be performed by one or more systems, components, modules, or elements depicted in FIGS. 1-7B, including, for example, a neural stimulation system (NSS). Briefly, in overview, the NSS can identify a visual signal to provide at block 805. At block 810, the NSS can generate and transmit the identified visual signal. At 815, the NSS can receive or determine feedback related to neural activity, physiological activity, environmental parameters, or device parameters. At 820, the NSS can manage, control, or adjust the visual signal based on the feedback.

[0213] NSS working with frames The NSS 105 can operate in conjunction with a frame 400 that includes a light source 305, as shown in Figure 4A. The NSS 105 can operate in conjunction with a frame 400 that includes a light source 305 and a feedback sensor 605, as shown in Figure 6A. The NSS 105 can operate in conjunction with a frame 400 that includes at least one shutter 430, as shown in Figure 4B. The NSS 105 can operate in conjunction with a frame 400 that includes at least one shutter 430 and a feedback sensor 605.

[0214] In operation, a user of the frame 400 can wear the frame 400 on their head so that the eyewires 415 surround or substantially surround their eyes. In some cases, the user can indicate to the NSS 105 that the eyeglass frame 400 is being worn and that the user is ready to receive the sensory elicitation of neural oscillations. The indication can include an instruction, command, selection, input, or other indication via an input / output interface, such as a keyboard 726, a pointing device 727, or other I / O devices 730a-n. The indication can be a motion-based indication, a visual indication, or an audio-based indication. For example, the user can provide a voice command indicating that the user is ready to receive the sensory elicitation of brainwave vibrations.

[0215] In some cases, the feedback sensor 605 can determine that the user is ready to receive the sensory elicitation of neural oscillations. The feedback sensor 605 can detect that the eyeglass frame 400 is placed on the user's head. The NSS 105 can receive motion data, acceleration data, gyroscope data, temperature data, or capacitive touch data to determine that the frame 400 is placed on the user's head. Received data, such as motion data, can indicate that the frame 400 has been picked up and placed on the user's head. Temperature data can measure the temperature of or near the frame 400, which can indicate that the frame is on the user's head. In some cases, the feedback sensor 605 can perform eye tracking to determine the level of attention the user is paying to the light source 305 or the feedback sensor 605. The NSS 105 can detect that the user is ready in response to determining that the user is paying a high level of attention to the light source 305 or the feedback sensor 605. For example, gazing, gazing, or looking in the direction of the light source 305 or feedback sensor 605 can indicate that the user is ready to receive sensory elicitation of neural oscillations.

[0216] Thus, the NSS 105 can detect or determine that the frame 400 is being worn and that the user is ready, or the NSS 105 can receive an indication or confirmation from the user that the user is wearing the frame 400 and is ready to receive sensory elicitation of neural oscillations. Upon determining that the user is ready, the NSS 105 can initialize the sensory elicitation of neural oscillations process. In some embodiments, the NSS 105 can access the profile data structure 145. For example, the profile manager 125 can query the profile data structure 145 to determine one or more parameters for the external visual stimulation to be used in the sensory elicitation of neural oscillations process. The parameters may include, for example, the type of visual stimulation, the intensity of the visual stimulation, the frequency of the visual stimulation, the duration of the visual stimulation, or the wavelength of the visual stimulation. The profile manager 125 can query the profile data structure 145 to obtain past sensory elicitation of neural oscillations information, such as previous visual stimulation sessions. The profile manager 125 can perform a lookup in the profile data structure 145. The profile manager 125 may perform a lookup using the user's name, a user identifier, location information, fingerprints, biometric identifiers, retinal scans, voice recognition and authentication, or other identification techniques.

[0217] The NSS 105 can determine the type of external visual stimulus based on the hardware 400. The NSS 105 can determine the type of external visual stimulus based on the type of available light source 305. For example, if the light source 305 includes a monochromatic LED that produces light waves in the red spectrum, the NSS 105 can determine that the type of visual stimulus includes pulses of light transmitted by the light source. However, if the frame 400 does not include an active light source 305 but instead includes one or more shutters 430, the NSS 105 can determine that the light source is sunlight or ambient light that is modulated as it enters the user's eye through the plane formed by the eyewire 415.

[0218] In some embodiments, the NSS 105 can determine the type of external visual stimulus based on past sensory elicitation sessions of neural oscillations. For example, the profile data structure 145 can be pre-configured with information about the type of visual signaling component 150.

[0219] The NSS 105 can determine the modulation frequency of the pulse train or ambient light via the profile manager 125. For example, the NSS 105 can determine from the profile data structure 145 that the modulation frequency for the external visual stimulus can be set to 40 Hz. Depending on the type of visual stimulus, the profile data structure 145 can further indicate the pulse length, intensity, wavelength of the light waves forming the light pulse, or duration of the pulse train.

[0220] In some cases, the NSS 105 can determine or adjust one or more parameters of the external visual stimulus. For example, the NSS 105 can determine the level or amount of ambient light (e.g., via the feedback component 160 or the feedback sensor 605). The NSS 105 can establish, initialize, set, or adjust the intensity or wavelength of the light pulses (e.g., via the light adjustment module 115 or the side effect management module 130). For example, the NSS 105 can determine that there is a low level of ambient light. Low levels of ambient light can cause the user's pupils to dilate. Based on detecting the low level of ambient light, the NSS 105 can determine that the user's pupils are likely dilated. In response to determining that the user's pupils are likely dilated, the NSS 105 can set a lower level of intensity for the pulse train. Additionally, the NSS 105 can use light waves with a longer wavelength (e.g., red), which can reduce eye strain.

[0221] In some embodiments, NSS 105 can automatically and periodically adjust the intensity or color of the light pulses by monitoring ambient light levels (e.g., via feedback monitor 135 and feedback component 160) throughout the process of sensory elicitation of neural oscillations. For example, if a user initiates the process of sensory elicitation of neural oscillations when high levels of ambient light are present, NSS 105 can initially set a higher intensity level of the light pulses and use a color including light waves with lower wavelengths (e.g., blue). However, in some embodiments in which ambient light levels decrease throughout the process of sensory elicitation of neural oscillations, NSS 105 can automatically detect the decrease in ambient light and, in response to the detection, adjust or lower the intensity while increasing the wavelength of the light waves. NSS 105 can adjust the light pulses to provide a high contrast ratio to facilitate the elicitation of neural oscillations.

[0222] In some embodiments, the NSS 105 can monitor or measure physiological conditions (e.g., via feedback monitor 135 and feedback component 160) to set or adjust parameters of the light waves. For example, the NSS 105 can adjust or set parameters of the light waves by monitoring or measuring the level of pupil dilation. In some embodiments, the NSS 105 can set or adjust parameters of the light waves by monitoring or measuring heart rate, pulse rate, blood pressure, body temperature, sweating, or brain activity.

[0223] In some embodiments, the NSS 105 can be pre-configured to initially transmit light pulses at the lowest light wave intensity setting (e.g., low light wave amplitude or high light wave wavelength) and gradually increase the intensity (e.g., increase the light wave amplitude or decrease the light wave wavelength) while monitoring feedback until an optimal light intensity is reached. The optimal light intensity can refer to the highest intensity that is not associated with physiological side effects such as blindness, seizures, heart attacks, migraines, or other discomfort. The NSS 105 can identify adverse side effects of external visual stimuli by monitoring physiological symptoms (e.g., via side effect management module 130) and can accordingly adjust the external visual stimuli (e.g., via light adjustment module 115) to reduce or eliminate the adverse side effects.

[0224] In some embodiments, the NSS 105 can adjust parameters of the light waves or light pulses (e.g., via the light adjustment module 115) based on the attention level. For example, during the sensory elicitation process of neural oscillations, the user may become bored, lose concentration, fall asleep, or otherwise not pay attention to the light pulses. Not paying attention to the light pulses can reduce the effectiveness of the sensory elicitation process of neural oscillations, leading to neurons oscillating at a frequency different from the desired modulation frequency of the light pulses.

[0225] The NSS 105 can detect the level of attention the user is paying to the light pulse using the feedback monitor 135 and one or more feedback components 160. The NSS 105 can perform eye tracking to determine the level of attention the user is paying to the light pulse based on the gaze direction of the retina or pupil. The NSS 105 can measure eye movement to determine the level of attention the user is paying to the light pulse. The NSS 105 can provide a survey or prompt asking for user feedback indicating the level of attention the user is paying to the light pulse. In response to determining that the user is not paying a sufficient amount of attention to the light pulse (e.g., a level of eye movement above a threshold or a gaze direction outside the direct field of view of the light source 305), the light adjustment module 115 can alter parameters of the light source to gain the user's attention. For example, the light adjustment module 115 can increase the intensity of the light pulse, adjust the color of the light pulse, or change the duration of the light pulse. The light adjustment module 115 can randomly alter one or more parameters of the light pulse. The light adjustment module 115 can initiate an attention-requesting light sequence configured to regain the user's attention. For example, the light sequence can include changes in color or intensity of light pulses in a predetermined, random, or pseudo-random pattern. The attention-requesting light sequence can enable or disable different light sources if the visual signaling component 150 includes multiple light sources. Thus, the light adjustment module 115 can interact with the feedback monitor 135 to determine the level of attention the user pays to the light pulses and adjust the light pulses to regain the user's attention if the level of attention falls below a threshold.

[0226] In some embodiments, the light adjustment module 115 may change or adjust one or more parameters of the light pulses or waves at predetermined time intervals (e.g., every 5 minutes, every 10 minutes, every 15 minutes, or every 20 minutes) to restore or maintain the user's level of attention.

[0227] In some embodiments, the NSS 105 can filter, block, attenuate, or remove unwanted visual extraneous stimuli (e.g., via the unwanted frequency filtering module 120). Unwanted visual extraneous stimuli can include, for example, unwanted modulation frequencies of light waves, unwanted intensities, or unwanted wavelengths. The NSS 105 can consider a modulation frequency of a pulse train to be unwanted if it differs from, or differs substantially (e.g., by 1%, 2%, 5%, 10%, 15%, 20%, 25%, or more than 25%) from, a desired frequency.

[0228] For example, a desired modulation frequency for sensory elicitation of neural oscillations may be 40 Hz. However, modulation frequencies of, for example, 15 Hz or 90 Hz may interfere with the sensory elicitation of neural oscillations. Therefore, the NSS 105 can filter out light pulses or light waves corresponding to modulation frequencies of 15 Hz or 90 Hz.

[0229] In some embodiments, the NSS 105 can detect, via the feedback component 160, the presence of light pulses from an ambient light source corresponding to an unwanted modulation frequency of 20 Hz. The NSS 105 can further determine the wavelength of the light waves of the light pulses corresponding to the unwanted modulation frequency. The NSS 105 can instruct the filtering component 155 to filter out the wavelength corresponding to the unwanted modulation frequency. For example, the wavelength corresponding to the unwanted modulation frequency may correspond to blue. The filtering component 155 can include an optical filter that can selectively transmit light of a particular range of wavelengths or colors while blocking one or more other ranges of wavelengths or colors. The optical filter can modulate the magnitude or phase of the incident light waves for a range of wavelengths. For example, the optical filter can be configured to block, reflect, or attenuate blue light waves corresponding to the unwanted modulation frequency. The light conditioning module 115 can modify the wavelength of the light waves generated by the light generating module 110 and the light source 305 so that the desired modulation frequency is not blocked or attenuated by the unwanted frequency filtering module 120.

[0230] NSS works with virtual reality headsets The NSS 105 can operate in conjunction with a virtual reality headset 401 that includes a light source 305, as shown in FIG. 4C. The NSS 105 can operate in conjunction with a virtual reality headset 401 that includes a light source 305 and a feedback sensor 605, as shown in FIG. 4C. In some embodiments, the NSS 105 can determine that the hardware of the visual signaling component 150 includes a virtual reality headset 401. In response to determining that the visual signaling component 150 includes a virtual reality headset 401, the NSS 105 can determine that the light source 305 includes a display screen of a smartphone or other mobile computing device.

[0231] The virtual reality headset 401 can provide an immersive and uninterrupted visual stimulation experience. The virtual reality headset 401 can provide an augmented reality experience. The feedback sensor 605 can capture photos or videos of the physical real world to provide the augmented reality experience. The unwanted frequency filtering module 120 can filter out unwanted modulation frequencies before projecting, displaying, or providing the augmented reality image via the display screen 305.

[0232] In operation, a user of the frame 401 can wear the frame 401 on their head such that the virtual reality headset's eye sockets 465 cover the user's eyes. The virtual reality headset's eye sockets 465 can encircle or substantially encircle the eyes. The user can secure the virtual reality headset 401 to the user's headset using one or more straps 455 or 460, a skull cap, or other fastening mechanism. In some cases, the user can indicate to the NSS 105 that the virtual reality headset 401 is positioned and secured on the user's head and that the user is ready to receive the sensory elicitation of neural oscillations. The indication can include an instruction, command, selection, input, or other indication via an input / output interface, such as the keyboard 726, the pointing device 727, or other I / O devices 730a-n. The indication can be an action-based indication, a visual indication, or an audio-based indication. For example, the user can provide a voice command indicating that the user is ready to receive the sensory elicitation of neural oscillations.

[0233] In some cases, the feedback sensor 605 can determine that the user is ready to receive the sensory elicitation of neural oscillations. The feedback sensor 605 can detect that the virtual reality headset 401 is placed on the user's head. The NSS 105 can receive motion data, acceleration data, gyroscope data, temperature data, or capacitive touch data to determine that the virtual reality headset 401 is placed on the user's head. Received data, such as motion data, can indicate that the virtual reality headset 401 has been picked up and placed on the user's head. Temperature data can measure the temperature of or near the virtual reality headset 401, which can indicate that the virtual reality headset 401 is on the user's head. In some cases, the feedback sensor 605 can perform eye tracking to determine the level of attention the user is paying to the light source 305 or the feedback sensor 605. The NSS 105 can detect that the user is ready in response to determining that the user is paying a high level of attention to the light source 305 or the feedback sensor 605. For example, gazing, gazing, or looking in the direction of the light source 305 or feedback sensor 605 can indicate that the user is ready to receive sensory elicitation of neural oscillations.

[0234] In some embodiments, a sensor 605 in strap 455, strap 460, or eye socket 605 can detect when virtual reality headset 401 is secured, placed, or positioned on the user's head. Sensor 605 can be a touch sensor that senses or detects contact with the user's head.

[0235] Thus, the NSS 105 can detect or determine that the virtual reality headset 401 is being worn and that the user is ready, or the NSS 105 can receive an indication or confirmation from the user that the user is wearing the virtual reality headset 401 and that the user is ready to receive sensory elicitation of neural oscillations. Upon determining that the user is ready, the NSS 105 can initialize the sensory elicitation of neural oscillations process. In some embodiments, the NSS 105 can access the profile data structure 145. For example, the profile manager 125 can query the profile data structure 145 to determine one or more parameters for the external visual stimulation to be used in the sensory elicitation of neural oscillations process. The parameters may include, for example, the type of visual stimulation, the intensity of the visual stimulation, the frequency of the visual stimulation, the duration of the visual stimulation, or the wavelength of the visual stimulation. The profile manager 125 can query the profile data structure 145 to obtain past sensory elicited neural oscillation information, such as previous visual stimulation sessions. The profile manager 125 can perform a lookup in the profile data structure 145. The profile manager 125 may perform a lookup using the user's name, a user identifier, location information, fingerprints, biometric identifiers, retinal scans, voice recognition and authentication, or other identification techniques.

[0236] The NSS 105 can determine the type of external visual stimulus based on the hardware 401. The NSS 105 can determine the type of external visual stimulus based on the type of light source 305 available. For example, if the light source 305 includes a smartphone or display device, the visual stimulus can include turning the display screen of the display device on and off. The visual stimulus can include displaying a pattern on the display device 305, such as a checkerboard pattern, which can alternate according to a desired frequency modulation. The visual stimulus can include light pulses generated by a light source 305, such as an LED, located within the enclosure of the virtual reality headset 401.

[0237] If the virtual reality headset 401 provides an augmented reality experience, the visual stimuli may include overlaying content on a display device and modulating the overlaid content at a desired modulation frequency. For example, the virtual reality headset 401 may include a camera 605 that captures the real physical world. While displaying the captured image of the real physical world, the NSS 105 may also display content modulated at a desired modulation frequency. The NSS 105 may overlay the content modulated at the desired modulation frequency. Alternatively, the NSS 105 may modify, manipulate, modulate, or adjust a portion of the display screen or a portion of the augmented reality to generate or provide the desired modulation frequency.

[0238] For example, the NSS 105 can modify one or more pixels based on a desired modulation frequency. The NSS 105 can turn pixels on and off based on the modulation frequency. The NSS 105 can turn off pixels in any portion of the display device. The NSS 105 can turn pixels on and off in a pattern. The NSS 105 can turn pixels on and off in the direct field of view or the peripheral field of view. The NSS 105 can track or detect the eye's gaze direction and turn on and off pixels in the gaze direction such that the light pulse (or modulation) is in the direct field of view. Thus, by modulating overlaid content or otherwise manipulating an augmented reality display or other image provided via a display device in the virtual reality headset 401, light pulses or light flashes can be generated having a modulation frequency configured to facilitate the sensory elicitation of neural oscillations.

[0239] NSS 105 can determine the modulation frequency of the pulse train or ambient light via profile manager 125. For example, NSS 105 can determine from profile data structure 145 that the modulation frequency for the external visual stimulus can be set to 40 Hz. Depending on the type of visual stimulus, profile data structure 145 can further indicate the number of pixels to modulate, the intensity of the pixels to modulate, the pulse length, the intensity, the wavelength of the light waves forming the light pulse, or the duration of the pulse train.

[0240] In some cases, the NSS 105 may determine or adjust one or more parameters of the external visual stimulus. For example, the NSS 105 may determine (e.g., via the feedback component 160 or the feedback sensor 605) the level or amount of light in the captured image used to provide the augmented reality experience. The NSS 105 may establish, initialize, set, or adjust (e.g., via the light adjustment module 115 or the side effect management module 130) the intensity or wavelength of the light pulses based on the light level of the image data corresponding to the augmented reality experience. For example, the NSS 105 may determine that the light level of the augmented reality display is low because it may be dark outside. The low light level of the augmented reality display may cause the user's pupils to dilate. The NSS 105 may determine that the user's pupils are likely dilated based on detecting the low level of light. In response to determining that the user's pupils are likely dilated, the NSS 105 may set the level of the light pulses providing the modulation frequency or the intensity of the light source to a low level. Additionally, the NSS 105 may use light waves with longer wavelengths (eg, red), which may reduce strain on the eyes.

[0241] In some embodiments, NSS 105 can automatically and periodically adjust the intensity or color of the light pulses by monitoring the light level (e.g., via feedback monitor 135 and feedback component 160) throughout the sensory elicitation of neural oscillations. For example, if a user initiates the sensory elicitation of neural oscillations when there is a high level of ambient light, NSS 105 can initially set the intensity level of the light pulses higher and use a color including light waves with lower wavelengths (e.g., blue). However, as the light level decreases throughout the sensory elicitation of neural oscillations, NSS 105 can automatically detect the decrease in light and, in response, adjust or lower the intensity while increasing the wavelength of the light waves. NSS 105 can adjust the light pulses to provide a high contrast ratio to facilitate the sensory elicitation of neural oscillations.

[0242] In some embodiments, the NSS 105 can monitor or measure physiological conditions (e.g., via feedback monitor 135 and feedback component 160) to set or adjust parameters of the light pulses while the user is wearing the virtual reality headset 401. For example, the NSS 105 can adjust or set parameters of the light waves by monitoring or measuring the level of pupil dilation. In some embodiments, the NSS 105 can set or adjust parameters of the light waves by monitoring or measuring heart rate, pulse rate, blood pressure, body temperature, sweating, or brain activity via one or more feedback sensors in the virtual reality headset 401 or other feedback sensors.

[0243] In some embodiments, the NSS 105 can be pre-configured via the display device 305 to initially transmit light pulses at the lowest intensity setting (e.g., low amplitude or high wavelength) and gradually increase the intensity (e.g., increase the amplitude or decrease the wavelength) while monitoring feedback until an optimal light intensity is reached. The optimal light intensity may refer to the highest intensity that is not associated with physiological side effects, such as blindness, seizures, heart attacks, migraines, or other discomfort. The NSS 105 can identify adverse side effects of the external visual stimuli by monitoring physiological symptoms (e.g., via the side effect management module 130) and can adjust the external visual stimuli accordingly (e.g., via the light adjustment module 115) to reduce or eliminate the adverse side effects.

[0244] In some embodiments, the NSS 105 can adjust parameters of the light waves or light pulses (e.g., via the light adjustment module 115) based on the attention level. For example, during the sensory elicitation process of neural oscillations, the user may become bored, lose concentration, fall asleep, or otherwise stop paying attention to the light pulses generated via the display screen 305 of the virtual reality headset 401. Not paying attention to the light pulses may reduce the effectiveness of the sensory elicitation process of neural oscillations, leading to neurons oscillating at a frequency different from the desired modulation frequency of the light pulses.

[0245] The NSS 105 can detect the level of attention the user is paying or directing to the light pulse using the feedback monitor 135 and one or more feedback components 160 (e.g., including the feedback sensor 605). The NSS 105 can perform eye tracking to determine the level of attention the user is directing to the light pulse based on the gaze direction of the retina or pupil. The NSS 105 can measure eye movement to determine the level of attention the user is paying to the light pulse. The NSS 105 can provide a survey or prompt asking for user feedback indicating the level of attention the user is paying to the light pulse. In response to determining that the user is not paying a sufficient amount of attention to the light pulse (e.g., a level of eye movement above a threshold or a gaze direction outside the direct field of view of the light source 305), the light adjustment module 115 can alter parameters of the light source 305 or the display device 305 to gain the user's attention. For example, the light adjustment module 115 can increase the intensity of the light pulse, adjust the color of the light pulse, or change the duration of the light pulse. The light adjustment module 115 can randomly vary one or more parameters of the light pulses. The light adjustment module 115 can initiate an attention-requesting light sequence configured to regain the user's attention. For example, the light sequence can include changes in color or intensity of the light pulses in a predetermined, random, or pseudo-random pattern. The attention-requesting light sequence can enable or disable different light sources when the visual signaling component 150 includes multiple light sources. Thus, the light adjustment module 115 can interact with the feedback monitor 135 to determine the level of attention the user is paying to the light pulses and adjust the light pulses to regain the user's attention if the level of attention falls below a threshold.

[0246] In some embodiments, the light adjustment module 115 may change or adjust one or more parameters of the light pulses or waves at predetermined time intervals (e.g., every 5 minutes, every 10 minutes, every 15 minutes, or every 20 minutes) to restore or maintain the user's level of attention.

[0247] In some embodiments, the NSS 105 can filter, block, attenuate, or remove unwanted visual extraneous stimuli (e.g., via the unwanted frequency filtering module 120). Unwanted visual extraneous stimuli can include, for example, unwanted modulation frequencies of light waves, unwanted intensities, or unwanted wavelengths. The NSS 105 can consider a modulation frequency of a pulse train to be unwanted if it differs from, or differs substantially (e.g., by 1%, 2%, 5%, 10%, 15%, 20%, 25%, or more than 25%) from, a desired frequency.

[0248] For example, a desired modulation frequency for sensory elicitation of neural oscillations may be 40 Hz. However, modulation frequencies of, for example, 15 Hz or 90 Hz may interfere with the sensory elicitation of neural oscillations. Therefore, the NSS 105 can filter out light pulses or light waves corresponding to modulation frequencies of 15 Hz or 90 Hz. For example, the virtual reality headset 401 can detect unwanted modulation frequencies in the physical world and reject, attenuate, filter out, or otherwise remove the unwanted frequencies used to generate or provide an augmented reality experience. The NSS 105 can include optical filters configured to perform digital signal processing or digital image processing to detect unwanted modulation frequencies in the real world captured by the feedback sensor 605. The NSS 105 can detect other content, images, or motion with unwanted parameters (e.g., color, brightness, contrast ratio, modulation frequency) and remove them from the augmented reality experience projected to the user via the display screen 305. The NSS 105 can apply color filters to adjust the color of the augmented reality display or to remove colors. The NSS 105 may adjust, modify, or otherwise manipulate the brightness, contrast ratio, sharpness, color tone, hue, or other parameters of the images or videos displayed via the display device 305 .

[0249] In some embodiments, the NSS 105 can detect, via the feedback component 160, that there is image or video content captured from the real physical world that corresponds to an unwanted modulation frequency of 20 Hz. The NSS 105 can further determine the wavelength of the light waves of the light pulses that corresponds to the unwanted modulation frequency. The NSS 105 can instruct the filtering component 155 to filter out the wavelength corresponding to the unwanted modulation frequency. For example, the wavelength corresponding to the unwanted modulation frequency may correspond to blue. The filtering component 155 can include a digital optical filter that can digitally filter out content or light of a specific range of wavelengths or colors while allowing one or more other ranges of wavelengths or colors. The digital optical filter can change the magnitude or phase of the image for a range of wavelengths. For example, the digital optical filter can be configured to attenuate, cancel, replace, or otherwise modify blue light waves that correspond to the unwanted modulation frequency. The light conditioning module 115 can change the wavelength of the light waves generated by the light generating module 110 and the display device 305 so that the desired modulation frequency is not blocked or attenuated by the unwanted frequency filtering module 120.

[0250] NSS working with tablets The NSS 105 can operate in conjunction with a tablet 500, as shown in FIGS. 5A-5D. In some embodiments, the NSS 105 can determine that the hardware of the visual signaling component 150 includes a tablet device 500 or other display screen that is not attached or secured to the user's head. The tablet 500 can include a display screen having one or more components or functions of the display screen 305 or light source 305 depicted in connection with FIGS. 4A and 4C. The light source 305 in the tablet can be a display screen. The tablet 500 can include one or more feedback sensors, including one or more components or functions of the feedback sensors depicted in connection with FIGS. 4B, 4C, and 6A.

[0251] The tablet 500 can communicate with the NSS 105 over a network, such as a wireless network or a cellular network. The NSS 105, in some embodiments, can execute the NSS 105 or components thereof. For example, the tablet 500 can launch, open, or switch between applications or resources configured to provide at least one function of the NSS 105. The tablet 500 can execute applications as background or foreground processes. For example, the application's graphical user interface can be in the background while the application overlays content or light on the tablet's display screen 305 that changes or modulates at a desired frequency (e.g., 40 Hz) for sensory elicitation of neural oscillations.

[0252] The tablet 500 may include one or more feedback sensors 605. In some embodiments, the tablet can use the one or more feedback sensors 605 to detect that a user is holding the tablet 500. The tablet can use the one or more feedback sensors 605 to determine the distance between the light source 305 and the user. The tablet can use the one or more feedback sensors 605 to determine the distance between the light source 305 and the user's head. The tablet can use the one or more feedback sensors 605 to determine the distance between the light source 305 and the user's eyes.

[0253] In some embodiments, the tablet 500 can determine distance using a feedback sensor 605 that includes a receiver. The tablet can transmit a signal and measure the time it takes for the transmitted signal to leave the tablet 500, bounce off an object (e.g., the user's head), and be received by the feedback sensor 605. The tablet 500 or NSS 105 can determine distance based on the measured amount of time and the speed of the transmitted signal (e.g., the speed of light).

[0254] In some embodiments, the tablet 500 may include two feedback sensors 605 to determine distance. The two feedback sensors 605 may include a first feedback sensor 605 that is a transmitter and a second feedback sensor 605 that is a receiver.

[0255] In some embodiments, tablet 500 may include two or more feedback sensors 605, including two or more cameras, that measure the angle and position of an object (e.g., a user's head) with each camera, and the measured angle and position can be used to determine or calculate the distance between tablet 500 and the object.

[0256] In some embodiments, tablet 500 (or an application thereof) can determine the distance between the tablet and the user's head by receiving user input. For example, the user input can include an approximate size of the user's head. Tablet 500 can then determine the distance from the user's head based on the input approximate size.

[0257] The tablet 500, the application, or the NSS 105 can use the measured or determined distance to adjust the light pulse or flash emitted by the light source 305 of the tablet 500. The tablet 500, the application, or the NSS 105 can use the distance to adjust one or more parameters of the light pulse, flash, or other content emitted via the light source 305 of the tablet 500. For example, the tablet 500 can adjust the intensity of the light pulse emitted by the light source 305 based on the distance. The tablet 500 can adjust the intensity based on the distance to maintain a consistent or similar intensity at the eye regardless of the distance between the light source 305 and the eye. The tablet can increase the intensity in proportion to the square of the distance.

[0258] The tablet 500 can manipulate one or more pixels on the display screen 305 to generate light pulses or modulated frequencies for the sensory elicitation of neural oscillations. The tablet 500 can overlay light sources, light pulses, or other patterns to generate modulated frequencies for the sensory elicitation of neural oscillations. Similar to the virtual reality headset 401, the tablet can filter out or alter unwanted frequencies, wavelengths, or intensities.

[0259] Similar to the frame 400, the tablet 500 can adjust the parameters of the light pulses or flashes of light generated by the light source 305 based on ambient light, environmental parameters, or feedback.

[0260] In some embodiments, the tablet 500 may execute an application configured to generate light pulses or modulation frequencies for sensory elicitation of neural oscillations. The application may run in the background of the tablet such that all content displayed on the tablet's display screen is displayed as light pulses of the desired frequency. The tablet may be configured to detect the direction of a user's gaze. In some embodiments, the tablet may detect the direction of gaze by capturing an image of the user's eye via the tablet's camera. The tablet 500 may be configured to generate light pulses at specific locations on the display screen based on the user's direction of gaze. In embodiments using a direct field of view, the light pulses may be displayed at a location on the display screen that corresponds to the user's line of sight. In embodiments using peripheral vision, the light pulses may be displayed at a location on the display screen that is outside of the portion of the display screen that corresponds to the user's line of sight.

[0261] Nerve stimulation by auditory stimulation 9 is a block diagram illustrating a system for neural stimulation via auditory stimulation, according to one embodiment. System 900 may include a neural stimulation system (“NSS”) 905. NSS 905 may be referred to as an auditory NSS 905 or NSS 905. Briefly summarized, NSS 905 may include, access, interface with, or otherwise communicate with one or more of an audio generation module 910, an audio conditioning module 915, an unwanted frequency filtering module 920, a profile manager 925, a side effect management module 930, a feedback monitor 935, a data repository 940, an audio signaling component 950, a filtering component 955, or a feedback component 960. The audio generation module 910, the audio adjustment module 915, the unwanted frequency filtering module 920, the profile manager 925, the side effect management module 930, the feedback monitor 935, the audio signaling component 950, the filtering component 955, or the feedback component 960 may each include at least one processing unit or other logic device, such as a programmable logic array engine or a module configured to communicate with the database repository 950. The audio generation module 910, the audio adjustment module 915, the unwanted frequency filtering module 920, the profile manager 925, the side effect management module 930, the feedback monitor 935, the audio signaling component 950, the filtering component 955, or the feedback component 960 may be separate components, a single component, or part of the NSS 905. The system 100 and its components, such as the NSS 905, may include hardware elements, such as one or more processors, logic devices, or circuits. System 100 and its components, such as NSS 905, may include one or more of the hardware or interface components depicted in system 700 of Figures 7A and 7B.For example, the components of the system 100 may include or execute on one or more processors 721 , access storage 728 , or memory 722 , and may communicate via a network interface 718 .

[0262] Still referring to FIG. 9 , in more detail, the NSS 905 may include at least one audio generation module 910. The audio generation module 910 may be designed and configured to interface with an audio signaling component 950 to instruct or otherwise cause or facilitate the generation of an audio signal, such as an audio burst, audio pulse, audio chirp, audio sweep, or other acoustic wave, having one or more predetermined parameters. The audio generation module 910 may include hardware or software for receiving and processing instructions or data packets from one or more modules or components of the NSS 905. The audio generation module 910 may generate instructions to cause the audio signaling component 950 to generate an audio signal. The audio generation module 910 may control or enable the audio signaling component 950 to generate an audio signal having one or more predetermined parameters.

[0263] The audio generation module 910 can be communicatively coupled to the audio signaling component 950. The audio generation module 910 can communicate with the audio signaling component 950 via a circuit, a wire, a data port, a network port, a power line, a ground, an electrical contact, or a pin. The audio generation module 910 can wirelessly communicate with the audio signaling component 950 using one or more wireless protocols, such as BlueTooth, BlueTooth Low Energy, Zigbee, Z-wave, IEEE 802, WIFI, 3G, 4G, LTE, Near Field Communication (“NFC”), or other short-, medium-, or long-range communication protocols. The audio generation module 910 can include or have access to a network interface 718 for wireless or wired communication with the audio signaling component 950.

[0264] The audio-generation module 910 can interface with, control, or otherwise manage various types of audio signaling components 950 to cause the audio signaling components 950 to generate, block, control, or otherwise provide an audio signal having one or more predetermined parameters. The audio-generation module 910 can include a driver configured to drive an audio source of the audio signaling component 950. For example, the audio source can include a speaker, and the audio-generation module 910 (or audio signaling component) can include a transducer that converts electrical energy into acoustic or sound waves. The audio-generation module 910 can include a computing chip, microchip, circuit, microcontroller, operational amplifier, transistor, resistor, or diode configured to provide electricity or power having specific voltage and current characteristics to drive the speaker to generate an audio signal with desired acoustic characteristics.

[0265] In some embodiments, the audio generation module 910 can instruct the audio signaling component 950 to provide an audio signal. For example, the audio signal can include an acoustic wave 1000 as depicted in FIG. 10A . The audio signal can include multiple acoustic waves. The audio signal can generate one or more acoustic waves. The acoustic wave 1000 can include or be formed from mechanical waves of pressure and displacement that travel through media such as gases, liquids, and solids. Acoustic waves can travel through a medium and cause vibrations, sound, ultrasound, or infrasound. Acoustic waves can propagate as longitudinal waves through air, water, or solids. Acoustic waves can propagate as transverse waves through solids.

[0266] Acoustic waves can produce sound by vibrations of pressure, stress, particle displacement, or particle velocity propagated in a medium with internal forces (e.g., elastic or viscous), or by the superposition of such propagated vibrations. Sound can refer to the auditory sensation induced by this vibration. For example, sound can refer to the reception of acoustic waves and their perception by the brain.

[0267] The sound signaling component 950 or its sound source can generate acoustic waves by vibrating a diaphragm of the sound source. For example, the sound source can include a diaphragm, such as a transducer configured to transduce mechanical vibrations into sound. The diaphragm can include a thin film or sheet of various materials suspended at its edge. The varying pressure of the acoustic waves can impart mechanical vibrations to the diaphragm, which can then generate acoustic waves or sound.

[0268] The acoustic wave 1000 illustrated in FIG. 10A includes a wavelength 1010. The wavelength 1010 may refer to the distance between successive peaks 1020 of the wave. The wavelength 1010 may be related to the frequency of the acoustic wave and the velocity of the acoustic wave. For example, the wavelength may be determined as the velocity of the acoustic wave divided by the frequency of the acoustic wave. The velocity of the acoustic wave may be the product of the frequency and the wavelength. The frequency of the acoustic wave may be the velocity of the acoustic wave divided by the wavelength of the acoustic wave. Therefore, the frequency and wavelength of the acoustic wave may be inversely proportional. The speed of sound may vary based on the medium through which the acoustic wave propagates. For example, the speed of sound in air is 343 meters per second.

[0269] The crest 1020 can refer to the crest of the wave, or the point on the wave that has a maximum value. The displacement of the medium is greatest at the crest 1020 of the wave. The trough 1015 is opposite the crest 1020. The trough 1015 is the minimum or lowest point of the wave that corresponds to the smallest amount of displacement.

[0270] The acoustic wave 1000 may include an amplitude 1005. The amplitude 1005 may refer to the maximum extent of oscillation or vibration of the acoustic wave 1000, measured from an equilibrium position. The acoustic wave 1000 may be a longitudinal wave if it oscillates or oscillates in the same direction as the direction of propagation 1025. In some cases, the acoustic wave 1000 may be a transverse wave, oscillating perpendicular to its direction of propagation.

[0271] The audio generation module 910 can instruct the audio signaling component 950 to generate acoustic waves having one or more predetermined amplitudes or wavelengths. The wavelength of acoustic waves audible to the human ear ranges from approximately 17 meters to 17 millimeters (or 20 Hz to 20 kHz). The audio generation module 910 can further specify one or more characteristics of the acoustic waves within or outside the audible spectrum. For example, the frequency of the acoustic waves can range from 0 to 50 kHz. In some embodiments, the frequency of the acoustic waves can range from 8 to 12 kHz. In some embodiments, the frequency of the acoustic waves can be 10 kHz.

[0272] The NSS 905 can modulate, change, alter, or otherwise modify the properties of the acoustic wave 1000. For example, the NSS 905 can modulate the amplitude or wavelength of the acoustic wave. As shown in Figures 10B and 10C, the NSS 905 can adjust, manipulate, or otherwise modify the amplitude 1005 of the acoustic wave 1000. For example, the NSS 905 can reduce the amplitude 1005 to make the sound quieter, as shown in Figure 10B, or increase the amplitude 1005 to make the sound louder, as shown in Figure 10C.

[0273] In some cases, the NSS 905 can adjust, manipulate, or otherwise modify the wavelength 1010 of the acoustic wave. As shown in Figures 10D and 10E, the NSS 905 can adjust, manipulate, or otherwise modify the wavelength 1010 of the acoustic wave 1000. For example, the NSS 905 can increase the wavelength 1010, making the sound lower-pitched, as shown in Figure 10D, or decrease the wavelength 1010, making the sound higher-pitched, as shown in Figure 10E.

[0274] The NSS 905 can modulate the acoustic wave. Modulating the acoustic wave may include modulating one or more properties of the acoustic wave. Modulating the acoustic wave may include filtering the acoustic wave, such as filtering out unwanted frequencies or attenuating the acoustic wave to reduce amplitude. Modulating the acoustic wave may include adding one or more additional acoustic waves to the original acoustic wave. Modulating the acoustic wave may include combining acoustic waves such that there is constructive or destructive interference, where the resulting combined acoustic wave corresponds to the modulated acoustic wave.

[0275] The NSS 905 can modulate or change one or more characteristics of the acoustic wave based on a time interval. The NSS 905 can change one or more characteristics of the acoustic wave at the end of the time interval. For example, the NSS 905 can change the characteristics of the acoustic wave every 30 seconds, 1 minute, 2 minutes, 3 minutes, 5 minutes, 7 minutes, 10 minutes, or 15 minutes. The NSS 905 can change the modulation frequency of the acoustic wave, where the modulation frequency refers to the reciprocal of the modulation or pulse rate interval of the acoustic pulses. The modulation frequency can be a predetermined frequency or a desired frequency. The modulation frequency can correspond to a desired stimulation frequency of neural oscillations. The modulation frequency can be set to promote or induce sensory elicitation of neural oscillations. The NSS 905 can set the modulation frequency to a frequency ranging from 0.1 Hz to 10,000 Hz. For example, the NSS The 905 can adjust the modulation frequency to 1Hz, 1Hz, 5Hz, 10Hz, 20Hz, 25Hz, 30Hz, 31Hz, 32Hz, 33Hz, 34Hz, 35Hz, 36Hz, 37Hz, 38Hz, 39Hz, 40Hz, 41Hz, 42Hz, 43Hz, 44Hz, 45Hz, 46Hz, 47Hz, 48Hz, 49Hz, 50Hz, 60Hz, 70Hz, 80Hz, 90Hz, 100Hz, 110Hz, 120Hz, 130Hz, 140Hz, 150Hz, 160Hz, 170Hz, 180Hz, 190Hz, 210Hz, 220Hz, 230Hz, 240Hz, 250Hz, 260Hz, 270Hz, 280Hz, 290Hz, 300Hz, 310Hz, 320Hz, 330Hz, 340Hz, 350Hz, 360Hz, 370Hz, 380Hz, 390Hz, 400Hz, 410Hz, 420Hz, 430Hz, 440Hz, 450Hz, 460Hz, 470Hz, 480Hz, 490Hz, 500Hz, 600Hz, 700Hz, 800Hz, 900Hz, 1000Hz, 1100Hz, 1200Hz, 1300Hz, 1400Hz, 1500Hz, 1600Hz, 1700Hz, 1800Hz, 1900Hz, 2100Hz, 2200Hz, It can be set to Hz, 150Hz, 160Hz, 200Hz, 240Hz, 250Hz, 300Hz, 320Hz, 400Hz, 480Hz, 500Hz, 640Hz, 1000Hz, 1280Hz, 2000Hz, 3000Hz, 4000Hz, 5000Hz, 6000Hz, 7000Hz, 8000Hz, 9000Hz or 10000Hz.

[0276] The audio generation module 910 can be configured to provide an audio signal including a burst of acoustic waves, an audio pulse, or an acoustic wave modulation. The light generation module 910 can instruct the audio signaling component 950 to generate or otherwise generate an acoustic burst or pulse. An acoustic pulse can refer to a modulation on the characteristics of an acoustic wave that is perceived by the brain as a burst of acoustic waves or a change in sound. For example, an audio source that is intermittently turned on and off can generate an audio burst or a change in sound. The audio source can be turned on and off based on a predetermined or fixed pulse rate interval, such as every 0.025 seconds, to provide a pulse repetition frequency of 40 Hz. The audio source can be turned on and off to provide a pulse repetition frequency ranging from 0.1 Hz to 10 kHz or greater.

[0277] 10F-10I illustrate bursts of acoustic waves or bursts of modulation that can be applied to acoustic waves. The bursts of acoustic waves can include, for example, audio tones, beeps, or clicks. Modulation can refer to changing the amplitude of the acoustic wave, changing the frequency or wavelength of the acoustic wave, overlaying another acoustic wave on the original acoustic wave, presenting the acoustic wave at intervals of a desired frequency, or otherwise modifying or altering the acoustic wave.

[0278] For example, Figure 10F illustrates acoustic bursts 1035a-c (or modulated pulses 1035a-c) according to one embodiment. The acoustic bursts 1035a-c may be illustrated via a graph in which the y-axis represents a parameter of the acoustic wave (e.g., the frequency, wavelength, or amplitude of the acoustic wave). The x-axis may represent time (e.g., seconds, milliseconds, or microseconds).

[0279] The audio signal may include modulated acoustic waves that are modulated between different frequencies, wavelengths, or amplitudes. For example, the NSS 905 may modulate acoustic waves between frequencies within the audio spectrum, such as Ma, and frequencies outside the audio spectrum, such as Mo. The NSS 905 may modulate acoustic waves between two or more frequencies, between on and off states, or between high and low power states.

[0280] The acoustic bursts 1035a-c may have an acoustic wave parameter with a value Ma that is different from the value of the acoustic wave parameter Mo. The modulation Ma may refer to frequency or wavelength, or amplitude. The pulses 1035a-c may be generated with a pulse rate interval (PRI) 1040.

[0281] For example, the acoustic wave parameter may be the frequency of the acoustic wave. The first value Mo may be a low frequency or carrier frequency of the acoustic wave, such as 10 kHz. The second value Ma may be different from the first frequency Mo. The second frequency Ma may be lower or higher than the first frequency Mo. For example, the second frequency Ma may be 11 kHz. The difference between the first frequency and the second frequency may be determined or set based on the sensitivity level of the human ear. The difference between the first frequency and the second frequency may be determined or set based on the subject's profile information 945. The difference between the first frequency Mo and the second frequency Ma may be determined so that modulation or variation of the acoustic wave promotes sensory elicitation of neural oscillations.

[0282] In some cases, the parameters of the acoustic wave used to generate acoustic burst 1035a may be constant at Ma, thereby generating a square wave as shown in Figure 10F. In some embodiments, each of the three pulses 1035a-c may include an acoustic wave having the same frequency Ma.

[0283] The width of each acoustic burst or pulse (e.g., the duration of a burst of acoustic waves having parameter Ma) may correspond to a pulse width 1030a. Pulse width 1030a may refer to the length or duration of the burst. Pulse width 1030a may be measured in units of time or distance. In some embodiments, pulses 1035a-c may include acoustic waves having different frequencies from one another. In some embodiments, pulses 1035a-c may have different pulse widths 1030a from one another, as illustrated in FIG. 10G. For example, first pulse 1035d in FIG. 10G may have pulse width 1030a, while second pulse 1035e has second pulse width 1030b that is greater than first pulse width 1030a. Third pulse 1035f may have third pulse width 1030c that is less than second pulse width 1030b. The third pulse width 1030c may be less than the first pulse width 1030a. Although the pulse widths 1030a-c of the pulses 1035d-f of the pulse train may vary, the audio generation module 910 may maintain a constant pulse rate spacing 1040 of the pulse train.

[0284] The pulses 1035a-c can form a pulse train having a pulse rate interval 1040. The pulse rate interval 1040 can be quantified using units of time. The pulse rate interval 1040 can be based on the frequency of the pulses in the pulse train 201. The frequency of the pulses in the pulse train 201 can be referred to as the modulation frequency. For example, the audio generation module 910 can provide the pulse train 201 with a predetermined frequency, such as 40 Hz. To do so, the audio generation module 910 can determine the pulse rate interval 1040 by taking the multiplicative inverse (or reciprocal) of the frequency (e.g., dividing 1 by the predetermined frequency of the pulse train). For example, the audio generation module 910 can take the multiplicative inverse of 40 Hz by dividing 1 by 40 Hz to determine the pulse rate interval 1040 as 0.025 seconds. The pulse rate interval 1040 can remain constant throughout the pulse train. In some embodiments, the pulse rate interval 1040 may vary throughout the pulse train or from one pulse train to the subsequent pulse train. In some embodiments, the pulse rate interval 1040 varies, but the number of pulses transmitted per second may be fixed.

[0285] In some embodiments, the audio generation module 910 can generate audio bursts or audio pulses having acoustic waves with varying frequency, amplitude, or wavelength. For example, the audio generation module 910 can generate an up-chirp pulse, as illustrated in FIG. 10H, in which the frequency, amplitude, or wavelength of the acoustic waves of the audio pulse increases from the beginning of the pulse to the end of the pulse. For example, the frequency, amplitude, or wavelength of the acoustic waves at the beginning of the pulse 1035g can be Ma. The frequency, amplitude, or wavelength of the acoustic waves of the pulse 1035g can increase from Ma to Mb in the middle of the pulse 1035g and then increase to a maximum Mc at the end of the pulse 1035g. Thus, the frequency, amplitude, or wavelength of the acoustic waves used to generate the pulse 1035g can range from Ma to Mc. The frequency, amplitude, or wavelength can increase linearly, exponentially, or based on some other rate or curve. One or more of the frequency, amplitude, or wavelength of the acoustic waves can vary from the beginning of the pulse to the end of the pulse.

[0286] For example, the audio generation module 910 can generate a down-chirp pulse as illustrated in FIG. 10I, where the frequency, amplitude, or wavelength of the acoustic wave of the audio pulse decreases from the beginning of the pulse to the end of the pulse. For example, the frequency, amplitude, or wavelength of the acoustic wave at the beginning of pulse 1035j may be Mc. The frequency, amplitude, or wavelength of the acoustic wave of pulse 1035j may decrease from Mc to Mb in the middle of pulse 1035g, and then decrease to a minimum Ma at the end of pulse 1035j. Thus, the frequency, amplitude, or wavelength of the acoustic wave used to generate pulse 1035j may range from Mc to Ma. The frequency, amplitude, or wavelength may decrease linearly, exponentially, or based on some other rate or curve. One or more of the frequency, amplitude, or wavelength of the acoustic wave may change from the beginning of the pulse to the end of the pulse.

[0287] In some embodiments, the audio generation module 910 can command or cause the audio signaling component 950 to generate audio pulses to stimulate specific or predetermined portions of the brain or specific cortices. The frequency, wavelength, modulation frequency, amplitude, and other aspects of the audio pulses, tones, or music-based stimuli can specify which cortex is recruited to process the stimuli. The audio signaling component 950 can stimulate distinct portions of the cortex by tailoring the presentation of the stimuli to target specific or general regions of interest. The modulation parameters or amplitude of the audio stimuli can specify which areas of the cortex are stimulated. For example, different areas of the cortex are recruited to process sounds of different frequencies, referred to as their respective signature frequencies. Furthermore, the laterality of the stimulation can affect the cortical response, as some subjects may be treated by stimulating one ear rather than both ears.

[0288] The audio signaling component 950 can be designed and configured to generate audio pulses in response to instructions from the audio generation module 910. The instructions can include parameters of the audio pulses, such as the frequency, wavelength, or acoustic wave, pulse duration, pulse train frequency, pulse rate interval, or pulse train duration (e.g., the number of pulses in a pulse train or the length of time to transmit a pulse train having a predetermined frequency). The audio pulses can be perceived, observed, or otherwise identified by the brain through cochlear means such as the ear. The audio pulses can be transmitted to the ear via a sound source speaker in close proximity to the ear, such as headphones, earphones, a bone conduction transducer, or a cochlear implant. The audio pulses can also be transmitted to the ear via a sound source or speaker not in close proximity to the ear, such as a surround sound speaker system, bookshelf speakers, or other speakers not in direct or indirect contact with the ear.

[0289] 11A illustrates an audio signal generated using binaural beats or binaural pulses, according to one embodiment. Briefly summarized, binaural beats refer to providing a different tone to each ear of a subject. When the brain perceives two different tones, it mixes the two tones together to generate a pulse. Two different tones can be selected such that the sum of the tones produces a pulse train with a desired pulse rate interval 1040.

[0290] The audio signaling component 950 may include a first audio source that provides an audio signal to a first ear of the subject and a second audio source that provides a second audio signal to a second ear of the subject. The first audio source and the second audio source may be different. The first ear can perceive only the first audio signal from the first audio source, and the second ear can receive only the second audio signal from the second audio source. The audio source may include, for example, headphones, earphones, or a bone conduction transducer. The audio source may include a stereo audio source.

[0291] The audio generation component 910 can select a first tone for a first ear and a different second tone for a second ear. The tones can be characterized by their duration, pitch, intensity (volume), or timbre (or sound quality). In some cases, the first tone and the second tone can differ if they have different frequencies. In some cases, the first tone and the second tone can differ if they have different phase offsets. The first tone and the second tone can each be a pure tone. A pure tone can be a tone having a single-frequency sine wave.

[0292] As shown in FIG. 11A , a first tone or offset wave 1105 is slightly different from a second tone 1110 or carrier wave 1110. The first tone 1105 has a higher frequency than the second tone 1110. The first tone 1105 may be generated by a first earphone inserted into one ear of a subject, and the second tone 1110 may be generated by a second earphone inserted into the other ear of the subject. When the auditory cortex of the brain perceives the first tone 1105 and the second tone 1110, the brain can sum the two tones. The brain can sum the acoustic waveforms corresponding to the two tones. The brain can sum the two waveforms, as illustrated by waveform sum 1115. With the first and second tones having different parameters (such as different frequencies or phase offsets), portions of the waveform can be added and subtracted from another to result in waveform 1115 having one or more pulses 1130 (or beats 1130). The pulses 1130 can be separated by a balanced portion 1125. By mixing these two different waveforms together, the pulses 1130 perceived by the brain can produce a sensory elicitation of neural oscillations.

[0293] In some embodiments, the NSS 905 can generate binaural beats using pitch panning techniques. For example, the sound generation module 910 or sound adjustment module 915 can include or use a filter to modulate the pitch of a sound file or a single tone up or down, simultaneously panning the modulation of stereo sides so that one side has a slightly higher pitch and the other side has a slightly lower pitch. A stereo side can refer to a first sound source that generates and provides an audio signal to a first ear of a subject and a second sound source that generates and provides an audio signal to a second ear of the subject. A sound file can refer to a file format configured to store a representation of an acoustic wave or information about an acoustic wave. Exemplary sound file formats can include .mp3, .wav, .aac, .m4a, .smf, etc.

[0294] Using this pitch panning technique, the NSS 905 can generate a type of spatial positioning that, when heard through stereo headphones, is perceived by the brain in a manner similar to binaural beats. Thus, using this pitch panning technique, the NSS 905 can generate pulses or beats using a single tone or a single sound file.

[0295] In some cases, the NSS 905 can generate a mono beat or a mono pulse. A mono beat or pulse is similar to a binaural beat in that it can also be generated by combining two tones to form a beat. The NSS 905 or a component of the system 100 can use digital or analog techniques to form a mono beat by combining two tones before the sound reaches the ear, as opposed to the brain combining waveforms as in binaural beats. For example, the NSS 905 (or the audio generation component 910) can identify and select two different waveforms that, when combined, generate a beat or pulse with a desired pulse rate interval. The NSS 905 can identify a first digital representation of a first acoustic waveform and a second digital representation of a second acoustic waveform having different parameters than the first acoustic waveform. The NSS 905 can combine the first digital waveform and the second digital waveform to generate a third digital waveform that is different from the first and second digital waveforms. The NSS 905 can then transmit the third digital waveform in digital format to the audio signaling component 950. The NSS 905 can convert the digital waveform to an analog format and transmit the analog format to the audio signaling component 950. The audio signaling component 950 can then generate, via a sound source, a sound perceived by one ear or both ears. The same sound may be perceived by both ears. The sound may include pulses or beats spaced apart by a desired pulse rate interval 1040.

[0296] FIG. 11B illustrates an acoustic pulse having isochronic tones, according to one embodiment. Isochronic tones are evenly spaced tone pulses. Isochronic tones can be generated without combining two different tones. The NSS 905 or other components of the system 100 can generate isochronic tones by turning tones on and off. The NSS 905 can generate isochronic tones or pulses by commanding the audio signaling component to turn them on and off. The NSS 905 can modify the digital representation of the acoustic wave to remove or set the digital values ​​of the acoustic wave so that sound is generated during the pulse 1135 and no sound is generated during the null portion 1140.

[0297] By turning acoustic waves on and off, the NSS 905 can establish acoustic pulses 1135 spaced apart by a pulse rate interval 1040 corresponding to a desired stimulation frequency, such as 40 Hz. Isochronic pulses spaced apart at a desired PRI 1040 can produce a sensory elicitation of neural oscillations.

[0298] 11C illustrates audio pulses generated by the NSS 905 using a soundtrack, according to one embodiment. A soundtrack can include or refer to complex acoustic waves containing multiple different frequencies, amplitudes, or tones. For example, a soundtrack can include a voice track, an instrument track, a music track containing both voices and instruments, nature sounds, or white noise.

[0299] The NSS 905 can modulate the soundtrack by rhythmically adjusting the sound components to generate a sensory elicitation of neural oscillations. For example, the NSS 905 can modulate the volume by increasing or decreasing the amplitude of the acoustic waves or soundtrack to generate rhythmic stimuli corresponding to the stimulation frequency for generating a sensory elicitation of neural oscillations. Thus, the NSS 905 can embed acoustic pulses having a pulse rate interval corresponding to a desired stimulation frequency into the soundtrack to generate a sensory elicitation of neural oscillations. The NSS 905 can manipulate the soundtrack to generate a new, modified soundtrack with acoustic pulses having a pulse rate interval corresponding to the desired stimulation frequency to generate a sensory elicitation of neural oscillations.

[0300] As illustrated in FIG. 11C , pulse 1135 is generated by modulating the volume from a first level Va to a second level Vb. During portion 1140 of acoustic wave 345, NSS 905 can set or maintain the volume at Va. Volume Va can refer to the amplitude of the wave, or the maximum amplitude or crest of wave 345 during portion 1140. NSS 905 can then adjust, change, or increase the volume to Vb during portion 1135. NSS 905 can increase the volume by a predetermined amount, such as a percentage, a number of decibels, a subject-specified amount, or other amount. NSS 905 can set or maintain the volume at Vb for a duration corresponding to the desired pulse length of pulse 1135.

[0301] In some embodiments, the NSS 905 may include an attenuator that attenuates the volume from level Vb to level Va. In some embodiments, the NSS 905 can instruct an attenuator (e.g., an attenuator of the audio signaling component 950) to attenuate the volume from level Vb to level Va. In some embodiments, the NSS 905 may include an amplifier to amplify or increase the volume from Va to Vb. In some embodiments, the NSS 905 can instruct an amplifier (e.g., an amplifier of the audio signaling component 950) to amplify or increase the volume from Va to Vb.

[0302] Referring back to FIG. 9 , the NSS 905 may include, access, interface with, or otherwise communicate with at least one audio adjustment module 915. The audio adjustment module 915 may be designed and configured to adjust parameters associated with the audio signal, such as the frequency, amplitude, wavelength, pattern, or other parameters of the audio signal. The audio adjustment module 915 may automatically modify the parameters of the audio signal based on profile information or feedback. The audio adjustment module 915 may receive feedback information from a feedback monitor 935. The audio adjustment module 915 may receive instructions or information from a side effect management module 930. The audio adjustment module 915 may receive profile information from a profile manager 925.

[0303] The NSS 905 may include, access, interface with, or otherwise communicate with at least one unwanted frequency filtering module 920. The unwanted frequency filtering module 920 may be designed and configured to block, attenuate, reduce, or otherwise filter out frequencies of audio signals that are undesirable to prevent or reduce the perception of a certain amount of such audio signals by the brain. The unwanted frequency filtering module 920 may interface with, instruct, control, or otherwise communicate with the filtering component 955 to cause the filtering component 955 to block, attenuate, or otherwise reduce the effect of unwanted frequencies on neural oscillations.

[0304] The unwanted frequency filtering module 920 may include an active noise control component (e.g., the active noise cancellation component 1215 depicted in FIG. 12B). Active noise control can refer to or include active noise cancellation or active noise reduction. Active noise control can reduce an unwanted sound by adding a second sound with parameters specifically selected to cancel or attenuate the first sound. In some cases, the active noise control component can emit an acoustic wave with the same amplitude but in opposite phase (or anti-phase) to the original unwanted sound. The two waves can combine to form a new wave, effectively canceling each other out through destructive interference.

[0305] The active noise control component may include analog circuitry or digital signal processing. The active noise control component may include adaptive technology for analyzing the waveform of background aural or non-aural noise. In response to background noise, the active noise control component may generate an audio signal that can phase-shift or invert the polarity of the original signal. This inverted signal can be amplified by a transducer or speaker to create sound waves that are directly proportional to the amplitude of the original waveform, resulting in destructive interference and reducing the volume of the perceptible noise.

[0306] In some embodiments, the noise cancellation speaker may be co-located with the sound source speaker.In some embodiments, the noise cancellation speaker may be co-located with the sound source to be attenuated.

[0307] The unwanted frequency filtering module 920 can filter out unwanted frequencies that may adversely affect the auditory elicitation of neural oscillations. For example, the active noise control component can identify that an audio signal includes acoustic bursts with a desired pulse rate interval and acoustic bursts with an unwanted pulse rate interval. The active noise control component can identify waveforms corresponding to the acoustic bursts with the unwanted pulse rate intervals and generate inverted phase waveforms to cancel or attenuate the unwanted acoustic bursts.

[0308] The NSS 905 may include, access, interface with, or otherwise communicate with at least one profile manager 925. The profile manager 925 may be designed or configured to store, update, retrieve, or otherwise manage information related to one or more subjects associated with auditory elicitation of neural oscillations. The profile information may include, for example, past treatment information, past brain sensory-evoked neural oscillation information, administration information, acoustic wave meter feedback, physiological information, environmental information, or other data related to the systems and methods for sensory elicitation of neural oscillations.

[0309] The NSS 905 may include, access, interface with, or otherwise communicate with at least one side effect management module 930. The side effect management module 930 may be designed and configured to provide information to the audio module 915 or audio module 910 to modify one or more parameters of the audio signal to reduce side effects. Side effects include, for example, nausea, migraine, fatigue, seizures, ear strain, hearing loss, tinnitus, or tinnitus.

[0310] The side effect management module 930 can automatically command components of the NSS 905 to modify or change parameters of the audio signal. The side effect management module 930 can be configured with predetermined thresholds to reduce side effects. For example, the side effect management module 930 can be configured with a maximum duration of a pulse train, a maximum amplitude of acoustic waves, a maximum volume, a maximum duty cycle of a pulse train (e.g., pulse width multiplied by the frequency of the pulse train), and a maximum number of treatments for sensory elicitation of neural oscillations over a period of time (e.g., 1 hour, 2 hours, 12 hours, or 24 hours).

[0311] The side effect management module 930 can modify parameters of the audio signal in response to the feedback information. The side effect management module 930 can receive feedback from a feedback monitor 935. The side effect management module 930 can determine to adjust parameters of the audio signal based on the feedback. The side effect management module 930 can compare the feedback to a threshold and determine to adjust parameters of the audio signal.

[0312] The side effect management module 930 may be configured with or include a policy engine that applies policies or rules to the current audio signal or feedback and determines adjustments to the audio signal. For example, if the feedback indicates that the patient receiving the audio signal has a heart rate or pulse rate above a threshold, the side effect management module 930 may turn off the pulse train until the pulse rate stabilizes below the threshold or below a second threshold that is below the threshold.

[0313] The NSS 905 may include, access, interface with, or otherwise communicate with at least one feedback monitor 935. The feedback monitor may be designed and configured to receive feedback information from a feedback component 960. The feedback component 960 may include feedback sensors 1405 such as, for example, a temperature sensor, a heart rate or pulse rate monitor, a physiological sensor, an ambient noise sensor, an ambient temperature sensor, a blood pressure monitor, an electroencephalogram sensor, an EEG probe, an electro-oculogram (“EOG”) probe configured to measure corneal-retinal standing potentials present between the front and back of a human eye, an accelerometer, a gyroscope, a motion detector, a proximity sensor, a camera, a microphone, or a photodetector.

[0314] Systems and devices configured for neural stimulation via auditory stimulation - Patents.com 12A illustrates a system for auditory guidance of neural oscillations according to one embodiment. System 1200 can include one or more speakers 1205. System 1200 can include one or more microphones. In some embodiments, the system can include both a speaker 1205 and a microphone 1210. In some embodiments, system 1200 can include a speaker 1205 but not a microphone 1210. In some embodiments, system 1200 can include a microphone 1210 but not a speaker 1210.

[0315] The speaker 1205 can be integrated with the audio signaling component 950. The audio signaling component 950 can comprise the speaker 1205. The speaker 1205 can interact or communicate with the audio signaling component 950. For example, the audio signaling component 950 can instruct the speaker 1205 to generate a sound.

[0316] The microphone 1210 can be integrated with the feedback component 960. The feedback component 960 can comprise the microphone 1210. The microphone 1210 can interact or communicate with the feedback component 960. For example, the feedback component 960 can receive information, data, or signals from the microphone 1210.

[0317] In some embodiments, the speaker 1205 and the microphone 1210 can be integrated or can be the same device. For example, the speaker 1205 can be configured to function as the microphone 1210. The NSS 905 can switch the speaker 1205 from speaker mode to microphone mode.

[0318] In some embodiments, system 1200 may include one speaker 1205 located at one ear of the subject. In some embodiments, system 1200 may include two speakers. A first of the two speakers may be located at the first ear and a second of the two speakers may be located at the second ear. In some embodiments, an additional speaker may be located in front of the subject's head or behind the subject's head. In some embodiments, one or more microphones 1210 may be located at one or both ears, in front of the subject's head, or behind the subject's head.

[0319] The speaker 1205 may include a dynamic cone speaker configured to generate sound from an electrical signal. The speaker 1205 may include a full-range driver that generates sound waves at frequencies spanning some or all of the audible range (e.g., 60 Hz to 20,000 Hz). The speaker 1205 may include a driver that generates sound waves outside the audible range, such as 0 to 60 Hz, or at frequencies within the ultrasonic range, such as 20 kHz to 4 GHz. The speaker 1205 may include one or more transducers or drivers that generate sound in various portions of the audible frequency range. For example, the speaker 1205 may include a tweeter for high-range frequencies (e.g., 2,000 Hz to 20,000 Hz), a midrange driver for middle frequencies (e.g., 250 Hz to 2000 Hz), or a woofer for low frequencies (e.g., 60 Hz to 250 Hz).

[0320] Speaker 1205 can comprise one or more types of speaker hardware, components, or technology products that generate sound. For example, speaker 1205 can comprise a diaphragm that generates sound. Speaker 1205 can comprise a moving iron loudspeaker that uses a stationary coil to vibrate a magnetized piece of metal. Speaker 1205 can include a piezoelectric speaker. A piezoelectric speaker can use the piezoelectric effect to generate sound by applying a voltage to a piezoelectric material to generate motion, which is converted into audible sound using a diaphragm and a resonator.

[0321] The speaker 1205 may include various other types of hardware or technology products, such as magnetostatic loudspeakers, magnetostrictive loudspeakers, electrostatic loudspeakers, ribbon speakers, planar magnetic loudspeakers, bending wave loudspeakers, coaxial drivers, horn loudspeakers, Heil air motion transducers, or transparent ion conduction speakers.

[0322] In some cases, the speaker 1205 may not have a diaphragm. For example, the speaker 1205 may be a plasma arc speaker that uses an electric plasma as a radiating element. The speaker 1205 may be a thermoacoustic speaker that uses carbon nanotube thin films. The speaker 1205 may be a rotating woofer with a fan having blades that constantly change pitch.

[0323] In some embodiments, the speaker 1205 may comprise a headphone or pair of headphones, ear speakers, earphones, or earbuds. A headphone may be a relatively small speaker compared to a loudspeaker. A headphone may be designed and constructed to be placed in, around, or otherwise near the ear. A headphone may comprise an electroacoustic transducer that converts an electrical signal into a corresponding sound at a subject's ear. In some embodiments, the headphone 1205 may comprise or interface with a headphone amplifier, such as an integrated amplifier or a separate unit.

[0324] In some embodiments, the speaker 1205 can comprise headphones that can include air jets that force air into the ear canal and push against the eardrum, similar to sound waves. The compression and rarefaction of the eardrum by the burst of air (with or without any discernible sound) can control neural vibration frequencies similar to auditory signals. For example, the speaker 1205 can comprise air jets or devices similar to in-ear headphones that push air into the ear canal, pull air from the ear canal, or both, to compress or pull on the eardrum and thereby affect the frequency of neural vibrations. The NSS 905 can command, configure, or cause the air jets to create bursts of air at predetermined frequencies.

[0325] In some embodiments, headphones can be connected to the audio signaling component 950 via a wired or wireless connection. In some embodiments, the audio signaling component 950 can include headphones. In some embodiments, the headphones 1205 can interface with one or more components of the NSS 905 via a wired or wireless connection. In some embodiments, the headphones 1205 can include one or more components of the NSS 905 or system 100, such as the audio generation module 910, the audio adjustment module 915, the unwanted frequency filtering module 920, the profile manager 925, the side effect management module 930, the feedback monitor 935, the audio signaling component 950, the filtering component 955, or the feedback component 960.

[0326] The speaker 1205 can comprise or be integrated into various types of headphones. For example, the headphones can include circumaural headphones (e.g., full-size headphones) with circular or oval ear pads designed and configured to seal with the head and attenuate external noise. Circumaural headphones can facilitate providing an immersive auditory EEG wave stimulation experience while reducing external distractions. In some embodiments, the headphones can include supraaural headphones with pads that press against the ears rather than around the ears. Supraaural headphones can provide less attenuation of external noise.

[0327] Both circumaural and supraaural headphones can have open, closed, or semi-open designs. Open designs allow more noise to leak out and more ambient sound to enter, but provide a more natural or speaker-like sound. Closed headphones block out more ambient noise compared to open headphones, providing a more immersive auditory EEG stimulation experience with reduced external distractions.

[0328] In some embodiments, the headphones can include ear-fitting headphones, such as earbuds or in-ear headphones. Earbuds (or earbuds) can refer to small headphones that are worn directly on the outer ear, facing the ear canal but not inserted into it. However, earbuds have minimal acoustic isolation and allow ambient noise to enter. In-ear headphones (or in-ear monitors or canalphones) can refer to small headphones that can be designed and constructed for insertion into the ear canal. By engaging the ear canal, in-ear headphones can block out more ambient noise than earbuds, thus providing a more immersive auditory EEG stimulation experience. In-ear headphones can include an ear canal plug made or formed from one or more materials, such as silicone rubber, elastomer, or foam. In some embodiments, in-ear headphones can include a custom molding that fits the ear canal to create a custom-shaped plug that provides additional comfort and noise isolation for the subject, thereby further improving the immersion of the auditory EEG stimulation experience.

[0329] In some embodiments, one or more microphones 1210 may be used to detect sound. The microphones 1210 may be integrated with the speaker 1205. The microphones 1210 may provide feedback information to the NSS 905 or other components of the system 100. The microphones 1210 may provide feedback to components of the speaker 1205 to cause the speaker 1205 to adjust parameters of the audio signal.

[0330] The microphone 1210 can include a transducer that converts sound into an electrical signal. The microphone 1210 can generate an electrical signal from air pressure fluctuations using electromagnetic induction, capacitance change, or piezoelectricity. Optionally, the microphone 1210 can include or be connected to a preamplifier that can amplify the signal before it is recorded or processed. The microphone 1210 can include one or more types of microphones, including, for example, a condenser microphone, an RF condenser microphone, an electret condenser, a dynamic microphone, a moving coil microphone, a ribbon microphone, a carbon microphone, a piezoelectric microphone, a crystal microphone, a fiber optic microphone, a laser microphone, a liquid or water microphone, a microelectromechanical system (“MEMS”) microphone, or a speaker as a microphone.

[0331] The feedback component 960 may include or interface with a microphone 1210 to capture, identify, or receive sounds. The feedback component 960 may capture ambient noise. The feedback component 960 may capture sounds from the speaker 1205 to facilitate the NSS 905 adjusting characteristics of the audio signal generated by the speaker 1205. The microphone 1210 may receive audio input from the subject, such as voice commands, instructions, requests, feedback information, or responses to survey questions.

[0332] In some embodiments, one or more speakers 1205 can be integrated with one or more microphones 1210. For example, the speakers 1205 and microphones 1210 can form a headset, be located in a single housing, or be the same device, as the speakers 1205 and microphones 1210 can be designed to structurally switch between sound-generating and sound-receiving modes.

[0333] 12B illustrates a system configuration for auditory guidance of neural oscillations, according to one embodiment. The system 1200 may include at least one speaker 1205. The system 1200 may include at least a microphone 1210. The system 1200 may include at least one active noise cancellation component 1215. The system 1200 may include at least one feedback sensor 1225. The system 1200 may include or interface with an NSS 905. The system 1200 may include or interface with an audio player 1220.

[0334] The system 1200 can include a first speaker 1205 disposed at a first ear. The system 1200 can include a second speaker 1205 disposed at a second ear. The system 1200 can include a first active noise cancellation component 1215 communicatively coupled to a first microphone 1210. The system 1200 can include a second active noise cancellation component 1215 communicatively coupled to the second microphone 1210. In some cases, the active noise cancellation component 1215 can communicate with both the first speaker 1205 and the second speaker 1205, or with both the first microphone 1210 and the second microphone 1210. The system 1200 can include the first microphone 1210 communicatively coupled to the active noise cancellation component 1215. The system 1200 can include the second microphone 1210 communicatively coupled to the active noise cancellation component 1215. In some embodiments, each of the microphone 1210, the speaker 1205, and the active noise cancellation component may communicate or interface with the NSS 905. In some embodiments, the system 1200 may include a feedback sensor 1225 and a second feedback sensor 1225 communicatively coupled to the NSS 905, the speaker 1205, the microphone 1210, or the active noise cancellation component 1215.

[0335] In operation, and in some embodiments, the audio player 1220 can play a music track. The audio player 1220 can provide an audio signal corresponding to the music track via a wired or wireless connection to the first and second speakers 1205. In some embodiments, the NSS 905 can intercept the audio signal from the audio player. For example, the NSS 905 can receive a digital or analog audio signal from the audio player 1220. The NSS 905 can be intermediate between the audio player 1220 and the speakers 1205. The NSS 905 can analyze the audio signal corresponding to music to embed an auditory EEG stimulation signal. For example, the NSS 905 can adjust the volume of the auditory signal from the audio player 1220 to generate acoustic pulses having a pulse rate interval as depicted in FIG. 11C. In some embodiments, the NSS 905 can use binaural beat techniques to provide various auditory signals to the first and second speakers that combine to have a desired stimulation frequency when perceived by the brain.

[0336] In some embodiments, the NSS 905 can adjust for any latency between the first speaker 1205 and the second speaker 1205 so that the brain perceives the audio signals simultaneously or nearly simultaneously (e.g., within 1 millisecond, 2 milliseconds, 5 milliseconds, or 10 milliseconds). The NSS 905 can buffer the audio signals to account for latency so that the audio signals are transmitted from the speakers simultaneously.

[0337] In some embodiments, the NSS 905 may not be intermediate between the audio player 1220 and the speaker. For example, the NSS 905 may receive music tracks from a digital music repository. The NSS 905 may manipulate or modify the music tracks to embed acoustic pulses according to a desired PRI. The NSS 905 may then provide the modified music tracks to the audio player 1220, which may provide modified audio signals to the speaker 1205.

[0338] In some embodiments, the active noise cancellation component 1215 can receive ambient noise information from the microphone 1210, identify unwanted frequencies or noise, and generate an anti-phase waveform to cancel or attenuate the unwanted waveform. In some embodiments, the system 1200 can include an additional speaker that generates the noise cancellation waveform provided by the noise cancellation component 1215. The noise cancellation component 1215 can include an additional speaker.

[0339] The feedback sensor 1225 of the system 1200 can detect feedback information, such as environmental parameters or physiological conditions. The feedback sensor 1225 can provide the feedback information to the NSS 905. The NSS 905 can adjust or modify the audio signal based on the feedback information. For example, the NSS 905 can determine that the subject's pulse rate exceeds a predetermined threshold and then reduce the volume of the audio signal. The NSS 905 can detect that the volume of the auditory signal exceeds a threshold and reduce the amplitude. The NSS 905 can determine that the pulse rate interval falls below a threshold, which can indicate that the subject is losing focus or not paying sufficient attention to the audio signal, and the NSS 905 can increase the amplitude of the audio signal or change the tone or music track. In some embodiments, the NSS 905 can change the tone or music track based on a time interval. Changing the tone or music track can encourage the subject to pay greater attention to the auditory stimuli, thereby facilitating sensory guidance of neural oscillations.

[0340] In some embodiments, the NSS 905 can receive neural oscillation information from the EEG probe 1225 and adjust the auditory stimulation based on the EEG information. For example, the NSS 905 can determine from the probe information that neurons are oscillating at undesirable frequencies. The NSS 905 can then identify corresponding undesirable frequencies in ambient noise using the microphone 1210. The NSS 905 can then instruct the active noise cancellation component 1215 to cancel waveforms corresponding to the ambient noise having the undesirable frequencies.

[0341] In some embodiments, the NSS 905 can enable passive noise filtering. A passive noise filter can include a circuit with one or more resistors, capacitors, or inductors that filter out undesired frequencies of noise. In some cases, a passive filter can include sound-insulating, sound-proof, or sound-absorbing materials.

[0342] 4C illustrates a system configuration for auditory induction of neural oscillations, according to one embodiment. The system 401 can provide auditory brainwave stimulation using an ambient noise source 1230. For example, the system 401 can include a microphone 1210 that detects the ambient noise 1230. The microphone 1210 can provide the detected ambient noise to the NSS 905. The NSS 905 can modify the ambient noise 1230 before providing it to the first speaker 1205 or the second speaker 1205. In some embodiments, the system 401 can be integrated with or interfaced with a hearing aid device. A hearing aid can be a device designed to improve hearing.

[0343] The NSS 905 can increase or decrease the amplitude of the ambient noise 1230 to produce acoustic bursts with a desired pulse rate interval. The NSS 905 can provide modified audio signals to the first and second speakers 1205 to facilitate auditory induction of neural oscillations.

[0344] In some embodiments, the NSS 905 can overlay a click train, tone, or other acoustic pulse on top of the ambient noise 1230. For example, the NSS 905 can receive ambient noise information from the microphone 1210, apply an auditory stimulation signal to the ambient noise information, and then present the combination of the ambient noise information and the auditory stimulation signal to the first and second speakers 1205. In some cases, the NSS 905 can remove unwanted frequencies in the ambient noise 1230 before providing the auditory stimulation signal to the speakers 1205.

[0345] Thus, by using ambient noise 1230 as part of the auditory stimulation, the subject can receive auditory stimulation while observing their surroundings or continuing their daily activities, facilitating the sensory guidance of neural oscillations.

[0346] FIG. 13 illustrates a system configuration for auditory induction of neural oscillations, according to one embodiment. The system 1300 can use a room environment to provide auditory stimuli for sensory induction of neural oscillations. The system 1300 can include one or more speakers. The system 1300 can include a surround sound system. For example, the system 1300 can include a left speaker 1310, a right speaker 1315, a center speaker 1305, a right surround speaker 1325, and a left surround speaker 1330. The system 1300 can include a subwoofer 1320. The system 1300 can include a microphone 1210. The system 1300 can include or refer to a 5.1 surround system. In some embodiments, the system 1300 can have one, two, three, four, five, six, seven, or more speakers.

[0347] When a surround system is used to provide auditory stimuli, the NSS 905 can provide the same or different audio signals to each of the speakers in the system 1300. The NSS 905 can modify or adjust the audio signals provided to one or more of the speakers in the system 1300 to facilitate sensory guidance of neural vibrations. For example, the NSS 905 can receive feedback from the microphone 1210 and modify, manipulate, or otherwise adjust the audio signals to optimize the auditory stimuli provided to a subject in a room location corresponding to the location of the microphone 1210. The NSS 905 can optimize or improve the auditory stimuli perceived at the location corresponding to the microphone 1210 by analyzing the acoustic beams or waves generated by the speakers that propagate toward the microphone 1210.

[0348] NSS 905 can be configured with information about the design and configuration of each speaker. For example, speaker 1305 can generate sound in a direction having an angle of 1335, speaker 1310 can generate sound traveling in a direction having an angle of 1340, speaker 1315 can generate sound traveling in a direction having an angle of 1345, speaker 1325 can generate sound traveling in a direction having an angle of 1355, and speaker 1330 can generate sound traveling in a direction having an angle of 1350. These angles can be optimal angles or predetermined angles for each of the speakers. These angles can refer to the optimal angle for each speaker so that a person in a location corresponding to microphone 1210 receives optimal auditory stimuli. Thus, speakers in system 1300 can be oriented to transmit auditory stimuli toward a target.

[0349] In some embodiments, the NSS 905 can enable or disable one or more speakers. In some embodiments, the NSS 905 can increase or decrease the volume of a speaker to facilitate the sensory guidance of neural oscillations. The NSS 905 can intercept music tracks, television audio, movie audio, internet audio, audio output from a set-top box, or other audio source. The NSS 905 can adjust or manipulate the received audio and send the adjusted audio signal to a speaker in the system 1300 to generate the sensory guidance of neural oscillations.

[0350] 14 illustrates a feedback sensor 1405 placed or positioned on, on, or near an individual's head. The feedback sensor 1405 may comprise, for example, an EEG probe that detects brain wave activity.

[0351] The feedback monitor 935 may detect, receive, acquire, or otherwise determine feedback information from one or more feedback sensors 1405. The feedback monitor 935 may provide the feedback information to one or more components of the NSS 905 for further processing or storage. For example, the profile manager 925 may update a profile data structure 945 stored in the data repository 940 with the feedback information. The profile manager 925 may associate the feedback information with an identifier of the patient or individual receiving auditory brain stimulation, as well as a timestamp and datestamp corresponding to the receipt or detection of the feedback information.

[0352] The feedback monitor 935 can determine the attention level. The attention level can refer to the focus given to the acoustic pulses used for brain stimulation. The feedback monitor 935 can determine the attention level using a variety of hardware and software techniques. The feedback monitor 935 can assign a score to the attention level (e.g., 1 to 10 (1 being low attention and 10 being high attention, or vice versa), 1 to 100 (1 being low attention and 100 being high attention, or vice versa), 0 to 1 (0 being low attention and 1 being high attention, or vice versa), categorize the attention level (e.g., low, medium, high), grade the attention (e.g., A, B, C, D, or F), or otherwise provide an indication of the attention level.

[0353] In some embodiments, the feedback monitor 935 can track the individual's eye movements to determine attention levels. The feedback monitor 935 can interface with a feedback component 960 that includes an eye tracker. The feedback monitor 935 (e.g., via the feedback component 960) can detect and record the individual's eye movements and analyze the recorded eye movements to determine attention span or attention level. The feedback monitor 935 can measure gaze, which can display or provide information related to spatial attention. For example, the feedback monitor 935 (e.g., via the feedback component 960) can be configured with electrooculography ("EOG"), which measures the skin potential around the eyes, which can indicate the direction the eyes are pointing relative to the head. In some embodiments, the EOG can include a system or device for stabilizing the head so that it cannot move in order to determine the direction of the eyes relative to the head. In some embodiments, the EOG can include or interface with a head tracking system that determines the position of the head and subsequently the direction of the eyes relative to the head.

[0354] In some embodiments, the feedback monitor 935 and the feedback component 960 can determine the level of attention the subject pays to the auditory stimulus based on eye movement. For example, increased eye movement may indicate that the subject is focusing on the visual stimulus rather than the auditory stimulus. To determine the level of attention the subject pays to the visual stimulus rather than the auditory stimulus, the feedback monitor 935 and the feedback component 960 can determine or track eye direction or eye movement using video detection of the pupil or corneal reflex. For example, the feedback component 960 can include one or more cameras or video cameras. The feedback component 960 can include an infrared source that transmits light pulses toward the eye. The light can be reflected by the eye. The feedback component 960 can detect the location of the reflection. The feedback component 960 can capture or record the location of the reflection. The feedback component 960 can perform image processing on the reflection to determine or calculate the eye direction or the eye's gaze direction.

[0355] The feedback monitor 935 can compare the eye direction or movement with the same individual's eye direction or movement history, subtle eye movements, or other eye movement information history to determine the level of attention. For example, the feedback monitor 935 can determine the history of eye movement volume during an auditory stimulus history session. The feedback monitor 935 can compare the current eye movement with the eye movement history to identify deviations. Based on the comparison, the NSS 905 can determine an increase in eye movement and further determine that the subject is paying less attention to the current auditory stimulus based on the increase in eye movement. In response to detecting a decrease in attention, the feedback monitor 935 can instruct the audio adjustment module 915 to modify parameters of the audio signal to capture the subject's attention. The audio adjustment module 915 can modify the volume, tone, pitch, or music track to capture the subject's attention or increase the level of attention the subject pays to the auditory stimulus. While modifying the audio signal, the NSS 905 can continue to monitor the level of attention. For example, when modifying an audio signal, the NSS 905 may detect a decrease in eye movement, which may indicate an increase in the level of attention being given to the audio signal.

[0356] The feedback sensor 1405 can interact or communicate with the NSS 905. For example, the feedback sensor 1405 can provide detected feedback information or data to the NSS 905 (e.g., to the feedback monitor 935). The feedback sensor 1405 can provide data to the NSS 905 in real time, for example, as the feedback sensor 1405 detects or senses information. The feedback sensor 1405 can provide feedback information to the NSS 905 based on a time interval, such as 1 minute, 2 minutes, 5 minutes, 10 minutes, 1 hour, 2 hours, 4 hours, 12 hours, or 24 hours. The feedback sensor 1405 can provide feedback information to the NSS 905 in response to a condition or event, such as a feedback measurement value exceeding or below a threshold. The feedback sensor 1405 can provide feedback information in response to a change in a feedback parameter. In some embodiments, the NSS 905 may ping, query, or send a request for information to the feedback sensor 1405, and the feedback sensor 1405 may provide feedback information in response to the ping, request, or query.

[0357] Method for nerve stimulation by auditory stimulation FIG. 15 is a flow diagram of a method for performing auditory guidance of neural oscillations, according to one embodiment. Method 800 may be performed by one or more systems, components, modules, or elements shown in FIGS. 7A, 7B, and 9-14, including, for example, a neural stimulation system (NSS). Briefly, the NSS may identify an audio signal to provide in block 1505. In block 1510, the NSS may generate and transmit the identified audio signal. In 1515, the NSS may receive or determine feedback related to neural activity, physiological activity, environmental parameters, or device parameters. In 1520, the NSS may manage, control, or adjust the audio signal based on the feedback.

[0358] NNS that works with headphones The NSS 905 can operate with a speaker 1205 as depicted in Figure 12A. The NSS 905 can operate with an earphone or in-earphone that includes the speaker 1205 and a feedback sensor 1405.

[0359] In operation, a subject using headphones can wear the headphones on their head so that the speakers are positioned at or within the ear canal. Optionally, the subject can provide an indication to the NSS 905 that the headphones are worn and that the subject is ready to receive sensory guidance of neural vibrations. This indication can include an instruction, command, selection, input, or other indication via an input / output interface, such as the keyboard 726, pointing device 727, or other I / O devices 730a-n. The indication can be a movement-based indication, a visual indication, or an audio-based indication. For example, the subject can provide a voice command indicating that the subject is ready to receive sensory guidance of neural vibrations.

[0360] In some cases, the feedback sensor 1405 can determine that the subject is ready to receive sensory guidance of neural oscillations. The feedback sensor 1405 can detect that the headphones are placed on the subject's head. The NSS 905 can receive motion data, acceleration data, gyroscope data, temperature data, or capacitive touch data to determine that the headphones are placed on the subject's head. The received data, such as motion data, can indicate that the headphones have been picked up and placed on the subject's head. The temperature data can measure the temperature at or near the headphones and can indicate that the headphones are on the subject's head. The NSS 905 can detect that the subject is ready in response to determining that the subject is paying a high level of attention to the headphones or the feedback sensor 1405.

[0361] In this manner, the NSS 905 can detect or determine that the headphones are worn and the subject is ready, or the NSS 905 can receive an indication or confirmation from the subject that the subject is wearing the headphones and is ready to receive sensory guidance of neural oscillations. After determining that the subject is ready, the NSS 905 can initialize the sensory guidance of the neural oscillation process. In some embodiments, the NSS 905 can access the profile data structure 945. For example, the profile manager 925 can query the profile data structure 945 to determine one or more parameters of the external auditory stimulus used for the sensory guidance of the neural oscillation process. The parameters can include, for example, the type of audio stimulation technique, the intensity or volume of the audio stimulation, the frequency of the audio stimulation, the duration of the audio stimulation, or the wavelength of the audio stimulation. The profile manager 925 can query the profile data structure 945 to obtain sensory-evoked neural oscillation history information, such as past auditory stimulation sessions. The profile manager 925 can perform a lookup in the profile data structure 945. The profile manager 925 can perform a lookup using a username, a user identifier, location information, a fingerprint, a biometric identifier, a retinal scan, voice recognition and authentication, or other identification techniques.

[0362] The NSS 905 can determine the type of external auditory stimulus based on the components connected to the headphones. The NSS 905 can determine the type of external auditory stimulus based on the type of speakers 1205 available. For example, if the headphones are connected to an audio player, the NSS 905 can determine to embed an acoustic pulse. If the headphones are not connected to an audio player and are connected only to a microphone, the NSS 905 can determine to inject a pure tone or to modify the ambient noise.

[0363] In some embodiments, the NSS 905 can determine the type of external auditory stimulus based on the sensory guidance history of the neural oscillation session. For example, the profile data structure 945 can be pre-configured with information about the type of audio signaling component 950.

[0364] The NSS 905 can determine the modulation frequency of the pulse train or audio signal via the profile manager 925. For example, the NSS 905 can determine from the profile data structure 945 that the modulation frequency for the external auditory stimulus should be set to 40 Hz. Depending on the type of auditory stimulus, the profile data structure 945 can further indicate the pulse length, intensity, wavelength of the acoustic waves forming the audio signal, or duration of the pulse train.

[0365] In some cases, the NSS 905 can determine or adjust one or more parameters of the external auditory stimulus. For example, the NSS 905 (e.g., via the feedback component 960 or the feedback sensor 1405) can determine the amplitude of the acoustic wave or the volume level of the sound. The NSS 905 (e.g., via the sound adjustment module 915 or the side effect management module 930) can establish, initialize, set, or adjust the amplitude or wavelength of the acoustic wave or acoustic pulse. For example, the NSS 905 can determine that a low level of ambient noise is present. The low level of ambient noise may not impair the subject's hearing or distract them. Based on the detection of the low level of ambient noise, the NSS 905 can determine that the volume may not need to be increased or that the volume may be lowered to maintain the effectiveness of the sensory guidance of neural oscillations.

[0366] In some embodiments, the NSS 905 can monitor the level of ambient noise (e.g., via the feedback monitor 935 and the feedback component 960) to automatically and periodically adjust the amplitude of the acoustic pulses through the sensory induction of neural oscillation processes. For example, if a subject initiates a brainwave entrainment process when high levels of ambient noise are present, the NSS 905 can initially set a higher amplitude for the acoustic pulses and use a tone with a more perceptible frequency, such as 10 kHz. However, in some embodiments where the ambient noise level decreases through the sensory induction of neural oscillation processes, the NSS 905 can automatically detect a decrease in ambient noise and, in response, adjust or lower the volume while decreasing the frequency of the acoustic waves. The NSS 905 can adjust the acoustic pulses to provide a high contrast ratio relative to the ambient noise to facilitate the sensory induction of neural oscillations.

[0367] In some embodiments, the NSS 905 (e.g., via the feedback monitor 935 and the feedback component 960) can monitor or measure a physiological condition to set or adjust parameters of the acoustic waves. In some embodiments, the NSS 905 can monitor or measure heart rate, pulse rate, blood pressure, body temperature, sweating, or brain activity to set or adjust parameters of the acoustic waves.

[0368] In some embodiments, the NSS 905 can be pre-configured to initially transmit acoustic pulses at the lowest acoustic wave intensity setting (e.g., low amplitude or high wavelength) and gradually increase the intensity (e.g., increase the amplitude or decrease the wavelength) while monitoring feedback until an optimal audio intensity is reached. The optimal audio intensity can refer to the highest intensity without adverse physiological side effects such as hearing loss, seizures, heart attacks, migraines, or other discomfort. The NSS 905 (e.g., via the side effect management module 930) can monitor physiological symptoms to identify adverse side effects of the external auditory stimulation and adjust the external auditory stimulation accordingly (e.g., via the sound adjustment module 915) to reduce or eliminate the adverse side effects.

[0369] In some embodiments, the NSS 905 (e.g., via the sound adjustment module 915) can adjust parameters of the sound waves or acoustic pulses based on the attention level. For example, during sensory guidance of neural oscillatory processes, the subject may become bored, lose focus, fall asleep, or otherwise not pay attention to the acoustic pulses. Not paying attention to the acoustic pulses may reduce the effectiveness of the sensory guidance of neural oscillatory processes, resulting in neurons oscillating at a frequency different from the desired modulation frequency of the acoustic pulses.

[0370] The NSS 905 can use the feedback monitor 935 and one or more feedback components 960 to detect the level of attention the subject is paying to the audio pulse. In response to determining that the subject is not paying a sufficient amount of attention to the audio pulse, the audio adjustment module 915 can modify parameters of the audio signal to gain the subject's attention. For example, the audio adjustment module 915 can increase the amplitude of the audio pulse, adjust the tone of the audio pulse, or change the duration of the audio pulse. The audio adjustment module 915 can randomly vary one or more parameters of the audio pulse. The audio adjustment module 915 can initiate an attention-seeking audio sequence configured to regain the subject's attention. For example, the audio sequence can include changes in frequency, tone, amplitude, or the insertion of words or music in a predetermined, random, or pseudo-random pattern. The attention-seeking audio sequence can enable or disable different audio sources if the audio signaling component 950 includes multiple audio sources or speakers. In this way, the sound adjustment module 915 can interact with the feedback monitor 935 to determine the level of attention the subject is giving to the sound pulse, and if the attention level falls below a threshold, adjust the sound pulse to regain the subject's attention.

[0371] In some embodiments, the sound adjustment module 915 may modify or adjust one or more parameters of the sound pulses or waves at predetermined time intervals (e.g., every 5 minutes, every 10 minutes, every 15 minutes, or every 20 minutes) to regain or maintain the subject's attention level.

[0372] In some embodiments, the NSS 905 (e.g., via the unwanted frequency filtering module 920) can filter, block, attenuate, or remove unwanted auditory extraneous stimuli. Unwanted auditory extraneous stimuli may include, for example, unwanted modulation frequencies, unwanted intensities, or unwanted wavelengths of sound waves. The NSS 905 can consider a modulation frequency to be unwanted if the modulation frequency of a pulse train differs or differs substantially (e.g., by 1%, 2%, 5%, 10%, 15%, 20%, 25%, or more) from a desired frequency.

[0373] For example, a desirable modulation frequency for sensory induction of neural oscillations may be 40 Hz. However, a modulation frequency of 20 Hz or 80 Hz may reduce the beneficial effects on brain cognitive function, brain cognitive state, the immune system, or inflammation that may result from sensory induction of neural oscillations at other frequencies, such as 40 Hz. Therefore, the NSS 905 may filter acoustic pulses corresponding to modulation frequencies of 20 Hz or 80 Hz.

[0374] In some embodiments, the NSS 905 can detect the presence of an acoustic pulse from an ambient noise source corresponding to an unwanted modulation frequency of 20 Hz via the feedback component 960. The NSS 905 can further determine the wavelength of the acoustic wave of the acoustic pulse corresponding to the unwanted modulation frequency. The NSS 905 can instruct the filtering component 955 to filter out the wavelength corresponding to the unwanted modulation frequency.

[0375] Nerve stimulation by peripheral nerve stimulation In some embodiments, the disclosed systems and methods can provide peripheral nerve stimulation to cause or induce neural oscillations. For example, tactile stimulation of the skin surrounding sensory nerves that form part of or are connected to the peripheral nervous system can cause or induce electrical activity in the sensory nerves that can be perceived by the brain, which can cause transmission to the brain via the central nervous system, or can cause or induce electrical and neural activity in the brain, including activity that results in neural oscillations. Similarly, passing an electrical current through or on the skin surrounding sensory nerves that form part of or are connected to the peripheral nervous system can cause or induce electrical activity in the sensory nerves that can be perceived by the brain, which can cause transmission to the brain via the central nervous system, or can cause or induce electrical and neural activity in the brain, including activity that results in neural oscillations. The brain can adjust, manage, or control the frequency of neural oscillations in response to receiving peripheral nerve stimulation. The electrical current can cause depolarization of neurons, such as through current stimulation, such as time-varying pulses. Current pulses can directly cause depolarization. Side effects in other brain regions can be gated or controlled by the brain in response to depolarization. Peripheral nerve stimulation generated at a predetermined frequency can induce neural activity in the brain, causing or inducing neural oscillations. The frequency of the neural oscillations can be based on or correspond to the frequency of the peripheral nerve stimulation or a modulation frequency associated with the peripheral nerve stimulation. Thus, the disclosed systems and methods can cause or induce neural oscillations using peripheral nerve stimulation, such as current pulses modulated at a predetermined frequency, to synchronize electrical activity among groups of neurons based on the frequency of the peripheral nerve stimulation. Sensory induction of neural oscillations can be observed based on the total frequency of neural oscillations produced by synchronous electrical activity in a population of cortical neurons. The frequency of the current or modulation of that pulse can cause or adjust this synchronous electrical activity in a population of cortical neurons to oscillate at a frequency corresponding to the frequency of the peripheral nerve stimulation pulse.

[0376] 16A is a block diagram representing a system for performing peripheral nerve stimulation to cause or induce neural oscillations, such as to produce brain entrainment, according to one embodiment. System 1600 may include a peripheral nerve stimulation system 1605. Briefly, in overview, peripheral nerve stimulation system (or peripheral nerve stimulation neurostimulation system) (“NSS”) 1605 may include, access, interface with, or otherwise communicate with one or more of a neurostimulation generation module 1610, a neurostimulation adjustment module 1615, a profile manager 1625, a side effect management module 1630, a feedback monitor 1635, a data repository 1640, a neurostimulator generator component 1650, a shielding component 1655, a feedback component 1660, or a neurostimulation amplification component 1665. The neural stimulation generation module 1610, the neural stimulation adjustment module 1615, the profile manager 1625, the side effect management module 1630, the feedback monitor 1635, the neural stimulator generator component 1650, the shielding component 1655, the feedback component 1660, or the neural stimulation amplification component 1665 may each comprise at least one processing unit or other logic device, e.g., a programmable logic array engine, or module, configured to communicate with the database repository 1650. The neural stimulation generation module 1610, the neural stimulation adjustment module 1615, the profile manager 1625, the side effect management module 1630, the feedback monitor 1635, the neural stimulator generator component 1650, the shielding component 1655, the feedback component 1660, or the neural stimulation amplification component 1665 may be separate components, a single component, or part of the NSS 1605. The system 1600 and its components, such as the NSS 1605, may comprise hardware elements, such as one or more processors, logic devices, or circuits.System 1600 and its components, such as NSS 1605, can include one or more of the hardware or interface components depicted in system 700 of Figures 7A and 7B. For example, the components of system 1600 can include or execute on one or more processors 721, access storage 728, or memory 722 and communicate via network interface 718.

[0377] Nerve stimulation with multiple stimulation modes FIG. 16B is a block diagram illustrating a system for neural stimulation via multiple stimulation modes, according to one embodiment. System 1600 can include a neural stimulation orchestration system (“NSOS”) 1605. NSOS 1605 can provide multiple stimulation modes. For example, NSOS 1605 can provide a first stimulation mode including visual stimulation and a second stimulation mode including auditory stimulation. In each stimulation mode, NSOS 1605 can provide one type of signal. For example, in a visual stimulation mode, NSOS 1605 can provide the following types of signals: light pulse, image pattern, ambient light flicker, or augmented reality. NSOS 1605 can coordinate, manage, control, or otherwise facilitate the delivery of multiple stimulation modes and types of stimulation.

[0378] Briefly, in overview, the NSOS 1605 may include, access, interface with, or otherwise communicate with one or more of a stimulus orchestration component 1610, a subject assessment module 1650, a data repository 1615, one or more signaling components 1630a-n, one or more filtering components 1635a-n, one or more feedback components 1640a-n, and one or more neural stimulation systems (“NSS”) 1645a-n. The data repository 1615 may include or store a profile data structure 1620 and a policy data structure 1625. The stimulus orchestration component 1610 and the subject assessment module 1650 may comprise at least one processing unit or other logic device, e.g., a programmable logic array engine, or module, configured to communicate with the database repository 1615. The stimulus orchestration component 1610 and the subject assessment module 1650 can be a single component, comprise separate components, or be part of the NSOS 1605. The system 1600 and its components, such as the NSOS 1605, may comprise hardware elements, such as one or more processors, logic devices, or circuits. The system 1600 and its components, such as the NSOS 1605, can comprise one or more hardware or interface components depicted in the system 700 of FIGS. 7A and 7B. For example, the components of the system 1600 can comprise or execute on one or more processors 721, access storage 728, or memory 722 and communicate via the network interface 718. The system 1600 can include one or more components or functionality depicted in FIGS. 1-15, including, for example, the system 100, the system 900, the visual NSS 105, or the auditory NSS 905.For example, at least one of the signaling components 1630a-n may include one or more components or functionality of the visual signaling component 150 or the audio signaling component 950. At least one of the filtering components 1635a-n may include one or more components or functionality of the filtering component 155 or the filtering component 955. At least one of the feedback components 1640a-n may include one or more components or functionality of the feedback component 160 or the feedback component 960. At least one of the NSSs 1645a-n may include one or more components or functionality of the visual NSS 105 or the audio NSS 905.

[0379] 16B , in further detail, the NSOS 1605 can include at least a stimulation orchestration component 1610. The stimulation orchestration component 1610 can be designed and cons...

Claims

1. A method for predicting the likelihood that a subject will benefit from a treatment, (a) A step of measuring the response from a subject to which gamma vibration-induced non-invasive sensory stimulation has been administered, wherein the gamma vibration-induced non-invasive sensory stimulation includes auditory stimulation and visual stimulation. (b) A step of predicting the likelihood of an expected treatment outcome for the subject using a statistical algorithm, a machine learning algorithm, or a combination thereof, wherein the prediction is at least in part based on the measurement in (b), and the expected treatment outcome includes reduction of neurodegeneration, deceleration of neurodegeneration, reduction or prevention of age-related or neurodegenerative brain atrophy, deceleration of age-related or neurodegenerative brain atrophy, improvement of neurodegenerative symptoms, deceleration of cognitive and functional decline, improvement of cognitive function, improvement of functional status, improvement of neurological and psychiatric symptoms, or a combination thereof. Methods that include...

2. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation includes frequency components in the range of about 30 Hz to about 50 Hz.

3. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation includes frequency components in the range of about 20 Hz to about 160 Hz.

4. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation further comprises a kinesthetic stimulation.

5. The method according to claim 1, wherein the subject is diagnosed with a neurodegenerative disorder related to cognitive decline or is at risk of developing the neurodegenerative disorder.

6. The method according to claim 1, wherein the neurodegenerative disorder includes supranuclear palsy (PSP), prion disease, or infectious spongiform encephalopathy.

7. The method according to claim 1, wherein the response includes measuring baseline EEG coherence.

8. The method according to claim 1, wherein the response includes measuring the baseline EEG force.

9. The method according to claim 1, wherein the response comprises measuring force in the alpha frequency band, delta frequency band, theta frequency band, beta frequency band, or a combination thereof.

10. The method according to claim 1, wherein the neurodegenerative disorder is Alzheimer's disease, Creutzfeldt-Jakob disease (CJD), variant CJD, Gerstmann-Sträussler-Scheinker syndrome, fatal familial insomnia, Kuru disease, or any combination thereof.

11. The method according to claim 1, wherein the subject is diagnosed with behavioral and psychological symptoms of dementia (BPSD) or is at risk of developing such behavioral and psychological symptoms.

12. The method according to claim 1, wherein the subject is diagnosed with or at risk of developing a mood disorder, depression, bipolar disorder, anxiety, addiction, neurosis, anorexia, bulimia, apathy, agitation, dementia, mild cognitive impairment, subjective cognitive decline, Lewy body dementia, Parkinson's disease, sleep fragmentation, schizophrenia, or any combination thereof.

13. The method according to claim 1, wherein the response is measured using electroencephalography (EEG).

14. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation is administered continuously over a predetermined period of time.

15. The method according to claim 14, wherein the predetermined period is 10 minutes to 2 hours.

16. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation is administered over a plurality of discrete time intervals.

17. The method according to claim 16, wherein the plurality of discrete times occur at least once a day, at least once every two days, at least once a week, at least once every two weeks, at least once a month, or at least once every two months.

18. The method according to claim 17, wherein the plurality of discrete time periods extend to at least two days, at least one week, at least two weeks, at least one month, at least three months, at least six months, at least one year, at least two years, or at least five years.

19. The method according to claim 1, wherein (b) includes making a prediction using a machine learning algorithm.

20. The method according to claim 1, wherein the machine learning algorithm includes a neural network, a deep learning algorithm, an ensemble, regularization, a rule system, regression, Bayesian analysis, a decision tree, dimensionality reduction, an example-based algorithm, or a clustering algorithm.

21. The method according to claim 1, wherein the prediction includes using a separate mean analysis.

22. The method according to claim 1, further comprising the step of predicting the expected treatment outcome of the subject using the subject's biometric data.

23. The method according to claim 22, wherein the biometric data includes heart rate, blood pressure, respiratory rate, body temperature, electrical signals from any area of ​​the subject's body, or sleep data.

24. The method according to claim 23, wherein the sleep data includes sleep fragmentation.

25. The method according to claim 1, wherein the step of measuring the response includes using a Mini-Mental State Examination (MMSE), Alzheimer's Disease Rating Scale (ADAS-Cog), Clinical Dementia Assessment (CDR), Collaborative Alzheimer's Disease Study - Activities of Daily Living (ADCS-ADL), Neuropsychiatric Investigation (NPI), Positron Emission Tomography (PET), or Magnetic Resonance Imaging (MRI) Volumetric Data Assessment.

26. The method according to claim 1, wherein the gamma-oscillation-induced non-invasive sensory stimulation comprises a plurality of pulse rates including a pulse rate interval, the pulse rate interval being between 0.02 seconds and 0.033 seconds.

27. ​​The method according to claim 1, wherein the response consists of measurement using an infrared optical sensor.

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