Intermittent responsive implanted stimulation and adaptive behavioral training system

Abstract

Systems and methods for treating injuries, disorders, and / or diseases in a patient's brain are disclosed herein. For example, the systems disclosed herein can include a treatment subsystem that can present a patient with various trials and a stimulation device communicably coupled to the treatment subsystem. The stimulation device can provide stimulation to various regions of the user's brain (e.g., the nucleus accumbens, caudate, entorhinal cortex, and / or the like) based on responses received by the treatment subsystem in response to the trials. The stimulation can help build, reinforce, and / or augment associations in the patient's brain to encourage learning and / or reinforce or enhance memory to help treat brain injuries and / or degenerative diseases. Additionally, or alternatively, the stimulation can help attenuate associations in the patient's brain to help discourage maladaptive associations to help treat neuropsychiatric disorders (e.g., substance use disorder (SUD), obsessive-compulsive disorder (OCD), and / or the like).

Description

INTERMITTENT RESPONSIVE IMPLANTED STIMULATION AND ADAPTIVE BEHAVIORAL TRAINING SYSTEM CROSS-REFERENCE TO RELATED APPLICATION(S)

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 537,695, filed on September 11, 2023, which is incorporated by reference herein in its entirety. TECHNICAL FIELD

[0002] The disclosure is generally directed to an intracranial neural implant and method of use, and in particular, an implant for use with a system to coordinate the delivery of brain stimulation at behaviorally and physiologically relevant epochs. BACKGROUND

[0003] Stroke and traumatic brain injury (TBI) are diseases characterized by areas of absent or abnormal brain activity and resulting functional deficits. Stroke and TBI collectively affect millions of individuals in the US and greater numbers worldwide. Treatment for these diseases is largely supportive. While physiotherapy and occupational therapy can be effective, many individuals experience significant and persistent functional deficits. Critically, means by which disrupted brain circuity can be effectively modulated to improve function are currently lacking, constituting a significant public health issue that is not adequately met. Relatedly, memory disorders such as Alzheimer's disease (AD) affect a growing number of people worldwide. Current treatments are limited and generally provide poor efficacy in resisting degeneration of the brain. As a result, there is an urgent need for more effective therapies to enhance memory and mitigate progression of neurodegeneration. In addition, neuropsychiatric diseases such as addictive and anxiety disorders represent a major public health burden and often do not respond to existing treatments. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] Many aspects of the present disclosure can be better understood with reference to the following drawings. The components in the drawings are not necessarily to scale. Instead, emphasis is placed on illustrating clearly the principles of the present disclosure. The drawings should not be -1- 169064111.3taken to limit the disclosure to the specific embodiments depicted, but are for explanation and understanding only.

[0005] FIG. 1A is a schematic drawing of a system for treating injuries, disorders, and / or diseases in a patient’s brain configured in accordance with embodiments of the present technology.

[0006] FIG.1B is a schematic block diagram of a system for treating injuries, disorders, and / or diseases in a patient’s brain configured in accordance with embodiments of the present technology.

[0007] FIG.2A is a schematic drawing of an implantable device for treating injuries, disorders, and / or diseases in a patient’s brain configured in accordance with embodiments of the present technology.

[0008] FIG. 2B is a schematic drawing of a main controller for an implantable device configured in accordance with embodiments of the present technology.

[0009] FIG. 3 is a flow diagram of a process for treating a brain injury in accordance with embodiments of the present technology.

[0010] FIG.4 is a flow diagram of an adaptive process for treating a brain injury in accordance with embodiments of the present technology.

[0011] FIGS.5A and 5B are schematic drawings of trials presented to a user during an adaptive process for treating a brain injury in accordance with embodiments of the present technology.

[0012] FIG. 6 is a flow diagram of a process for treating a neuropsychiatric disorder in accordance with embodiments of the present technology.

[0013] FIGS. 7 and 8 are schematic drawings of trials presented to a user during a process for treating a neuropsychiatric disorder in accordance with embodiments of the present technology.

[0014] FIG. 9 is a flow diagram of a process for treating a degenerative disease in accordance with embodiments of the present technology.

[0015] FIG. 10 is a block diagram of a process for selecting electrode groups for a process of treating a degenerative disease in accordance with embodiments of the present technology.

[0016] FIG.11A is a schematic drawing of an implantable device implanted in a patient’s brain in accordance with further embodiments of the present technology. -2- 169064111.3

[0017] FIG. 11B is a chart illustrating neural activity during a memory task in response to stimulation from varying groups of electrodes of an implantable device in accordance with further embodiments of the present technology.

[0018] FIG. 12A is a partially schematic side view of an electrode shank for an implantable device configured in accordance with embodiments of the present technology.

[0019] FIG. 12B is a partially schematic cross-sectional view illustrating additional details of the electrode shank of FIG. 2A in accordance with embodiments of the present technology.

[0020] FIG. 13 is a schematic drawing of an implantable device implanted in a patient’s brain in accordance with embodiments of the present technology.

[0021] FIG.14A is a schematic drawing illustrating additional details of an implantable device implanted in a patient’s brain in accordance with embodiments of the present technology.

[0022] FIG.14B is a schematic drawing illustrating additional details of an implantable device implanted in a patient’s brain in accordance with embodiments of the present technology.

[0023] FIG. 15 is a schematic drawing of an electrode patch for an implantable device configured in accordance with embodiments of the present technology.

[0024] FIGS. 16A and 16B are schematic drawings of the electrode patch implanted in a patient’s brain in accordance with embodiments of the present technology.

[0025] FIG. 17 is a schematic drawing of a non-invasive device for treating injuries, disorders, and / or diseases in a patient’s brain configured in accordance with embodiments of the present technology.

[0026] FIG.18 is a block diagram illustrating an overview of an example of a device on which some embodiments of the present technology can operate.

[0027] FIG.19 is a block diagram illustrating components of a computing device configured in accordance with some embodiments of the present technology.

[0028] Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and are not necessarily drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to aid in understanding of various aspects of the present technology. In addition, common but well-understood elements or -3- 169064111.3methods that are useful or necessary in a commercially feasible embodiment are often not depicted in the figures, or described in detail below, to avoid unnecessarily obscuring the description of various aspects of the present technology. DETAILED DESCRIPTION Overview

[0029] Systems and methods for treating injuries, disorders, and / or diseases in a patient’s brain are disclosed herein. For example, the systems disclosed herein can include a treatment subsystem that can present a patient with various different trials during treatment-related tasks and a stimulation device communicably coupled to the treatment subsystem. The stimulation device can provide stimulation (e.g., electrical stimulation, ultrasonic stimulation, microwave stimulation, and / or the like) to various regions of the user’s brain (e.g., the nucleus accumbens, caudate, front orbital cortex, dorsolateral prefrontal cortex, pars triangularis of the inferior frontal gyrus (expressive speech area), posterior superior temporal gyrus (receptive speech area), premotor cortex putamen, inferior temporal cortex, entorhinal cortex, and / or the like) based on responses received by the treatment subsystem in response to the trials. The stimulation can help build, reinforce, and / or augment associations in the patient’s brain to encourage learning, reinforce memory, and / or confer neuroprotection to help treat brain injuries and / or degenerative diseases. Additionally, or alternatively, the stimulation can help attenuate associations in the patient’s brain to help discourage maladaptive associations to help treat neuropsychiatric disorders (e.g., substance abuse disorder (SUD), obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), phobias, and / or the like).

[0030] In some embodiments, the stimulation device includes a main controller and one or more electrode shanks implanted into the patient’s brain. The electrode shank(s) can include a plurality of electrode groupings extending along a body of the electrode shank that each include a plurality of electrodes that are in contact with the targeted regions of the patient's brain. The main controller can receive signals from the treatment subsystem and deliver electric stimulation to subsets of the electrode groupings in the electrode shank depending on an epoch of the trial and / or treatment trial and / or the response received from the patient. Purely by way of example, a first subset of the electrode groupings can be in contact with the nucleus accumbens region while a second subset of the electrode groupings can be in contact with the caudate region. The main controller can provide electrical -4- 169064111.3stimulation to the first subset at the start of a trial to help engage the patient with the trial, then provide electrical stimulation to the second subset based on the response from the user. A relatively high frequency can be provided to the second subset to help encourage learning after a correct response while a low frequency can be provided to the second subset to help learning and / or associations after an incorrect response.

[0031] In some embodiments, the stimulation device includes a non-invasive device. The non- invasive device can include a helmet (or other suitable structural element, such as a flexible cap, exoskeleton, and / or the like) defining an outer body of the non-invasive device, as well as a plurality of stimulation emitters and a conductive gel each carried by the helmet. The helmet is sized to fit over the patient’s head. The plurality of stimulation emitters are positioned to direct stimulation signals (e.g., electrical signals, ultrasound waves, microwaves, and / or the like) into targeted regions of the patient’s brain once the patient puts the helmet on. The conductive gel is positioned to provide a buffer between the plurality of stimulation emitters and the patient’s head without impeding the flow of the stimulation signals.

[0032] In some embodiments, the treatment subsystem is configured to adapt over time based on a patient’s progress. Purely by way of example, the treatment subsystem can measure an accuracy of the patient's responses (e.g., correct, incorrect, nearly correct, a percentage score, timeliness of the response, and / or the like) to determine if a current difficulty of the tasks is correct. As a patient learns (or a degenerative disease impacts memory functions), the treatment subsystem can automatically adjust a difficulty of the tasks to match the patient’s cognitive abilities. In some embodiments, the complexity or difficulty level of tasks provided to the patient (and / or the adjustments made) are at least partially dependent on the patient’s willingness to engage with the trials. For example, the difficulty can be increased on a day the patient is energized and motivated to train, and decreased on a day when the patient is tired and / or disinterested in the training.

[0033] Additional details on various aspects of the technology are set out below. In the following description, specific details are set forth to provide a thorough understanding of aspects of the present technology. One skilled in the relevant art will recognize, however, that the systems, devices, and techniques described herein can be practiced without one or more of the specific details set forth herein, or with other methods, components, materials, etc. For example, one of skill in the art will understand that the technology disclosed herein is not limited to the specific arrangements -5- 169064111.3and parameters of electrode-devices are illustrated and discussed herein. In a specific, non-limiting example, subject to the express considerations set out below, an electrode shank can include ten, sixteen, thirty-two, and / or any other suitable number of electrode groupings.

[0034] As another example, although specific causes of brain injuries (e.g., strokes), specific neuropsychiatric disorders, and specific degenerative diseases are discussed below, one of skill in the art will understand that the technology disclosed herein can be used to help treat a wide variety of other brain disorders and / or diseases. In various specific, non-limiting example, the systems and methods disclosed herein can also be used to help treat attention deficit disorders, migraine headaches, eating disorders, depression, anxiety, and / or the like.

[0035] As yet another example, it will be understood that any of the systems and methods discussed below can be combined with other treatments for injuries, disorders, and / or diseases. For example, the systems and methods discussed below for treating a brain injury can be combined with other treatments; pharmaceuticals, medicines, and / or other ingested substances; and / or any other suitable methods of treatment to help rehabilitate a patient. In another example, the systems and methods discussed below for treating a neuropsychiatric disorder can be combined with various other pharmaceuticals, medicines, and / or other ingested substances and / or any other suitable treatment to help address the neuropsychiatric disorder.

[0036] Reference throughout this specification to an “example” or an “embodiment” means that a particular feature, structure, or characteristic described in connection with the example or embodiment is included in at least one example or embodiment of the present technology. Thus, use of the phrases “for example,” “as an example,” “in one embodiment,” or “an embodiment” herein are not necessarily all referring to the same example or embodiment and are not necessarily limited to the specific example or embodiment discussed. Furthermore, features, structures, or characteristics of the present technology described herein may be combined in any suitable manner to provide further examples or embodiments of the present technology.

[0037] Spatially relative terms (e.g., “beneath,” “below,” “over,” “under,” “above,” “upper,” “top,” “bottom,” “left,” “right,” “center,” “middle,” and the like) may be used herein for ease of description to describe one element’s or feature’s relationship relative to one or more other elements or features, as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of a device or system in use or operation, in addition to -6- 169064111.3the orientation depicted in the figures. For example, if a device or system illustrated in the figures is rotated, turned, or flipped about a horizontal axis, elements or features described as “below” or “beneath” or “under” one or more other elements or features may then be oriented “above” the one or more other elements or features. Thus, the terms “below” and “under” are non-limiting and can encompass both an orientation of above and below. The device or system may additionally, or alternatively, be otherwise oriented (e.g., rotated ninety degrees about a vertical axis, or at other orientations) than illustrated in the figures, and the spatially relative descriptors used herein are interpreted accordingly. In addition, it will also be understood that when an element is referred to as being “between” two other elements, it can be the only element between the two other elements, or one or more intervening elements may also be present.

[0038] It should also be noted that the terms “proximal” and “distal” as used herein, are intended to refer to a direction toward (proximal) and away from (distal) a surgeon or other user. Furthermore, the term electrical signal, as used herein, may include, for example, electrical impulses and signals with time-varying degrees of voltage, current, frequency, pulse duration, and / or wavelength. Introduction

[0039] The areas of the brain responsible for encoding sensory information and commanding movements (e.g., primary sensory and motor cortices) account for only a fraction (e.g., roughly 20%) of the cerebral cortex in humans. The remaining areas are association cortices in the parietal, temporal, and frontal lobes. The association cortices are concerned with attending to complex stimuli, identifying the relevant features of such stimuli, recognizing related objects, planning appropriate responses, understanding and generating speech, performing mathematics, and / or storing or remembering relevant aspects of this information. The association cortices are significantly larger in humans compared to other animals and are primarily responsible for the high level of human intellect compared to non-human animals.

[0040] The functions of the primary motor and sensory cortices are derived from their connectivity and are innate or relatively hardwired. In contrast, the capabilities of the association cortices are reached through learning and the development of neural pathways. For example, most human children will all gain a similar ability to walk in the same way at a certain point in their -7- 169064111.3development but learn very different languages depending on their families, countries of origin, and / or surroundings. The same applies to many other human capabilities such that much of the human brain, and the attendant behaviors thereof (both adaptive and maladaptive), depend in large part on learning.

[0041] Learning from naïveté to proficiency involves a complex sequence of behaviors, engaging multiple cortical-striatal circuits that vary depending on the learning task. The striatum includes multiple nuclei that are the input stage for the basal ganglia. The main circuits of interest for a majority of learning functions include the following cortical-striatal circuits (sometimes referred to herein as “loops”): (1) an Orbital Frontal Cortex (OFC) and Nucleus accumbens (NAcc) loop; (2) a Dorsolateral Prefrontal Cortex (DLPFC) and head of caudate (CDh) loop; (3) a premotor cortex (PMC) and putamen (PT) loop; (4) an Inferior Temporal Cortex (ITC) and caudate tail (CDt) loop; and (4) an ITC and hippocampus (HC) loop.

[0042] Each of these loops is broadly linked with important cognitive functions. For example, the OFC–NAcc loop is associated with assigning value and relative salience to stimuli, behaviors, and goals. In another example, the DLPFC–CDh loop is associated with exploration, trial-and error- learning, and decision-making. In another example, the PMC–PT loop is associated with the refinement and optimization of newly learned behaviors. In yet another example, the temporal lobe has two circuits associated with memory formation. One of these circuits, the ITC–CDt loop, is associated with assigning value and learning complex or multimodal stimuli (visual, auditory, and sensory). The other of these circuits, the ITC–HC loop, is critical in the encoding and consolidation of long-term visual, spatial, and verbal memories.

[0043] Further, each of the cortical and subcortical areas discussed above have strong projections from midbrain dopamine neurons. As a result, dopaminergic signaling plays a central role in learning. For example, short episodic bursts of phasic dopamine release signals reward prediction error (RPE), which is a feedback signal in temporal difference reinforcement learning models (TDRL). These bursts of phasic dopamine result in long-lasting potentiation of active cortical-striatal synapses, providing the mechanism for the physical instantiation of learning.

[0044] For example, the prefrontal cortex and striatum have strong inputs from midbrain dopaminergic neurons and respond to dopamine release during normal learning. Some of the inputs to the striatum (e.g., to the NAcc and / or the CD) arise primarily from the Ventral Tegmental Area -8- 169064111.3(VTA), whereas some of the inputs to the prefrontal cortex (e.g., to the dorsal PT) arise from the Substantia Nigra pars compacta (SNpc). In a specific example, typical striatal medium spiny projection neurons have inputs from 100–1000 dopamine neurons. These dopamine neurons fire maximally to an unexpected reward, moderately to an expected reward, and exhibit activity below tonic baseline levels in response to omitted rewards. As a result, the dopamine neurons signal a discrepancy, or temporal difference error, between expected and actual outcomes that can be utilized in reinforcement learning algorithms used in machine learning and / or as models of cortical striatal learning circuits. Additional details on examples of the cortical striatal learning circuits, as well as a demonstration that neurons in the DLPFC, NAcc, and CD are also modulated by prediction error (e.g., reflecting potential dopamine signaling), are discussed in Katnani, H. A. et al. Temporally Coordinated Deep Brain Stimulation in the Dorsal and Ventral Striatum Synergistically Enhances Associative Learning, SCI. REP. 6, 18806 (2016); Joshua P. Aronson et a., Phasic stimulation in the nucleus accumbens enhances learning after traumatic brain injury, 3 CEREBRALCORTEXCOMMUNICATIONS 2, pp.1–13 (2022); Ziv M Williams and Emad N Eskandar, Selective enhancement of associative learning by microstimulation of the anterior caudate, 9 NATURE NEUROSCIENCE 4, pp. 562–568 (Apr. 2006), and Sarah K. Bick et al., Caudate stimulation enhances learning, 142 BRAIN, pp. 2930–2937 (2019), the entirety of each of which is incorporated herein by reference.

[0045] Most adaptive learning is goal-directed and implemented by an exploratory trial-and- error approach, which can enhance the probability of discovering the most profitable associations between stimuli, behavioral responses, and positive outcomes. In humans and non-human primates, exploratory learning can engage the OFC–NAcc circuit implicated in salience and reward valuation, along with the DLPFC–CD circuit involved in forming associations between stimuli, behaviors, and outcomes. In both circuits, phasic dopamine release plays an important by signaling RPE.

[0046] Further, once an association is learned, behavior shifts toward a more efficient (but less flexible) approach that emphasizes the rapid generation of consistent responses or habits over reward outcomes. Habits serve an important purpose by optimizing the rapid attainment of predictable and biologically important rewards. The shift toward habitual responses coupled with well-learned memories correlates with a transfer of activity from the DLPFC–CD circuit to the PMC–PT circuit implicated in habitual behaviors. The PMC–PT circuit is more sensitive to the behavioral outcome than reward-contingency and is engaged in the selection and execution of well-learned behaviors. -9- 169064111.3Shifts from habitual behavior back to exploratory learning need to occur with fluidity to allow for adaptation in a dynamic environment.

[0047] That is, learning and memory work in tandem. For example, an organism in a new environment must quickly adapt to survive, using exploratory learning to investigate and attach value to novel elements, and forming long-term memories to retain salient features for rapid recall at later points in time. There are two parallel circuits (e.g., loops) involved in memory. One circuit resembles other cortical striatal loops and includes the neural activity connections from the temporal cortex to the tail of the caudate nucleus, to the globus pallidus externus, to the substantia nigra pars reticulata, to the thalamus, and then back to the temporal cortex. The other circuit also has the temporal cortex as its input stage, with information funneling into the entorhinal cortex (EC), and then sequentially through the hippocampus, mammillary bodies, anterior nucleus of the thalamus, and then back to the temporal cortex. Further, the ITC–HC loop discussed above is involved in both encoding and consolidation, which are both important steps of memory formation. Encoding is a process whereby new stimuli are, in essence, uploaded into the brain. The encoding process is driven through input by low-gamma (e.g., between about 30 Hertz (Hz) and about 70 Hz) and high-gamma (e.g., about 70 to 120 Hz) activity in superficial layers (e.g., layers I–III) of the EC at the time the stimuli are perceived. Consolidation is a process of strengthening salient memories while attenuating adjacent but imperfect, incomplete, or distorted perceptions. Consolidation can be mediated by a higher frequency of gamma (e.g., between about 70-120 Hz) and ripple-frequency (e.g., about 120 to 200 Hz) oscillatory activity in deeper layers of the EC (e.g., layers V–VI), in intervening periods or during sleep.

[0048] Traumatic brain injury, stroke, addictive substances, various neuropsychiatric disorders, and degenerative brain diseases can cause disruption of circuits mediating previously learned capabilities along with the learning and memory circuits discussed above. The disruption can lead to a range of disabilities and / or impairments in cognitive function and / or physical coordination. Reduced or subnormal activity in any of the circuits can result in atrophy, impairment of learning and motor behaviors, and / or decreased ability in the functions associated with the circuits discussed above. In a specific example, stroke and / or traumatic brain injury often result in focal damage to associative brain areas subserving functions such as speech, mathematical computation, cognitive processing, and complex decision-making. These functions can be relearned by adjacent, intact associative cortical -10- 169064111.3areas and / or homologous areas in the contralateral hemisphere. However, spontaneous recovery is often incomplete and / or frustrating for patients, despite rehabilitation.

[0049] Additionally, or alternatively, various neuropsychiatric disorders and / or conditions (e.g., substance abuse disorder (SUD), obsessive-compulsive disorder (OCD), post-traumatic stress disorder, phobias, and / or the like), reflect a pathological over-expression of normal functions so that salience leads to impulsivity, or an irresistible urge to act on various stimuli. For example, attaining common but biologically important stimuli such as food or water is rewarding and generates pulses of phasic dopamine release, though indirectly. Complex and finely tuned systems regulate food and fluid intake, where dopamine signaling plays an important role as a privileged internal control signal. In contrast, addictive substances enter the bloodstream, cross the blood-brain-barrier, and directly promote high amplitude bursts of phasic dopamine release through 1) excitation of dopaminergic neurons and inhibition of dopamine reuptake (stimulants), 2) mu-receptor mediated inhibition of GABAergic midbrain interneurons (opiates), or 3) modulation of ionic conductance (ethanol). The resultant bursts of phasic dopamine release can severely distort all phases of learning. As a result, for example, stimuli associated with an addictive substance become highly salient, triggering impulsive behavior, which is mediated by the NAcc and OFC. The capacity for novel exploratory learning becomes focused on drug-seeking, which is mediated by DLPFC and CD. Learned behaviors associated with the substance rapidly evolve into persistent habits that are difficult to reverse, despite absent or minimal reward and the risk of adverse outcomes. In another example, paralyzing anxiety, phobias, and disorders such as OCD also reflect learned or acquired behaviors that become maladaptive. These disorders do not arise from a pharmacologically exaggerated internal reward as in SUD, but rather an exaggerated value ascribed to avoidance of harm or other negative outcomes, which can come to have a greatly elevated internal reward value. Nonetheless, these are acquired or learned behavioral patterns that localize to associative cortices. As a result, learning can become dominated by avoidance of provocative stimuli for OCD. Additionally, or alternatively, habits can become compulsions (e.g., using drugs despite known overt harm, or spending hours handwashing in OCD despite known consequences of over-washing). Still further, memories can become intrusive and / or disabling (e.g., flashbacks in PTSD).

[0050] Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of individuals and is clinically characterized by gradual deterioration of memory, or -11- 169064111.3dementia. In the early stages of AD, an individual may function independently, work, and be part of social activities, despite having memory lapses, such as forgetting familiar words or the location of everyday objects. As the dementia progresses. the person may confuse words, get frustrated or angry, and act in unexpected ways, such as refusing to bathe. In the late stages of the disease, dementia symptoms are severe, and affected individuals lose the ability to respond to their environment, to carry on a conversation, and / or to control movement, requiring extensive care.

[0051] The development of intraneuronal lesions at selectively vulnerable brain sites is central to the pathological process in AD. The lesions consist chiefly of the accumulation of hyperphosphorylated Tau protein and the resulting neurofibrillary tangles (NFTs) in cell bodies, along with the presence of plaques composed of the amyloid-beta peptide (Aβ). Neuroanatomically, AD progresses in well characterized stages that correlate with clinical progression. The earliest abnormality in Stage I is the deposition of Tau protein in the entorhinal cortex exclusively. In Stage II, Tau protein deposition expands to involve the hippocampus. In Stage III, the abnormality expands to the lingual and fusiform gyri in the temporal association cortex. In Stages IV-VI, the disease progresses more widely into neocortical association areas and eventually involves most of the brain.

[0052] Critically, the pathological process begins in the entorhinal cortex and hippocampus. Sensory stimulation in a low gamma band at 40 Hz has been shown to help clear abnormal protein deposition in a mouse model of AD. The systems and methods disclosed herein include embodiments designed to support an increase (or maximization of) the amplitude of low gamma and / or high gamma neuronal activity in a patient’s brain, continuously, to help support and / or strengthen memory encoding and / or consolidation, respectively. Further, the systems and methods disclosed herein can continuously adapt the spatiotemporal stimulation patterns to help keep the amplitude at a desired level (e.g., a level associated with a known, target state). Still further, the systems and methods disclosed herein can help normalize activity in the entorhinal cortex and hippocampus in a chronic and physiological manner to enhance and normalize memory formation and consolidation. The stimulation may thus promote clearance of abnormal Tau and Aβ deposits, as well as the reversal of other pathological changes, thereby helping impede (or prevent) the otherwise relentless progression of Alzheimer’s disease.

[0053] The systems and methods discussed in more detail below can help treat injuries, disorders, and / or diseases in a patient’s brain. For example, the systems and methods discussed herein -12- 169064111.3can help direct the augmentation of learning in intact areas of the patient's brain after an injury and / or accelerate and / or enhance neurological recovery. In a related example, the systems and methods discussed herein can help strengthen and / or maintain existing neurological functions to mitigate the progression and / or effects of degenerative diseases. In another example, the systems and methods discussed herein can help attenuate maladaptive associations and / or augment useful or healthy associations to help provide a more complete and durable treatment of substance abuse and related disorders. In yet another example, the systems and methods discussed herein can help attenuate maladaptive associations and / or augment useful or healthy associations to help provide a more complete and durable treatment of OCD, PTSD, phobias, and other anxiety-spectrum disorders. Examples of Suitable Systems and Methods for Treating Injuries, Disorders, and / or Diseases in a Patient’s Brain

[0054] FIG. 1A is a schematic drawing of a system 100 for treating injuries, disorders, and / or diseases in a brain of a patient 10 configured in accordance with embodiments of the present technology. As illustrated in FIG. 1A, the system 100 can include a stimulation device 110 and a treatment subsystem 120 communicably coupled to the stimulation device 110. As discussed in more detail below, the stimulation device 110 can include one or more implanted components (e.g., an electrode shank implanted in the patient’s brain, an electrode patch coupled to an exterior surface of the patient’s brain, a main controller embedded within and / or under the scalp (but superficial to the patient’s skull), and / or the like) and / or various non-invasive devices. As also discussed in more detail below, the treatment subsystem 120 (sometimes also referred to herein as a “therapy subsystem,” a “learning subsystem,” a “rehabilitation subsystem,” a “training subsystem,” and / or the like) can administer various trials to the patient 10 that are related to treating various injuries, disorders, and / or diseases. The treatment subsystem 120 can also receive responses from the patient 10 for each trial. The treatment subsystem 120 (or another suitable device, such as a cloud computing device coupled to the treatment subsystem 120) can then evaluate the response to determine whether the response is correct or incorrect, an accuracy level of the response (e.g., 70% correct and / or any other measure of accuracy), whether the accuracy level is above a predetermined threshold, and / or the like. The treatment subsystem 120 can then communicate with the stimulation device 110 to deliver (or withhold) stimulation based on the evaluation of the response. Additional details on examples of the stimulation device 110 and various processes implemented by the system 100 are discussed below. -13- 169064111.3

[0055] FIG. 1B is a block diagram illustrating additional details of the system 100 of FIG. 1A in accordance with embodiments of the present technology. For example, as illustrated in FIG. 1B, the stimulation device 110 can include stimulation generators 112 that are positioned (or positionable) to deliver stimulation to the patient 10 as well as a communication component 114. The communication component 114 can include a shortrange wireless component, such as Medical Device Radiocommunications Service (MedRadio), a Bluetooth® component, a Zigbee component, a near- field communication component, a Wi-Fi component, a Wireless Medical Telemetry Service (WMTS) component, and / or any other suitable shortrange component. As further illustrated in FIG. 1B, the treatment subsystem 120 can be implemented (fully or in part) on a patient user device that provides a user interface (UI) 122 as well as a communication component 124. In various embodiments, the patient user device can include a personal computer, a handheld or laptop device, a cellular telephone, wearable electronics, a gaming console, a tablet device, an augmented reality device, a virtual reality device, a network PC, a minicomputer, and / or any combination thereof. Similar to the discussion above, the communication component 124 of the treatment subsystem 120 communicates with the communication component 114 of the stimulation device 110 to instruct the stimulation device 110 on when to deliver stimulation. Additionally, or alternatively, the stimulation device 110 can communicate with the treatment subsystem 120 to provide various telemetric measurements (e.g., measurements of neural activity in the patient’s brain).

[0056] As still further illustrated in FIG.1B, the system 100 can also include various peripheral subsystems, such as a medical user device 130 and / or a remote subsystem 140 (e.g., a cloud computing system). In the illustrated embodiment, the medical user device 130 is generally similar to the patient user device. For example, the medical user device 130 includes a UI 132 as well as a communication component 134. A medical practitioner can interact with the UI 132 to provide various evaluations of the patient 10 during a treatment session, to set and / or scale a difficulty of trials during a treatment session, to evaluate responses from the patient 10, and / or the like. The communication component 134 can then communicate with the treatment subsystem 120 in the patient user device to implement any of the treatment processes discussed in more detail below. Additionally, or alternatively, the communication component 134 can communicate directly with the communication component 114 in the stimulation device 110 to instruct the stimulation device 110 -14- 169064111.3to provide stimulation to the patient’s brain, to receive various telemetric measurements, and / or the like.

[0057] The remote subsystem 140 can include one or more servers as well as one or more databases that allow the remote subsystem 140 to support and / or facilitate various operations in the system 100. For example, as discussed in more detail below, various processes of the treatment subsystem 120 can include artificial intelligence (AI) and / or machine learning (ML) processing, speech recognition processing, and / or complex computations. In these and other embodiments, the remote subsystem 140 can execute the computationally heavy processing to accelerate the operation of the treatment subsystem 120. In some such embodiments, the remote processing can be critical to allowing the treatment subsystem 120 to respond to inputs (e.g., speech, touch inputs, and / or the like) from the patient 10 in real-time to instruct the stimulation device 110 to provide (or withhold) stimulation to the patient’s brain, provide new prompts to the patient to continue a trial (or start a new trial), adjust a difficulty of trials being administered to the patient 10, and / or the like. Additionally, or alternatively, the remote subsystem 140 can communicate with the medical user device 130 to perform various computational functions (e.g., to help determine a difficulty level for trials, evaluate responses from the patient 10, and / or the like), to record and / or store data related to the system 100 (e.g., measurements of the patient’s accuracy in their responses, a record of the trials administered, measurements from the stimulation device (e.g., neural activity), a record of evaluations from a medical practitioner, and / or the like), and / or any other suitable function.

[0058] FIG. 2A is a schematic drawing of an implantable device 200 for treating injuries, disorders, and / or diseases in a patient’s brain configured in accordance with embodiments of the present technology. The implantable device 200 illustrated in FIG. 2A can be a part (or all) of the stimulation device 110 discussed above with respect to FIGS. 1A and 1B to provide stimulation to a patient’s brain 12. In the illustrated embodiment, the implantable device 200 includes a main controller 210, bilateral electrode shanks 230 (e.g., implanted in the left and right hemispheres of the patient’s brain 12), and one or more communication lines 240 (one illustrated in FIG. 2A for each of the bilateral electrode shanks 230) coupled between each of the bilateral electrode shanks 230 and the main controller 210. In some embodiments, the implantable device 200 further includes one or more electrode patches (e.g., as discussed below with reference to FIGS. 15–16B) that can be coupled to an external surface of the patient’s brain. In various embodiments, the implantable device 200 can -15- 169064111.3include other numbers of the bilateral electrode shanks 230, such as one, three, four, and / or any other suitable number of electrode shanks implanted in the patient’s brain 12. Additional details on various specific aspects of the electrode shanks are discussed below with reference to FIGS. 12A–14B.

[0059] FIG.2B is a schematic drawing illustrating additional details on the main controller 210 of the implantable device 200 of FIG.2A in accordance with embodiments of the present technology. As illustrated in FIG. 2B, the main controller 210 (sometimes also referred to herein as an “implant controller,” a “control chip,” and / or the like) can include a processor chip 212 (e.g., a processing unit and one or more memory devices), a battery 214 (or other power source), a power conditioning module 216 coupled to the battery 214 and the processor chip 212, a communication component 218 coupled to the processor chip 212, and an input / output (I / O) component 220 coupled between the processor chip 212 and the one or more communication lines 240 (four illustrated in FIG. 2B).

[0060] During operation of the implantable device 200 of FIG. 2A, the communication component 218 can receive information from and / or send information to a peripheral computing system (e.g., the treatment subsystem 120 of FIG.1A, the medical user device 130 of FIG.1B, and / or the like). The information can include, for example, instructions to provide stimulation to the patient’s brain 12 (FIG.2A). The communication component 218 can then pass the information to the processor chip 212 which receives the instructions, then controls the battery 214 and / or the power conditioning module 216 to drive an electric current through the one or more communication lines 240. As a result, the processor chip 212 causes an electric current to be delivered to the bilateral electrode shanks 230 (FIG. 2A), thereby delivering stimulation to the patient’s brain 12. In another example, the processor chip 212 can receive information from the bilateral electrode shanks (FIG.2A), such as measurements of neural activity, process and / or format the information, then send the information to a peripheral computing device via the communication component 218.

[0061] It will be understood that the main controller 210 can include various additional, or alternative, components not illustrated in FIG. 2B. For example, in embodiments where the implantable device 200 (FIG. 2A) also includes one or more electrode patches, the main controller 210 can include another I / O component coupled between the processor chip 212 and communication line(s) coupled to the electrode patch(es).

[0062] FIG. 3 is a flow diagram of a process 300 for treating a brain injury in accordance with embodiments of the present technology. It will be understood that the process 300 can be executed -16- 169064111.3by any suitable device (or devices) in the system 100 discussed above with respect to FIGS. 1A and 1B. For example, the process 300 can be executed by the treatment subsystem 120 operating on a patient’s user device (e.g., a smartphone, tablet, computer, wearable device, augmented reality device, virtual reality device, and / or any other suitable device). Additionally, or alternatively, although discussed herein in the context of being executed primarily within a single component (e.g., entirely within the patient’s user device), it will be understood that a first subset of the process 300 can be executed by a different device than a second subset of the process 300.

[0063] The process 300 can begin at block 302 by initiating a treatment session for a patient. The process 300 can initiate a treatment session in response to inputs from a medical professional (e.g., a nurse, a doctor, a physiatrist, and / or the like interacting with the patient user device and / or the medical user device 130 of FIG.1B). As a result, for example, the process 300 can be initiated during supervised rehabilitation and / or other treatment sessions with the patient. In another example, the process 300 can initiate a treatment session in response to a patient interacting with an electronic device (e.g., interacting with an application on the patient user device of FIG. 1B). As a result, for example, the process 300 can allow a patient to receive treatment (e.g., continue rehabilitation) without direct supervision from a medical professional (e.g., at home). In yet another example, the process 300 can be initiated automatically by a treatment subsystem. In a specific, non-limiting example, the process 300 can be initiated in response to a detection of one or more conditions (e.g., that a patient is interacting with a user device, a detection of one or more stimulants, and / or the like). In another specific, non-limiting example, the process 300 can be initiated in response to an analysis of a patient’s interactions with a surrounding environment (e.g., by an AI algorithm detecting that the patient is engaging in or with exploratory learning, trial-and-error learning, memory-related tasks, or maladaptive behavior triggers including exposure to substances, exposure to OCD triggers, and / or the like).

[0064] At block 304, the process 300 includes administering one or more trials within a task to the patient. The task can be a broad category related to the treatment of the patient. For example, for a patient with a traumatic brain injury resulting in expressive aphasia, receptive aphasia, and / or the like the tasks can include word matching games, speech games, and / or the like. In a specific, non- limiting example, individual trials within a speech game task can include presenting the patient with an audio-visual prompt (e.g., a picture of an object, an image of a word and / or phrase, an image of a -17- 169064111.3sentence, a recording of a word and / or phrase, an audio-video prompt, and / or the like) that requests that the patient respond with spoken words. In another example, for a patient with OCD, the tasks can include reaction training to common triggers, where individual trials present the patient with an audio- visual trigger (e.g., a picture of a public railing, a recording of a sneeze, and / or the like) and a prompt for the user to respond with various reactions (e.g., a prompt asking the user if they should say “bless you,” or run to wash their hands after hearing the sneeze).

[0065] At block 306, the process 300 includes receiving a response from the patient. In some embodiments, the response is received through patient interactions with a user interface (e.g., the UI 122 of FIG. 1B), such as selecting one or more responses on the user interface. In some embodiments, the response is received through various other interactions with a user device (e.g., audio recordings of the patient’s response during speech games, audio recordings of the patient’s reaction to a prompt (sometimes also referred to herein as a “cue”), a measurement of the patient’s motion based on gyroscopic measurements from a user device, and / or the like). In some embodiments, the response is received through one or more recordings and / or measurements of the patient. For example, the measurements can include eye-tracking measurements to track a patient’s response to the prompts, triggers, and / or the like. The eye tracking can allow the trials to be administered to patients who lack various ranges of motion (e.g., a patient with a traumatic brain injury impacting their motor skills). Additionally, or alternatively, the eye tracking can help record other metrics of a response, such as whether the patient considered alternative responses to the one they input into a user device. Additionally, or alternatively, the eye-tracking measurements can serve as inputs to machine learning algorithms that can be utilized to inform, configure, modify, steer, and / or present tasks and / or trials. In another example, the measurements can include various audio-visual measurements of a patient within an environment. In a specific, non-limiting example, the audio- visual measurements can track patient movement and interactions within an environment to record how the patient responds to a prompt, trigger, and / or the like (e.g., “go pick up a book,” a coughing noise, and / or the like). These audio-visual measurements can serve as inputs to machine learning algorithms that can be utilized to inform, configure, modify, steer, and / or present tasks and / or trials.

[0066] At block 308, the process 300 includes determining if the response received from the patient is correct. The determination can check whether a selection, spoken, and / or action response conforms with an expectation based on the prompt, trigger, and / or the like. In a specific, non-limiting -18- 169064111.3example of a trial for a patient with receptive aphasia, the prompt can include an audio recording instructing the user to select the color “green” on the user interface and the user interface can present a green box, a blue box, a red box, and a yellow. If the patient selects the green box, the process 300 determines that the response was correct. Conversely, if the patient selects any of the blue, red, and / or yellow boxes, the process determines that the response is incorrect.

[0067] At block 310, in response to determine that the response is correct at block 308, the process 300 includes indicating the correct response to the patient and delivering a high-frequency stimulation to the patient’s brain (e.g., to the caudate region of the patient’s brain). The indication can confirm to the patient that they responded to the prompt and / or trigger correctly, allowing the patient to learn (or reinforce) the correct responses. Further, as discussed above, the high-frequency stimulation can help reinforce learning associated with the correct response to enable the patient to learn more quickly, form stronger associations with the correct responses, build positive behaviors, maintain memory and / or other cognitive functions, and / or the like. In various embodiments, the high- frequency stimulation can be between about 180 Hz and about 220 Hz, between about 190 Hz and about 210 Hz, and / or about 200 Hz. Further, the high-frequency stimulation can be delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second. Still further, the high-frequency stimulation can be delivered with an amplitude between about 0.5 milliamperes (mA) and about 2 mA, or of about 1 mA. The process 300 at block 310 can include communicating with a stimulation system (e.g., an implanted device and / or a non-invasive device) to cause the stimulation system to deliver the stimulation. Purely by way of example, the process 300 at block 310 can include communicating with the main controller 210 of FIG. 2A to deliver stimulation to the patient’s brain (e.g., to the caudate region, to the entorhinal cortex, and / or the like) via the bilateral electrode shanks 230.

[0068] Conversely, in response to a determination that the response is incorrect at block 310, the process 300 can include indicating the incorrect response to the patient. The indication can allow the patient to confirm that their response was incorrect to try a different response to future prompts and / or triggers.

[0069] Additional details on examples of processes for stimulating a patient’s brain during learning tasks are discussed in U.S. Patent Application No. 2013 / 0184781 entitled BRAIN STIMULATION FOR ENHANCEMENT OF LEARNING, MOTIVATION, AND MEMORY, filed -19- 169064111.3July 6, 2011; U.S. Patent Application No. 2016 / 0331973 entitled IMPLANTABLE HUB AND SATELLITE SYSTEM FOR NEURAL RECORDING AND STIMULATION, filed May 13, 2016; U.S. Patent Application No. 2017 / 0281846 entitled SYSTEMS AND METHODS FOR PATIENT REHABILITATION USING BRAIN STIMULATION, filed September 28, 2015; Katnani, H. A. et al. Temporally Coordinated Deep Brain Stimulation in the Dorsal and Ventral Striatum Synergistically Enhances Associative Learning, Sci. Rep. 6, 18806 (2016); Joshua P. Aronson et a., Phasic stimulation in the nucleus accumbens enhances learning after traumatic brain injury, 3 Cerebral Cortex Communications 2, pp. 1–13 (2022); Ziv M Williams and Emad N Eskandar, Selective enhancement of associative learning by microstimulation of the anterior caudate, 9 Nature Neuroscience 4, pp. 562–568 (Apr. 2006), and Sarah K. Bick et al., Caudate stimulation enhances learning, 142 Brain, pp. 2930–2937 (2019), the entirety of each of which is incorporated herein by reference. Specific Examples of Suitable Adaptive Behavioral Training Systems and Methods for Treating Injuries in a Patient’s Brain

[0070] FIG. 4 is a flow diagram of an adaptive process 400 for treating a brain injury and / or a degenerative disease in accordance with embodiments of the present technology. Similar to the process 300 discussed above with respect to FIG. 3, the process 400 can be executed by any suitable device (or devices) in the system 100 discussed above with respect to FIGS.1A and 1B. For example, the process 400 can be executed by the treatment subsystem 120 operating on a patient’s user device (e.g., a smartphone, tablet, computer, and / or any other suitable device). Additionally, or alternatively, although discussed herein in the context of being executed primarily within a single component (e.g., entirely within the patient’s user device), it will be understood that a first subset of the process 400 can be executed by a different device than a second subset of the process 400. Further, as illustrated in FIG.4, the process 400 is generally similar to the process 300 discussed above, modified to include an adaptive behavioral training (ABT) system. The ABT system can adjust a difficulty level of the tasks and / or trials based on a patient’s performance, a patient’s engagement level, and / or various other considerations (e.g., inputs from a medical professional, how many other tasks and / or trials the patient has completed in a given day, and / or the like). As a result, as discussed in more detail below, the ABT system can automatically adapt the tasks and / or trials according to a patient’s cognitive levels (e.g., -20- 169064111.3based on where the patient is in their rehabilitation, their motivation and / or energy levels to engage with the trials, peripheral observations from a medical professional, and / or the like).

[0071] The process 400 begins at block 402 by initiating a treatment session. Similar to the process 300 discussed above, the process 400 can be initiated by a patient (e.g., interacting with a user device), a medical professional (e.g., during a rehabilitation session), and / or automatically by an algorithm (e.g., in response to a detection that the patient is engaging with exploratory learning and / or trial-and-error learning; by an AI model detecting interactions between a patient and an environment; by an AI model and / or algorithm after detecting that a patient has sufficient energy levels for a session based on neural activity measurements, and / or the like); and / or the like. In some embodiments, initiating a treatment session includes selecting one or more tasks for the patient during the treatment session (e.g., image recognition tasks, word / phrase recognition tasks, word / phrase pronunciation tasks, motion-based tasks; memory-related tasks; and / or the like).

[0072] At block 404, the process 400 includes determining a difficulty level for the treatment session. The difficulty level can be determined automatically based on a previous difficulty level (e.g., the most recent difficulty level, a reduction of the most recent difficulty level to allow the patient to warm up, an increase of the most recent difficulty level to challenge the patient, and / or the like). In some embodiments, the difficulty level can be based on one or more algorithmic determinations and / or one or more AI processes. In a specific, non-limiting example, a generative AI model can interact with the patient while initiating the treatment session (e.g., via text-to-speech, text on a user interface, and / or the like) and assess a cognitive level of the patient, an energy level of the patient, an engagement level of the patient, and / or the like. Additionally, or alternatively, the difficulty level can be based on inputs from a medical professional. For example, when the patient has engaged in other rehabilitation activities with a physiatrist, the physiatrist can set the difficulty level based on their evaluations of the patient.

[0073] Additionally, or alternatively, the difficulty level can be based on inputs from the patient related to their current rehabilitation level and / or their level of interest and / or readiness. In a specific, non-limiting example, the patient-inputs can include a self-reported value on a linear scale (e.g., a response of one of: “I feel ready to perform the task,” “I am willing and able to perform the task,” “I do not feel ready but am capable of performing the task,” “I do not feel ready today and wish to postpone the task”; a to “My cognitive load feels” of: “High,” “Normal,” “Low”; a rating of readiness -21- 169064111.3a scale of 1–10; and / or the like), where higher self-reported values can result in a higher difficulty (e.g., to challenge the patient while they feel engaged) and / or lower self-reported values can result in a lower difficulty (e.g., to provide some rehabilitation to the patient without exhausting the patient). In another specific, non-limiting example, the patient-inputs can include responses to one or more indexing trials (e.g., trials performed repeatedly to set a baseline during the course of treatment, such as solving an easy puzzle). The responses can then be compared to a known baseline for the indexing trials to determine a relative readiness of the patient compared to their average.

[0074] At block 406, at the start of one of the selected tasks, the process 400 can apply stimulation to the nucleus accumbens (NAcc) region of the patient’s brain at the start of a first trial. The process 400 at block 406 can include communicating with a stimulation system (e.g., an implanted device and / or a non-invasive device) to cause the stimulation system to deliver the stimulation. Purely by way of example, the process 400 at block 406 can include communicating with the main controller 210 of FIG. 2A to deliver stimulation to the nucleus accumbens via the bilateral electrode shanks 230. As discussed above, the stimulation to the nucleus accumbens can help the patient engage with the trial, in helping increase the benefits of the stimulation system during the treatment of the brain injury and / or degenerative disease. In some embodiments, the stimulation delivered at block 406 can be a high-frequency stimulation (e.g., stimulation between about 180 Hz and about 220 Hz, between about 190 Hz and about 210 Hz, and / or about 200 Hz; delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second; and delivered with an amplitude between about 0.5 mA and about 2 mA, or of about 1 mA).

[0075] At block 408, the process 400 includes administering the trial to the patient simultaneously (or generally simultaneously) with the delivery of stimulation at block 406. Similar to the discussion above, administering (e.g., presenting) the trial to the patient at block 408 can include providing the patient with an audio-visual prompt that elicits a response from the patient (e.g., an audio recording asking the patient to select an image associated with a phrase; a graphic that the patient must identify by speaking a word or phrase; a series of numbers, words, actions, and / or the like the patient must repeat; and / or the like). The trial can be administered via a patient user device (e.g., a tablet, smartphone, laptop computer, desktop computer, and / or the like), an augmented reality device, a virtual reality device, a gaming console, and / or the like. -22- 169064111.3

[0076] At block 410, the process 400 includes receiving a response from the patient. Similar to the discussion above, the process 400 can receive the response via an interaction with a user device (e.g., touching one or more areas of a user interface), recording an audio response from the patient (e.g., the patient pronouncing a word or phrase), recording the patient’s interactions with their environment, recording eye motion in the patient, and / or the like. Further, the process 400 at block 410 can receive various supplementary information in (or with) the response. For example, the supplementary information can include how long the patient took to provide the response, whether the patient attempted the response multiple times (e.g., attempted to speak, stuttered, attempted to touch a region of a user interface, and / or the like), various metrics that assess attention, vigilance, or alertness (e.g., from an infrared eye tracker (pupil diameter; saccade rate, magnitude, and / or velocity of eye movement; and / or the like), sensors providing recordings of electric fields (field potentials) produced by brain activity (e.g., externally-placed electroencephalography (EEG) electrodes, implanted subdural electrocorticography (ECoG) electrodes, intracortical micro and macro electrodes, and / or other intracranial electrodes), and / or the like), whether the patient had to be redirected to the trial (e.g., by a medical professional), and / or any other suitable information.

[0077] At block 412, the process 400 includes determining an accuracy of the response. In some embodiments, the accuracy is limited to correct and incorrect (e.g., did the patient select the correct response). In some embodiments, the accuracy is evaluated on a scale (e.g., a percentage grade, on a scale from 0 to 1, and / or the like). For example, a patient prompted to select a “green square” from a user interface that includes a green square, a yellow square, a red triangle, and a blue circle that selects the yellow square can be given a 50% accuracy score. In another example, the process 400 can determine the accuracy based on a summed magnitude of a rectified cross-correlation of produced speech compared to a reference template for a desired sound (e.g., in response to a prompt to say the word “banana,” a first response from the patient saying “banan” can be given a higher accuracy than a second response from the patient saying “ban”). In another example, the process 400 can determine the accuracy based on a matching index resulting from standard speech recognition software. In another example, the process 400 can determine the accuracy based on a spatial accuracy measured as a radial distance of where the response is received from the target for a touch or eye movement cue (e.g., the patient can be given a higher accuracy for touching a user interface 1 inch from the target than for touching the user interface 2 inches from the target). In some embodiments, the -23- 169064111.3supplementary information can be factored into the determination of the accuracy. For example, the patient can receive a lower accuracy score when they stutter before pronouncing a word (or phrase) than when they do not stutter. In another example, the process 400 can determine a lower accuracy score for the patient when they needed to be redirected to the trial compared to when they did not need redirection.

[0078] At block 414, the process 400 includes applying (or withholding) stimulation to the caudate region (and / or any other suitable region) of the patient’s brain based on the accuracy of the response. For example, when the patient responds to the prompt at block 408 correctly (e.g., indicating some learning) and / or above a predetermined threshold (e.g., above 60% accuracy), the process 400 at block 414 can instruct a stimulation device (e.g., an implanted device and / or a non-invasive device) to deliver a high-frequency stimulation to the caudate region of the user’s brain. As discussed above, the high-frequency stimulation can help reinforce learning associated with the correct response to enable the patient to learn more quickly, form stronger associations with the correct responses, and / or the like. Further, in various embodiments, the high-frequency stimulation can be between about 180 Hz and about 220 Hz, between about 190 Hz and about 210 Hz, and / or about 200 Hz; delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second; and delivered with an amplitude between about 0.5 mA and about 2 mA, or of about 1 mA. In another example, the process 400 can instruct the stimulation device to deliver stimulation to various other portions of the entorhinal cortex to reinforce memory formation and / or maintenance. In some embodiments, the magnitude and / or duration of the stimulation can be based on the accuracy of the response. For example, a perfectly accurate response can be given a longer (or higher magnitude) stimulation than a 75% accurate response. The scaling of the stimulation can allow the process 400 to moderately reward partially correct answers to encourage learning while maximally rewarding very correct answers to help increase the resulting benefit from very correct responses.

[0079] At block 416, the process 400 includes determining a difficulty of the next trial based on the accuracy of the response, any of the supplementary information (e.g., how long the patient took to respond to the prompt), inputs from a medical professional, and / or various other information (e.g., an indication of how interested, engaged, energized, and / or willing to participate the patient is). For example, when the patient is consistently responding to prompts accurately and quickly, the process 400 can determine that the patient is ready for more difficult trials (e.g., to be prompted to -24- 169064111.3pronounce words with multiple syllables, non-phonetic spellings, complex phrases, and / or the like). Conversely, if the patient is not answering prompts correctly and / or is disengaged, the process 400 can reduce the difficulty of the trials to help keep the patient motivated and / or to make some progress on learning.

[0080] The process 400 can then return to block 406 to apply stimulation to the nucleus accumbens region of the patient’s brain at the start of the next trial, administer the next trial to the patient, receive a response from the patient, determine an accuracy of the response, apply (or withhold) stimulation to the caudate (or other) region of the patient’s brain, and determine the difficulty of the next trial. The process 400 can repeat the loop in blocks 406–416 any suitable number of times during a task (e.g., twice, three times, five times, ten times, fifty times, one hundred times, and / or any other suitable number of times) before moving to a next task and / or completing the treatment session. In some embodiments, the number of trials (e.g., loops through blocks 406–416) in a treatment session and / or individual task of a treatment session is variable. For example, the number of trials can vary based on the patient’s energy, engagement levels, willingness to participate, the number of other tasks and / or treatment sessions already completed on a given day, and / or the like. Once the process 400 is done looping through blocks 406–416, the process 400 moves to block 418.

[0081] At block 418, the process 400 includes recording an evaluation of the patient’s responses to the trial(s) in the task. For example, the process 400 can record an overall accuracy (e.g., average accuracy, weighted accuracy, and / or the like) of the responses to the trials. Additionally, or alternatively, the process 400 can record observations from a medical professional on the patient’s performance during the trials. Additionally, or alternatively, the process 400 can record supplemental information, such as an average response time from the patient, engagement levels with the trials, and / or the like. The record can be used before future treatment sessions to determine a difficulty level of the tasks in the future treatment sessions. Additionally, or alternatively, the record can provide a review of the patient’s progress that can be reviewed by a medical professional to track the patient’s rehabilitation.

[0082] Although the blocks 402–418 of the process 400 are discussed and illustrated in a particular order, the process 400 illustrated in FIG. 4 is not so limited. For example, various steps of the process 400 can be performed in a different order and / or combined. In these and other embodiments, any of the blocks 402–424 of the process 400 can be performed before, during, and / or -25- 169064111.3after any of the other blocks 402–424 of the process 400. In a specific, non-limiting example, block 418 can be executed before block 416 after looping through blocks 406–414 to administer a plurality of trials to the patient within a task at a determined difficulty level, evaluate the patient’s performance across the task, then determine a difficulty level of the next task (or treatment session). In this example, the process 400 can adjust the difficulty level more slowly, but can better account for minor variations in performance between trials (e.g., to not overreact to an especially good or bad performance in any given trial). Moreover, a person of ordinary skill in the relevant art will recognize that the illustrated process 400 can be altered and still remain within these and other embodiments of the present technology. For example, the process 400 can be modified in view of any of the processes discussed below with reference to FIGS. 6, 9, and / or 10.

[0083] In a specific, non-limiting example, the process 400 can be modified for relatively unstructured trials being administered by a generative AI tool. In this example, the generative AI tool can interact with the patient to provide various prompts associated with different tasks, evaluate the patient’s responses, and reward correct responses. In this example, the generative AI can more closely mimic rehabilitation administered directly from a medical professional while incorporating stimulation to the patient’s brain to help accelerate outcomes.

[0084] In another specific, non-limiting example, the process 400 can be modified to omit the administration of tasks through a specific user device and instead monitor the patient’s engagement with their environment. In this example, the process 400 can identify trials and / or tasks the patient encounters in their environment (e.g., learning how to play with a toy, completing a simple puzzle, learning to open a door, remembering directions between locations, and / or the like) and reward the patient when they correctly interact with their environment. In this example, the process 400 can extend rehabilitation stimulation beyond supervised treatments to continuously stimulate the patient in response to their improvements. As a result, the modified process can help accelerate rehabilitation outcomes and / or improve overall results.

[0085] In yet another specific, non-limiting example, the process 400 discussed above can be implemented by an ABT system (e.g., within a treatment subsystem of the type discussed above with reference to FIGS. 1A and 1B) built to rehabilitate a patient with expressive aphasia. In some cases, expressive aphasia impacts a patient’s ability to speak fluently despite the patient’s comprehension being relatively preserved, which can result in a frustrating, slow rehabilitation process. In this -26- 169064111.3example, the ABT system can be built to account for five domains of human language: (1) phonology, which is based around the sounds in a language (phonemes) and rules that govern sound combinations; (2) morphology, which is based around the smallest units in a language which have meaning (morphemes) and their rules for use and combination (e.g., combining individual words and / or grammatical markers (e.g., “-ed” to show past tense); (3) syntax, which is based around the rules that determine how words are organized into sentences; (4) semantics, which is based around the meaning of words and groups of words; and (5) pragmatics, which is based around how language is used in specific contexts to communicate and the rules governing its use. Further, the ABT system can be trained and / or programmed with a language model that is adjusted based on the patient’s age, educational level, and / or dialect. Additionally, or alternatively, the ABT system can be trained and / or adjusted with audio-visual recordings of the patient prior to a brain injury and / or training sessions with family and friends of the patient.

[0086] In yet another specific, non-limiting example, the process 400 discussed above can be implemented by an ABT system (e.g., within a treatment subsystem of the type discussed above with reference to FIGS. 1A and 1B) built to rehabilitate a patient with receptive aphasia. Individuals suffering from receptive aphasia can have impaired comprehension and / or significant difficulty in understanding spoken language. For example, patients with receptive aphasia can struggle to follow conversations and / or comprehend instructions. Further, while their speech production is usually fluent, their speech often lacks meaningful content. For example, patients with receptive aphasia can produce long, rambling sentences that include irrelevant and / or nonsensical words and / or can substitute words / phrases with incorrect words (phonemic or semantic paraphasias). Still further, their writing can reflect the same comprehension issues as the speech impairment. Unlike expressive aphasia, however, patients with receptive aphasia may be unaware of their language difficulties, often believing their speech is coherent and meaningful. In this example, the ABT system can be built to account for the five domains of human language discussed above and trained to rehabilitate the patient toward previous levels of comprehension and / or understanding spoken language.

[0087] In yet another specific, non-limiting example, the process 400 discussed above can be implemented by an ABT system (e.g., within a treatment subsystem of the type discussed above with reference to FIGS. 1A and 1B) built to rehabilitate a patient with global aphasia. Global aphasia is the most severe form of aphasia and affects both the production and comprehension of language. -27- 169064111.3Global aphasia typically arises from damage to both the receptive and expressive speech areas. Global aphasia is characterized by severe communication impairments. For example, patients experience profound difficulties in understanding spoken or written language, and often have great difficulty communicating. When patients attempt speech, their speech may be very limited, consisting of only a few words or phrases. Many patients with global aphasia rely on non-verbal communication methods, such as gestures or facial expressions, to attempt to convey their needs or emotions

[0088] Once trained, the ABT system can adapt the process 400 to rehabilitate the patient. For example, the ABT system can perform an initial assessment of the patient’s language capacity using a range of tasks to characterize the underlying deficits. The ABT system can use the initial assessment to select one or more specific tasks tailored to treat the specific underlying deficit, as well as to select a difficulty level for each of the selected tasks. For example, the tasks can include confrontation naming tasks, generative naming tasks, grammar tasks, and / or any other suitable tasks.

[0089] Confrontation naming tasks can include presenting standardized pictures for various nouns and / or verbs and prompting the patient to provide the correct words and / or phrases associated with the pictures.

[0090] Generative naming tasks prompt a patient to “generate,” (e.g., speak) different words that share a common feature, such as words / phrases beginning with a certain letter (associated with letter fluency) or within a prescribed category (associated with semantic fluency) within a restricted time frame (e.g., within 60 seconds). The primary variable measured is the number of accurate and unique words / phrases produced. However, the ABT system can also track the number of switches between clusters (e.g., words that share a more common association than the prompt, such as words that share the same base word for a prompt to generate words with the same first letter (e.g., fight, fights, fighting, fighter, fought, etc.). In letter fluency tasks, trials can prompt the patient to generate words that share the first letter, share the first two letters, differ only by a vowel sound, rhyme, are homonyms (e.g., share the same letters or sounds but differ in meaning), and / or the like. In semantic fluency tasks, the trials can prompt the patient to sequentially generate words that belong to the same subcategory (e.g., fast food chains, animals, and / or the like).

[0091] Grammar tasks can include presenting patients with a picture of a semantically reversible event (e.g., a picture of a boy kissing a girl) and prompting the patient to explain the presentation (e.g., “what is happening here?”). The patient’s response can then be evaluated for -28- 169064111.3agrammatism (e.g., an omission of words and morphemes), paragrammatism (e.g., a substitution of closed class items (“girl kissing boy” is acceptable but “boy kissing bench” is not); where possessive tenses are used correctly; whether plural tenses are used correctly; whether verb tenses are used correctly; whether rules for combining free and bound morphemes are followed (e.g., “-ly” can be appended to the adjective “quick” but not to the noun “house”); whether a subject or object is in the wrong place in a sentence; whether complex and / or compound sentences have the appropriate connectors (e.g., coordinating clauses); and / or the like.

[0092] Once tasks are selected, the ABT system can then administer the tasks in batches and / or in an intermixed fashion during treatment sessions. The ABT system can adapt each of the treatment sessions to help maintain the patient’s engagement, participation, and / or interest in the treatment sessions (e.g., by providing a variety of tasks, adapting the difficulty level based on patient engagement and / or energy levels, and / or the like). Each treatment session can be initiated based on input from the patient, a medical professional, and / or a detection that the patient is engaging in exploratory learning and / or trial-and-error learning. After initiation, the ABT system can apply stimulation to the patient’s brain to encourage engagement, administer a series of trials within a selected task to the patient, and receive responses thereto from the patient. The ABT system can then evaluate the responses and apply stimulation to the patient’s brain based on task engagement and / or performance.

[0093] Patients with expressive aphasia have some common error types. For example, errors include incidences of unintelligible words (e.g., individual sounds or syllables or words that are not recognizable), neologisms (e.g., new words / nonwords that are not recognizable as being related to any potential target), paraphasic errors (e.g., substitutions of one word for another, such as naming a button a “belt”), semantic paraphasias (e.g., real words that are semantically related to the target word, such as calling a tomato an “onion” or “pepper”), phonological paraphasias (e.g., real words that are phonologically related to the target word), semantic jargon (e.g., when a patient’s connected spoken language involves real words in combinations that have little (or no) meaning, such as “and now the lady the guy who’s owned is gone so his dead and so nobody can help the two”).

[0094] While administering the trials, the ABT system can analyze the patient’s performance and adjust and / or adapt task (or trial) difficulty or complexity based on the patient’s performance. For example, performance at or greater than 75% correct (or average accuracy) can advance to the -29- 169064111.3next difficulty level, performance at 25%–75% can continue training at the same difficulty level, and performance at less than 25% correct can prompt initiation of a less complex task (or trial). Still further, the ABT system can perform interim and ongoing assessments of the patient’s performance in comparison to their initial state, as well as assessments of the patient’s performance compared to a model and / or desired performance (e.g., based on an average rehabilitation timeline). The assessments can help determine whether stimulation should be administered, whether sufficient stimulation is being administered, whether the rate of underlying deficits is improving, and / or the extent to which the patient’s learning is generalizing. The ABT can then report on the assessments of performance (e.g., to a medical professional monitoring the rehabilitation).

[0095] In some embodiments, the training tasks are administered in a structured fashion that is parallel to the assessment tasks (e.g., confrontation name, noun generation, verb generation, etc.). In some embodiments, the training tasks are administered in a less structured and / or fully unstructured manner. Unstructured administration can be more akin to real conversations with ongoing assessments of the patient’s rehabilitation, correct (and incorrect) word choices, grammar, and / or increasing sentence length. In some such embodiments, the ABT system can include a generative AI system that progresses towards conducting full conversations with the patient while evaluating their responses to identifying tasks (and trials) that the patient is still struggling with. The generative AI can then guide the conversation toward the areas that need further rehabilitation to prompt the patient, evaluate the patient’s conversational response to the prompts, reward the patient for improvements, and provide minor corrections to the patient where needed.

[0096] In some embodiments, the training tasks begin by reinforcing the simplest building blocks of language, such as expressing the first phoneme or sound of a word correct (the “p” of plate), then including first two phonemes (the “p” and “l” of plate) and so forth. The ABT then advance to reinforcing whole words, pairs of words, short sentences, tenses, grammatical correctness, long sentences, dependent clauses, eventually approaching the level of normal conversational dialogue.

[0097] In some embodiments, the ABT creates a multi-parameter model of the individual’s current language ability and compares it with a language model based on a normal person of comparable age and education. The control algorithm aims to reduce the difference between the two models, by initially selecting tasks that target the most severe impairments, then using a broader variety of tasks to ensure that all aspects of language approach normal levels. -30- 169064111.3

[0098] FIGS. 5A and 5B are schematic drawings of trials 500, 510 presented to a user during an adaptive process for treating a brain injury in accordance with embodiments of the present technology. The trials 500, 510 are examples of trials that can presented during a process 400 of the type discussed above with reference to FIG. 4.

[0099] For example, FIG. 5A illustrates a trial 500 for treating a patient with expressive aphasia. At step 502, the trial 500 provides an audible prompt to the patient (“what is this?”) and at step 504 the trial presents an image of bananas. As discussed above, the trial 500 at step 504 can include delivering stimulation to the patient’s brain (e.g., to the nucleus accumbens). The trial 500 then listens for a spoken response from the patient. At step 506, the trial 500 receives the response from the user (e.g., “Bananas,” or “Arr”) and evaluates the accuracy of the response. At step 508, the trial 500 provides (or withholds) stimulation to the patient’s brain (e.g., to the caudate region of the patient’s brain) and provides an indication of the accuracy to the patient. For example, when the patient correctly says “Bananas,” the trial 500 delivers stimulation and indicates a correct response. Conversely, when the patient incorrectly says “Arr,” the trial 500 withholds stimulation and indicates an incorrect response. Early in the process, the ABT may deliver stimulation if the patient expresses only the first phoneme “Ba”, then deliver stimulation for the 1stand 2ndphoneme, and eventually for the whole word.

[0100] FIG. 5B illustrates a trial 510 for treating a patient with receptive aphasia. At step 512, the trial 510 provides an audible prompt to the patient (“apple”) and presents two or more images to the patient. As discussed above, the trial 510 at step 512 can include delivering stimulation to the patient’s brain (e.g., to the nucleus accumbens region). The trial 510 then waits for a response from the patient (e.g., via contact on the user interface). At step 514, the trial 510 receives the response from the user (e.g., touching the apple or touching a cat) and evaluates the accuracy of the response. The trial 510 then provides (or withholds) stimulation to the patient’s brain (e.g., to the caudate region of the patient’s brain) and provides an indication of the accuracy to the patient. For example, when the patient correctly touches the image of an apple, the trial 510 delivers stimulation and indicates a correct response. Conversely, when the patient incorrectly touches the cat, the trial 510 withholds stimulation and indicates an incorrect response. -31- 169064111.3Specific Examples of Suitable Systems and Methods for Treating Neuropsychiatric Disorders via Targeted Stimulation to a Patient’s Brain

[0101] FIG. 6 is a flow diagram of a process 600 for treating a neuropsychiatric disorder in accordance with embodiments of the present technology. Similar to the processes 300, 400 discussed above with respect to FIGS. 3 and 4, the process 600 can be executed by any suitable device (or devices) in the system 100 discussed above with respect to FIGS. 1A and 1B. For example, the process 600 can be executed by the treatment subsystem 120 operating on a patient’s user device (e.g., a smartphone, tablet, computer, and / or any other suitable device). Additionally, or alternatively, although discussed herein in the context of being executed primarily within a single component (e.g., entirely within the patient’s user device), it will be understood that a first subset of the process 600 can be executed by a different device than a second subset of the process 600.

[0102] The process 600 begins at block 602 by initiating a treatment session. Similar to the discussion above, the process 600 can be initiated by a patient (e.g., interacting with a user device), a medical professional (e.g., during a rehabilitation session), and / or automatically by an algorithm (e.g., in response to a detection that the patient is engaging with exploratory learning and / or trial-and-error learning; by an AI model detecting interactions between a patient and an environment; by an AI model and / or algorithm after detecting that a patient has sufficient energy levels for a session based on neural activity measurements, and / or the like); and / or the like. In some embodiments, initiating a treatment session includes selecting one or more tasks for the patient during the treatment session (e.g., image recognition tasks, word / phrase recognition tasks, word / phrase pronunciation tasks, motion-based tasks; memory-related tasks; and / or the like). Further, the initiation at block 602 can include determining a difficulty level for the tasks and / or trials for the patient. The difficulty level can be determined automatically based on a previous difficulty level, one or more algorithmic determinations and / or one or more AI processes, inputs from a medical professional, and / or the like.

[0103] At block 604 (e.g., at the start of a selected task), the process 600 includes applying stimulation to the nucleus accumbens (NAcc) region of the patient’s brain at the start of a first trial. The process 600 at block 604 can include communicating with a stimulation system (e.g., an implanted device and / or a non-invasive device) to cause the stimulation system to deliver the stimulation. Purely by way of example, the process 600 at block 604 can include communicating with the main controller 210 of FIG. 2A to deliver stimulation to the nucleus accumbens via the bilateral -32- 169064111.3electrode shanks 230. As discussed above, the stimulation to the nucleus accumbens can help the patient engage with the trial, in turn helping increase the benefits of the stimulation system in the treatment of the brain injury and / or degenerative disease. In some embodiments, the stimulation delivered at block 604 is a high-frequency stimulation (e.g., stimulation between about 180 Hz and about 220 Hz, between about 190 Hz and about 210 Hz, and / or about 200 Hz; delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second; and delivered with an amplitude between about 0.5 mA and about 2 mA, or of about 1 mA).

[0104] At block 606, the process 600 includes administering a trial to the patient simultaneously (or generally simultaneously) with the delivery of stimulation at block 604. Similar to the discussion above, administering (e.g., presenting) the trial to the patient at block 606 can include providing the patient with an audio-visual prompt that elicits a response from the patient (e.g., an audio recording of an OCD trigger such as a cough, sneeze, mispronounced word, and / or the like; an audio-visual trigger such as a line of cocaine and / or images of a substance and / or noises associated with using substances; and / or the like). The trial can be administered via a patient user device (e.g., a tablet, smartphone, laptop computer, desktop computer, and / or the like), an augmented reality device, a virtual reality device, a gaming console, and / or the like.

[0105] At block 608, the process 600 includes receiving a response from the patient. Similar to the discussion above, the process 600 can receive the response via an interaction with a user device (e.g., touching one or more areas of a user interface to indicate what the patient is thinking about after the trigger), recording an audio response from the patient (e.g., the patient describing their reaction or desires), recording the patient’s interactions with their environment, recording eye motion in the patient, and / or the like. Further, the process 600 at block 608 can receive various supplementary information in (or with) the response. For example, the supplementary information can include how long the patient took to provide the response, whether the patient considered alternative responses (e.g., looked at a response indicating they want to wash their hands, use a substance, and / or the like; and / or how long they looked at alternative responses), various metrics that assess attention, vigilance, or alertness, sensors providing recordings of neural activity, whether the patient had to be redirected to the trial (e.g., by a medical professional), and / or any other suitable information.

[0106] At block 610, the process 600 includes determining whether the response exhibits a negative or positive behavioral response to the trial. The negative response (or elements associated -33- 169064111.3with the negative response) and the positive response (or elements associated with the positive response) can be identified before administering the trial. Purely by way of example, negative responses for a person with OCD can include wanting to wash their hands, shower, and / or otherwise sanitize after hearing a cough or sneeze, while positive behaviors can include wanting to say “bless you,” not react, and / or the like.

[0107] At decision block 612, if the response is indicative of a negative behavior, the process 600 proceeds to block 614, else the process proceeds to decision block 616. At block 614, the process 600 includes delivering low-frequency stimulation to the caudate region (and / or another suitable region) of the patient’s brain. Delivering the stimulation can include communicating with a stimulation system, such as an implanted device and / or a non-invasive. The low-frequency stimulation can be between about 10 Hz and about 40 Hz, about 40 Hz, and / or about 10 Hz. Further, the low-frequency stimulation can be delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second. Still further, the low-frequency stimulation can be delivered with an amplitude between about 0.5 mA and about 2 mA, or of about 1 mA. The low-frequency stimulation can help discourage, undermine, and / or remove associations between the trigger (e.g., audio-visual cues related to a substance and / or OCD trigger) and the negative behavior. That is, the low-frequency stimulation can help reduce the chance that the user will respond to the next trigger with the same negative behavior. After delivering the low-frequency stimulation, the process 600 can proceed to block 620 to select the next trial and return to block 604.

[0108] At decision block 616, if the response is indicative of a positive behavior, the process 600 proceeds to block 618, else the process proceeds directly to block 620 to select the next trial and return to block 604. At block 618, the process includes delivering a high-frequency stimulation to the caudate (or other) region of the patient’s brain. Delivering the stimulation can include communicating with a stimulation system, such as an implanted device and / or a non-invasive. Similar to the discussion above, the high-frequency stimulation can be between about 180 Hz and about 220 Hz, between about 190 Hz and about 210 Hz, and / or about 200 Hz; delivered for between about 0.5 seconds to about 2 seconds, or for about 1 second; and delivered with an amplitude between about 0.5 mA and about 2 mA, or of about 1 mA. In some embodiments, the duration and / or amplitude of the stimulation is based on various supplemental information received with the response. For example, if the user immediately exhibits the positive behavior, the process 600 can deliver a -34- 169064111.3high amplitude and / or long duration of the stimulation. Conversely, if the patient considered negative behavior (e.g., detected by the patient looking at a negative response for an extended period of time), the process 600 can deliver a lower amplitude of stimulation and / or a shorter duration. In contrast to the low-frequency stimulation, the high-frequency stimulation can help encourage, build, and / or reinforce an association between the trigger and the positive behavior. That is, the high-frequency stimulation can help increase the chance that the user will respond to the next trigger with a positive behavior. After delivering the high-frequency stimulation, the process 600 can proceed to block 620 to select the next trial and return to block 604.

[0109] By combining the low-frequency stimulation and high-frequency stimulation pathways, the process 600 can actively discourage negative behaviors while encouraging positive behaviors during a treatment session. The combination can help improve the speed at which the user overcomes associations between the triggers and negative behaviors and / or learns associations between the triggers and positive behaviors. As a result, the combination of the low-frequency stimulation and high-frequency stimulation pathways can significantly improve the treatment of neuropsychiatric disorders and improve patient outcomes.

[0110] FIGS. 7 and 8 are schematic drawings of trials 700, 800 presented to a user during a process for treating neuropsychiatric disorders in accordance with embodiments of the present technology. The trials 700, 800 are examples of trials that can presented during a process 600 of the type discussed above with reference to FIG. 6.

[0111] For example, FIG. 7 illustrates a trial 700 for treating a patient with addiction and / or another substance abuse disorder. At step 702, the trial 700 provides an audio-visual trigger to the patient (images, videos, and / or sounds associated with using the substance) and at step 704 the trial presents two options for a response (e.g., going to jail and partying). As discussed above, the trial 700 at steps 702, 704 can include delivering stimulation to the patient’s brain (e.g., to the nucleus accumbens). In some embodiments, high-frequency is delivered upon engagement with the trial, before (or while) the cue is presented. In some embodiments, low-frequency stimulation is delivered upon presentation of a provocative trigger or cue to pre-emptively reduce its salience and therefore encourage a positive behavioral response. At step 706, the trial 700 receives a response from the user (e.g., a selection of one of the options) and evaluates whether the response indicates positive or negative behavior. At step 708, the trial 700 provides stimulation to the patient’s brain (e.g., to the -35- 169064111.3caudate region of the patient’s brain) based on the response and provides an indication to the patient on whether the response was correct or incorrect. For example, when the patient selects going to jail, the trial 700 delivers high-frequency stimulation and indicates a correct response. Conversely, when the patient selects partying, the trial 700 delivers low-frequency stimulation and indicates an incorrect response.

[0112] FIG. 8 illustrates a trial 800 for treating a patient with OCD, germaphobia, and / or another related disorder. At step 802, the trial 800 provides an audio-visual trigger to the patient (images, videos, and / or sounds associated with a door handle surface having an association with contamination) and at step 804 the trial presents two options for a response (e.g., opening a door and needing to wash their hands). As discussed above, the trial 800 at steps 802, 804 can include delivering stimulation to the patient’s brain (e.g., to the nucleus accumbens). In some embodiments, high-frequency is delivered upon engagement with the trial, before (or while) the cue is presented 800. In some embodiments, low-frequency stimulation is delivered upon presentation of a provocative trigger or cue to pre-emptively reduce its salience and therefore encourage a positive behavioral response 802. At step 806, the trial 800 receives a response from the user (e.g., a selection of one of the options) and evaluates whether the response indicates positive or negative behavior. At step 808, the trial 800 provides stimulation to the patient’s brain (e.g., to the caudate region of the patient’s brain) based on the response and provides an indication to the patient on whether the response was correct or incorrect. For example, when the patient selects opening a door, the trial 800 delivers high- frequency stimulation and indicates a correct response. Conversely, when the patient selects needing to wash their hands, the trial 800 delivers low-frequency stimulation and indicates an incorrect response. Specific Examples of Suitable Systems and Methods for Treating Diseases in a Patient’s Brain via Targeted Stimulation to a Patient’s Brain

[0113] In some embodiments, the systems and methods disclosed herein are used to treat various degenerative diseases (e.g., Alzheimer’s disease) in the patient’s brain. For example, the systems and methods disclosed herein can be used to help enhance memory through context- dependent electrical stimulation, cell layer-specific stimulation, stimulation as part of closed-loop control of entorhinal cortex neuronal subpopulation activity, and / or any combination thereof. In this example, the systems and methods disclosed herein can identify beneficial activity patterns in the -36- 169064111.3entorhinal cortex during an indexing memory task (e.g., a baseline setting task), then use closed-loop stimulation to shape entorhinal cortex activity to emulate those patterns and enhance explicit memory processes (e.g., encoding, storage, consolidation, recognition, retrieval, and recall) during future tasks.

[0114] FIG. 9 is a flow diagram of a process 900 for treating a degenerative disease in accordance with embodiments of the present technology. Similar to the processes discussed above with respect to FIGS.3, 4, and 6, the process 900 can be executed by any suitable device (or devices) in the system 100 discussed above with respect to FIGS. 1A and 1B. For example, the process 900 can be executed by the treatment subsystem 120 operating on a patient’s user device (e.g., a smartphone, tablet, computer, and / or any other suitable device). Additionally, or alternatively, although discussed herein in the context of being executed primarily within a single component (e.g., entirely within the patient’s user device), it will be understood that a first subset of the process 900 can be executed by a different device than a second subset of the process 900.

[0115] The process 900 begins at block 902 by presenting one or more memory-related trials to a patient during an indexing task. The indexing task sets a baseline for patient performance during various memory-related trials to assess how well the patient encodes new memories and / or recognizes information before receiving stimulation treatment. Similar to the discussion above, presenting the memory-related trials to the patient can include providing the patient with various audio-visual prompts that elicit (e.g., request) a response from the patient (e.g., visual memory game, a spoken memory game, a quiz of information known to the patient (e.g., the patient’s name, birthday, address, and / or the like) and / or any other suitable trials). The trials can be administered via a patient user device (e.g., a tablet, smartphone, laptop computer, desktop computer, and / or the like), an augmented reality device, a virtual reality device, a gaming console, and / or the like.

[0116] At block 904, the process 900 includes measuring neural activity in the entorhinal cortex of the patient’s brain (and / or any neuronal population that serves as a suitable readout, such as in the hippocampus or other synaptically connected region) during the one or more trials and identifying target activity states (e.g., desirable activity states (such as those correlated with strong encoding) and / or undesirable activity states). The measurements can be completed by an implant device in the patient’s brain (e.g., the implantable device 200 discussed above with reference to FIG. 2A), such as via an array of electrodes in contact with the patient’s entorhinal cortex. Additionally, or alternatively, -37- 169064111.3the measurements can be completed by a non-invasive device (e.g., electroencephalography (EEG), or magnetic resonance imaging (MRI)), and / or the like. The target activity states can be patient- specific and / or can fluctuate within a patient over time. In some examples, the target activity states can be associated with maintaining relatively high gamma-band synchronization in superficial layers of the entorhinal cortex during mnemonic encoding periods of the memory-related trials and / or reducing gamma-band synchronization in the superficial layers during recognition periods of the memory-related trials. Additionally, or alternatively, the target activity states can be associated with desynchronizing deep layers of the entorhinal cortex during encoding to enhance encoding. Additionally, or alternatively, the target activity states can be associated with measured neural activity during which the patient has better performance of the memory-related trials (e.g., completes memory games quickly and / or with a high accuracy score). In some embodiments, the performance of the memory-related trials is based on objective measurements (e.g., whether the patient correctly responded to various memory-related prompts and / or games). In some embodiments, the performance of the memory-related trials is based on or evaluated by at least partially using eye tracking (e.g., video camera-based, infrared camera-based, scleral eye coil-based, and / or electrooculogram-based). The eye tracking can be used to compute viewing preferences (e.g., what the patient looks at during the memory-related trial), which are associated with an innate novelty preference and represent a metric sensitive to damage to the medial temporal lobe. In this example, the eye tracking process can account for saccade durations and / or differentiations across patients (and implants). For example, an initial sensory processing window for the superficial and deep layer activation of the entorhinal cortex is about 200 millisecond (msec), accounting for saccade durations that are typically between about 20 msec and about 60 msec during free-viewing visual exploration. Visual information is greatly suppressed during each saccadic eye movement. As a result, once new visual information hits the retina following a saccade, it can take about 200 msec for the information to be processed and for the deep layers of the entorhinal cortex to receive hippocampal output. The entorhinal cortex- hippocampal loop can be required for any stimulus to be consciously recognized and coincides with a measurable decrease in gamma-band synchronization in superficial layers for familiar items.

[0117] At block 906, the process 900 includes presenting one or more memory-related trials to a patient during a stimulated task (e.g., a task involving stimulation to the patient’s brain). Similar to the discussion above, presenting the memory-related trials to the patient can include providing the patient with various audio-visual prompts that elicit a response from the patient (e.g., a visual memory -38- 169064111.3game, a spoken memory game, a quiz of new information presented to the patient, and / or any other suitable trials). The trials can be administered via a patient user device (e.g., a tablet, smartphone, laptop computer, desktop computer, and / or the like), an augmented reality device, a virtual reality device, a gaming console, and / or the like.

[0118] At block 908, the process 900 includes delivering stimulation to the entorhinal cortex via a subset of electrodes (or other suitable contacts) on an implanted device during the one or more first memory-related trials. In some embodiments, the subset of the electrodes is selected from a plurality of predefined stimulation patterns. The stimulation patterns can be defined to resemble different melody structures. Additionally, or alternatively, the stimulation patterns can be defined to provide stimulation to a variety of different layers in the entorhinal cortex, concentrate stimulation in one or more layers, and / or the like. In some embodiments, each stimulation pattern requires eight or more electrodes to deliver a sufficient amount (and / or melodic variety) of stimulation. In such embodiments, the implant device can require at least thirty-two electrodes on the implant device to help ensure that the implant device has a sufficiently large number of different predefined stimulation patterns to cycle through and / or select from while providing treatment.

[0119] At block 910, the process 900 includes measuring neural activity in the entorhinal cortex of the patient’s brain (and / or any neuronal population that serves as a suitable readout) during the one or more first trials of the stimulated task. The measurements can be completed by the implant device, such as via one or more of the electrodes not providing stimulation to the patient’s entorhinal cortex. Additionally, or alternatively, the measurements can be completed by a non-invasive device (e.g., a computed tomography (CT) scanner), ultrasound device, and / or the like.

[0120] In a specific, non-limiting example, the process 900 can define a number of epochs (e.g., trials), T, for storing a history of r (e.g., a measure of recorded neural activity within the stimulated regions of the brain) and for computation of y (e.g., an output from a feedback sensor based on a measurement from the electrodes). T is set to be ≥ 1. Each epoch has a duration N, where the length of r is N’ = N x T. The process 900 at block 910 can calculate the feedback signal y within the block representing feedback sensor processing of r. For example: ^ = |^^^^^| = 2 ⋅ ^^^ ∑^^^^^^^^^^^^^^^^^, or:-39- 169064111.3^phase^^^ = arg "ℋ$%^^^&'^ ^=1-. ^freq^^^^^^ In the calculations above, ℋ$%^^^& represents a Hilbert transform of the signal %^^^. The Hilbert transform creates an analytic signal from a real-valued signal, allowing for the extraction of phase and amplitude information. Further, arg^⋅^ denotes an argument (or phase angle) of the complex- valued signal after applying the Hilbert transform. The argument (or phase angle) provides the instantaneous phase at each time step n. / / ^represents a derivative with respect to n, which is used to compute a rate of change of thecorresponding to an instantaneous frequency. Theinstantaneous frequency can be extracted by taking the derivative of the phase with respect to time, normalized by 2+.

[0121] At block 912, the process 900 includes evaluating an efficacy of the subset of electrodes based on the measured neural activity. The efficacy can be based on a comparison between the measured neural activity (e.g., a recorded activity state) and the target activity state to identify similarities, differences, and / or the like. In some embodiments, the process 900 at block 912 can calculate an empirical distance between the recorded activity state and the target activity state, normalized to a value between 0 and 1 to help provide stability to the process 900 at block 914, discussed below. In a specific, non-limiting example, ^^^^and ^^01can be programmer-defined minimum and maximum values for y, such as minimum and maximum estimated sinusoidal amplitudes, with distance (d) given by: , = 1 − min "678^y^:^;<,=^:^>?, 1'

[0122] In another example,a programmer (e.g., a medical professional) can define the maximum and minimum frequencies based on a sampling frequency, such as ^^^^=^DE and ^^01= 200 Hz, then use ^ = min^max^^, ^min^ , ^max^. In this− ^minis the maximum possible distance between the constrained frequency bounds ^maxand ^min, which can be used to normalize the frequency differences. The instantaneous frequency distance d is computed as the absolute difference between the constrained instantaneous -40- 169064111.3frequency y and the ideal target frequency ^ideal, normalized by the maximum possible distance ,max. The result is a value between 0 and 1. ,=|^ − ^ideal|,max

[0123] It will be understood that, in some embodiments, a flip in the distance calculation is used. The flip can, for example, invert the distance measure d, to switch from maximizing to minimizing or vice versa. The flip can be used when a converse case is needed, such as minimizing a frequency difference instead of maximizing it. d = |d - 1|

[0124] At block 914, the process 900 includes generating a variation of the subset of the electrodes for one or more second memory-related trials in the stimulated task. The variation can be based on how far apart from the target activity state the recorded activity state is. For example, if the recorded activity state is close to the target activity state, the process 900 can generate a new subset of electrodes that is generally similar to the current subset of electrodes (e.g., varying one or two electrodes of eight electrodes, selecting similar melodies in the electrodes, and / or the like). Conversely, if the recorded activity state is far apart from the target activity state (and / or close to a known bad activity state), the process 900 can generate a very different subset of electrodes at block 914. In some embodiments, the generation is based on a selection from the plurality of predefined stimulation patterns. In such embodiments, the selection can be randomized, with probabilities for each of the plurality of predefined stimulation patterns adjusted based on (1) the distance between the recorded activity state and the target activity state, and / or (2) a similarity between the current stimulation pattern and each other stimulation pattern. Further, the generation at block 914 can eliminate one or more predefined stimulation patterns (e.g., when the distance between a tested pattern and the target activity state is above a predetermined threshold). Still further, the generation at block 914 can add one or more new stimulation patterns to the predefined stimulation patterns (e.g., when the distance between a tested pattern and the target activity state is below a predetermined threshold, the process 900 can add one or more similar stimulation patterns).

[0125] In a specific, non-limiting example, the process 900 at block 914 can begin by defining minimum and maximum probability values for each of the stimulation patterns. The process 900 can also define a pivot point (sometimes also referred to as a threshold or cutoff, KLMN). Values below the -41- 169064111.3pivot point will increase the probability of a given stimulation pattern while values above will decrease the probability. For each stimulation pattern (e.g., each “melody”), the probability is adjusted proportionally to how its distance metric compares to Pcut, scaled by Pscalar, which represents a maximum absolute weight change (probability change) per iteration. A small random value is added to introduce variability and prevent overfitting a controller. The random value is given by KO0^ / _^01×rand(1), which generates a random number between 0 and KO0^ / _^01. Example values for a pool of integer M melodies are: initial probabilities K₀= 1 / S, K^^^= 0.5 / S, K^01= 0.95, KLMN= 0.5, Kscalar= 0.25, and KO0^ / _^01= 0.05. The process 900 can then calculate the probability for selecting each melody as: K Kcut − ,mel= min ^max ^Kmel+ × K Kscalar, K`a^b , K`cdb + K%c^,_`cd× rand^1^ cut

[0126] where the P correspondsto the maximum increase in Kmelfor d=0, up to the maximum K^01, before the addition of the random value and before normalizing the entire distribution P; this is useful for increasing the relative weight of stimulation patterns that result in neuronal activity in a graded fashion, with greater increases as the activity gets closer to the desired activity, or setpoint. The process 900 can then generate the next melody (e.g., the next subset of electrodes) by randomly drawing from P. The formulation of the change to Kmelcan also be refactored as some arbitrary function of d and P, Q(d,P), where Q can incorporate the history of d and P. In some embodiments, parameters of the function Q(d,P) can be adjusted to help reach an optimal state (e.g., a global maximum of memory performance or any other quantification of memory).

[0127] The process 900 can then return to block 906 to present the one or more second stimulation trials to the patient, deliver stimulation using the new subset of electrodes, measure neural activity in the entorhinal cortex of the patient’s brain (and / or any neuronal population that serves as a suitable readout), evaluate the efficacy of the new subset of electrodes, and generate another new subset of electrodes. The process 900 can repeat the loop through blocks 906–914 any suitable number of times during the stimulated task to continue to try to identify the most effective subset of electrodes (or several effective subsets of electrodes) to nudge the neural activity toward the target activity state. Because the generation of new electrodes is based at least partially on the distance between a recorded activity state and the target activity state, the loops through blocks 906–914 tend to move closer and closer to producing the target activity state. In various embodiments, each loop through -42- 169064111.3blocks 906–914 can be implemented in microseconds, seconds, minutes, hours, and / or days to provide sufficient time for each loop to effectively measure an impact of the stimulation on the patient’s brain.

[0128] At block 916, the process 900 includes storing the most effective variation of the electrodes (e.g., the most effective stimulation pattern or patterns, where a set of patterns may have distinct weights associated with each pattern in the set). The process 900 can store the most effective variation in a database on a user device, in a database in the implanted device, a database in a remote system (e.g., a cloud system), and / or any other suitable database. The storage allows the most effective variation(s) to be used as a starting point for the next treatment session. However, it will be understood that the stimulation pattern that is most effective one day may or may not be the most effective another day. Accordingly, the process 900 will continue to generate and test new stimulation patterns during each stimulated treatment session.

[0129] FIG.10 is a block diagram of a process 1000 for selecting electrode groups for a process of treating various memory disorders (e.g., neurodegenerative diseases, temporal lobe epilepsy, stroke, infection, psychiatric diseases or disorders, traumatic brain injury, and / or the like) in accordance with embodiments of the present technology. The process 1000 can be generally similar to the process 900 of FIG. 9 in blocks 906–914. For example, at step 1004 the process 1000 can generate a new melody (e.g., a new stimulation pattern of a subset of electrodes on an implanted device). At step 1004 the process 1000 can determine changes to the operating conditions for the new melody, including changes to a frequency of the stimulation, amplitude of the stimulation, and / or a duty cycle of stimulation. At step 1006, the process 1000 plays the melody, meaning delivers the stimulation, potentially during administration of one or more memory-related trials to the patient. At step 1008, the process 1000 measures neural activity in the stimulated regions of the patient’s brain (e.g., the entorhinal cortex and / or any other suitable region). At step 1010, the process 1000 includes processing signals associated with the measurements, for example by estimating the sinusoidal amplitude at a frequency of interest, fm. The process 1000 then computes an error signal at step 1002 with respect to a reference setpoint, x(t), which may be time-varying. The error signal, d, x – y, or a related function of x and y, such as those described above with reference to FIG. 9 is used in generating a new melody again at step 1004. -43- 169064111.3

[0130] FIG. 11A is a schematic drawing of an implantable device 1120 implanted in a subregion of the entorhinal cortex of a patient’s brain in accordance with embodiments of the present technology. The implantable device 1120 can span various layers of the entorhinal cortex (e.g., layers I–VI), with contacts 1122 (e.g., an array of 64 electrodes) spaced to record from and stimulate specific zones or layers based on a previously obtained template of entorhinal cortex activity (e.g., from the indexing memory tasks discussed above with reference to FIG.9). That is, while the patient performs an indexing memory task, the implantable device 1120 can record neural activity. The neural activity can then be analyzed to identify patient-specific activity patterns as a target activity state (e.g., elevated gamma power in superficial layers, desynchronization in deep layers, and / or the like) that correlate with successful or strong (as opposed to weak) memory processes (such as encoding or consolidation).

[0131] The implantable device 1120 can then apply stimulation in a closed-loop fashion during a stimulated memory task. The stimulation can be delivered through a subset of the contacts 1122 associated with a first predefined stimulation pattern (sometimes also referred to herein as a first melody of the contacts 1122). The recorded activity can then be analyzed in real-time (e.g., within about 30 milliseconds) and compared to the target activity state. FIG.11B is a chart 1130 illustrating recorded activity states in a computer model of a network of cortical neurons, during stimulated memory trials with varying groups of the contacts 1122 of the implantable device 1120 in accordance with embodiments of the present technology. Each spatiotemporal stimulation pattern, a group, is termed a melody and evokes distinct neuronal responses, as shown in the average spiking activity curves during 8 msec long stimulation patterns “Stim,” and for 30 msec after stimulus delivery. Each curve corresponds to a different melody. cortical network is represented by a different

[0132] Based on the difference between the recorded activity state and the target activity state, the probability of delivering different predefined stimulation patterns is adjusted to nudge the activity in the entorhinal cortex toward the target activity state. The evolution of the stimulation patterns allows the system to continuously adapt the stimulation delivered to help maximize efficacy and adapt to changing conditions in the patient’s brain (e.g., a stimulation pattern that works one day may not work the next day). The computational approaches to adapting stimulation patterns over time may be enhanced by incorporating AI or machine learning algorithms, such as directly in the computations of steps 1004 or 1010 of the control system described in FIG. 10. -44- 169064111.3

[0133] The stimulation patterns in the contacts 1122 of FIG. 11A can each be configured to target different combinations of the superficial or deep entorhinal cortex layers. Further, the process of adjusting the stimulation patterns can also adjust stimulation parameters such as frequency, amplitude, and / or duty cycle in the stimulation. For example, gamma entrainment can be promoted in superficial layers during encoding periods by delivering stimulation in the delta-theta frequency bands. In another example, synchronizing and desynchronizing deep layers can be achieved in a similar control scheme (in any entorhinal cortex layer group) by inverting the d value as discussed above with reference to FIG. 9. The resulting stimulation patterns may either help maximize or minimize synchronization via arbitrarily complex patterns of stimulation (e.g. regular or periodic, or nonlinear and generally irregular).

[0134] It will be understood that although the systems and methods discussed above with reference to FIGS. 9–11A have been discussed primarily with the example of delivering stimulation to the entorhinal cortex of the patient’s brain, the systems and methods disclosed herein are not so limited. Purely by way of example, the systems and methods discussed above can be used to deliver closed-loop stimulation to therapeutically modulate patterns of activity in any cortical or subcortical area, including the frontal, parietal, and temporal cortices, striatal nuclei, and / or the hippocampus.

[0135] Still further, similar to the discussion above with reference to FIGS. 3–8, it will be understood that the systems and methods discussed above with reference to FIGS. 9–11A can be adapted to provide treatment outside of memory-related trials. In a specific, non-limiting example, the process 900 can be modified to include measuring neural activity in a patient’s brain during a non- stimulated memory-related trial, identifying various brain states (e.g., target brain states, normal brain states, abnormal brain states, and / or the like) from the measurements, then applying closed-loop stimulation to the patient’s brain outside of memory-related trials. In this example, the closed-loop stimulation can be delivered via a subset of electrodes in an electrode array (e.g., a first stimulation pattern) while measuring neural activity in the patient’s brain (e.g., in the entorhinal cortex, frontal, parietal, and temporal cortices, striatal nuclei, the hippocampus, and / or the like). The process can generate a new subset of electrodes in the electrode array to deliver stimulation based on a distance between the recorded neural activity and target activity state(s), a distance between the recorded neural activity and abnormal activity state(s), and / or the like. The closed-loop stimulation can provide bursts of stimulation patterns for courses of minutes, hours, days, weeks, and / or the like to slowly -45- 169064111.3evolve and / or adapt the stimulation patterns towards desirable stimulation patterns to help strengthen, build, and / or maintain memory.

[0136] In a specific, non-limiting example, the process 900 can be modified to help maintain and / or trigger sharp-wave ripple patterns. Deep entorhinal cortex layers can be initial recipients of sharp-wave ripple patterns that originate in the hippocampus. The sharp-wave ripple patterns can be observed in the local field potential as brief bouts of activity with a frequency between about 120 Hz and about 200 Hz. Ripples are important for memory consolidation and the transfer of information initially encoded in the hippocampus to other brain areas. As discussed above, the encoding can occur during idle wakefulness and during NREM stages of sleep. In this example, the process can record and detect the onset of sharp-wave ripple patterns and trigger closed-loop stimulation patterns to enhance (but not disrupt) ripple propagation. Further, in this example, the predetermined stimulation patterns can have a unique probability distribution that can be tuned over relatively long periods (e.g., days to weeks). In some embodiments, the closed-loop stimulation is particularly delivered during NREM sleep, which can readily be detected by tracking an amplitude of delta-band oscillatory activity, |A(fdelta)|, over time and identifying when it crosses a threshold amplitude. In this example, delta frequencies can be in a range between about 0.5 Hz and about 2 Hz and, like all rhythms, may be tuned to a particular frequency value characteristic of the patient. The setpoint, x(t), and readout r, in this example, can be a linear combination of the amplitude and rate of ripple occurrence (ripples per unit time during NREM). Further, an additional parameter of tstimulation_start – tripple_start may be introduced to help avoid delivering stimulation during an ongoing ripple (which may be disruptive because ripples may contain memory engrams, such as replayed episodic memory traces or cell assembly reactivation events). Specific Examples of Suitable Electrode Devices for Use in an Implantable Device for Treating Injuries, Disorders, and / or Diseases in a Patient’s Brain

[0137] FIG.12A is a partially schematic side view of a distal region of an electrode shank 1200 for an implantable device configured in accordance with embodiments of the present technology. For example, the electrode shank 1200 of FIG. 12A can be used in conjunction with the implantable device 200 described above with reference to FIG. 2A. As illustrated in FIG. 12A, the distal region of the electrode shank 1200 can include a body 1202 extending from a proximal end region 1204 to a distal end region 1206. Further, the body 1202 can include a blunt tip 1208 (e.g., a rounded cone) -46- 169064111.3that can help facilitate insertion of the electrode shank 1200 into a patient’s brain (e.g., reducing the chance that the insertion damages the brain).

[0138] As further illustrated in FIG.12A, the electrode shank 1200 can also include a plurality of electrode groupings 1210 (eight illustrated in FIG. 12A) positioned along the body 1202. Each of the electrode groupings 1210 includes two or more electrodes 1212 (two illustrated in the view of FIG.12A) that are exposed at an outer surface of the body 1202. Further, each of the electrodes 1212 can be coupled to one or more connection lines 1214 (illustrated schematically connected to only half of the electrodes 1212 to avoid obscuring the technology) in an interior lumen of the body 1202. The connection lines 1214 allow the electrodes 1212 to be couplable to a controller (e.g., the main controller 210 of FIG. 2A). As a result, once the electrode shank 1200 is implanted in the patient’s brain with the electrodes 1212 in contact with any of one or more regions of the patient’s brain (e.g., the entorhinal cortex, the nucleus accumbens, the caudate, and / or any other suitable region), the electrodes 1212 can deliver stimulation (e.g., electrical stimulation) to targeted regions of the patient’s brain.

[0139] In the embodiment illustrated in FIG.12A, the distal region of the electrode shank 1200 can have an overall length L1 and a width W1. The overall length L1 can be between about 20 millimeters (mm) and about 30 mm, or about 26 mm, while the width W1can be between about 1 mm and about 1.4 mm, or about 1.2 mm. Further, the electrode groupings can be distributed about a portion of body 1202 having a second length L2 that is less than the overall length L1 of the distal region of the electrode shank 1200. For example, the second length L2 can be between about 15 mm and about 28 mm, or about 25 mm. Still further, the electrodes 1212 can have a length D1of between about 1 mm and about 2.5 mm or about 2 mm, while the electrode groupings are spaced apart along a longitudinal axis A of the electrode shank 1200 by a distance D2 of between about 0.75 mm and 2 mm, or about 1.25 mm.

[0140] The dimensions discussed above can help allow the electrode shank 1200 to have a sufficiently small overall size to be implanted without damaging the patient’s brain. Further, the dimensions discussed above can allow the electrode shank 1200 to include a sufficient number of the electrode groupings 1210 to stimulate different regions of the patient’s brain independently. For example, as discussed in more detail below, the dimensions of the electrode shank 1200 discussed above can allow the electrode shank 1200 to independently stimulate the nucleus accumbens and -47- 169064111.3caudate regions of the patient’s brain, thereby reducing the overall number of shanks that must be implanted in the patient’s brain to perform the treatments discussed above. Still further, the dimensions discussed above can allow the electrode shank 1200 to include above a minimum threshold number of electrode groupings (e.g., eight of the electrode groupings 1210) to implement the processes discussed above with respect to FIGS. 9–11B to vary the exact electrodes that deliver stimulation at a given time.

[0141] FIG. 12B is a partially schematic cross-sectional view illustrating additional details of the electrode shank 1200 of FIG. 12A in accordance with embodiments of the present technology. More specifically, FIG. 12B is a partially schematic cross-sectional view taken along lines B-B in FIG. 12A. As illustrated in FIG. 12B, the electrode shank 1200 can further include an image marker 1220 (e.g., a radio-opaque marker). The image marker 1220 can help identify the position of the electrode shank 1200 during and / or after implantation.

[0142] As further illustrated in FIG. 12B, the body 1202 of the electrode shank 1200 can have a generally circular (or otherwise curved) cross-sectional shape. The cross-sectional shape can also help reduce the chance that the electrode shank 1200 damages the patient’s brain during implantation. Still further, the electrode grouping 1210 in the cross-sectional view of FIG. 12B includes four of the electrodes 1212 (individually referred to as “first–fourth electrodes 1212A–1212D”), each of which has an arc-shaped cross-sectional profile. Further, the first–fourth electrodes 1212A–1212D (sometimes also referred to herein as “electrode quadrants”) are distributed radially (e.g., circumferentially) about the exterior surface of the body 1202. For example, in the illustrated embodiment, each of the first–fourth electrodes 1212A–1212D extends along a section of about 70° of the exterior surface of the body 1202, providing about 20° of separation between adjacent pairs of the first–fourth electrodes 1212A–1212D (e.g., to electrically isolate the electrodes 1212). In various other embodiments, the first–fourth electrodes 1212A–1212D can extend along any other suitable section of the exterior surface of the body 1202 (e.g., along sections of about 45°, 50°, 80°, and / or any other suitable section). Further, in some embodiments, the first–fourth electrodes 1212A–1212D are not distributed evenly about the exterior surface of the body 1202. Purely by way of example, the first and second electrodes 1212A, 1212B can be positioned with about 10° of separation therebetween and the third and fourth electrodes 1212C, 1212D can be positioned with about 10° of -48- 169064111.3separation therebetween (resulting in, for example, about 30° of separation between the first electrode and fourth electrodes 1212A, 1212D).

[0143] FIG. 13 is a schematic drawing of an implantable device 1300 implanted in a patient’s brain 12 in accordance with embodiments of the present technology. As illustrated in FIG. 13, the implantable device 1300 can be generally similar to the implantable device 200 discussed above with reference to FIGS.2A and 2B. For example, as illustrated in FIG.13 the implantable device 1300 can include a controller 1310, one or more electrode shanks 1330 (two illustrated in FIG. 13, sometimes referred to as bilateral electrode shanks based on their placement in adjacent hemispheres), and one or more connection lines 1340 (e.g., electrical connections) each coupled between the controller 1310 and one of the electrode shanks 1330.

[0144] Further, the electrode shanks 1330 illustrated in FIG. 13 can be generally similar to the electrode shanks 1200 discussed above with reference to FIGS. 12A and 12B. For example, each of the electrode shanks 1330 can include a plurality of electrodes 1336 distributed along a distal portion 1334 of a body 1332 the electrode shanks 1330. Further, the size and distribution of the electrodes 1336 can allow the electrodes to contact multiple regions of the patient’s brain 12. For example, in the illustrated embodiment, a first subset of the electrodes 1336a is in contact with a caudate region 14 of the patient’s brain 12 while a second subset of the electrodes 1336b is in contact with a nucleus accumbens region 16 of the patient’s brain 12. As a result, the electrode shanks 1330 of the implantable device 1300 can deliver stimulation to multiple regions of the patient’s brain 12 during the treatment of various injuries, disorders, and / or diseases (e.g., to deliver stimulation to the nucleus accumbens at block 406 of FIG. 4 and deliver stimulation to the caudate at block 414 of FIG. 4).

[0145] It will be understood that, in various other embodiments, the electrode shanks can be positioned in various other portions of the patient’s brain to deliver stimulation for various other treatments discussed above. Purely by way of example, FIGS. 14A and 14B are schematic drawings illustrating additional details of an electrode shank 1400 of an implantable device positioned in an entorhinal cortex 18 of a patient’s brain 12 in accordance with embodiments of the present technology. As best illustrated in FIG. 14A, the electrode shank 1400 can be generally similar (or identical) to the electrode shanks 1330 discussed above with respect to FIG. 13, positioned in a different region of the patient’s brain 12. As a result, for example, the electrode shank 1400 includes -49- 169064111.3an array of electrodes 1406 distributed along a distal portion 1404 of a body 1402 of the electrode shank 1400. In turn, the distribution can allow the electrodes 1406 on the electrode shank 1400 to contact and deliver stimulation to a variety of regions within the entorhinal cortex 16.

[0146] Further, as best illustrated in the schematic cross-sectional illustration of FIG. 14B, the electrodes 1406 can be distributed radially (e.g., circumferentially) about the body 1402 of the electrode shank 1400. As a result, the electrodes 1406 can deliver stimulation to different layers within the entorhinal cortex 16. For example, first and second electrodes 1406A, 1406B can deliver stimulation to deep layers (e.g., layers V–VI) of the entorhinal cortex 16 (e.g., with the first electrode 1406A acting as a working electrode and the second electrode 1406B acting as a receiving electrode to create a current pathway between the first and second electrodes 1406A, 1406B). In another example, third and fourth electrodes 1406C, 1406D can deliver stimulation to superficial layers (e.g., layers I–III) of the entorhinal cortex 16 (e.g., with the third electrode 1406C acting as a working electrode and the fourth electrode 1406D acting as a receiving electrode to create a current pathway between the third and fourth electrodes 1406C, 1406D).

[0147] In still further embodiments, the electrode shanks discussed above with reference to FIGS. 12A–14B can be positioned in still other portions of the patient’s brain to deliver stimulation for various other treatments discussed above. For, the electrode shanks can be positioned to place electrodes in contact with various portions (and / or varying layers) of the hippocampus of the patient’s brain to provide stimulation thereto during the treatment of degenerative brain diseases.

[0148] FIG. 15 is a schematic drawing of an electrode patch 1500 for an implantable device configured in accordance with embodiments of the present technology. In various embodiments, the electrode patch 1500 can be incorporated into an implantable device of the type discussed above with reference to FIGS. 2A, 2B, and / or 13 to provide stimulation to the patient’s brain. As illustrated in FIG. 15, the electrode patch 1500 includes a patch-body 1502 that extends from a proximal end portion 1504 to a distal end portion 1506. The body is placeable on an external surface of a patient’s brain adjacent to one or more targeted regions of the patient’s brain. The electrode patch 1500 also includes a plurality of electrodes 1510 (thirty-two in the illustrated embodiment) dispersed along a brain-facing surface of the patch-body 1502 and a connection line 1520.

[0149] In some embodiments, the electrode patch 1500 (and the components thereof) is sized to fit through a burr hole of a common size used during invasive procedures on a patient’s brain. For -50- 169064111.3example, the brain-facing surface of the patch-body 1502 can have an overall height H1of less than (or equal to) about 14 mm. Further, the brain-facing surface of the patch-body 1502 can have an overall length L3 between about 40 mm and about 60mm, or of about 50 mm, with the electrodes 1510 distributed about a portion thereof, such as a portion with a length L4of about 46 mm. The dimensions of the electrodes 1510 can vary based on the overall size of the electrode patch 1500 as well as the number of the electrodes 1510 included in the electrode patch 1500. For example, the electrode patch 1500 in FIG. 15 includes thirty-two of the electrodes 1510 arranged in an eight-by-four grid. Each of the electrodes 1510 is a generally flat (e.g., planar) electrode with an electrode-height H2 between about 1.5 mm and about 2.5 mm, or about 3 mm; and an electrode-length D3 between about 3 mm and about 5 mm, or about 4 mm. Further, each of the electrodes 1510 is spaced apart (center- to-center) from the other electrodes along a longitudinal axis of the patch-body 1502 by a first electrode-spacing distance D4 of between about 5 mm and about 7 mm, or about 6mm; and apart (center-to-center) from the other electrodes along a transverse axis of the patch-body 1502 by a second electrode-spacing distance H3of between about 3 mm and about 5 mm, or about 4 mm. It will be understood, however, that the electrodes 1510 can have various different sizes and / or can be arranged in various different arrays. Purely by way of example, the electrode patch 1500 can include sixty-four electrodes (e.g., by reducing the electrode-length D3and / or the electrode-height H2). In another example, the spacing between the electrodes 1510 can be non-constant (e.g., with a first spacing between a first subset of the electrodes 1510 based on geometries of a first target brain region and a second spacing between a second subset of the electrodes 1510 based on geometries of a second brain region).

[0150] The electrode patch 1500 can supplement (and / or augment) stimulation from the electrode shanks during treatment of various injuries, disorders, and / or diseases in the patient’s brain. Alternatively, the electrode patch 1500 can be implemented in an implantable device independent of electrode shanks. For example, middle cerebral artery strokes affect the lateral cortices of the patient’s brain and often result in cognitive deficits due to dorsolateral prefrontal cortex injury and expressive aphasia, secondary to damage of the expressive speech area in the inferior frontal gyrus. In this example, the electrode patch 1500 can be used to target both the dorsolateral prefrontal cortex and the expressive speech area in the affected hemisphere and / or in the contralateral hemisphere. -51- 169064111.3

[0151] In some embodiments, the stimulation through the electrode patch 1500 augments the effects evoked by striatal stimulation from the electrode shanks since the cortical areas are part of the same learning circuit. In some embodiments, the stimulation through the electrode patch 1500 is provided as a standalone treatment. In a specific, non-limiting example, the cortical stimulation can be tuned to induce cortical β-band oscillations to enhance attention and performance. In another specific, non-limiting example, the cortical stimulation coupled with stimulation to the nucleus accumbens and caudate can help enhance learning by directing plasticity to areas of the cortex adjacent to the site of injury and / or to homologous areas in the contralateral hemisphere. Within this example, the electrode patch 1500 can be positioned with contacts overlying the dorsolateral prefrontal cortex to promote exploration and learning; contacts overlying the expressive speech area to promote more rapid and complete recovery from expressive aphasia; contacts overlying the receptive speech area to promote more rapid and complete recovery from receptive aphasia; contacts overlying the Premotor and / or Motor cortexes to promote more rapid and complete recovery from deficits such as motor weakness and apraxia; contacts overlying the Inferior parietal lobule to promote more rapid and complete recovery from deficits in calculation (acalculia); contacts overlying the posterior superior temporal gyrus to promote recovery from receptive aphasia; contacts overlying the inferior temporal cortex to promote more rapid and complete recovery from deficits in object recognition and / or memory formation due to injury or neurodegenerative diseases; and / or the like.

[0152] Additionally, or alternatively, the electrode patch 1500 can be used to measure neural activity within the patient’s brain. For example, measurements from the electrode patch 1500 can help detect event-related desynchronization and / or synchronization to help optimize stimulation parameters (e.g., to help evolve the stimulation patterns during the process 900 of FIG.9). In another example, the measurements from the electrode patch 1500 can help detect β-band oscillations in the dorsolateral prefrontal cortex during exploratory learning, and / or in the Motor and / or Premotor areas during habitual performance.

[0153] FIGS. 16A and 16B are schematic drawings of an electrode patch 1600 implanted in a patient’s brain 12 in accordance with embodiments of the present technology. In the illustrated embodiments, the electrode patch 1600 is generally similar to the electrode patch 1500 discussed above with reference to FIG. 15. For example, as illustrated in FIG. 16A, the electrode patch 1600 includes a body 1602 and a plurality of electrodes 1610 dispersed along the body 1602. In the -52- 169064111.3embodiments illustrated in FIG. 16A, the electrode patch 1600 is positioned with a first subset 1612 of the electrodes 1610 in contact with the dorsal lateral prefrontal cortex of the patient’s brain 12 and a second subset 1614 of the electrodes 1610 in contact with an expressive speech area of the patient’s brain 12. As a result, as discussed above, the electrode patch 1600 can help augment stimulation delivered to the patient’s brain 12 (e.g., to help treat a patient with expressive aphasia). In the embodiments illustrated in FIG.16B, the electrode patch 1600 is positioned with the first subset 1612 of the electrodes 1610 in contact with the parietal association cortex of the patient’s brain 12 and the second subset 1614 of the electrodes 1610 in contact with a receptive speech area of the patient’s brain 12. As a result, as discussed above, the electrode patch 1600 can help augment stimulation delivered to the patient’s brain 12 (e.g., to help treat a patient with receptive aphasia). Specific Examples of Suitable Non-Invasive for Treating Injuries, Disorders, and / or Diseases in a Patient’s Brain

[0154] FIG. 17 is a schematic drawing of a non-invasive device 1700 for treating injuries, disorders, and / or diseases in a patient’s brain 12 configured in accordance with embodiments of the present technology. The non-invasive device 1700 illustrated in FIG. 17 can deliver stimulation to various portions of the patient’s brain in accordance with any of the processes discussed above with reference to FIGS.1A–11B. For example, as illustrated in FIG.17, the non-invasive device 1700 can deliver stimulation to the nucleus accumbens 16 region of the patient’s brain 12 (e.g., at the start of a learning trial at block 406 of FIG. 4, at the start of a trial presenting a trigger at block 604 of FIG. 6, and / or the like) as well as the caudate 14 region of the patient’s brain (e.g., after receiving and evaluating a response at blocks 410–414 of FIG. 4, blocks 608–618 of FIGS. 6, and / or the like).

[0155] As further illustrated in FIG. 17, the non-invasive device 1700 can include a helmet 1710, as well as a plurality of stimulation emitters 1720 and a conductive gel 1730 each carried by the helmet 1710. The helmet 1710 helmet (or other suitable structural element, such as a flexible cap, exoskeleton, and / or the like) defines an outer body of the non-invasive device 1700 (e.g., an overall shape of the non-invasive device) and is sized to fit over the patient’s head. In some embodiments, the helmet 1710 (and the non-invasive device 1700 overall) are customized to a shape of the patient’s head (e.g., custom-molded to the patient’s head). In some embodiments, the helmet 1710 is a generic size (e.g., small, medium, large; and / or the like), with the conductive gel 1730 acting as a buffer to fit the non-invasive device 1700 to the patient’s head. In some -53- 169064111.3embodiments, the helmet 1710 is not a rigid material (e.g., is a flexible cap carrying the stimulation emitters 1720 and the conductive gel 1730). In some embodiments, the helmet 1710 is significantly bigger than the patient’s head and is positionable to allow the stimulation emitters 1720 to target the patient’s brain (e.g., with or without the conductive gel 1730).

[0156] The stimulation emitters 1720 are carried by the helmet 1710 in a position such that, when the patient puts the helmet on, the stimulation emitters 1720 are positioned to direct one or more forms of stimulation toward the patient’s head (and more specifically into the patient’s brain). The conductive gel 1730 provides a buffer between the stimulation emitters 1720 and the patient’s head while wearing the non-invasive device 1700. That is, the conductive gel 1730 can help mold the non- invasive device 1700 to the patient’s head, without blocking and / or otherwise altering stimulation emitted by the stimulation emitters 1720.

[0157] In some embodiments, the stimulation emitters 1720 include ultrasound emitters (sometimes also referred to as ultrasonic transducers) that emit Low-Intensity Focused Ultrasound (LiFU) to deliver stimulation to the patient’s brain 12. For example, a treatment subsystem (e.g., the treatment subsystem 120 of FIG.1A) can communicate with the non-invasive device 1700 to instruct the non-invasive device 1700 on when to deliver short bursts of ultrasound via the stimulation emitters 1720, what frequency of ultrasonic waves to emit, and / or which of the stimulation emitters 1720 to operate to target different regions of the patient’s brain 12 as appropriate for a given treatment. Further, in embodiments having ultrasonic transducers for the stimulation emitters 1720, the conductive gel 1730 can include an ultrasound-conducting gel.

[0158] In some embodiments, the stimulation emitters 1720 include electrodes such that the non-invasive device 1700 uses Transcranial Temporal Interference Electrical Stimulation (TTIS) to deliver stimulation to the patient’s brain. Further, in such embodiments, the non-invasive device 1700 can operate different pairs of the stimulation emitters 1720 at different frequencies to target different regions of the patient’s brain. Purely by way of example, the non-invasive device 1700 can operate a first electrode 1720A to emit a first electrical stimulation with a first frequency along a first emission travel path (e.g., by delivering a first drive current from a controller (such as the main controller 210 of FIG.2A) to the first electrode 1720A). Further, the non-invasive device 1700 can operate a second electrode 1720B to emit a second electrical stimulation with a second frequency along a second emission travel path (e.g., by delivering a second drive current from the controller to the second -54- 169064111.3electrode 1720B). In this example, the first emission travel path and the second emission travel path can overlap in a targeted region of the patient’s brain 12 (e.g., in the nucleus accumbens), causing the emissions from the first and second electrodes 1720A, 1720B to interact. Further, the first and second frequencies can be selected to result in constructive interference where they overlap to amplify and construct a stimulation in the targeted region of the patient’s brain with a desired frequency and amplitude. The constructive interference allows the first and second electrical stimulations to have a sufficiently low amplitude to reduce (or avoid) interactions with other (e.g., non-targeted) regions of the patient’s brain 12). Further, a treatment subsystem (e.g., the treatment subsystem 120 of FIG. 1A) can communicate with the non-invasive device 1700 (e.g., to the controller)) to instruct the non- invasive device 1700 on when to deliver short bursts of electrical stimulation via the stimulation emitters 1720, what frequency of electrical stimulation to emit, and / or which of the stimulation emitters 1720 to operate to target different regions of the patient’s brain 12 as appropriate for a given treatment. Still further, in embodiments having electrodes for the stimulation emitters 1720, the conductive gel 1730 can include an electrically conductive gel.

[0159] In some embodiments, the stimulation emitters 1720 include a plurality of coherent microwave emitters that are positioned to emit low-amplitude coherent microwaves toward a target region (e.g., a target location) within the patient’s brain. That is, the non-invasive device 1700 can use electromagnetic radiation such as coherent microwave emissions or Microwave Amplification through Stimulated Emission of Radiation (MASER) to deliver stimulation to the patient’s brain. In such embodiments, a treatment subsystem (e.g., the treatment subsystem 120 of FIG. 1A) can communicate with the non-invasive device 1700 to instruct the non-invasive device 1700 on when to deliver short bursts of coherent microwave emissions via the stimulation emitters 1720, what frequency of microwaves to emit, and / or which of the stimulation emitters 1720 to operate to target different regions of the patient’s brain 12 as appropriate for a given treatment. Further, in embodiments having microwave emitters for the stimulation emitters 1720, the conductive gel 1730 can include a microwave-conductive gel.

[0160] Although the non-invasive device 1700 is discussed above primarily in the context of a wearable device, it will be understood that the technology disclosed herein is not so limited. For example, the stimulation emitters 1720 of the non-invasive device 1700 can be positioned remote -55- 169064111.3from the patient’s body (e.g., within a kiosk the patient sits in, on separate elements around the patient, and / or the like) and target various regions within the patient’s brain. Examples of Suitable Computing Devices and Systems for Implementing Various Aspects of the Present Technology

[0161] FIG. 18 is a block diagram illustrating an overview of an example of a device 1800 on which some embodiments of the present technology can operate. In the illustrated embodiment, device 1800 includes one or more input devices 1820 that provide input to one or more CPU(s) (processor, “the CPU”) 1810, notifying it of actions. The actions can be mediated by a hardware controller that interprets the signals received from the input device and communicates the information to the CPU 1810 using a communication protocol. Input devices 1820 include, for example, a mouse, a keyboard, a touchscreen, an infrared sensor, a touchpad, a wearable input device, a camera (or other image-based input devices), a microphone, or other suitable user input devices.

[0162] The CPU 1810 can be a single processing unit or multiple processing units in a device or distributed across multiple devices. CPU 1810 can be coupled to other hardware devices, for example, with the use of a bus, such as a PCI bus or SCSI bus. The CPU 1810 can communicate with a hardware controller for devices, such as for a display 1830. The display 1830 can be used to display text and graphics. For example, the display 1830 can present audio-visual information related to one or more tasks during a trial in accordance with the systems and methods discussed above. In some embodiments, the display 1830 includes the input device as part of the display, such as when the input device is equipped with an eye direction monitoring system. In some embodiments, the display 1830 is separate from the input device. Examples of display devices are discussed in more detail below but can generally include: rotating LCDs; rotating LEDs; rotating OLEDs; rotating AMOLEDs; rotating semitransparent screens and associated projectors, lasers, and / or LEDs; digital micromirror devices; and the like. Other I / O devices 1840 can also be coupled to the processor, such as a network card, video card, audio card, USB, firewire or other external device, infrared (or near-infrared device) device, speakers, and the like.

[0163] In some embodiments, the device 1800 also includes a communication device capable of communicating wirelessly or wire-based with a network node. The communication device can communicate with another device or a server through a network using, for example, TCP / IP protocols, a Q-LAN protocol, or others. Device 1800 can utilize the communication device to distribute -56- 169064111.3operations across multiple network devices. Additionally, or alternatively, the communication device can include a short-range wireless communication component configured to communicate with a main controller of an implantable device (e.g., the main controller 210 of FIG.2A). Purely by way of example, the communication component can use Bluetooth® and / or other shortrange wireless protocols and / or telemetry methods to communicate with the main controller of the implanted device.

[0164] The CPU 1810 can have access to a memory 1850 in a device or distributed across multiple devices. A memory includes one or more of various hardware devices for volatile and non- volatile storage, and can include both read-only and writable memory. For example, a memory can comprise random access memory (RAM), various caches, CPU registers, read-only memory (ROM), and writable non-volatile memory, such as flash memory, hard drives, floppy disks, CDs, DVDs, magnetic storage devices, tape drives, device buffers, and so forth. A memory is not a propagating signal divorced from underlying hardware; a memory is thus non-transitory. Memory 1850 can include program memory 1860 that stores programs and software, such as an adaptive behavioral training 1862 module, a stimulation generator 1864 module, and other application programs 1866. Memory 1850 can also include data memory 1870 that can include data to be operated on by applications, configuration data, settings, options or preferences, etc., which can be provided to the program memory 1860 or any element of the device 1800.

[0165] Some embodiments can be operational with numerous other computing system environments or configurations. Examples of computing systems, environments, and / or configurations that may be suitable for use with the technology include, but are not limited to, personal computers, server computers, handheld or laptop devices, cellular telephones, wearable electronics, gaming consoles, tablet devices, augmented reality devices, virtual reality devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, or the like.

[0166] FIG. 19 is a block diagram illustrating components of a computing device 1900 configured in accordance with some embodiments of the present technology. The components of the computing device 1900 include hardware 1902, general software 1920, and specialized components 1940. As discussed above, a system implementing the disclosed technology can use various hardware including processing units 1904 (e.g., CPUs, GPUs, APUs, etc.), working memory -57- 169064111.31906, storage memory 1908 (local storage or as an interface to remote storage, such as a database), and input and output (I / O) devices 1910. In various embodiments, storage memory 1908 can be one or more of: local devices, interfaces to remote storage devices, or combinations thereof. For example, storage memory 1908 can be a set of one or more memory dies (e.g., DRAM dies, NAND dies, and / or the like) accessible through a system bus or can be a cloud storage provider or other network storage accessible via one or more communications networks (e.g., a network accessible storage (NAS) device, such as database or storage provided through another server computing device). The components of the computing device 1900 can be implemented in a client computing device such as the computing device 1800 of FIG. 18.

[0167] General software 1920 can include various applications including a communication system 1922 (e.g., a telecommunication platform), local programs 1924, and a basic input output system (BIOS) 1926. In some embodiments, specialized components 1940 can be subcomponents of one or more of the general software 1920 applications and / or integrated with one or more of the general software 1920 applications (e.g., integrated with the communication system 1922). The specialized components 1940 can include trial and task generation component 1942, a response analysis component 1944, an adaptive behavioral training component 1946, a brain activity tracking component 1948, and / or various other suitable components to implement the features discussed in more detail below. In some embodiments, the components of the computing device 1900 can be implemented by a computing system that is distributed across multiple computing devices and / or can interface with a server-based application executing one or more of specialized components 1940. Examples

[0168] The present technology is illustrated, for example, according to various aspects described below. Various examples of aspects of the present technology are described as numbered examples (1, 2, 3, etc.) for convenience. These are provided as examples and do not limit the present technology. It is noted that any of the dependent examples can be combined in any suitable manner, and placed into a respective independent example. The other examples can be presented in a similar manner. -58- 169064111.31. An implantable device for delivering electrical stimulation to a plurality of regions of a human brain, the implantable device comprising: a main controller; and an electrode shank implantable within the human brain, wherein the electrode shank is electrically coupled to the main controller by one or more connection lines, and wherein the electrode shank comprises: a body extending from a proximal end region to a distal end region, wherein the body comprises an exterior surface and an interior lumen extending from the proximal end region to the distal end region; and a plurality of electrode groupings positioned along the body, wherein each individual electrode grouping of the plurality of electrode groupings comprises two or more electrodes distributed radially about the exterior surface and electrically isolated at the exterior surface, and wherein each electrode grouping of the plurality of electrode groupings is independently addressable by the main controller via the one or more connection lines. 2. The implantable device of example 1, wherein each individual electrode grouping of the plurality of electrode groupings comprises four electrodes positioned in individual quadrants circumferentially around the exterior surface of the body. 3. The implantable device of any of examples 1 and 2, wherein each individual electrode in the plurality of electrode groupings is coupled to the main controller via an independent connection line from the one or more connection lines extending through the interior lumen of the body. 4. The implantable device of any of examples 1–3, wherein the main controller includes a short-range wireless communication component and a control unit, and wherein the control unit is configured to: receive, via the short-range wireless communication component, one or more first signals indicative of a first epoch associated with a start of a task in a learning trial; provide, in response to the one or more first signals, a first electric current to a first subset of the plurality of electrode groupings, wherein the first subset of the plurality of -59- 169064111.3electrode groupings are positionable within a nucleus accumbens region of the human brain; receive, via the short-range wireless communication component, one or more second signals indicative of a second epoch associated with a response to the task; and provide, in response to the one or more second signals, a second electric current to a second subset of the plurality of electrode groupings, wherein the second subset of the plurality of electrode groupings are positionable within a caudate region of the human brain. 5. The implantable device of example 4, wherein: when the one or more second signals are indicative of a correct response to the task, the control unit is configured to deliver the second electric current with a frequency between about 180 Hertz (Hz) and about 220 Hz to encourage learning the correct response to the task; and when the one or more second signals are indicative of an incorrect response to the task, the control unit is configured to deliver the second electric current with a frequency between about 10 Hz and about 40 Hz to discourage repeating the incorrect response to the task. 6. The implantable device of any of examples 1–5, wherein the electrode shank is a first electrode shank implantable into a first hemisphere of the human brain, and wherein the implantable device further comprises a second electrode shank implantable into a second hemisphere of the human brain. 7. The implantable device of any of examples 1–6, wherein: wherein the one or more connection lines are one or more first connection lines; and the implantable device further comprises further comprising an electrode patch placeable on an external surface of the human brain, wherein the electrode patch is electrically coupled to the main controller by one or more second connection lines, and wherein the electrode patch comprises: -60- 169064111.3a patch-body extending from a first end region to a second end region, wherein the patch-body comprises a brain-facing surface positionable to contact the external surface of the human brain; and an array of electrodes distributed across the brain-facing surface between the first end region and the second end region, wherein each electrode in the array of electrodes is electrically isolated at the brain-facing surface. 8. The implantable device of example 7, wherein the array of electrodes includes thirty- two electrodes arranged in an eight-by-four array. 9. The implantable device of any of examples 7 and 8, wherein each electrode in the array of electrodes has a length of about 4 millimeters (mm) and a width of about 2 mm. 10. The implantable device of any of examples 7–9, wherein the patch-body has a length of about 50 millimeters (mm) and a width of about 14 mm. 11. The implantable device of any of examples 7–10, wherein the main controller is configured to: provide a first electric current to a first subset of the plurality of electrode groupings to deliver a first electrical stimulation to a first region of the human brain; provide a second current to a second subset of the plurality of electrode groupings to deliver a second electrical stimulation to a second region of the human brain; provide a third current to a first subset of electrodes in the array of electrodes to deliver a third electrical stimulation to a third region of the human brain; and provide a fourth current to a second subset of electrodes in the array of electrodes to deliver a fourth electrical stimulation to a fourth region of the human brain. 12. The implantable device of any of examples 7–11, wherein the electrode patch is positionable over at least one of: a Dorsolateral Prefrontal Cortex, a Premotor cortex, a Motor cortex, pars traingularis of inferior frontal gyrus (receptive speech area), posterior aspect of superior temporal -61- 169064111.3gyrus (receptive speech area), an Inferior parietal lobule, and / or an inferior temporal cortex region of the human brain. 13. The implantable device of any of examples 1–12, wherein the main controller is implantable within an interior region of a human skull. 14. The implantable device of any of examples 1–13, wherein the main controller is implantable on an exterior surface of a human skull. 15. An electrode shank for delivering electrical stimulation to a human brain, the electrode shank comprising: a body positionable within the human brain and extending from a proximal end region to a distal end region, wherein the body comprises an exterior surface and an interior lumen extending from the proximal end region toward the distal end region; and a plurality of electrode groupings distributed along longitudinal axis of the body, wherein each individual electrode grouping of the plurality of electrode groupings comprises a plurality of electrodes distributed radially about the exterior surface, and wherein each electrode grouping of the plurality of electrode groupings is independently couplable to an external controller to receive an electric current. 16. The electrode shank of example 15, wherein each individual electrode grouping of the plurality of electrode groupings comprises four independent electrodes distributed radially about the exterior surface. 17. The electrode shank of example 16, wherein the body has a generally circular cross- sectional shape, and wherein each of the four independent electrodes extends along a 70° section of the exterior surface. 18. The electrode shank of any of examples 15–17, wherein each individual electrode grouping of the plurality of electrode groupings comprises two or more electrode pairs, and wherein each electrode pair comprises a working electrode and a receiving electrode. -62- 169064111.319. The electrode shank of example 18, wherein a first electrode pair is positioned to deliver the electrical stimulation to stimulate a first subset of layers of the human brain when the electrode shank is implanted, and wherein a second electrode pair is positioned to deliver the electrical stimulation to stimulate a second subset of layers of the human brain when the electrode shank is implanted. 20. The electrode shank of any of examples 15–19, wherein a first subset of the plurality of electrode groupings are coupled to one or more first connection lines within the interior lumen of the body, and wherein a second subset of the plurality of electrode groupings are coupled to one or more second connection lines within the interior lumen of the body independent from the first subset of the plurality of electrode groupings. 21. The electrode shank of any of examples 15–20, wherein the plurality of electrode groupings are distributed along a distal portion of the body adjacent to the distal end region. 22. The electrode shank of any of examples 15–21, wherein each electrode in the plurality of electrode groupings is electrically coupled to an individual connection line within the interior lumen of the body. 23. The electrode shank of any of examples 15–22, further comprising a radio-opaque marker positioned within the body adjacent to the distal end region of the body. 24. The electrode shank of any of examples 15–23, wherein the distal end region of the body comprises a blunt tip. 25. The electrode shank of any of examples 15–24, wherein the plurality of electrode groupings comprises at least eight electrode groupings. 26. The electrode shank of any of examples 15–25, wherein the body has a diameter between about 1 millimeter (mm) and about 1.4 mm. -63- 169064111.327. The electrode shank of any of examples 15–26, wherein each individual electrode has a length of about 2 millimeters. 28. The electrode shank of any of examples 15–27, wherein each individual electrode grouping is spaced apart from an adjacent electrode grouping along the longitudinal axis by about 1.25 millimeters. 29. The electrode shank of any of examples 15–28, wherein the plurality of electrode groupings are distributed along an active region of the body, and wherein the active region of the body has a length of about 25 millimeters. 30. A non-invasive device for delivering stimulation to a human brain, the non-invasive device comprising: a helmet defining an outer body of the non-invasive device, wherein the helmet is sized to fit over a user’s head; a plurality of stimulation emitters carried by the helmet and positioned to direct the stimulation toward the user’s head during operation of the non-invasive device; and a conductive gel carried by the helmet and positioned to provide a buffer between the plurality of stimulation emitters and the user’s head during operation of the non-invasive device. 31. The non-invasive device of example 30, wherein the plurality of stimulation emitters comprise ultrasonic transducers, and wherein the conductive gel comprises an ultrasound-conducting gel. 32. The non-invasive device of any of examples 30 and 31, wherein the plurality of stimulation emitters comprise a plurality of electrode pairs distributed around the helmet (e.g., in addition to or as an alternative to the ultrasonic emitters), wherein each individual electrode pair comprises a first electrode with a first emission travel path and a second electrode with a second emission travel path, and wherein the second electrode is positioned such that the second emission -64- 169064111.3travel path overlaps with the first emission travel path at a predetermined location within the user’s head during operation of the non-invasive device. 33. The non-invasive device of example 32, further comprising a controller coupled to each of the plurality of electrode pairs, and wherein the controller is configured to: deliver a first drive current to the first electrode to emit a first electric stimulation along the first emission travel path; and deliver a second drive current to the second electrode to emit a second electric stimulation along the second emission travel path, wherein the second electric stimulation is configured to cause constructive interference with the first electric stimulation at the predetermined location. 34. The non-invasive device of any of examples 30–33, wherein the plurality of stimulation emitters comprise a plurality of coherent microwave emitters (e.g., in addition to or as an alternative to the ultrasonic emitters and / or electrodes) positioned to deliver low-amplitude coherent microwaves to a target location within the user’s head during operation of the non-invasive device. 35. The non-invasive device of any of examples 30–34, wherein the helmet is custom- molded to the user’s head. 36. The non-invasive device of any of examples 30–35, wherein conductive gel is configured to at least partially mold around the user’s head during operation of the non-invasive device. 37. A system for treating an injury to a user’s brain, the system comprising: a stimulation device, the stimulation device comprising a main controller and bilateral electrode shanks, wherein each of the bilateral electrode shanks is implanted at least partially within the user’s brain to provide contact between one or more first electrodes and a nucleus accumbens region of the user’s brain and contact between one or more second electrodes and a caudate region of the user’s brain; and -65- 169064111.3a learning subsystem communicably coupled to the main controller of the stimulation device, wherein the learning subsystem includes processor and a memory storing instructions that when executed by the processor cause the learning subsystem to: present, via a user interface coupled to the learning subsystem, a rehabilitation task to the user; instruct the main controller to deliver a first stimulation to the nucleus accumbens region of the user’s brain via the one or more first electrodes simultaneous with presenting the rehabilitation task; receive, from the user via the user interface, a response from the user related to the rehabilitation task; and in response to a determination that the response from the user was a correct response to the rehabilitation task, instruct the main controller to deliver a second stimulation to the caudate region of the user’s brain via the one or more second electrodes. 38. A method for treating an injury to a patient’s brain, the method comprising: determining an initial difficulty level for a task comprising a plurality of rehabilitation trial related to the injury to the patient’s brain; for each individual trial in the plurality of rehabilitation trial: presenting the individual trial, wherein presenting the individual trial comprises presenting a prompt to the patient requesting a response; at a start of the individual trial, administering stimulation to a nucleus accumbens region of the brain via an electrode device implanted in the patient’s brain; receiving, via a rehabilitation subsystem, the response to the prompt from the patient; evaluating the response to determine if an accuracy of the response to the individual task is above a predetermined threshold for the individual trial; in response to a determination that the accuracy is above the predetermined threshold, administering stimulation to a caudate region of the patient’s brain via the electrode device; recording the accuracy of the response to the individual trial; and -66- 169064111.3determining a new difficulty level for a next individual trial based at least partially the accuracy of the response to the individual trial; and recording an overall accuracy of responses to the plurality of rehabilitation trials based on the accuracy of the response to each of the individual trials in the plurality of rehabilitation trials. 39. The method of example 38, wherein presenting the prompt to the patient comprises presenting a visual cue to the patient to pronounce a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises comparing a summed magnitude of a rectified cross-correlation of produced speech to a reference template for a desired speech sound for the word or the phrase. 40. The method of any of examples 38 and 39, wherein presenting the prompt to the patient comprises presenting a visual cue to the patient to pronounce a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises evaluating a spoken response with speech recognition software to generate a matching index and comparing the matching index to a predetermined threshold index value. 41. The method of any of examples 38–40, wherein presenting the prompt to the patient comprises providing an audio or visual cue to the patient to select an image matching a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises evaluating a spatial accuracy of a touch or eye movement response based on a radial distance of the response from a target displayed to the patient. 42. The method of any of examples 38–41, wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises comparing a response time associated with receiving the response to a predetermined threshold value. 43. The method of any of examples 38–42, further comprising, for each individual trial in the plurality of rehabilitation trials: measuring one or more metrics of brain activity after presenting the prompt to the patient; and -67- 169064111.3determining, based on the one or more metrics of brain activity, an engagement score associated with patient readiness to participate in the individual trial. 44. The method of example 43, wherein determining the new difficulty level for the next individual trial is further based at least partially on the engagement score for each of the plurality of rehabilitation trials. 45. The method of example 43, wherein at least one of the trials in the plurality of rehabilitation trials is a indexing trial previously presented to the patient, and wherein determining the new difficulty level for the next individual trial is further based at least partially on a comparison of a response received for the indexing trial to previous responses received for the indexing trial. 46. The method of any of examples 38–45, further comprising prompting the patient to provide a score for their readiness to engage in the plurality of rehabilitation trials within the task before presenting any of the plurality of rehabilitation trials, wherein determining the new difficulty level for the next individual trial is further based at least partially on the score received from the patient. 47. The method of any of examples 38–46, further comprising prompting the patient to provide a score for their readiness to engage in the plurality of rehabilitation trials within the task after presenting a subset of the plurality of rehabilitation trials, wherein determining the new difficulty level for the next individual trial is further based at least partially on the score received from the patient. 48. A method for treating a neuropsychiatric disorder of a patient via stimulation to a brain of the patient, the method comprising: presenting an individual trial to the patient via a rehabilitation subsystem, wherein presenting the individual trial comprises presenting an audio-visual trigger associated with the neuropsychiatric disorder to the patient; -68- 169064111.3at a start of the individual trial, administering a first stimulation to a nucleus accumbens region of the patient’s brain via an electrode device implanted in the patient’s brain, wherein the first stimulation has a first frequency; receiving, via the rehabilitation subsystem, a response to the audio-visual trigger from the patient; evaluating the response to determine if the response indicates a negative behavioral response to the audio-visual trigger; and in response to a determination that the response indicates the negative behavioral response, administering a second stimulation to a caudate region of the patient’s brain via the electrode device, wherein the second stimulation has a second frequency lower than the first frequency. 49. The method of example 48, wherein the individual trial is a first individual trial, and wherein the method further comprises: presenting a second individual trial to the patient via the rehabilitation subsystem, wherein presenting the second individual trial comprises presenting a second audio-visual trigger associated with the neuropsychiatric disorder to the patient; at a start of the second individual trial, administering the first stimulation to the nucleus accumbens region of the patient’s brain via the electrode device; receiving, via the rehabilitation subsystem, a second response to the second audio-visual trigger from the patient; evaluating the second response to determine if the second response indicates the negative behavioral response to the second audio-visual trigger; and in response to a determination that the second response does not indicate the negative behavioral response, administering a third stimulation to the caudate region of the patient’s brain via the electrode device, wherein the third stimulation has a third frequency generally equal to the first frequency. 50. The method of any of examples 48 and 49, wherein the first frequency is between about 180 Hertz (Hz) and about 220 Hz, and wherein the second frequency is between about 10 Hz and about 40 Hz. -69- 169064111.351. The method of any of examples 48–50, wherein the neuropsychiatric disorder is addiction to a substance, and wherein the audio-visual trigger includes audio-visual cues associated with the substance. 52. The method of any of examples 48–51, wherein the neuropsychiatric disorder is obsessive-compulsive disorder, and wherein the audio-visual trigger includes one or more cues associated with patient-specific triggers for the obsessive-compulsive disorder. 53. A method for treating a degenerative brain disease, the method comprising: presenting, via a memory training subsystem, one or more first memory-related trials to a patient during an indexing task; measuring, during performance of the one or more first memory-related trials, neural activity in an entorhinal cortex region of the patient’s brain; and during a stimulated task: presenting, via the memory training subsystem, one or more second memory-related trials to the patient; delivering stimulation to the entorhinal cortex region of the patient’s brain via an individual subset of an array of electrodes on a stimulation device implanted in the patient’s brain; measuring, during performance of the one or more second memory-related trials, the neural activity in the entorhinal cortex region of the patient’s brain; evaluating an efficacy of the individual subset of electrodes based at least partially on the neural activity measured during the performance of the one or more first memory-related trials; and generating a new subset of electrodes to deliver stimulation during one or more third memory-related trials of the stimulated task. 54. The method of example 53, wherein: the method further comprises identifying patient-specific activity patterns correlated with successful memory encoding, storage, consolidation, recognition, retrieval, and / or -70- 169064111.3recall based on the neural activity during performance of the one or more first memory- related trials; and generating the new subset of electrodes is based on a distance between the neural activity during performance of the one or more second memory-related trials and the patient- specific activity patterns correlated with successful memory encoding, storage, consolidation, recognition, retrieval, and / or recall. 55. The method of example 54, wherein: generating the new subset of electrodes comprises randomly selecting from a plurality of predefined stimulation patterns for subsets of electrodes; and the distance adjusts a probability of selecting each of the plurality of predefined stimulation patterns for subsets of electrodes. 56. The method of example 55 wherein the probability of selecting each of the plurality of predefined stimulation patterns is given by: Kmel= min "max "Kmel+ecut^ / ecut× Kscalar, K^^^' , K^01' + KO0^ / _^01× rand^1^, wherein dbetween 0 and 1. 57. The method of any of examples 53–56, wherein measuring the neural activity in the entorhinal cortex region of the patient’s brain comprises measuring gamma-band synchronization in superficial layers of the entorhinal cortex. 58. The method of example 57, further comprising identifying patient-specific activity patterns correlated with successful memory encoding based on greater gamma-band synchronization in the superficial layers of the entorhinal cortex during mnemonic encoding time periods of the one or more first memory-related trials. 59. The method of any of examples 57 and 58, further comprising identifying patient- specific activity patterns correlated with successful memory encoding based on reduced gamma-band -71- 169064111.3synchronization in the superficial layers of the entorhinal cortex during recognition time periods of the one or more first memory-related trials. 60. The method of any of examples 53–59, further comprising identifying patient-specific activity patterns correlated with desynchronization in deep layers of the entorhinal cortex during memory encoding based on the neural activity during performance of the one or more first memory- related trials. 61. The method of any of examples 53–60, wherein the new subset of electrodes includes no electrodes on stimulation device implanted in the patient’s brain to conduct a control test during the one or more third memory-related trials of the stimulated task. 62. The method of any of examples 53–61, wherein measuring the neural activity in the entorhinal cortex region of the patient’s brain comprises measuring an amplitude of gamma-band synchronization, and wherein the method further comprises identifying one or more subsets of electrodes associated with increased gamma-band synchronization over a predetermined period. 63. The method of claim of example 62, wherein the predetermined period is on a scale of minutes, hours, or days. 64. The method of claim of any of examples 53–63, further comprising identifying a target activity state in the patient’s brain, wherein the target activity is associated with a brain state that recruits glial cells to clear abnormal tau and amyloid-beta from the entorhinal cortex region of the patient’s brain. 65. The method of any of examples 53–63, further comprising identifying a target activity state in the patient’s brain, wherein the target activity state is associated with a brain state that recruits glial cells to clear abnormal tau and amyloid-beta from a second stimulated region of the patient’s brain. -72- 169064111.366. The method of example 64 or example 65, wherein clearance of the abnormal tau and amyloid-beta is associated with slowing a progression of or reversing a course of Alzheimer’s disease. 67. The method of any of examples 53–66, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more first memory-related trials, and wherein evaluating the efficacy of the individual subset of electrodes is further based on a distance between a measured activity state during performance of the one or more second memory-related trials and the one or more abnormal memory states. 68. The method of any of examples 53–67, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more first memory-related trials, wherein generating the new subset of electrodes is based on a distance between the neural activity during performance of the one or more second memory-related trials and the one or more abnormal activity states. 69. A method for enhancing memory, the method comprising: recording, via measurements from an electrode array implanted in a patient’s brain, neural activity in the patient’s brain during one or more memory-related trials; identifying: one or more patient-specific target neural activity patterns that correlate with successful memory encoding, recognition, and / or consolidation; or one or more patient-specific abnormal neural activity patterns; and delivering stimulation to the patient’s brain via a closed-loop stimulation process, the closed- loop stimulation process comprising: delivering stimulation to the patient’s brain via a subset of electrodes in the electrode array implanted in the patient’s brain; recording, via measurements from the electrode array implanted in the patient’s brain, neural activity in the patient’s brain while receiving the stimulation; performing a real-time analysis of the neural activity in the patient’s brain while receiving the stimulation; and -73- 169064111.3generating a new subset of electrodes in the electrode array based at least partially on the real-time analysis of the neural activity in the patient’s brain while receiving the stimulation. 70. The method of example 69, wherein generating the new subset of electrodes in the electrode array comprises: adapting a probability of selecting one or more predefined stimulation patterns based on a difference between the neural activity in the patient’s brain while receiving the stimulation and a target neural activity state; and randomly selecting from the predefined stimulation patterns. 71. The method of any of examples 69 and 70, wherein generating the new subset of electrodes in the electrode array nudges the neural activity in the patient’s brain while receiving the stimulation toward a target activity state defined via neural activity in the patient’s brain during one or more memory-related trials. 72. The method of any of examples 69–71, further comprising evaluating an efficacy of the closed-loop stimulation process based at least partially on a comparison of memory performance between stimulation and non-stimulation trials. 73. The method of any of examples 69–72, further comprising evaluating an efficacy of the closed-loop stimulation process based on neural activity in the patient’s brain while receiving the stimulation for a predetermined period. 74. The method of example 73, wherein the predetermined period is on a scale of minutes, hours, or days. 75. The method of any of examples 69–74, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more memory- related trials, wherein generating the new subset of electrodes is based on a distance between the -74- 169064111.3neural activity in the patient’s brain while receiving the stimulation and the one or more abnormal activity states. 76. The method of any of examples 69–75, further comprising identifying one or more target activity states based on the neural activity during performance of the one or more memory- related trials, wherein generating the new subset of electrodes is based on a distance between the neural activity in the patient’s brain while receiving the stimulation and the one or more target activity states. 77. A method for enhancing memory, the method comprising: recording, via measurements from an electrode array implanted in a patient’s brain, neural activity in the patient’s brain; identifying sharp-wave ripple patterns in the neural activity in the patient’s brain; and in response to detecting the sharp-wave ripple patterns, delivering stimulation to the patient’s brain via a closed-loop stimulation process, the closed-loop stimulation process comprising: delivering stimulation to the patient’s brain via a subset of electrodes in the electrode array implanted in the patient’s brain; recording, via measurements from the electrode array implanted in the patient’s brain, neural activity in the patient’s brain while receiving the stimulation; performing a real-time analysis of the neural activity in the patient’s brain while receiving the stimulation; and generating a new subset of electrodes in the electrode array based at least partially on the real-time analysis of the neural activity in the patient’s brain while receiving the stimulation. 78. The method of example 77, wherein performing the real-time analysis comprises assessing an impact of the stimulation on a propagation of the sharp-wave ripple patterns. 79. The method of any of examples 77 and 78, wherein delivering stimulation to the patient’s brain is performed after a propagation of an individual sharp-wave ripples. -75- 169064111.380. The method of any of examples 77–79, wherein the sharp-wave ripple patterns are associated with a first sharp-wave ripple pattern event, and wherein the method further comprises: identifying a second sharp-wave ripple pattern event in the neural activity in the patient’s brain; and in response to detecting the second sharp-wave ripple pattern event, delivering stimulation to the patient’s brain via the closed-loop stimulation process. 81. The method of any of examples 77–80, wherein the sharp-wave ripple patterns are associated with a sharp-wave ripple pattern event, and wherein the method delivers the stimulation to the patient’s brain via the closed-loop stimulation process throughout the sharp-wave ripple pattern event. Conclusion

[0169] From the foregoing, it will be appreciated that specific embodiments of the technology have been described herein for purposes of illustration, but well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments of the technology. To the extent any material incorporated herein by reference conflicts with the present disclosure, the present disclosure controls. Where the context permits, singular or plural terms may also include the plural or singular term, respectively. Moreover, unless the word “or” is expressly limited to mean only a single item exclusive from the other items in reference to a list of two or more items, then the use of “or” in such a list is to be interpreted as including (a) any single item in the list, (b) all of the items in the list, or (c) any combination of the items in the list. Furthermore, as used herein, the phrase “and / or” as in “A and / or B” refers to A alone, B alone, and both A and B. Additionally, the terms “comprising,” “including,” “having,” and “with” are used throughout to mean including at least the recited feature(s) such that any greater number of the same features and / or additional types of other features are not precluded. Further, the terms “approximately,” “about,” and “generally” are used herein to mean within at least within 10% of a given value or limit. Purely by way of example, an approximate ratio means within 10% of the given ratio. -76- 169064111.3

[0170] Several implementations of the disclosed technology are described above in reference to the figures. The computing devices on which the described technology may be implemented can include one or more central processing units, memory, input devices (e.g., keyboard and pointing devices), output devices (e.g., display devices), storage devices (e.g., disk drives), and network devices (e.g., network interfaces). The memory and storage devices are computer-readable storage media that can store instructions that implement at least portions of the described technology. In addition, the data structures and message structures can be stored or transmitted via a data transmission medium, such as a signal on a communications link. Various communications links can be used, such as the Internet, a local area network, a wide area network, or a point-to-point dial-up connection. Thus, computer-readable media can comprise computer-readable storage media (e.g., “non-transitory” media) and computer-readable transmission media.

[0171] From the foregoing, it will also be appreciated that various modifications may be made without deviating from the disclosure or the technology. For example, one of ordinary skill in the art will understand that various components of the technology can be further divided into subcomponents, or that various components and functions of the technology may be combined and integrated. In addition, certain aspects of the technology described in the context of particular embodiments may also be combined or eliminated in other embodiments.

[0172] Furthermore, although advantages associated with certain embodiments of the technology have been described in the context of those embodiments, other embodiments may also exhibit such advantages, and not all embodiments need necessarily exhibit such advantages to fall within the scope of the technology. Accordingly, the disclosure and associated technology can encompass other embodiments not expressly shown or described herein. -77- 169064111.3

Claims

CLAIMS We claim:

1. An implantable device for delivering electrical stimulation to a plurality of regions of a human brain, the implantable device comprising: a main controller; and an electrode shank implantable within the human brain, wherein the electrode shank is electrically coupled to the main controller by one or more connection lines, and wherein the electrode shank comprises: a body extending from a proximal end region to a distal end region, wherein the body comprises an exterior surface and an interior lumen extending from the proximal end region to the distal end region; and a plurality of electrode groupings positioned along the body, wherein each individual electrode grouping of the plurality of electrode groupings comprises two or more electrodes distributed radially about the exterior surface and electrically isolated at the exterior surface, and wherein each electrode grouping of the plurality of electrode groupings is independently addressable by the main controller via the one or more connection lines.

2. The implantable device of claim 1, wherein each individual electrode grouping of the plurality of electrode groupings comprises four electrodes positioned in individual quadrants circumferentially around the exterior surface of the body.

3. The implantable device of claim 1, wherein each individual electrode in the plurality of electrode groupings is coupled to the main controller via an independent connection line from the one or more connection lines extending through the interior lumen of the body. -78- 169064111.

34. The implantable device of claim 1, wherein the main controller includes a short-range wireless communication component and a control unit, and wherein the control unit is configured to: receive, via the short-range wireless communication component, one or more first signals indicative of a first epoch associated with a start of a task in a learning trial; provide, in response to the one or more first signals, a first electric current to a first subset of the plurality of electrode groupings, wherein the first subset of the plurality of electrode groupings are positionable within a nucleus accumbens region of the human brain; receive, via the short-range wireless communication component, one or more second signals indicative of a second epoch associated with a response to the task; and provide, in response to the one or more second signals, a second electric current to a second subset of the plurality of electrode groupings, wherein the second subset of the plurality of electrode groupings are positionable within a caudate region of the human brain.

5. The implantable device of claim 4, wherein: when the one or more second signals are indicative of a correct response to the task, the control unit is configured to deliver the second electric current with a frequency between about 180 Hertz (Hz) and about 220 Hz to encourage learning the correct response to the task; and when the one or more second signals are indicative of an incorrect response to the task, the control unit is configured to deliver the second electric current with a frequency between about 10 Hz and about 40 Hz to discourage repeating the incorrect response to the task.

6. The implantable device of claim 1, wherein the electrode shank is a first electrode shank implantable into a first hemisphere of the human brain, and wherein the implantable device further comprises a second electrode shank implantable into a second hemisphere of the human brain.

7. The implantable device of claim 1, wherein: wherein the one or more connection lines are one or more first connection lines; and -79- 169064111.3the implantable device further comprises further comprising an electrode patch placeable on an external surface of the human brain, wherein the electrode patch is electrically coupled to the main controller by one or more second connection lines, and wherein the electrode patch comprises: a patch-body extending from a first end region to a second end region, wherein the patch-body comprises a brain-facing surface positionable to contact the external surface of the human brain; and an array of electrodes distributed across the brain-facing surface between the first end region and the second end region, wherein each electrode in the array of electrodes is electrically isolated at the brain-facing surface.

8. The implantable device of claim 7, wherein the array of electrodes includes thirty-two electrodes arranged in an eight-by-four array.

9. The implantable device of claim 7, wherein each electrode in the array of electrodes has a length of about 4 millimeters (mm) and a width of about 2 mm.

10. The implantable device of claim 7, wherein the patch-body has a length of about 50 millimeters (mm) and a width of about 14 mm.

11. The implantable device of claim 7, wherein the main controller is configured to: provide a first electric current to a first subset of the plurality of electrode groupings to deliver a first electrical stimulation to a first region of the human brain; provide a second current to a second subset of the plurality of electrode groupings to deliver a second electrical stimulation to a second region of the human brain; provide a third current to a first subset of electrodes in the array of electrodes to deliver a third electrical stimulation to a third region of the human brain; and provide a fourth current to a second subset of electrodes in the array of electrodes to deliver a fourth electrical stimulation to a fourth region of the human brain. -80- 169064111.

312. The implantable device of claim 7, wherein the electrode patch is positionable over at least one of: a Dorsolateral Prefrontal Cortex, a Premotor cortex, a Motor cortex, an Inferior parietal lobule, and / or an inferior temporal cortex region of the human brain.

13. The implantable device of claim 1, wherein the main controller is implantable within an interior region of a human skull.

14. The implantable device of claim 1, wherein the main controller is implantable on an exterior surface of a human skull.

15. An electrode shank for delivering electrical stimulation to a human brain, the electrode shank comprising: a body positionable within the human brain and extending from a proximal end region to a distal end region, wherein the body comprises an exterior surface and an interior lumen extending from the proximal end region toward the distal end region; and a plurality of electrode groupings distributed along longitudinal axis of the body, wherein each individual electrode grouping of the plurality of electrode groupings comprises a plurality of electrodes distributed radially about the exterior surface, and wherein each electrode grouping of the plurality of electrode groupings is independently couplable to an external controller to receive an electric current.

16. The electrode shank of claim 15, wherein each individual electrode grouping of the plurality of electrode groupings comprises four independent electrodes distributed radially about the exterior surface.

17. The electrode shank of claim 16, wherein the body has a generally circular cross- sectional shape, and wherein each of the four independent electrodes extends along a 70° section of the exterior surface. -81- 169064111.

318. The electrode shank of claim 15, wherein each individual electrode grouping of the plurality of electrode groupings comprises two or more electrode pairs, and wherein each electrode pair comprises a working electrode and a receiving electrode.

19. The electrode shank of claim 18, wherein a first electrode pair is positioned to deliver the electrical stimulation to stimulate a first subset of layers of the human brain when the electrode shank is implanted, and wherein a second electrode pair is positioned to deliver the electrical stimulation to stimulate a second subset of layers of the human brain when the electrode shank is implanted.

20. The electrode shank of claim 15, wherein a first subset of the plurality of electrode groupings are coupled to one or more first connection lines within the interior lumen of the body, and wherein a second subset of the plurality of electrode groupings are coupled to one or more second connection lines within the interior lumen of the body independent from the first subset of the plurality of electrode groupings.

21. The electrode shank of claim 15, wherein the plurality of electrode groupings are distributed along a distal portion of the body adjacent to the distal end region.

22. The electrode shank of claim 15, wherein each electrode in the plurality of electrode groupings is electrically coupled to an individual connection line within the interior lumen of the body.

23. The electrode shank of claim 15, further comprising a radio-opaque marker positioned within the body adjacent to the distal end region of the body.

24. The electrode shank of claim 15, wherein the distal end region of the body comprises a blunt tip.

25. The electrode shank of claim 15, wherein the plurality of electrode groupings comprises at least eight electrode groupings. -82- 169064111.

326. The electrode shank of claim 15, wherein the body has a diameter between about 1 millimeter (mm) and about 1.4 mm.

27. The electrode shank of claim 15, wherein each individual electrode has a length of about 2 millimeters.

28. The electrode shank of claim 15, wherein each individual electrode grouping is spaced apart from an adjacent electrode grouping along the longitudinal axis by about 1.25 millimeters.

29. The electrode shank of claim 15, wherein the plurality of electrode groupings are distributed along an active region of the body, and wherein the active region of the body has a length of about 25 millimeters.

30. A non-invasive device for delivering stimulation to a human brain, the non-invasive device comprising: a helmet defining an outer body of the non-invasive device, wherein the helmet is sized to fit over a user’s head; a plurality of stimulation emitters carried by the helmet and positioned to direct the stimulation toward the user’s head during operation of the non-invasive device; and a conductive gel carried by the helmet and positioned to provide a buffer between the plurality of stimulation emitters and the user’s head during operation of the non-invasive device.

31. The non-invasive device of claim 30, wherein the plurality of stimulation emitters comprise ultrasonic transducers, and wherein the conductive gel comprises an ultrasound-conducting gel.

32. The non-invasive device of claim 30, wherein the plurality of stimulation emitters comprise a plurality of electrode pairs distributed around the helmet, wherein each individual electrode pair comprises a first electrode with a first emission travel path and a second electrode with a second emission travel path, and wherein the second electrode is positioned such that the second -83- 169064111.3emission travel path overlaps with the first emission travel path at a predetermined location within the user’s head during operation of the non-invasive device.

33. The non-invasive device of claim 32, further comprising a controller coupled to each of the plurality of electrode pairs, and wherein the controller is configured to: deliver a first drive current to the first electrode to emit a first electric stimulation along the first emission travel path; and deliver a second drive current to the second electrode to emit a second electric stimulation along the second emission travel path, wherein the second electric stimulation is configured to cause constructive interference with the first electric stimulation at the predetermined location.

34. The non-invasive device of claim 30, wherein the plurality of stimulation emitters comprise a plurality of coherent microwave emitters positioned to deliver low-amplitude coherent microwaves to a target location within the user’s head during operation of the non-invasive device.

35. The non-invasive device of claim 30, wherein the helmet is custom-molded to the user’s head.

36. The non-invasive device of claim 30, wherein conductive gel is configured to at least partially mold around the user’s head during operation of the non-invasive device.

37. A system for treating an injury to a user’s brain, the system comprising: a stimulation device, the stimulation device comprising a main controller and bilateral electrode shanks, wherein each of the bilateral electrode shanks is implanted at least partially within the user’s brain to provide contact between one or more first electrodes and a nucleus accumbens region of the user’s brain and contact between one or more second electrodes and a caudate region of the user’s brain; and a learning subsystem communicably coupled to the main controller of the stimulation device, wherein the learning subsystem includes processor and a memory storing instructions that when executed by the processor cause the learning subsystem to: -84- 169064111.3present, via a user interface coupled to the learning subsystem, a rehabilitation task to the user; instruct the main controller to deliver a first stimulation to the nucleus accumbens region of the user’s brain via the one or more first electrodes simultaneous with presenting the rehabilitation task; receive, from the user via the user interface, a response from the user related to the rehabilitation task; and in response to a determination that the response from the user was a correct response to the rehabilitation task, instruct the main controller to deliver a second stimulation to the caudate region of the user’s brain via the one or more second electrodes.

38. A method for treating an injury to a patient’s brain, the method comprising: determining an initial difficulty level for a task comprising a plurality of rehabilitation trial related to the injury to the patient’s brain; for each individual trial in the plurality of rehabilitation trial: presenting the individual trial, wherein presenting the individual trial comprises presenting a prompt to the patient requesting a response; at a start of the individual trial, administering stimulation to a nucleus accumbens region of the brain via an electrode device implanted in the patient’s brain; receiving, via a rehabilitation subsystem, the response to the prompt from the patient; evaluating the response to determine if an accuracy of the response to the individual task is above a predetermined threshold for the individual trial; in response to a determination that the accuracy is above the predetermined threshold, administering stimulation to a caudate region of the patient’s brain via the electrode device; recording the accuracy of the response to the individual trial; and determining a new difficulty level for a next individual trial based at least partially the accuracy of the response to the individual trial; and -85- 169064111.3recording an overall accuracy of responses to the plurality of rehabilitation trials based on the accuracy of the response to each of the individual trials in the plurality of rehabilitation trials.

39. The method of claim 38, wherein presenting the prompt to the patient comprises presenting a visual cue to the patient to pronounce a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises comparing a summed magnitude of a rectified cross-correlation of produced speech to a reference template for a desired speech sound for the word or the phrase.

40. The method of claim 38, wherein presenting the prompt to the patient comprises presenting a visual cue to the patient to pronounce a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises evaluating a spoken response with speech recognition software to generate a matching index and comparing the matching index to a predetermined threshold index value.

41. The method of claim 38, wherein presenting the prompt to the patient comprises providing an audio or visual cue to the patient to select an image matching a word or phrase, and wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises evaluating a spatial accuracy of a touch or eye movement response based on a radial distance of the response from a target displayed to the patient.

42. The method of claim 38, wherein evaluating the response to determine if the accuracy of the response is above the predetermined threshold comprises comparing a response time associated with receiving the response to a predetermined threshold value.

43. The method of claim 38, further comprising, for each individual trial in the plurality of rehabilitation trials: measuring one or more metrics of brain activity after presenting the prompt to the patient; and determining, based on the one or more metrics of brain activity, an engagement score associated with patient readiness to participate in the individual trial. -86- 169064111.

344. The method of claim 43, wherein at least one of the trials in the plurality of rehabilitation trials is a indexing trial previously presented to the patient, and wherein determining the new difficulty level for the next individual trial is further based at least partially on a comparison of a response received for the indexing trial to previous responses received for the indexing trial.

45. The method of claim 43, wherein determining the new difficulty level for the next individual trial is further based at least partially on the engagement score for each of the plurality of rehabilitation trials.

46. The method of claim 38, further comprising prompting the patient to provide a score for their readiness to engage in the plurality of rehabilitation trials within the task before presenting any of the plurality of rehabilitation trials, wherein determining the new difficulty level for the next individual trial is further based at least partially on the score received from the patient.

47. The method of claim 38, further comprising prompting the patient to provide a score for their readiness to engage in the plurality of rehabilitation trials within the task after presenting a subset of the plurality of rehabilitation trials, wherein determining the new difficulty level for the next individual trial is further based at least partially on the score received from the patient.

48. A method for treating a neuropsychiatric disorder of a patient via stimulation to a brain of the patient, the method comprising: presenting an individual trial to the patient via a rehabilitation subsystem, wherein presenting the individual trial comprises presenting an audio-visual trigger associated with the neuropsychiatric disorder to the patient; at a start of the individual trial, administering a first stimulation to a nucleus accumbens region of the patient’s brain via an electrode device implanted in the patient’s brain, wherein the first stimulation has a first frequency; receiving, via the rehabilitation subsystem, a response to the audio-visual trigger from the patient; evaluating the response to determine if the response indicates a negative behavioral response to the audio-visual trigger; and -87- 169064111.3in response to a determination that the response indicates the negative behavioral response, administering a second stimulation to a caudate region of the patient’s brain via the electrode device, wherein the second stimulation has a second frequency lower than the first frequency.

49. The method of claim 48, wherein the individual trial is a first individual trial, and wherein the method further comprises: presenting a second individual trial to the patient via the rehabilitation subsystem, wherein presenting the second individual trial comprises presenting a second audio-visual trigger associated with the neuropsychiatric disorder to the patient; at a start of the second individual trial, administering the first stimulation to the nucleus accumbens region of the patient’s brain via the electrode device; receiving, via the rehabilitation subsystem, a second response to the second audio-visual trigger from the patient; evaluating the second response to determine if the second response indicates the negative behavioral response to the second audio-visual trigger; and in response to a determination that the second response does not indicate the negative behavioral response, administering a third stimulation to the caudate region of the patient’s brain via the electrode device, wherein the third stimulation has a third frequency generally equal to the first frequency.

50. The method of claim 48, wherein the first frequency is between about 180 Hertz (Hz) and about 220 Hz, and wherein the second frequency is between about 10 Hz and about 40 Hz.

51. The method of claim 48, wherein the neuropsychiatric disorder is addiction to a substance, and wherein the audio-visual trigger includes audio-visual cues associated with the substance.

52. The method of claim 48, wherein the neuropsychiatric disorder is obsessive- compulsive disorder, and wherein the audio-visual trigger includes one or more cues associated with patient-specific triggers for the obsessive-compulsive disorder. -88- 169064111.

353. A method for treating a degenerative brain disease, the method comprising: presenting, via a memory training subsystem, one or more first memory-related trials to a patient during an indexing task; measuring, during performance of the one or more first memory-related trials, neural activity in an entorhinal cortex region of the patient’s brain; and during a stimulated task: presenting, via the memory training subsystem, one or more second memory-related trials to the patient; delivering stimulation to the entorhinal cortex region of the patient’s brain via an individual subset of an array of electrodes on a stimulation device implanted in the patient’s brain; measuring, during performance of the one or more second memory-related trials, the neural activity in the entorhinal cortex region of the patient’s brain; evaluating an efficacy of the individual subset of electrodes based at least partially on the neural activity measured during the performance of the one or more first memory-related trials; and generating a new subset of electrodes to deliver stimulation during one or more third memory-related trials of the stimulated task.

54. The method of claim 53, wherein: the method further comprises identifying patient-specific activity patterns correlated with successful memory encoding based on the neural activity during performance of the one or more first memory-related trials; and generating the new subset of electrodes is based on a distance between the neural activity during performance of the one or more second memory-related trials and the patient- specific activity patterns correlated with successful memory encoding.

55. The method of claim 54, wherein: generating the new subset of electrodes comprises randomly selecting from a plurality of predefined stimulation patterns for subsets of electrodes; and -89- 169064111.3the distance adjusts a probability of selecting each of the plurality of predefined stimulation patterns for subsets of electrodes.

56. The method of claim 55 wherein the probability of selecting each of the plurality of predefined stimulation patterns is given by: Kmel= min "max "Kmel+ecut^ / ecut× Kscalar, K^^^' , K^01' + KO0^ / _^01× rand^1^, wherein d is the number between 0and 1.

57. The method of claim 53, wherein measuring the neural activity in the entorhinal cortex region of the patient’s brain comprises measuring gamma-band synchronization in superficial layers of the entorhinal cortex.

58. The method of claim 57, further comprising identifying patient-specific activity patterns correlated with successful memory encoding based on greater gamma-band synchronization in the superficial layers of the entorhinal cortex during mnemonic encoding time periods of the one or more first memory-related trials.

59. The method of claim 57, further comprising identifying patient-specific activity patterns correlated with successful memory encoding based on reduced gamma-band synchronization in the superficial layers of the entorhinal cortex during recognition time periods of the one or more first memory-related trials.

60. The method of claim 53, further comprising identifying patient-specific activity patterns correlated with desynchronization in deep layers of the entorhinal cortex during memory encoding based on the neural activity during performance of the one or more first memory-related trials. -90- 169064111.

361. The method of claim 53, wherein the new subset of electrodes includes no electrodes on stimulation device implanted in the patient’s brain to conduct a control test during the one or more third memory-related trials of the stimulated task.

62. The method of claim 53, wherein measuring the neural activity in the entorhinal cortex region of the patient’s brain comprises measuring an amplitude of gamma-band synchronization, and wherein the method further comprises identifying one or more subsets of electrodes associated with increased gamma-band synchronization over a predetermined period.

63. The method of claim of claim 63, wherein the predetermined period is on a scale of minutes, hours, or days.

64. The method of claim of claim 53, further comprising identifying a target activity state in the patient’s brain, wherein the target activity is associated with a brain state that recruits glial cells to clear abnormal tau and amyloid-beta from the entorhinal cortex region of the patient’s brain.

65. The method of claim 53, further comprising identifying a target activity state in the patient’s brain, wherein the target activity state is associated with a brain state that recruits glial cells to clear abnormal tau and amyloid-beta from a second stimulated region of the patient’s brain.

66. The method of claim 64 or claim 65, wherein clearance of the abnormal tau and amyloid-beta is associated with slowing a progression of or reversing a course of Alzheimer’s disease.

67. The method of claim 53, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more first memory-related trials, and wherein evaluating the efficacy of the individual subset of electrodes is further based on a distance between a measured activity state during performance of the one or more second memory-related trials and the one or more abnormal memory states.

68. The method of claim 53, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more first memory-related trials, -91- 169064111.3wherein generating the new subset of electrodes is based on a distance between the neural activity during performance of the one or more second memory-related trials and the one or more abnormal activity states.

69. A method for enhancing memory, the method comprising: recording, via measurements from an electrode array implanted in a patient’s brain, neural activity in the patient’s brain during one or more memory-related trials; identifying: one or more patient-specific target neural activity patterns that correlate with successful memory encoding, recognition, and / or consolidation; or one or more patient-specific abnormal neural activity patterns; and delivering stimulation to the patient’s brain via a closed-loop stimulation process, the closed- loop stimulation process comprising: delivering stimulation to the patient’s brain via a subset of electrodes in the electrode array implanted in the patient’s brain; recording, via measurements from the electrode array implanted in the patient’s brain, neural activity in the patient’s brain while receiving the stimulation; performing a real-time analysis of the neural activity in the patient’s brain while receiving the stimulation; and generating a new subset of electrodes in the electrode array based at least partially on the real-time analysis of the neural activity in the patient’s brain while receiving the stimulation.

70. The method of claim 69, wherein generating the new subset of electrodes in the electrode array comprises: adapting a probability of selecting one or more predefined stimulation patterns based on a difference between the neural activity in the patient’s brain while receiving the stimulation and a target neural activity state; and randomly selecting from the predefined stimulation patterns. -92- 169064111.

371. The method of claim 69, wherein generating the new subset of electrodes in the electrode array nudges the neural activity in the patient’s brain while receiving the stimulation toward a target activity state defined via neural activity in the patient’s brain during one or more memory- related trials.

72. The method of claim 69, further comprising evaluating an efficacy of the closed-loop stimulation process based at least partially on a comparison of memory performance between stimulation and non-stimulation trials.

73. The method of claim 69, further comprising evaluating an efficacy of the closed-loop stimulation process based on neural activity in the patient’s brain while receiving the stimulation for a predetermined period.

74. The method of claim 73, wherein the predetermined period is on a scale of minutes, hours, or days.

75. The method of claim 69, further comprising identifying one or more abnormal activity states based on the neural activity during performance of the one or more memory-related trials, wherein generating the new subset of electrodes is based on a distance between the neural activity in the patient’s brain while receiving the stimulation and the one or more abnormal activity states.

76. The method of claim 69, further comprising identifying one or more target activity states based on the neural activity during performance of the one or more memory-related trials, wherein generating the new subset of electrodes is based on a distance between the neural activity in the patient’s brain while receiving the stimulation and the one or more target activity states.

77. A method for enhancing memory, the method comprising: recording, via measurements from an electrode array implanted in a patient’s brain, neural activity in the patient’s brain; identifying sharp-wave ripple patterns in the neural activity in the patient’s brain; and -93- 169064111.3in response to detecting the sharp-wave ripple patterns, delivering stimulation to the patient’s brain via a closed-loop stimulation process, the closed-loop stimulation process comprising: delivering stimulation to the patient’s brain via a subset of electrodes in the electrode array implanted in the patient’s brain; recording, via measurements from the electrode array implanted in the patient’s brain, neural activity in the patient’s brain while receiving the stimulation; performing a real-time analysis of the neural activity in the patient’s brain while receiving the stimulation; and generating a new subset of electrodes in the electrode array based at least partially on the real-time analysis of the neural activity in the patient’s brain while receiving the stimulation.

78. The method of claim 77, wherein performing the real-time analysis comprises assessing an impact of the stimulation on a propagation of the sharp-wave ripple patterns.

79. The method of claim 77, wherein delivering stimulation to the patient’s brain is performed after a propagation of an individual sharp-wave ripples.

80. The method of claim 77, wherein the sharp-wave ripple patterns are associated with a first sharp-wave ripple pattern event, and wherein the method further comprises: identifying a second sharp-wave ripple pattern event in the neural activity in the patient’s brain; and in response to detecting the second sharp-wave ripple pattern event, delivering stimulation to the patient’s brain via the closed-loop stimulation process.

81. The method of claim 77, wherein the sharp-wave ripple patterns are associated with a sharp-wave ripple pattern event, and wherein the method delivers the stimulation to the patient’s brain via the closed-loop stimulation process throughout the sharp-wave ripple pattern event. -94- 169064111.3

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