Presenting multimodal, multistable stimuli to reduce symptoms associated with attention biases due to impairment of cognitive functions in users

Abstract

To provide systems and methods for presenting multimodal stimuli to address symptoms associated with various pathological conditions.SOLUTION: A system includes one or more session management services and one or more user devices (referred to as client devices), communicatively coupled with one another via a network 115. A service is configured to: identify a first visual stimulus associated with a pathological condition, and a second visual stimulus (405); present the first visual stimulus at least partially overlapped with the second visual stimulus, in order to direct a client to interact with a display (410); detect a response identifying an interaction associated with one of the first and second visual stimuli (420); and generate an auditory stimulus to include one or more portions indicating feedback based on the response (445).SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Non-provisional Application No. 18 / 757,253, filed June 27, 2024, which claims priority to U.S. Provisional Application No. 63 / 547,456, filed November 6, 2023, and U.S. Provisional Application No. 63 / 530,640, filed August 3, 2023, each of which is incorporated by reference in its entirety herein. [Background technology]

[0002] Certain pathologies may cause subjects to pay attention to certain biases, which may ultimately worsen symptoms. Subjects may suffer from chronic pain, fear, and mood symptoms simultaneously, such as multiple sclerosis (MS) and cancer patients. The desire to pay attention to pain, fear, or other biases is innate, and subjects may further become more aware of the bias in response to relevant stimuli. For example, subjects with MS may pay more attention to pain-related stimuli than patients without chronic pain. Similarly, hypersensitivity to negative or threat-related stimuli may exacerbate a subject's fear. For example, patients with hypersensitivity may seek out signs of threat in social interactions, unlike patients without such conditions. This attention to negative stimuli may worsen the patient's symptoms. For example, a pain bias may lead to hypersensitivity for the patient. Furthermore, such hypersensitivity may worsen symptoms through fear avoidance, which causes the subject to avoid stimuli or activities that are perceived to be likely to cause pain or threat, further worsening the mental and physical state from the lack of activity.

[0003] Treating attentional bias in patients with chronic illnesses can be difficult due to the general decline in cognitive function that is often caused by these diseases. Therapeutic exercises to reduce the impact of such biases may reduce the severity of the condition. Certain behavioral therapies can help reduce or eliminate the bias that causes a person to pay attention to or away from certain stimuli. However, receiving such behavioral therapies can be difficult, especially for patients with chronic illnesses such as MS or cancer. Furthermore, these therapies are only useful to patients if there is consistent adherence, which may not be easy to ensure due to the nature of pain or fear. Finally, it can be difficult to determine which treatments will be most beneficial for an individual, or whether a combination of multiple therapies would be most beneficial.

[0004] Digitally addressing attention biases associated with subjects' chronic conditions through devices that present such therapeutic exercises can present a number of challenges. For one, users may be unable or have extreme difficulty refraining from paying attention to negative stimuli, thereby ignoring attempts at intervention from clinicians or through the device. As such, users may find it difficult to adhere to digitally delivered treatments due to the nature of their chronic condition, leading to ineffective clinical outcomes. For another, if subjects are in pain, it may be physically difficult to use a device to receive digital therapeutics, let alone contact a clinician to receive treatment. Summary of the Invention

[0005] To address these and other technical challenges, digital therapeutics using multimodal multistable correction of bias (or multimodal multistable bias correction or MMBM) can be provided to users with symptoms associated with attention bias caused by a pathology affecting the user's cognitive function. By linking two different senses (e.g., a combination of visual multistable perception using a set of visual stimuli and auditory multistable perception using auditory stimuli for multimodal perception), the synergistic effects obtained in this multimodal multistable approach can provide the user with reinforcement training to redirect attention to positive stimuli and resolve symptoms associated with the user's attention bias. Furthermore, the digital therapeutics presented herein can provide auditory stimuli (e.g., binaural beats) to address secondary symptoms (e.g., fatigue) associated with the user's pathology. In this way, the user can be conditioned to pay less attention to negative stimuli, such as stimuli associated with pain or stress, at the speed, frequency, and efficacy available through the digital therapeutic application.

[0006] A multimodal multistable perception modification approach that includes visual and auditory stimuli can enhance a user's ability to divert attention from negative stimuli. Controlling the bias towards negative stimuli can lead to the amelioration or resolution of symptoms of conditions such as MS and cancer. A multimodal approach refers to a therapy that applies to two or more of a user's senses, such as hearing and vision. Multistable perception refers to the superimposition of two media that are detected by the same sense of the user. For example, multistable perception can include two images presented to a user, each of which elicits the user's attention or is individually salient to the user at different times that the user views the images.

[0007] Visual multistable perception can include monocular rivalry and binocular rivalry. In monocular rivalry, a different image (or word) is presented to each eye of the subject. The subject then shifts between the image presented to the left eye and the image presented to the right eye. In binocular rivalry, two or more images can be superimposed so that the subject can use both eyes to identify one image at a different time. As a therapeutic approach, the subject can be presented with two stimuli presented as images or words. The first stimulus can be a negative stimulus or a stimulus associated with a disease. For example, the first stimulus can include the words "pain", "sickness", and "tired". The second stimulus can be a positive or neutral stimulus not associated with a disease. For example, the second stimulus can include the words "love", "good", and "happy". These two stimuli can be presented to the subject as superimposed images. Cognitive bias training can train subjects to see more clearly, pay more attention to, or be more inclined to notice positive or neutral stimuli than negative stimuli.

[0008] Additionally, binaural beats are a unique auditory multistable perception of this approach. The system can present binaural beats as a combination of two or more different tones or frequencies of sound. Binaural beats can include a first sound presented to a subject's first ear and a second sound simultaneously presented to the subject's second ear. For example, presenting a 415 Hz frequency to a patient's left ear and a 400 Hz frequency to the patient's right ear at the same time will result in the patient hearing a 15 Hz "beat." In some cases, the presentation of this beat can elicit a beneficial therapeutic response.

[0009] The combined use of binaural beats and binocular rivalry can synergistically increase a user's ability to tolerate a bias towards negative stimuli through a multimodal, multistable modification of the bias. Not succumbing to a bias towards negative stimuli can be an aspect of curing or resolving the symptoms of chronic diseases such as MS and oncological diseases, as examples. Multimodal, multistable modification of the bias can include interventions such as binaural beats. In this case, the user receives two or more sounds that are different but similar in each ear. Binaural beats can modulate brain activity based on the different frequency beats provided. For example, beats in the 14-30 Hz range have been shown to modulate brain activity related to focus, vigilance, and cognition. Thus, providing a 415 Hz tone to the patient's left ear and a 400 Hz tone to the patient's right ear can generate a 15 Hz beat that can stimulate brain activity related to focus, vigilance, and cognition.

[0010] Users may adapt to pay less attention to negativity, especially associated with pain, anxiety, and depressed mood. By performing binocular rivalry maneuvers, users can be conditioned to focus on positive or neutral stimuli over negative stimuli. By presenting two superimposed images, users can perform tasks such as selecting the image associated with a positive or neutral stimulus. Upon selecting the correct (e.g., positive or neutral) stimulus, they can receive positive feedback that biases the user toward the positive or neutral stimulus and away from the negative stimulus. In this way, users can be trained to focus on images associated with positive or neutral stimuli.

[0011] Combining these therapies can greatly reduce the bias towards negative stimuli. Combining these therapies can create a multimodal richness that more closely resembles a real-world environment by integrating multiple types of sensory information, such as vision and sound. In this illustrative example, the combination can include a service that provides a game to a user through the user's mobile device. The service can also be combined with a pair of speakers (e.g., headphones or earphones) to play tones to each ear. The service can present the user with two words superimposed on the screen of the mobile device. The user can select the word that represents the positive or neutral stimulus. This example shows binocular rivalry to encourage the user to focus on the positive or neutral stimulus over the negative stimulus.

[0012] Along with the presentation of visual stimuli, the service can provide one or more different tones to each ear. Each tone in one ear can have a corresponding tone presented to the other ear. The tones and corresponding tones can each have a different frequency, and the difference in frequency creates a beat. The beat can modulate brain activity to treat several disorders due to chronic conditions, such as fatigue, reduced cognitive acuity, anxiety, and pain sensation, among others. This multimodal approach can trigger cross-modal interactions between the associated brain regions of each stimulus. In this way, each brain region can be cross-activated by subsequent unisensory stimulation. Furthermore, this approach can increase the functional connectivity of sensory-specific regions. The combination of therapies provided by the service can reduce the symptomatic symptoms of chronic diseases.

[0013] To provide these therapies, the service may select two or more visual stimuli, including at least two words or images and associated actions, for the user to send to the end user device. The service may select stimuli including at least two tones played to the user through two or more speakers. The service may also time the delivery or presentation of the stimuli to the user such that the user does not need to actively access a digital therapeutic application on the device while suffering from a chronic condition. The service may also time the delivery or presentation of the stimuli to the user after completion of a previous action related to the stimuli. Additionally, as the service acquires additional data about the user, the service may select stimuli that are more targeted specifically to the user and his or her condition, and may store this data in the user's profile. The service may receive preferences from the user, such as a list of preferred words and preferred tones. The service may select subsequent stimuli based on at least the previous stimuli, the completion of a previous action, the user's profile, or an evaluation of the user's performance with the previous stimuli.

[0014] In this way, the user can easily receive stimuli related to the chronic condition to help retrain the bias against negative stimuli associated with the condition, as described herein. This can reduce or eliminate the barriers to the user physically accessing their device while battling the chronic condition. By selecting the stimuli sent to the user to address the subject's bias against negative stimuli, the quality of human-computer interaction (HCI) between the user and the device can be improved. In addition, the stimuli are more relevant to the user's condition, which can reduce unnecessary consumption of computational resources (e.g., processing and memory) and network bandwidth of the service and the user device compared to sending ineffective messages. Furthermore, in the context of digital therapeutic applications, such selection of stimuli tailored to the individual situation can provide a user-specific intervention and improve the subject's adherence to the treatment. As a result, not only can adherence to the therapeutic intervention be improved, but also the subject's bias against negative stimuli can be improved.

[0015] Because the digital therapeutic application runs on the subject's device, or at least on a device that the user can easily and reliably access (e.g., according to a predefined frequency, such as once a day), the application can provide real-time support to the subject. For example, upon receiving a request from the user to start a session, the application starts a session in near real time. Such rapid guidance cannot be achieved through an in-person visit, phone call, video conference, or text message between the user and a healthcare provider who sees the user for multiple sclerosis or cancer. This accessibility allows the application to challenge the user and tailor those challenges to the individual user based on the user's performance. This increases the usefulness of each session, thus creating an iteratively improved service for the user that minimizes overall bandwidth and data communication.

[0016] Aspects of the present disclosure relate to systems and methods for presenting multimodal stimuli to address symptoms associated with various disease states. The system may include a computing system having one or more processors coupled with a memory. The computing system may identify (i) a first visual stimulus associated with a disease state and (ii) a second visual stimulus to address a disease state of a user. The computing system may present the first visual stimulus at least partially overlaid with the second visual stimulus via a display to prompt the user to interact with the display. The system may detect a response identifying an interaction. The interaction may be associated with either the first visual stimulus or the second visual stimulus. The computing system may generate an auditory stimulus including one or more portions. The one or more portions may indicate feedback based on the response. The computing system may play the auditory stimulus via a transducer to provide the user with the feedback about the response.

[0017] In some embodiments, the computing system can determine that the response is correct based on the interaction associated with the second visual stimulus. The second visual stimulus can direct the user away from the pathology. In response to the determination that the response is correct, the computing system can add at least one portion to the auditory stimulus to provide positive reinforcement. In some embodiments, the computing system can determine that the response is incorrect based on the interaction associated with the first visual stimulus associated with the pathology. In response to the determination that the response is incorrect, the computing system can remove at least one portion from the auditory stimulus to provide negative reinforcement. In some embodiments, the computing system can assign (i) the first visual stimulus to a first type of interaction and (ii) the second visual stimulus to a second type of interaction. The computing system can (i) present the first visual stimulus with a first indicator to identify the first type of interaction and (ii) present the second visual stimulus with a second indicator to identify the second type of interaction.

[0018] In some embodiments, the computing system may select a difficulty level from a set of difficulty levels based on a percentage of correct responses from a previous presentation of a visual stimulus. Each of the set of difficulty levels may define one or more visual features. The computing system may modify the presentation of the first visual stimulus and the second visual stimulus according to the one difficulty level using the one or more visual features. In some embodiments, the computing system may generate the auditory stimulus to include (i) a first element played to a first ear of the user and (ii) a second element played to a second ear of the user. The computing system may present the first element to the first ear of the user via a first speaker and the second element to the second ear via a second speaker. In some embodiments, the interaction may include orienting the display to a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus.

[0019] In some embodiments, the computing system can modify visual features of one of the first visual stimulus or the second visual stimulus based on the response. In some embodiments, the computing system can play at least one portion of the one or more portions of the auditory stimulus. The computing system can play the one or more portions of the auditory stimulus at least partially concurrently with the presentation of the first visual stimulus and the second visual stimulus. In some embodiments, the computing system can receive, via an interface, a user selection of at least one property from a set of properties for the auditory stimulus. The computing system can generate the auditory stimulus according to the at least one property. In some embodiments, the computing system can receive, via an interface, a list identifying a plurality of words including a first subset of words associated with the condition and a second subset of words. The computing system can select the first visual stimulus from the first subset of words and the second visual stimulus from the second subset of words. In some embodiments, the user may be taking a medication to address the condition associated with at least one of cancer or multiple sclerosis at least partially concurrently with the session.

[0020] An aspect of the present disclosure relates to a system and method for providing a necessary relief for symptoms associated with attention bias in a user suffering from a condition affecting cognitive function. A computing system may obtain a first metric associated with the user prior to a plurality of sessions. During each of the plurality of sessions, the computing system may iteratively: (i) present a set of visual stimuli to the user via a display, the set including (a) a first visual stimulus associated with the symptoms, and (b) a second visual stimulus at least partially superimposed with the first visual stimulus, and prompt the user to perform an interaction; and (ii) play a corresponding auditory stimulus to the user via a transducer to provide feedback based on the interaction via the display with any of the plurality of sets of visual stimuli. The computing system may obtain a second metric associated with the user following at least one of the plurality of sessions. The symptoms associated with the attention bias in the user may be alleviated when the second metric (i) decreases from the first metric by a first predetermined margin or (ii) increases from the first metric by a second predetermined margin. In some embodiments, the attentional bias can include one or more of: (i) avoidance of stimuli or activities associated with the condition; (ii) anxiety induced by stimuli associated with the condition, multiple sclerosis, or cancer; or (iii) depressed mood.

[0021] In some embodiments, the symptoms of the user may include multiple sclerosis (MS) with or without mobility limitations. In some embodiments, the reduction in the symptoms occurs when the second metric increases from the first metric by the second predetermined margin, and the first metric and the second metric may be Symbol Digit Modalities Test (SDMT) values. In some embodiments, the user may have relapsed and be steroid-free for at least a period of time prior to the plurality of sessions. In some embodiments, the user may be taking a medication at least partially concurrently with the plurality of sessions, the medication being, in the case of multiple sclerosis, at least one of beta interferon, glatiramer, cladribine, dimethyl fumarate, diroximel fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponesimod, siponimod, teriflunomide, alemtuzumab, mitoxantrone, or natalizumab.

[0022] In some embodiments, the condition of the user may include at least one of lung cancer, colorectal cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, or gastric cancer. In some embodiments, the alleviation of the symptoms occurs when the second metric increases from the first metric by the second predetermined margin, and the first metric and the second metric may be Functional Assessment of Cancer Treatment-Cognitive (FACT-Cog) values. In some embodiments, the user may have completed cancer chemotherapy within a predetermined period prior to the plurality of sessions.

[0023] In some embodiments, the reduction in the symptom occurs when the second metric is reduced from the first metric by the first predetermined margin, and the first metric and the second metric may be Patient-Reported Outcomes Measurement Information System (PROMIS) values. In some embodiments, the reduction in the symptom occurs when the second metric is reduced from the first metric by the first predetermined margin, and the first metric and the second metric may be Brief Pain Questionnaire (BPI) values. In some embodiments, the reduction in the symptom occurs when the second metric is reduced from the first metric by the first predetermined margin, and the first metric and the second metric may be Pain Catastrophizing Scale (PCS) scores. In some embodiments, the first metric and the second metric may be computer cognitive assessment values.

[0024] In some embodiments, the user may experience an improvement in fatigue associated with the medical condition in response to binaural beats of the corresponding auditory stimuli in at least one of the plurality of sessions. In some embodiments, the set of visual stimuli for each session of the plurality of sessions may be selected from a plurality of visual stimuli including: (i) pain-related visual stimuli, (ii) threat-related visual stimuli, (iii) medical condition-related visual stimuli, (iv) negative visual stimuli, or (v) neutral visual stimuli.

[0025] In some embodiments, if the interaction with the set of visual stimuli is correct in at least one of the multiple sessions, the corresponding auditory stimulus may be played to provide positive reinforcement. In some embodiments, if the interaction with the set of visual stimuli is incorrect in at least one of the multiple sessions, the corresponding auditory stimulus may be played to provide negative reinforcement. In some embodiments, the presentation of the visual stimulus may be at least partially simultaneous with the playing of a portion of the corresponding auditory stimulus in at least one of the multiple sessions.

[0026] In some embodiments, in at least one of the plurality of sessions, the presentation of the set of visual stimuli may be modified according to a difficulty level selected based on responses in a previous session. In some embodiments, the interaction may include orienting the display to a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus. [Brief description of the drawings]

[0027] The above and other objects, aspects, features, and advantages of the present disclosure will become better understood with reference to the following description taken in conjunction with the accompanying drawings. [Figure 1] FIG. 1 illustrates a block diagram of a system for presenting multimodal stimuli to address symptoms associated with a pathology, according to an illustrative embodiment. [Diagram 2] FIG. 2 illustrates a block diagram of a process for presenting stimuli and detecting responses that identify interactions associated with the stimuli in accordance with an illustrative embodiment. [Diagram 3] FIG. 3 shows a block diagram of a process for generating auditory stimuli and playing auditory stimuli to provide feedback in accordance with an exemplary embodiment. [Figure 4] FIG. 4 shows a flowchart of a method for presenting multimodal stimuli to address symptoms associated with a pathology, according to an exemplary embodiment. [Diagram 5] FIG. 5 illustrates a screenshot of an exemplary user interface of a system for presenting multimodal stimuli to address symptoms associated with a pathology, according to an exemplary embodiment. [Figure 6] FIG. 6 illustrates a screenshot of an exemplary user interface of a system for presenting multimodal stimuli to address symptoms associated with a pathology, according to an exemplary embodiment. [Figure 7]FIG. 7 shows a flowchart of a method for providing needed relief from symptoms associated with attentional bias in a user suffering from a condition affecting cognitive function, according to an exemplary embodiment. [Figure 8] FIG. 8 shows a timeline of a randomized controlled exploratory basket study to evaluate multimodal multistable modification of attentional biases aimed at normalizing attentional biases and improving cognition in adults with multiple sclerosis, breast cancer, and lung cancer, according to an exemplary embodiment. [Figure 9] FIG. 9 is a block diagram of a server system and a client computer system according to an exemplary embodiment. [Figure 10] Figure 10 shows the results of the PROMIS-Fatigue study. In PROMIS-Fatigue, lower scores indicate improvement (patients feel less fatigued). Clinically important change: 2-6 points. [Figure 11] Figure 11 shows the results of the PROMIS-Depression study. On the PROMIS-Depression, lower scores indicate improvement (patients feel less depressed). Clinically important change: 2-6 points. [Figure 12] Figure 12 shows the results of the PROMIS-Anxiety study. In PROMIS-Anxiety, lower scores indicate improvement (patients feel less anxious). Clinically important change: 2-6 points. [Figure 13] Figure 13 shows the results of the PROMIS-Pain Interference study. On the PROMIS-Pain Interference, lower scores indicate improvement (less pain interference experienced by the patient). Clinically important change: 2-6 points. [Figure 14] Results of the study of PROMIS-Pain scores are shown in Figure 14. For PROMIS-Pain Interference, lower scores indicate improvement (less pain interference experienced by the patient). Clinically important change: ≧2. [Figure 15] Figure 15 shows the results of the PROMIS-Sleep Disorders study. On PROMIS-Sleep Disorders, lower scores indicate improvement (patients have less sleep disturbance). Clinically important change: 2-6 points. [Figure 16]Figure 16 shows the results of the PROMIS-Physical Function study. On PROMIS-Physical Function, higher scores indicate improvement (patients perceive better physical functioning). Clinically important change: 2-6 points. [Figure 17] Figure 17 shows the results of the PROMIS-Cognitive study. On PROMIS-Cognitive, higher scores indicate improvement (patients perceive better cognitive functioning). Clinically important change: 2-6 points. [Figure 18] Figure 18 shows the results of the PROMIS-Social Functioning study. On PROMIS-Social Functioning, higher scores indicate improvement (patients perceive better social functioning). Clinically important change: 2-6 points. [Figure 19] Figure 19 shows the results of the Brief Pain Questionnaire study on interference. Lower scores represent improvement (less pain interference). Clinically important change: >= 1 point. [Figure 20] Figure 20 shows the results of the Brief Pain Questionnaire study on worst pain severity. Lower scores represent improvement (less pain). Clinically important change: ≧1 point. [Figure 21] Figure 21 shows the results of the Brief Pain Questionnaire study for mildest pain severity. Lower scores represent improvement (less pain). Clinically important change: >= 1 point. [Figure 22] Figure 22 shows the results of the Brief Pain Questionnaire study for mean pain severity. Lower scores represent improvement (less pain). Clinically important change: ≧1 point. [Figure 23] Figure 23 shows the results of a Brief Pain Questionnaire study regarding current pain severity. Lower scores represent improvement (less pain). Clinically important change: ≧1 point. [Figure 24] Figure 24 shows the results of a study of the Pain Catastrophizing Scale. Lower score = lower pain catastrophizing (better condition). Minimal detectable change: 9.1 points. [Diagram 25]Figure 25 shows the results of patient reported outcomes for cognition in MS. Higher scores represent better cognitive function. Clinically important change: 4 points. [Figure 26] FIG. 26 shows the results of Global Rating Change (GRC) between DiNaMo and control. [Figure 27] Figure 27 shows the results of a study of the Attention Bias Index for depression. Attention Bias Index: The goal is to be close to 0 (no bias) or below 0 (biased away from triggering stimuli). [Figure 28] Figure 28 shows the results of a study of the Attentional Bias Index for Anxiety. Attentional Bias Index: The goal is to be close to 0 (no bias) or below 0 (biased away from trigger stimuli). [Figure 29] Figure 29 shows the results of a study of the Attention Bias Index for Adaptation. Attention Bias Index: The goal is to be close to 0 (no bias) or below 0 (biased away from the triggering stimulus). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] In reading the following description of the various embodiments, the descriptions and respective contents listed following each section of the specification should be helpful.

[0029] Section A describes systems and methods for presenting multimodal stimuli to address symptoms associated with various pathologies.

[0030] Section B describes how to provide the necessary relief from symptoms associated with attentional bias in users suffering from pathologies affecting cognitive function.

[0031] Section C is a description of network and computing environments that may be useful in implementing the embodiments described herein.

[0032] A. Systems and methods for presenting multimodal stimuli to address symptoms associated with a pathology Referring now to FIG. 1, a block diagram of a system 100 for presenting multimodal stimuli to address symptoms associated with a medical condition is shown. In general, the system 100 may include at least one session management service 105 and a set of user devices 110A-N (hereinafter generally referred to as user devices 110 or client devices) communicatively coupled to each other via at least one network 115. At least one user device 110 (e.g., the illustrated first user device 110A) may include at least one transducer 120 and at least one application 125. The application 125 may include or provide at least one user interface 130 having one or more user interface (UI) elements 135A-N (hereinafter generally referred to as UI elements 135). The session management service 105 may include, among others, at least one session manager 140, a stimulus selector 145, a response handler 150, a performance evaluator 155, or at least one feedback provider 160. The session management service 105 includes or has access to at least one database 165. The database 165 may store, maintain, or otherwise include, among other things, one or more user profiles 170A-N (hereinafter generally referred to as user profiles 170), one or more visual stimuli 175A-N (hereinafter generally referred to as visual stimuli 175), or one or more auditory stimuli 180A-N (hereinafter generally referred to as auditory stimuli 180). The functionality of the applications 125 may be executed in part on the session management service 105. The functionality of the applications 125 may also incorporate operations executed on the session management service 105.

[0033] More specifically, the session management service 105 (sometimes generally referred to herein as a computing system or service) may be any computing device including one or more processors coupled with memory and software capable of performing the various processes and tasks described herein. The session management service 105 may communicate with one or more user devices 110 and a database 165 via a network 115. The session management service 105 may be located, collocated, or otherwise associated with at least one server group. The server group may correspond to a data center, branch office, or campus where one or more servers corresponding to the session management service 105 are located. The session management service 105 may be located, collocated, or otherwise associated with one or more user devices 110. Some components of the session management service 105 may be located in a server group and some may be located in a client device. For example, the session manager 140 may run on or be located on the user device 110A, and the stimulus selector 145 may run on or be located on the server group.

[0034] Within the session management service 105, the session manager 140 can identify a session including a set of visual stimuli 175 to present to the user on each user device 110 via the application 125. The session manager 140 can identify a first visual stimulus and a second visual stimulus to address the user's condition. The stimulus selector 145 can present the first visual stimulus at least partially overlaid with the second visual stimulus via a display, such as the user interface 130, and prompt the user for a dialogue or interaction. The response handler 150 can detect a response identifying an interaction associated with the first visual stimulus or the second visual stimulus. The performance evaluator 155 can calculate a score based on the response. The feedback provider 160 can generate an auditory stimulus to the user via the transducer 120, the auditory stimulus including one or more portions indicative of feedback based on the response. The feedback provider 160 can generate an auditory stimulus that plays one or more portions at least partially concurrently with the presentation of the visual stimuli by the stimulus selector 145.

[0035] The user device 110 (sometimes referred to herein as an end-user computing device or client device) may be any computing device including one or more processors coupled with memory and software capable of performing the various processes and tasks described herein. The user device 110 may communicate with the session management service 105 and the database 165 via the network 115. The user device 110 may be a smartphone, other mobile phone, tablet computer, wearable computing device (e.g., smart watch, glasses) or laptop computer. The user device 110 may be used to access the application 125. In some embodiments, the application 125 may be downloaded (e.g., via a digital distribution platform) and installed on the user device 110. In some embodiments, the application 125 may be a web application with resources accessible via the network 115.

[0036] In some embodiments, the user device 110 can be coupled to at least one transducer 120. The transducer 120 can convert an electrical signal provided by the session management service 105 into an audio signal. The transducer 120 can generate one or more audio signals to be output by one or more speakers coupled to the transducer 120. The transducer 120 can generate audio signals such as tones, buzzers, musical notes, voices, or other sounds to be played by the speakers. The transducer 120 can generate instructions to cause the speakers to play one or more sounds. For example, the transducer 120 may generate audio signals in a Musical Instrument Digital Interface (MIDI) format for output by the speakers. The transducer can generate instructions including pre-recorded sounds to be played by the speakers. For example, the transducer can generate audio signals according to a pre-recorded audio format such as Moving Picture Experts Group (MPEG), Audio Layer 3 (MP3), Waveform Audio File (WAV), etc. The audio signal may include instructions regarding the reproduction of the audio, such as volume, pitch, speed, tempo, compression, panning, bit rate, distortion, or timbre.

[0037] The transducer 120 can then transmit the audio signal or command to one or more speakers. A speaker can be any device designed or configured to generate sound. A speaker can include, for example, a magnet, a cone, an audio amplifier, or other device to generate mechanical vibrations to output sound from a signal. In some embodiments, a speaker can be coupled to or included in at least one transducer 120. For example, the speaker and transducer 120 can be part of the same speaker, headphone, earbud, or other device to convert an electrical signal into sound and generate an output sound. In some embodiments, the transducer 120 can be configured to generate two or more audio signals to two or more speakers. For example, a first transducer 120 can generate a first audio signal for a first speaker for playback to the subject's left ear, and a second transducer 120 can simultaneously generate a second audio signal for a second speaker for playback to the subject's right ear. The transducer 120 can play multiple tones or sounds through each speaker. For example, the transducer 120 may superimpose a 500 Hz signal on a 300 Hz signal, or the transducer 120 may alternate between these two signals among other combinations that reproduce two or more signals through a single speaker.

[0038] The application 125 executing on the user device 110 may be a digital therapeutic application and may provide sessions (sometimes referred to herein as therapy sessions) to address symptoms associated with a medical condition. A user of the application 125 may be an individual suffering from or at risk for a medical condition. The medical condition may include, for example, cancer (e.g., lung cancer, colon cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, gastric cancer), multiple sclerosis (e.g., with or without mobility limitations), and the like. Attention biases associated with conditions such as cancer and multiple sclerosis may result in symptoms such as pain, fear, and fatigue.

[0039] Attentional biases may include, for example, avoidance of stimuli or activities related to a symptom, anxiety induced from stimuli associated with the symptom or condition, or depression (or depressed mood). A user may pay attention to stimuli associated with a symptom of the condition, such as pain, fatigue, or actions that trigger the symptom, such as a particular movement or behavior. For example, a user may refrain from an action that may cause pain, which may increase sensitivity to pain, thereby further limiting the user and causing anxiety associated with the action that is believed to cause pain. Other actions may cause or be related to the user's condition. The application 125 may be used to present stimuli to the user to encourage actions in order to reduce bias toward negative stimuli associated with the user's condition. These actions may be presented to the user as a result of, among other things, sending a session initiation request, user detection measurements received from the client device, or the passage of a scheduled time or period.

[0040] The user may at least partially simultaneously take an effective amount of a medication to address the condition, at least partially in parallel with a session via the application 125. The medication may be at least orally administered, intravenously administered, or topically applied. For example, in the case of multiple sclerosis, the user may be taking beta interferon, glatiramer, cladribine, dimethyl fumarate, diroximel fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponesimod, siponimod, teriflunomide, alemtuzumab, mitoxantrone, or natalizumab, among others. In the case of cancer, the user may be undergoing chemotherapy, radiation therapy, immunotherapy, and the like. Additionally, the user suffering from cancer may be taking painkillers, such as acetaminophen, aspirin, ibuprofen, naproxen, nonsteroidal anti-inflammatory drugs, among others. The application 125 may enhance the efficacy of the medication the user is taking to address the condition.

[0041] The application 125 may include, present, or otherwise provide a user interface 130 having one or more UI elements 135 to a user of the user device 110 according to a configuration on the application 125. The UI elements 135 may correspond to visual components of the user interface 130, such as command buttons, text boxes, check boxes, radio buttons, menu items, and sliders. In some embodiments, the application 125 may be a digital therapeutic application and may provide sessions (sometimes referred to herein as therapeutic sessions) via the user interface 130 to address a bias toward negative stimuli associated with a pathology.

[0042] The application 125 can receive instructions to present a visual stimulus 175 or an auditory stimulus 180 to the user. The visual stimulus 175 can be or include a stimulus or action that is presented to the user as text, an image, a video, or other visual presentation and can include instructions for the user to perform an action to address a symptom associated with the condition. The auditory stimulus 180 can be or include a stimulus or action that is presented audibly via a transducer 120 coupled with a speaker.

[0043] The action associated with the visual stimulus 175 may include interacting or not interacting with the user device 110. For example, the action may include tilting the user interface 130, tapping on the visual stimulus 175 presented by the user device 110, etc. In some embodiments, tilting the user device may alter the presentation of the visual stimulus 175. For example, tilting the mobile device to the left may cause a first visual stimulus to be more legible or more prominent than a second visual stimulus. Similarly, tilting the mobile device to the right may cause a second visual stimulus to be more legible or more prominent than the first visual stimulus. The action may include instructions for the user to address the condition. For example, the action may include a message including instructions describing an attentional bias to negative stimuli to be reduced. The action may include an interactive interface to engage the user, via the user interface 130, in one or more therapies designed to reduce or mitigate the bias to negative stimuli associated with the condition. For example, a user may play a game on the user device 110 presented by an application 125 that incorporates one or more therapies for addressing bias.

[0044] The database 165 may store and maintain various resources and data associated with the session management service 105 and the applications 125. The database 165 may include a database management system (DBMS) for organizing and arranging the data maintained on the database. The database 165 may communicate with the session management service 105 and one or more user devices 110 via the network 115. While performing various operations, the session management service 105 and the applications 125 may access the database 165 to retrieve identified data therefrom. The session management service 105 and the applications 125 may also write data to the database 165 from the performance of such operations.

[0045] Such operations may include maintaining a user profile 170 (sometimes referred to herein as a subject profile). The user profile 170 may include information related to the user's condition, as described herein. For example, the user profile 170 may include information related to, among other things, the severity of the condition, the occurrence of the condition (such as the occurrence of symptoms associated with attention bias due to the condition affecting the user's cognitive function), medications or treatments the user is taking for the condition, and / or the duration of the condition. The user profile 170 may be updated periodically (e.g., daily, weekly) in response to a schedule, in response to changes in user information (e.g., entered by the user via the user interface 130 or learned from the user device 110), or in response to a clinician (e.g., a doctor or nurse) addressing the user's condition, among other things.

[0046] The user profile 170 can store and maintain information related to a user of the application 125 via the user device 110. Each user profile 170 can be associated with or correspond to a subject or user of the application 125. The user profile 170 can include or store information for each session performed by the user. The session information can include various parameters, actions, visual stimuli 175, auditory stimuli 180, or challenges of previous sessions performed by the user, which can be initially blank. The user profile 170 can simplify communication to the user by presenting the user with challenges that are most likely to help the user address symptoms of their condition or reduce bias toward negative stimuli, based at least on the user profile 170. This managed approach can reduce the need for multiple communications with the user, thereby reducing bandwidth and increasing the benefits of user-computer interaction.

[0047] In some embodiments, user profile 170 may identify or include information about a treatment regimen undertaken by the user, such as the type of treatment (e.g., therapy, medication, or psychotherapy), duration (e.g., day, week, or year), and frequency (e.g., daily, weekly, quarterly, yearly). User profile 170 may be stored and maintained in database 165 using one or more files (e.g., Extensible Markup Language (XML), Comma Separated Values ​​(CSV) delimited text files, or Structured Query Language (SQL) files). User profile 170 may be iteratively updated as the user provides responses and performs actions in connection with visual stimuli 175, auditory stimuli 180, or sessions.

[0048] The visual stimuli 175 may be or include stimuli or actions presented to the user as text, images, videos, or other visual presentations. For example, the visual stimuli 175 may include animations presented via the user interface 130 of the user device 110. The visual stimuli 175 may include images, such as photographs, digital images, art, diagrams, shapes, or other images. The visual stimuli 175 may include live, pre-recorded, or generated videos or animations, such as video recordings, animated short films, or animated images (e.g., graphic interchange format (GIF)). The visual stimuli 175 may include three-dimensional (3D) visual presentations, such as holograms, projected images, or other 3D visual media. The visual stimuli 175 may be of any size or orientation actionable by the user interface 130. The visual stimuli 175 may include text, such as words or sentences, presented to the user via the user interface 130. The visual stimuli 175 may include instructions for the user to perform an action to address a symptom associated with the condition. For example, the visual stimulus 175 may include text or graphics that depict an action that a user should take or perform in association with the visual stimulus 175 .

[0049] The visual stimuli 175 may include two or more stimuli that are text-based or image-based. In some embodiments, the two or more stimuli may be overlaid on one another to allow the user to focus on and understand one stimulus at a time. For example, two visual stimuli including text may be presented via the user interface 130. The two visual stimuli may be overlaid in such a way that the user may read both visual stimuli. The user may focus on one of the two visual stimuli to provide greater focus to that one visual stimulus. In some embodiments, one or more visual stimuli 175 may have a positive or neutral connotation and one or more other visual stimuli 175 may have a negative connotation. For example, a first visual stimulus may be a word or image that carries a positive association, such as "love" or an image of a smiling baby. A second visual stimulus may be a word or image that carries a negative association, such as "pain" or an image of a crying baby. In some cases, the second visual stimulus may be associated with the user's condition. For example, the second visual stimulus may include a word associated with the condition, such as "pain," and an image or video associated with the condition, such as an image of a person experiencing pain.

[0050] The auditory stimulus 180 may be or include a stimulus that is audibly presented to the user via the transducer 120 coupled to the user device 110. The auditory stimulus 180 may include pre-recorded sounds such as voices, musical instruments, natural sounds (e.g., rain or whale sounds). The auditory stimulus 180 may include computer-generated sounds such as MIDI tones, white noise, brown noise, or computer-generated voices or other computer-generated sounds. The auditory stimulus 180 may include live sounds such as from a radio station. The auditory stimulus 180 may be divided into multiple parts. The auditory stimulus 180 may include or be divided into multiple parts, where each part is a subset of the auditory stimulus. For example, a part may be a tone over a period of time, multiple tones over a period of time, or a frequency of a tone of the first auditory stimulus, among others. The auditory stimulus 180 may be parts played together or different parts at different times such as a musical pattern. In some embodiments, the stimuli can include music, words with various color and font options, word choices, binaural beats including alpha or beta wavelengths (e.g., wavelengths associated with a relaxed or resting state of mind), and vibrations of various frequencies other than music.

[0051] Additionally, identification information for the visual stimuli 175 and the auditory stimuli 180 can be stored and maintained in the database 165. For example, the database 165 can maintain the visual stimuli 175 using one or more structures or files (e.g., Extensible Markup Language (XML), Comma Separated Values ​​Format (CSV) delimited text files, Photographic Experts Joint Group (JPEG), or Structured Query Language (SQL) files). Each visual stimulus 175 can prompt the user to perform an action via the application 125. For example, the application 125 can receive instructions presenting an activity to be performed as part of the visual stimulus 175. The visual stimuli 175 can be used to provide therapy to reduce bias toward negative stimuli associated with a condition, symptoms of the condition, or other cognitive or behavioral effects of the condition. The visual stimuli 175 can be presented as a game, activity, or action performed by the user via the user interface 130. For example, one or more of the visual stimuli 175 can be presented as overlaid text prompting the user to select a visual stimulus 175 that does not have a negative association.

[0052] 2, a block diagram of a process 200 for presenting a stimulus and detecting a response identifying an interaction associated with the stimulus is depicted. The process 200 may include or correspond to operations performed in the system 100 for presenting multimodal stimuli to address symptoms associated with a medical condition. Under the process 200, the session manager 140 executing on the session management service 105 may access the database 165 to retrieve, fetch, or otherwise identify a user profile 170 of a user 210 (sometimes referred to herein as a subject, patient, or person) of the application 125 on the user device 110. The user profile 170 may identify or define information associated with the user 210, the instance of the application 125 on the user device 110, the user device 110, and the like. For example, the user profile 170 may identify that the user 210 has a particular bias toward negative stimuli, symptoms associated with the medical condition, or other cognitive or behavioral consequences resulting from the medical condition. The user profile 170 may, among other things, identify that the user 210 is taking medication to address the user's 210 medical condition or symptoms associated with the medical condition.

[0053] The session manager 140 can determine or identify a session for the user 210 to address symptoms associated with the condition. A session can correspond to, include, or define a set of stimuli presented to the user 210 via the application 125, such as visual stimuli 175 or auditory stimuli 180. Each stimulus can be an audio, visual, or tactile stimulus to address the user's condition. The session manager 140 can identify a session for addressing the user's condition associated with the user profile 170.

[0054] The user profile 170 may include information about the visual stimuli 175, the auditory stimuli 180, previous sessions (e.g., previous visual stimuli 175 identified for the user 210), performance associated with visual stimuli 175 already identified for the user 210, or taking of medication by the user 210 to address the user's condition, etc. The user profile 170 may also identify or include information about the recorded performance of bias, such as the number of occurrences of negativity bias, symptoms associated with the condition, the number of occurrences of engaging in bias for negative, positive, or neutral stimuli associated with the condition, the duration of previous occurrences, and taking of medication, among others. The user profile 170 may initially lack information about previous sessions and may build information as the user 210 participates in and engages in sessions via the application 125. The user profile 170 may be utilized to select one or more stimuli 175 to provide to the user 210 via the application 125 in a session.

[0055] The session manager 140 may initiate a session in response to receiving a request from the user 210 via the application 125. The user 210 may provide a request to initiate a session via the user interface 130 executing via the application 125. The request may include information related to the onset of the user's condition. The request may include, among other things, an identification of the user 210 or a user profile 170, symptoms associated with the user's 210 condition, a time of the request, or attributes associated with the condition, such as the severity of the condition. The application 125 running on the user device 110 may generate a session initiation request to send to the session management service 105 in response to the user's 210 interaction with the application 125. In some embodiments, the session manager 140 may initiate a session in response to a scheduled session time, in response to receiving a setting 205, or based on the user's 210 taking a medication prescribed to address the condition, among other things.

[0056] The session manager 140 can initiate a session in response to receiving preferences for conducting a session. The session manager 140 can identify one or more stimuli to present to the user 210 to address a condition based on input from the user 210, including settings 205 (also referred to herein as user settings 205). The user 210 can submit or provide the settings 205 before, during, or after a session provided by the session manager 140. In some embodiments, the user 210 can provide the settings 205 with a request to initiate a session. The user 210 can provide the settings 205 via the user interface 130. The user 210 can interact with the user interface 130 via UI elements 135 to provide input of settings 205 for the execution of the session, identification of visual stimuli 175, a time period available for the session, or a symptom or condition to be addressed during the session, etc.

[0057] The stimulus selector 145 executing on the session management service 105 can select or identify a set of visual stimuli 175 to present to the user 210 for a session. The stimulus selector 145 can select the visual stimuli 175 from the stimuli identified by the session manager 140. The stimulus selector 145 can select the visual stimuli 175 as part of a session for performing attention bias modification training (ABMT) on the user 210 suffering from a pathological condition. The set of visual stimuli 175 can include at least one visual stimulus 175A associated with the pathological condition. As part of the ABMT session, the stimulus selector 145 can select a first visual stimulus 175A and a second visual stimulus 175B for the user 210. Each visual stimulus 175 can correspond to or be associated with an action performed by the user 210 through the application 125 or the user device 110 itself. For example, a first visual stimulus 175A may be associated with a leftward tilt of the user device 110, and a second visual stimulus 175B may be associated with a rightward tilt of the user device 110.

[0058] The first visual stimulus 175A can be a visual stimulus associated with a pathology (e.g., threat-related, pathology-related, pain-related, or other negatively associated). Conversely, the second visual stimulus 175B can be a visual stimulus associated with a pathology (e.g., neutrally or positively associated). In some cases, the first visual stimulus 175A can be a negative stimulus associated with a pathology. For example, the first visual stimulus 175A can include text including negative words associated with a pathology, such as "pain," "tingling," "fear," or "tired." The first visual stimulus 175A can include an image associated with a pathology. For example, the first visual stimulus 175A can include an image of a sad or frowning face, an image of stormy rain clouds, or an image of a growling dog, etc. In some cases, the second visual stimulus 175B can be a positive or neutral stimulus. The second visual stimulus 175B may not be associated with a pathology. For example, the second visual stimulus 175B can include positive text including one or more words such as "happy," "good," "smile," or "love." The second visual stimulus 175B can include neutral text including one or more words such as "beach," "puppy," or "dinner." The second visual stimulus 175B can include a positive or neutral image. For example, the second visual stimulus 175B can be an image of a tree, a baby, or a bicycle.

[0059] In some embodiments, the stimulus selector 145 can select the visual stimuli 175 based on a user profile 170. The user profile 170 can include historical information related to the user's condition, such as the occurrence or type of symptoms, the time of symptom occurrence, the strength of bias toward negative stimuli associated with the condition, demographic information, prescription information, location information, etc. For example, the session manager 140 can identify visual stimuli 175 that the user 210 has historically associated positively to improve the user's bias toward negative stimuli.

[0060] In some embodiments, the stimulus selector 145 can identify a set of visual stimuli 175 based on user settings 205. The user settings 205 can indicate stimuli that the user prefers, such as a preferred color, font type, or type of visual stimulus 175 (e.g., image or video), among others. The user settings 205 can identify images, text, or other visual stimuli 175 that the user 210 associates with a medical condition. The user settings 205 can identify visual stimuli 175 that the user 210 associates positively or that distract thoughts from the condition. For example, the user 210 can select a type of visual stimulus 175 or provide guidance or criteria for the visual stimulus 175. The user settings 205 can inform preferred auditory stimuli 180. For example, the user settings 205 can identify sounds that the user 210 associates positively and sounds that the user 210 associates negatively. In this manner, the stimulus selector 145 can select auditory stimuli 180 that can act as positive reinforcement or negative reinforcement to the user 210 .

[0061] A user may provide user settings 205 to the session manager 140, or the session manager 140 may retrieve the user settings 205. A user 210 may provide the user settings 205, or the session manager 140 may retrieve the settings 205 from an external computing system, a clinician, or a library of pre-generated visual or auditory stimuli. The user settings 205 may include settings 205 as a file, such as a comma separated value file (CSV), a word document (DOC), a standard MIDI file (SMF), or an MP3, among others. The user settings 205 may be provided via input to an application 125 running on the user device 110.

[0062] The user settings 205 may include a list that identifies a set of visual stimuli. For example, the user settings 205 may include a list of words that are selected from an interface provided prior to the start of any session or as part of a start-up process when signing into the application 125. The visual stimuli 175 may be selected from a set of words or a list of words provided in the settings 205. The user 210 may provide, via the interface 130, a first set of words that are associated with a condition (or symptom) and a second set of words that are not associated with a condition (or symptom). The user 210 may provide, via the interface 130, a first set of words with positive associations and a second set of words with positive or neutral associations. The stimuli selector 145 may select a first visual stimulus 175A from the first set of words and a second visual stimulus 175B from the second set of words.

[0063] The user settings 205 may include properties of the auditory stimulus. The properties may include attributes associated with the auditory stimulus, such as volume, pitch, speed, tempo, compression, panning, bit rate, distortion, or timbre. For example, the user settings 205 may include a desired, maximum, or minimum volume for playback of the auditory stimulus 180. The user settings 205 may include preferred or non-preferred instruments, tempos, or pitches. The properties may include a desired sound selected by the user 210. For example, the user 210 may select a preferred song or a preferred genre of song to play as part of the auditory stimulus 180. The user 210 may select a disliked sound or song as part of the auditory stimulus 180.

[0064] In some embodiments, the stimulus selector 145 may identify the visual stimulus 175 or the auditory stimulus 180 based on a predefined schedule of stimuli. For example, the stimulus selector 145 may identify a first visual stimulus 175A as a visual stimulus associated with a pathology according to a predefined schedule of a task. In this illustrative example, the stimulus selector 145 may identify a second visual stimulus 175B based on a subsequent stimulus of the predefined schedule. For example, the predefined schedule of stimuli may include a first and a second stimulus corresponding to a visual stimulus, a third stimulus corresponding to an auditory stimulus, or a fourth stimulus corresponding to a tactile stimulus. The session manager 140 may define a schedule or time at which the stimulus selector 145 identifies or marks a stimulus for presentation. In some embodiments, the stimulus selector 145 may identify the visual stimulus 175 or the auditory stimulus 180 based on a set of rules. The rules may be configured to present a visual stimulus 175 or a set of visual stimuli 175 to target underlying causes or alleviate symptoms of a condition in the user 210 in a systematic, objective, and therapeutically effective manner. The rules may be based on the time of completion of an action associated with the visual stimuli 175, the user profile 170, the playback of the auditory stimuli 180, or other attributes of the system 100.

[0065] In some embodiments, the stimulus selector 145 can assign a type of interaction to each of the visual stimuli 175. The stimulus selector 145 may assign a first type of interaction to the first visual stimulus 175A and a second type of interaction to the second visual stimulus 175B. The type of interaction can be or include, among others, a manipulation of the user device 110, a touch or press on the user interface 130, or a speech to the user device 110. For example, the interaction can include the user 210 tilting the user device 110. For example, the interaction can include the user 210 pressing a button (of the UI element 135) presented by the application 125. In some embodiments, the first type of interaction associated with the first visual stimulus 175A can be related to a medical condition of the user 210. For example, the first type of interaction can include selecting a button of the UI element 135 corresponding to the first visual stimulus 175A when the user interface 130 presents the word "pain." In some embodiments, the second type of interaction associated with the second visual stimulus 175B may include disassociating the user from the condition. For example, the second type of interaction may include not pressing a button associated with the word "pain" or pressing a button associated with a positive second visual stimulus 175B, such as the word "happy."

[0066] Once the set of visual stimuli 175 is identified, the session manager 140 can provide, send, or otherwise transmit the visual stimuli 175 to the user device 110. In some embodiments, the session manager 140 can send instructions to the application 125 on the user device 110 to present the visual stimuli 175 via the user interface 130. The instructions can include, for example, a specification of which UI element 135 should be used and can specify content to be displayed on the UI element 135 of the user interface 130. The instructions can further specify or include the visual stimuli 175. The instructions can be code, data packets, or control means for presenting the visual stimuli 175 to the user 210 via the application 125 executing on the user device 110.

[0067] Subsequently, the instructions may include processing instructions for displaying a visual stimulus 175 on the application 125. The instructions may include processing instructions for playing a sound associated with the auditory stimulus 180, or instructions for activating a haptic system of the user device 110. The instructions may also include instructions for the user 210 to execute in association with his or her session. For example, the instructions may display a message instructing the user 210 to take a medication associated with the session. The visual stimulus 175 may include text, an image, or a video presented by the user device 110 via the application 125. For example, the visual stimulus 175 may include the presentation of an image instructing the user 210 to interact with the application 125 via the user interface 130.

[0068] An application 125 on the user device 110 can render, display, or otherwise present a set of visual stimuli 175. The visual stimuli 175 can be presented via one or more UI elements 135 of a user interface 130 of the application 125 on the user device 110. The presentation of the UI elements 135 can be according to instructions provided by the session manager 140 to present the visual stimuli 175 to the user 210 via the application 125. In some embodiments, the application 125 can render, display, or otherwise present the visual stimuli 175 independent of the session management service 105. The application 125 can share functionality with or have the same functionality as the session manager 140, the stimuli selector 145, or other components of the session management service 105, as described above. For example, the application 125 can maintain a timer that tracks the time elapsed since the presentation of a previous visual stimuli 175. The application 125 can compare the elapsed time to a time limit for the visual stimuli 175. If the elapsed time exceeds the time limit, the application 125 may determine to present a visual stimulus 175. The application 125 may also use a schedule to determine when to present one or more visual stimuli 175. The application 125 may present the visual stimuli 175 for display via the user interface 130 on the user device 110.

[0069] The application 125 may display, render, or otherwise present the visual stimuli 175A and 175B at least partially in the same location on the user interface 130 of the user device 110. The same location may refer to a location on a display (e.g., the user interface 130) that presents at least a portion of the visual stimulus 175A overlapping at least a portion of the visual stimulus 175B. For example, the visual stimuli 175A and 175B may overlap in whole or in part. The visual stimuli 175A and 175B may overlap with varying opacity. The opacity may refer to the transparency of the visual stimulus 175A. In some cases, the opacity of the first visual stimulus 175A may be greater than the opacity of the second visual stimulus 175B such that the first visual stimulus 175A entirely covers the second visual stimulus 175B for the overlapping portions of the visual stimuli 175A and 175B, respectively. In some cases, the opacity of the first visual stimulus 175A may be equal to or sufficiently similar to the opacity of the second visual stimulus 175B such that both the first visual stimulus 175A and the second visual stimulus 175B are visible or legible while presented on the user interface 130 by the application 125. In the presentation of the overlapping visual stimuli 175A and 175B, the opacity may be varied. For example, during a first period, the opacity of the first visual stimulus 175A may be greater than the opacity of the second visual stimulus 175B, and during a second period, the opacity of the first visual stimulus 175A may be less than the opacity of the second visual stimulus 175B.

[0070] In some embodiments, the application 125 may display, render, or otherwise present the visual stimuli 175A and 175B for different time periods. The application 125 may present the first visual stimulus 175A for a first time period and the second visual stimulus 175B for a second time period. For example, the application 125 may present the first visual stimulus 175A during a first time period and then present the second visual stimulus 175B during a second time period. In some cases, the application 125 may delay the presentation of the second visual stimulus 175B after displaying the first visual stimulus 175A. The application may present the visual stimuli 175A and 175B simultaneously. The simultaneous presentation of the visual stimuli 175A and 175B may refer to displaying the visual stimuli 175 during a simultaneous time period or displaying the visual stimuli 175 at the same display location on the user interface 130. A concurrent period may refer to a first period and a second period overlapping in whole or in part. For example, the presentation of the first stimulus 175A may overlap in time with the presentation of the second stimulus 175B. The application 125 may present the visual stimuli 175A and 175B for the same or different periods. For example, a first period associated with the first visual stimulus 175A may be the same or equivalent to a second period associated with the second visual stimulus 175B.

[0071] In some embodiments, the application 125 may present the visual stimulus 175 simultaneously with another type of stimulus. For example, the application 125 may display the visual stimuli 175A and 175B simultaneously with the auditory stimulus 180. The application 125 may display one or more of the visual stimuli 175 for a first period of time without the auditory stimulus 180. The application 125 may display one or more of the visual stimuli 175 for a second period of time simultaneously with one or more of the auditory stimuli 180. The application 125 may present all or a portion of the auditory stimulus 180, such as presenting some portions of the auditory stimulus 180 as described herein. In other cases, the application 125 may present the visual stimulus 175 simultaneously with other types of stimuli, such as tactile stimuli. For example, the application 125 may present the first visual stimulus 175A while activating the user device 110 to cause a vibration, buzzer, or other tactile stimulus to the user 210.

[0072] The application 125 can display the visual stimuli 175A and 175B to prompt the user 210 to interact with the display. The visual stimuli 175A and 175B can include prompts to the user 210 to perform actions associated with the stimuli 175A and 175B. The actions can be or include an interaction 220 from the user 210 associated with the presentation of the visual stimuli 175. The interaction 220 can include actions such as physically manipulating the user device 110, activating a UI element 135, or viewing a video or image of the visual stimuli 175, among others. The interaction 220 can include actions such as moving, tapping, sliding, nodding, shaking, tilting, or orienting the user device 110 toward one side of the device. A side of the user device 110 can refer to a boundary formed by the user interface 130 associated with the user device 110, e.g., one side of a rectangular screen. One or more sides of the client can be associated with the first visual stimulus 175A. In some embodiments, the user 210 may perform an interaction 220 to tilt the user device 110 toward the side of the user device 110 that corresponds to the first visual stimulus 175A.

[0073] The interactions 220 can include actions such as touching, pressing, or otherwise activating a UI element 135 of the user interface 130 associated with at least one of the first stimulus 175A or the second stimulus 175B. For example, the user 210 can perform one or more interactions 220 via an application 125 running on the user device 110 by activating one or more of the UI elements 135 as described herein. The user 210 can perform the interactions 220 by pressing a button associated with the application 125 and displayed via the user interface 130. In some embodiments, one or more first UI elements 135A can be associated with the first visual stimulus 175A, and one or more second UI elements 135B can be associated with the second visual stimulus 175B. In this illustrative example, the user 210 can perform the interaction 220 associated with the first visual stimulus 175A by touching, tilting, nodding, swiping, tapping, or otherwise engaging with the first UI element 135A. Similarly, the user 210 may interact 220 with the second visual stimulus 175B by engaging with or manipulating the second UI element 135B.

[0074] An interaction 220 can include a series of actions that are performed sequentially or simultaneously. For example, an interaction 220 can include manipulating the user device 110 and pressing a UI element 135. The manipulation of the user device 110 and the pressing of the UI element 135 can be performed simultaneously as part of the same interaction 220, or can be performed sequentially as part of the same interaction 220. For example, the user 210 can tilt the user device 110 and press the UI element 135 simultaneously, or the user 210 can first tilt the user device 110 and then press the UI element 135. The application 125 may present one or more visual cues 175 via the user interface 130 to prompt the user 210 to perform an interaction 220 .

[0075] The presentation of the stimuli via the user interface 130 can include presenting the first visual stimulus 175A with a first indicator to identify the first type of interaction 220, and presenting the second visual stimulus 175B with a second indicator to identify the second type of interaction 220. The indicator can include a visual presentation such as text or color. For example, the indicator can include a green highlight on the first visual stimulus 175A and a red highlight on the second visual stimulus 175B to indicate that the user 210 should select the first visual stimulus 175A. As another example, the indicator can include text instructing the user 210 on the type of interaction 220 to perform, such as text that means "Tip toward the positive stimulus" or "Don't press the positive stimulus." Each visual stimulus presented by the application 125 can include an indicator. For example, the first visual stimulus 175A can include an indicator that indicates "Choose this one!" and the second visual stimulus 175B can include an indicator that indicates "Don't choose this one!".

[0076] In some embodiments, the indicator may include a timer. For example, the application 125 may present a timer as an indicator for the presentation of the visual stimulus 175 or for a countdown to the performance of the interaction 220. In some embodiments, the indicator may generate an audio tone prompting the user 210 to perform a specified interaction with the visual stimulus 175. For example, a first indicator may include a beep emitted from the user device 110 via the speaker and transducer 120 to indicate to the user 210 that they should interact with the first visual stimulus 175A. A second indicator may include a beep of a different (e.g., tone, duration, pitch, volume) emitted from the user device 110 via the speaker and transducer 120 to indicate to the user 210 that they should interact with the second visual stimulus 175B.

[0077] The application 125 can monitor at least one interaction 220 with the visual stimulus 175. The application 125 can perform the monitoring during a session in response to the presentation of the visual stimulus 175 or in response to the reception of the interaction 220. The application 125 can monitor the reception of the interaction 220. The application 125 can monitor the interaction 220, for example, via the user interface 130 or via a sensor associated with the user device 110. The application 125 can receive multiple interactions 220 during a session. For example, the application 125 can monitor a series of interactions 220 performed by the user 210 during a session. The application 125 can monitor and record information related to the received interactions 220. For example, the application 125 can monitor and record the time of the interaction 220, the duration of the interaction 220, the order of the multiple interactions 220, the visual stimuli 175 associated with the interaction 220, and / or the delay between the presentation of the visual stimuli 175 and the interaction 220, etc.

[0078] As the user 210 performs the interaction 220, the application 125 may generate at least one response 215. The response 215 may identify the interaction 220. The response 215 may include information about the interaction 220, such as a duration of the interaction 220, a time of the interaction 220, a visual stimulus 175 associated with the interaction 220, and / or a delay between the presentation of the visual stimulus 175 and the interaction 220. The application 125 may generate the response 215 for transmission to the session management service 105. The response 215 may be in a format readable by the session management service, such as an electronic file readable by the session management service or a data packet readable by the session management service 105.

[0079] The response handler 150 can receive, identify, or otherwise detect a response 215 identifying an interaction 220. The response handler 150 can receive the response 215 from the application 125. The response handler 150 can receive the response 215 at scheduled time intervals or when an interaction 220 occurs during a session. The response handler 150 can query or ping the application 125 for a response 215. The response handler 150 can receive multiple responses 215 during a period of time. For example, the response handler 150 can receive a first response 215 indicating a first interaction 220 and a second response 215 indicating a second interaction 220.

[0080] The response handler 150 can store the response 215, including the interaction 220, in the database 165. The response handler 150 can store information related to the response 215, including a time of the response 215, an action associated with the interaction 220, a user profile 170 associated with the response 215, and a visual stimulus 175 associated with the response 215, etc. The response 215 can include or identify an interaction 220 by the user 210 with the visual stimulus 175A or 175B. The response 215 can include a time taken to complete the task. For example, the response 215 can include that the user spent 4 minutes performing the action associated with the presentation of the visual stimulus 175. The response 215 can include a total time for the completion of the session to be completed, and can also include a start time of the session and a completion time of the session. The response 215 can include UI elements 135 interacted with during the presentation of the visual stimulus 175. For example, the response 215 may include a list of buttons, toggles, or other UI elements 135 selected by the user 210 at a specified time during the presentation of the visual stimuli 175. The response 215 may also include other information, such as the location of the user 210 while performing the session, such as geolocation, IP address, GPS location, or triangulation with cellular towers. The response 215 may also include measurements, such as measurements of time, location, or user data.

[0081] Referring now to FIG. 3, a block diagram of a process 300 for generating an auditory stimulus and playing an auditory stimulus to provide feedback is depicted. The process 300 may include or correspond to operations performed in the system 100 or the process 200. Under the process 300, the performance evaluator 155 may evaluate the response 215 to generate a response score 305. The feedback provider 160 may generate or select a stimulus according to the response score 305 to provide feedback. The session manager 140 may send the feedback to the application 125 for presentation to the user 210. The presentation of the visual stimulus 175 or the auditory stimulus 180 may be based on a previous visual stimulus 175, a user profile 170, a response 215, or a decision by the performance evaluator 155.

[0082] The performance evaluator 155 can calculate, generate, or otherwise determine a response score 305 associated with the response 215 based on the interaction 220 with the visual stimuli 175. The response score 305 can indicate a level of correctness, or conversely, a level of error, associated with the response 215. A high response score 305 can be correlated, for example, with a high level of correctness in selecting a visual stimulus 175 that is not associated with a bias toward a pathology. A low response score 305 can be correlated, for example, with a low level of correctness (e.g., a high level of error) in selecting a visual stimulus 175 that is not associated with a bias toward a pathology. For example, a low response score 305 can indicate that the user 210 is more likely to select a first visual stimulus 175A associated with a negative stimulus or associated with the user's pathology.

[0083] In determining the response score 305, the performance evaluator 155 can evaluate the response 215 based on the interaction 220. The response 215 can be correct, incorrect, or indeterminable. In some embodiments, the second visual stimulus 175B can be or include a stimulus to wean the user 210 away from the pathology. The user 210 can engage in an interaction 220 related to weaning the user 210 away from the pathology. For example, the user 210 can select the second visual stimulus 175B with the application 125 using the UI element 135. The user 210 can click, select, touch, or otherwise indicate a preference or selection for the second stimulus 175B through the interaction 220. The interaction 220 can indicate a selection or preference for the second visual stimulus 175B.

[0084] The performance evaluator 155 can identify or determine whether a response 215 by the user is correct or incorrect based on the selected visual stimulus 175. The response 215 can be correct if a dialogue 220 corresponding to the response 215 is associated with the second visual stimulus 175B. The performance evaluator 155 can determine that the response 215 is correct if the response 215 is associated with a dialogue 220 corresponding to the visual stimulus 175 that distracts thoughts from the condition. The performance evaluator 155 can determine that the response 215 including the dialogue 220 is correct.

[0085] The performance evaluator 155 can determine the response 215 as correct if the interaction 220 indicates a bias toward positive or neutral stimuli. In some embodiments, the interaction 220 can be associated with a positive or neutral visual stimulus 175B. For example, the interaction 220 can include a selection of a positive or neutral visual stimulus 175B. The positive or neutral stimulus 175B can include positive or neutral images, text, videos, or the like that are not related to the user's 210 condition or negative stimuli.

[0086] Conversely, the performance evaluator 155 may determine the response 215 as incorrect if the interaction 220 associated with the response 215 is an interaction with a first stimulus 175A associated with a medical condition. In some embodiments, the interaction 220 may be associated with a negative stimulus or a stimulus associated with the user's medical condition. For example, the interaction 220 may include selecting, orienting, sliding, or tilting the user device 110 toward the negative visual stimulus 175A. The negative visual stimulus 175A may include negative images, text, or videos, etc. The negative visual stimulus 175A may be related to the user's 210 medical condition. For example, the negative visual stimulus 175A may include a symptom or emotion associated with the medical condition presented as text, such as "pain" or "sadness."

[0087] Based on whether the response 215 is correct or incorrect, the performance evaluator 155 may calculate, generate, or otherwise evaluate a response score 305 of the user 210 based on the interaction 220 associated with the response 215. For example, the performance evaluator 155 may set the response score 305 for a given response 215 as "1" if correct and "-1" if incorrect. In some embodiments, the performance evaluator 155 may identify a response time or correctness of the user 210 in selecting a visual stimulus 175. For example, the performance evaluator 155 may determine from the response 215 that the user 210 has not performed one or more actions indicated by the visual stimulus 175 or that the user 210 has not performed an action within a threshold time. The threshold time may correspond to or be defined as an amount of time that the user 210 is expected to interact with one of the visual stimuli 175, and may range from 5 seconds to 10 minutes. This determination may cause the performance evaluator 155 to modify or adjust the response score 305 using the response time compared to the threshold time.

[0088] In some embodiments, the performance evaluator 155 may determine the degree of adherence of the user 210. The degree of adherence of the user 210 to a session may be based on the user's 210 response time to the presentation of the visual stimuli 175 being above or below a threshold time. For example, if the user 210 takes too long to perform the interaction 220, the user 210 may not be fully participating or following the session. The degree of adherence of the user 210 may be based on the responses 215 given by the user via the UI elements 135 while engaging and participating in the session. For example, if the user 210 presses a button presented by the application 125 during the session at an incorrect time or at a time not instructed to press the button, the degree of adherence of the user 210 may be low. Conversely, if the user 210 performs the correct interaction 220 within a threshold period of time and performs a threshold number of actions in accordance with the presented visual stimuli 175, the degree of adherence of the user 210 may be high.

[0089] In some embodiments, the performance evaluator 155 may calculate, generate, or otherwise determine a response score 305 related to the likelihood of overcoming the bias for negative stimuli. The likelihood of overcoming the bias for negative stimuli may refer to, include, or relate to the probability that the user 210 will not pay attention to stimuli associated with the condition. For example, if the user 210 successfully ignores the negative stimuli associated with the condition every time the negative stimuli are presented to the user 210 via the application 125, the user 210 may be said to have 100% of the time overcoming the bias for negative stimuli. The likelihood of overcoming the bias for negative stimuli may include a threshold number of occurrences of the bias. For example, the performance evaluator 155 may not determine the likelihood until a threshold number of occurrences of the negative stimuli is raised or a threshold number of interactions 220 are performed by the user 210. The performance evaluator 155 may determine the likelihood of overcoming the bias for negative stimuli based at least on the selection of UI elements 135 during the session, the user profile 170, or the time of the session, among others.

[0090] In some embodiments, the performance evaluator 155 can calculate, generate, or otherwise determine a response score 305 associated with an increase in mental acuity or a decrease in fatigue of the user 210. The performance evaluator 155 can determine the response score 305 based on a delay time between the presentation of the visual stimulus 175 and the receipt of the interaction 220. For example, the delay time between the subsequent presentation of the visual stimulus 175 and the receipt of the interaction 220 may decrease. This decrease in delay time may indicate an increase in mental acuity or a decrease in fatigue. The performance evaluator 155 can ask the user 210, via the application 125, an indication of the user's mental state. For example, the performance evaluator 155 can present the user 210, via the user interface 130, with a question asking about a perceived level of mental acuity or fatigue. The performance evaluator 155 can generate a response score 305 associated with mental acuity or fatigue based on a response by the user 210 to the question.

[0091] In conjunction, the feedback provider 160 may generate, output, or otherwise generate feedback for receipt by the user 210 via the application 125 operating on the user interface 130. The feedback provider 160 may generate feedback based on at least the response score 305, the user profile 170, the response 215, or historical stimulus presentation. The feedback may include text, video, or audio presented to the user 210 via the application 125 displayed via the user interface 130. The feedback may include one or more visual stimuli 175 or one or more auditory stimuli 180. The feedback may include presentation of the response score 305. The feedback may display messages such as motivational messages, suggestions to improve performance, congratulatory messages, comforting messages, etc. In some embodiments, the feedback provider may generate such feedback during a session being performed by the user 210.

[0092] Based on the response 215, the feedback provider 160 can generate the auditory stimulus 180A to include one or more portions 310A-N (hereinafter generally referred to as portions 310) to indicate feedback based on the response 215. The feedback provider 160 can generate the auditory stimulus 180 including the portions 310 based on the response score 305 or the settings 205, etc. In generating the stimulus, the feedback provider can generate portions 310 of the audio of the auditory stimulus 180. The portions 310 can be multiple sections, divisions, tones, or other such subsets of the auditory stimulus 180. In some embodiments, the first portion 310A of the auditory stimulus 180 can be an audio over a first period of time. For example, the first portion 310A can be or include the first two seconds of the auditory stimulus 180. In some embodiments, the first portion 310A of the auditory stimulus 180 can be a tone of the auditory stimulus 180. For example, the first portion 310A can be or include a B-flat musical tone. In some embodiments, the first portion 310A of the auditory stimulus 180 can be or include a musical portion, such as that represented by a musical score. For example, the first portion 310A can be or include a violin score or a soprano score, while the entire auditory stimulus 180 includes a complete musical score, such as a violin score, a soprano score, and a piano score.

[0093] In generating portion 310 of auditory stimulus 180, feedback provider 160 may identify or access recorded sounds or music. Feedback provider may draw from, retrieve, or access a library of pre-recorded sounds or music. Feedback provider may generate recorded sounds through a microphone of user device 110. Feedback provider 160 may generate auditory stimulus 180 from pre-recorded sounds or recorded sounds or music. Feedback provider 160 may generate auditory stimulus 180 by generating tones via user device 110, such as by a MIDI file associated with auditory stimulus 180. Feedback provider 160 may generate electronic sound files or files used to generate sounds, such as MIDI, MP3, WAV, etc.

[0094] Based on whether the response 215 is correct or incorrect, the feedback provider 160 can generate an auditory stimulus 180 indicative of the feedback. The feedback can provide a positive reinforcement or a negative reinforcement to the user 210 depending on the response 215 from the user 210. If the response 215 is determined to be correct, the feedback provider 160 can generate the auditory stimulus 180 for providing the positive reinforcement. To provide the positive reinforcement, the feedback provider 160 can insert, supplement, or otherwise add at least one portion 310 to the auditory stimulus 180. In some embodiments, the feedback provider 160 can generate or select a first portion 310A indicative of the positive feedback to provide to the user 210 based on the response score 305 being equal to or greater than a threshold score. For example, if the response score 305 associated with the user 210 for a session is above a threshold score, the feedback provider 160 can generate a first portion 310A for playing to the user for encouraging or providing positive reinforcement to the user. In some embodiments, the feedback provider 160 can change, adjust, or otherwise modify (eg, increase) the volume of the auditory stimulus 180 to provide positive reinforcement.

[0095] Conversely, if the response 215 is determined to be incorrect, the feedback provider 160 can generate the auditory stimulus 180 to provide a negative attenuation. To provide a negative attenuation, the feedback provider 160 can delete, remove, or otherwise remove at least one portion 310 from the auditory stimulus 180. In some embodiments, the feedback provider 160 can generate or select a second portion 310B indicating negative feedback to provide to the user 210 if the response score 305 is less than the threshold score. In some embodiments, the feedback provider 160 can change, adjust, or otherwise modify (e.g., decrease) the volume of the auditory stimulus 180 to provide a negative attenuation. The generation of positive reinforcement or negative attenuation can be used in conjunction with ABMT sessions to reduce a user's bias toward negative stimuli associated with their condition.

[0096] In some embodiments, the feedback provider 160 can provide the preferred portion or additional portion when the response 215 is correct or associated with a correct interaction 220 to give the user 210 positive reinforcement in correcting a bias toward negative stimuli associated with a pathology. The user 210 can select or indicate the preferred portion 310 or the auditory stimulus 180 as one or more items of the settings 205. The feedback provider 160 can provide the preferred portion 310A in response to receiving a response 215 indicating that the user 210 has performed a correct interaction 220 (e.g., an interaction 220 associated with a positive visual stimulus 175B or not associated with a pathology). The feedback provider 160 may provide the preferred portion 310A in response to the response score 305 being equal to or greater than a threshold score.

[0097] In some embodiments, the feedback provider 160 can provide an unfavorable portion for inclusion in the auditory stimulus 180 if the response 215 is incorrect or associated with an incorrect interaction 220. The feedback provider 160 can provide this unfavorable portion to provide a negative attenuation to the user 210 in correcting a bias toward negative stimuli associated with a pathological condition. The user 210 can select or indicate the unfavorable portion 310 or the auditory stimulus 180 as one or more items of the settings 205. The feedback provider 160 can provide the unfavorable portion 310B in response to receiving a response 215 indicating that the user 210 has engaged in an incorrect interaction 220 (e.g., a negative visual stimulus 175A or an interaction 220 associated with a pathological condition). In this manner, the feedback provider 160 can provide a negative attenuation to the user 210 when providing an incorrect response or when the response score 305 falls below a score threshold.

[0098] With respect to successive responses, the feedback provider 160 may transmit, communicate, or otherwise give feedback to the user 210 by adding or removing different portions 310 of the auditory stimulus 180. Upon receiving an incorrect response, the feedback provider 160 may remove the preferred portion 310a from playback to the user 210. Similarly, in response to a correct response 215 or a response score 305 being equal to or greater than a score threshold, the feedback provider 160 may provide the preferred portion 310A, remove the non-preferred portion 310B, or combine them. As the user 210 provides more correct responses 215 or as the response score 305 increases, the feedback provider 160 may provide additional preferred portions 310 for playback to the user 210. The additional preferred portions 310 may be played simultaneously. The simultaneous playback of the preferred portions 310 may generate a song, such as a favorite song indicated by the user 210 in the settings 205. In this manner, the feedback provider 160 can present the auditory stimulus 180A including the preferred portion for positive reinforcement. Similarly, the feedback provider 160 can add the non-preferred portion 310 to the auditory stimulus 180A for negative reinforcement in response to an incorrect response 215 or a response score 305 below a threshold score. In this manner, the user 210 can be presented with a non-preferred song based on the response 215 for negative reinforcement.

[0099] In some embodiments, the feedback provider 160 can generate an auditory stimulus 180 for playback to the left and right ears of the user 210. The auditory stimulus 180 can include stereo audio having different portions 310 played to the left and right ears. The feedback provider 160 can identify or select different portions 310 for playback to each ear of the user 210. In some embodiments, the portions 310 can be selected by the feedback provider 160 to achieve binaural perception by the user 210. For example, the feedback provider 160 can generate a first portion 310A including a tone with a frequency of 415 Hz and a second portion 310B including a tone with a frequency of 400 Hz to generate a binaural beat. A binaural beat can be provided via the auditory stimulus 180 to address fatigue associated with a condition of the user 210 (e.g., multiple sclerosis or cancer). The feedback provider 160 may play the first portion 310A to the left ear of the user 210 using a first speaker and the second portion 310B to the right ear of the user 210 using a second speaker.

[0100] In some embodiments, the feedback provider 160 can generate the auditory stimuli 180 based on a user profile 170. The user profile 170 can include a historical association between previously presented auditory stimuli 180 and previous responses 215. For example, the user profile 170 can indicate that the auditory stimulus 180A has historically produced a higher response score 305 for the user 210 during the session. For example, the user profile 170 can indicate that the auditory stimulus 180A has historically correlated with inaccurate responses 215.

[0101] In some embodiments, the feedback provider 160 can generate the auditory stimulus 180 based on the user settings 205. The user settings 205 can include properties of the auditory stimulus 180. The user 210 can provide preferred or unpreferred auditory stimuli 180 via the application 125. For example, the user 210 can indicate a preferred song or an unpreferred instrument. The feedback provider 160 can generate the auditory stimulus 180 for positive reinforcement feedback from the preferred auditory stimuli 180 provided by the user 210 in the settings 205. Similarly, the feedback provider 160 can generate the auditory stimulus 180 for negative attenuation feedback from the unpreferred auditory stimuli 180 provided by the user 210 in the settings 205.

[0102] In some embodiments, the feedback provider 160 can present one or more of the portions 310 at least partially concurrently with the presentation of the visual stimulus 175 by the stimulus selector 145. The feedback provider 160 can present one or more of the portions 310 at least partially concurrently with the presentation of the visual stimulus 175. For example, the feedback provider 160 can present the first portion 310A via a speaker coupled to the user device 110 while the application 125 is presenting the visual stimulus 175. The feedback provider 160 can present the one or more portions 310 in association with the visual stimulus 175. For example, the first visual stimulus 175A can correspond to the first auditory stimulus 180.

[0103] Once the auditory stimulus 180 is generated, the feedback provider 160 can send, transmit, or otherwise provide the auditory stimulus 180 to the application 125. The auditory stimulus 180 can be provided to the application 125 on the user device 110 in the form of an audio file (e.g., MPEG, FLAC, WAV, or WMA format) or as part of an audio stream (e.g., as MP3, AAC, or OGG format). In some embodiments, the feedback provider 160 can send, transmit, or otherwise provide visual feedback for presentation via the application 125 during the session or after receiving a response 215. For example, the response score 305 can indicate that the user 210 performing in the session is below a threshold correctness. The feedback provider 160 can generate feedback associated with a low response score 305, such as a motivational message that includes the response score 305. The feedback provider 160 can send the auditory stimulus 180 as part of the feedback. The feedback provider 160 can present feedback including an auditory stimulus 180 via an application 125 running on the user device 110 .

[0104] The application 125 can present, generate, or otherwise play the auditory stimulus 180 via one or more transducers 120 on the user device 110. The application 125 can generate a signal, packet, electronic file, or the like for playing via one or more speakers coupled to the user device 110. The application 125 can send a signal to the transducer 120 including instructions to play the auditory stimulus 180. The application 125 can play the auditory stimulus 180 via the transducer 120. The transducer 120 can include or be coupled to one or more speakers. In some embodiments, the application 125 can provide the auditory stimulus 180 to the transducer 120 for playing via one or more speakers by generating a signal including the auditory stimulus 180 that is received by the transducer 120. The transducer 120 can convert the signal into mechanical vibrations via the speaker to generate the sound of the auditory stimulus 180 for playing to the user 210.

[0105] The application 125 can play stereo audio of the auditory stimulus 180 to different ears of the user 210. For example, the transducer 120 can play a first portion 310A of the auditory stimulus 180 to a first ear and a second portion 310B of the auditory stimulus 180 to a second ear through two speakers. The transducer 120 can be coupled to one or more speakers or can be configured to activate one or more speakers. A signal including the auditory stimulus 180 can instruct the transducer 120 to play the first portion 310A to the first speaker and the second portion 310B to the second speaker.

[0106] For presenting the next stimulus (e.g., a subsequent round or session), the session manager 140 can identify or select a difficulty level to associate with the visual stimuli 175′A and 175′B (referred to herein as visual stimuli 175′). The level can be a level, score, or descriptor assigned by the stimulus selector 145 to determine the presentation of the visual stimuli 175′. For example, the level can correspond to “easy”, “medium”, or “difficult”, or the level can correspond to a numerical value, a title, or a duration, etc. The level can correspond to a duration. For example, a first level can include a first duration, and a second level can include a second duration. The level can define one or more characteristics for presenting the visual stimuli 175′. The characteristics can direct the presentation of the stimuli 175′. For example, the characteristics can be visual features defined by the level that affect the display of the visual stimuli or affect the selection of the visual stimuli. For example, a first visual stimulus 175'A may correspond to an "easy" level and thereby have a different presentation than a first visual stimulus 175'A corresponding to a "difficult" level. The presentation of the visual stimuli 175' may vary depending on the assigned level. It may be considered that the set of visual stimuli in the interface illustrated in FIG. 5 corresponds to a relatively easy level, while the set of visual stimuli in the interface illustrated in FIG. 6 corresponds to a relatively difficult level.

[0107] To identify or select a level of visual stimuli 175', the session manager 140 may use response time, response score 305, or correctness of the response 215, or the like. Response time may correspond to a delay between the presentation of the visual stimuli 175' and the receipt of the response 215, or performance of the interaction 220. For example, the session manager 140 may select a higher or more difficult level that corresponds to a response time below a threshold level. The session manager 140 may select a level to include more stimuli 175' or fewer stimuli 175' if the correctness of the previous response 215 is below a threshold or specified correctness.

[0108] In some embodiments, the session manager 140 can select a level to associate with the visual stimulus 175' based on the response score 305. For example, the session manager 140 can select a more difficult level to associate with the visual stimulus 175' if the response score 305 is above a threshold. For example, the session manager 140 can select an easier level to associate with the visual stimulus 175' if the response score 305 is below a threshold. In some embodiments, the performance evaluator 155 can select a level based on the reaction time and correctness of any previous responses 215. In this manner, more difficult visual stimuli 175' can be presented to the user 210 to facilitate the user's progress in the ABMT session.

[0109] In some embodiments, the session manager 140 may select a level based on the degree of adherence of the user 210. If the user 210 has a high degree of adherence to the session, the session manager 140 may select a higher level for the subsequent visual stimulus than that associated with the previously presented visual stimulus. Conversely, if the user 210 during the session showed a low degree of adherence to a level in the previously presented visual stimulus 175', the session manager 140 may select the same level for the subsequent visual stimulus. The session manager 140 may determine to select or modify the level of the stimulus 175' using any combination of the visual stimulus 175', the user profile 170, the responses 215, the response scores 305, or the interactions 220.

[0110] In some embodiments, the session manager 140 may select a level based on a previous presentation of the visual stimulus 175'. The session manager 140 may select a level based on a previous presentation, such as a visual, auditory, or tactile stimulus. For example, the session manager 140 may select a level based on a user's failure to make a correct interaction 220 with a previously presented visual stimulus 175'. The session manager 140 may select a level based on a response score 305. For example, if the response score 305 associated with the session is less than a threshold score, the session manager 140 may assign an easier level to a subsequent presentation of the visual stimulus 175'.

[0111] Once the level is determined, the stimulus selector 145 can modify the presentation of the visual stimulus 175' based on the level for the visual stimulus 175'. The stimulus selector 145 can modify the presentation of the first stimulus 175'A, the second stimulus 175'B, a subsequent visual stimulus, or a combination thereof. The stimulus selector 145 can provide instructions to the application 125 regarding the display of the visual stimulus 175'. The stimulus selector 145 or the application 125 can modify the presentation of the visual stimulus 175' during the presentation of the visual stimulus 175' or after the presentation of the visual stimulus 175'. For example, the stimulus selector 145 can modify the presentation of the first visual stimulus 175'A presented on the user interface 130 by the application 125. For example, the stimulus selector 145 can modify the presentation of the subsequent visual stimulus 175' during the same session or during a subsequent session.

[0112] The stimulus selector 145 can modify the visual stimuli 175′ using one or more visual characteristics associated with the assigned level. For example, a first level of “easy” can include a first characteristic indicative of an opacity of the first visual stimulus 175′A. A second level of “difficult” can include a second characteristic indicative of an opacity of the second visual stimulus 175′B. In some embodiments, the opacity associated with the second level can be less legible or distinguishable by the user 210 than the opacity associated with the first level. That is, the first stimulus 175′A having an “easy” level can be more legible, readable, or distinguishable than the second stimulus 175′B having a “difficult” level. In this manner, one or more overlapping visual stimuli associated with the “easy” level can be more distinguishable by the user 210 than one or more visual stimuli associated with the “difficult” level.

[0113] Interacting 220 with the visual stimuli 175' may cause the stimuli selector 145 to iteratively modify the presentation of the visual stimuli 175' based on the response score 305 and the level determined by the session manager 140. As an illustrative example, the user 210 may interact 220 tilting the user device 110 in response to the visual stimuli 175'. As the user 210 tilts the user device 110 toward a word associated with the first visual stimulus 175'A and away from a word associated with the second visual stimulus 175'B, the word associated with the first visual stimulus 175'A may become more prominent or opaque and the word associated with the second visual stimulus 175'B may become less prominent or visible. The visual stimuli 175' may be altered in other ways. For example, in response to a change in a characteristic of the level by the session manager 140, the image or word associated with the visual stimuli 175' may change color, size, font, opacity, position, alignment, or the like. In this manner, the presentation of the visual stimuli 175 ′ can be repeatedly changed depending on the responses 215 provided by the user 210 .

[0114] The session management service 105 may repeat the above-described functions (e.g., processes 200 and 300) over multiple sessions. The number of sessions may span a set number of days, weeks, or years, or may have no clear end point. By repeatedly providing visual and auditory stimuli based on at least the response score 305, the user profile 170, the responses 215, or the settings 205, the user 210 may receive content that helps to mitigate bias toward stimuli associated with a condition. This may mitigate symptoms faced by the user 210 even when suffering from a condition that may otherwise inhibit the user from seeking treatment or even physically accessing the user device 110. Additionally, the quality of human-computer interaction (HCI) between the user 210 and the user device 110 may be improved from participating in sessions presented via the user interface 130 of the application 125.

[0115] The user 210 may be more likely to participate in the session when the visual stimuli 175' are presented via the user device 110 because the visual stimuli 175' are related to the user's condition (e.g., cancer, MS, other chronic conditions) and associated with symptoms resulting from attention bias due to the condition. This reduces unnecessary consumption of the service and the computational resources (e.g., processing and memory) of the user device 110 and reduces network bandwidth usage compared to sending unnecessary or unimportant visual stimuli 175'. Furthermore, in the context of digital therapeutic applications, the selection of such visual stimuli 175' tailored to the individual's circumstances may provide a user-specific intervention and improve the subject's adherence to the treatment. This may result in higher adherence to the therapeutic intervention as well as potential improvement of the user's condition.

[0116]

[0023] Referring now to Figure 4, a flow chart of a method 400 for presenting multimodal stimuli to address symptoms associated with a medical condition is shown. Method 400 may be implemented or performed using any of the components detailed herein, such as session management service 105 and user device 110, or any combination thereof. Under method 400, a service (e.g., session management service 105) may identify (405) a set of visual stimuli. The service may provide (410) the set of visual stimuli to a client (e.g., user device 110). The client may present (415) the set of visual stimuli using a display device of the client. Upon presenting the stimuli, an application running on the client may detect (425) a response in one or more of the set of visual stimuli. The service may receive (420) the response. Upon receiving the response, the service may determine (430) whether the response is correct. If the response is incorrect, the service may remove (435) a portion from the auditory stimuli. If the response is correct, the service can add the portion to the auditory stimulus (440). The service can provide the auditory stimulus (445). The client can play the auditory stimulus as feedback to the user (450).

[0117] 5, a screenshot of a sample set 500 of interfaces for presenting multimodal stimuli to address symptoms associated with a medical condition is depicted. The sample set 500 can include an exemplary user interface 505, 510, or 515 and a set of instructions 520. The sample set 500 can include an installed application 125. The application 125 can be displayed on a user interface or display, such as a user interface 130 of the user device 110. In some embodiments, the application 125 can be presented on the user device 110 as a game, image, video, or interactive application 125. A user (e.g., user 210) can interact with the user interfaces 505-515. The user interfaces 505-515 can include one or more user elements, such as UI element 135, to accept input by the user 210 using at least one hand 525. The user 210 may press the screen of the user device 110 to perform an input operation, or may manipulate or rotate the user device 110 to register the movement of the user device 110 (via detection by an accelerometer, gyroscope, or other sensor associated with the user device 110).

[0118] The user 210 may operate the user device 110 according to the instructions 520. The instructions 520 may be presented to the user device 110 as part of the application 125 running on the user device 110. Through the user 210 operating the user device 110 according to the instructions 520, each of the user interfaces 505-515 may be displayed to the user 210 via the user device 110. For example, by tilting the user device 110 to the user's left, the user interface 505 may be displayed with the word "LOVE" more prominent than the word "PAIN". Conversely, by the user 210 tilting the user device 110 to the user's right, the application 125 may display the word "PAIN" more prominently than the word "LOVE". By maintaining the user device 110 in a neutral position, the client device 110 may display the user interface 510 with the words "LOVE" and "PAIN" being equally opaque. In this way, the user 210's interaction 220 of tilting the mobile phone causes the different stimuli "LOVE" and "PAIN" to take on different visual characteristics.

[0119] 6, a screenshot of a sample set 600 of user interfaces for presenting multimodal stimuli to address symptoms associated with a medical condition is depicted. The sample set 600 may include exemplary user interfaces 605, 610, or 615. The sample set 600 may include an installed application 125. The application 125 may be displayed on a user interface or display, such as a user interface 130 of the user device 110. In some embodiments, the application 125 may be presented on the user device 110 as a game, image, video, or interactive application 125. A user (e.g., user 210) may interact with the user interfaces 605-615. The user interfaces 605-615 may include one or more user elements, such as UI elements 135, to accept input by the user 210. The user 210 may press the screen of the user device 110 to perform an input operation, or may manipulate or rotate the user device 110 to register the movement of the user device 110 (via detection by an accelerometer, gyroscope, or other sensor associated with the user device 110).

[0120] The user interfaces 605-615 may correspond to respective difficulty levels. The user interface 605 may correspond to an "easy" difficulty level. The user interface 610 may correspond to a "medium" difficulty level. The user interface 615 may correspond to a "hard" difficulty level. The different difficulty levels associated with the user interfaces 605-615 may be determined by the session manager 140 in accordance with the systems and methods described herein. In this illustrative example, the increase in difficulty level is associated with an increasing difficulty in interpreting the visual stimuli by the user 210. For example, the user interface 615 may depict two stimuli ("love" and "pain") in similar fonts, coloring, and size, making it more difficult or challenging for the user 210 to distinguish between the two visual stimuli. Similarly, the user interface 605 may depict these same two visual stimuli in different fonts, sizes, and colors, making it easier for the user 210 to distinguish between the stimuli.

[0121] The application provides real-time support to the subject because the application runs on the subject's mobile device, or at least on a mobile device that the subject can easily and reliably access, for example, according to a predefined frequency (e.g., once a day). For example, upon receiving a request from the user to start a session, the application starts the session in real time, i.e., at least within a few milliseconds of receiving the request. Such rapid guidance cannot be achieved by a face-to-face visit, phone call, video conference, or text message between the user and a healthcare provider who sees the user for multiple sclerosis or cancer. In this way, the application can challenge the user and tailor those challenges to the individual user based on the user's performance. This can produce an iteratively improved service for the user, where the overall bandwidth and data traffic is minimized as each challenge becomes more useful.

[0122] B. How to reduce symptoms associated with attention bias in users suffering from conditions affecting cognitive function Referring now to FIG. 7, a flow chart of a method 700 for providing necessary relief to symptoms associated with attention bias in a user suffering from a condition affecting cognitive function is depicted. The method 700 can be performed by any of the components or actors described herein, such as the session management service 105 and the user device 110. The method 700 can be used in combination with any of the features or actions described in Section A, Example 1 of Section B, or Appendix A herein. In general terms, the method 700 can include obtaining a baseline metric (705). The method 700 can include selecting visual stimuli for a session (710). The method 700 can include presenting a set of visual stimuli (715). The method 700 can include playing an auditory stimuli (720). The method 700 can include obtaining a session metric (725). The method 700 can include determining whether to continue (730). The method 700 can include determining whether the session metric is an improvement over the baseline metric (735). The method 700 can include determining that a symptom reduction has occurred if the session metric is determined to have improved over the baseline metric (740). The method 700 can include determining that a symptom reduction has not occurred if the session metric is determined to have not improved over the baseline metric (745).

[0123] More specifically, the method 700 may include determining, identifying, or otherwise obtaining baseline metrics prior to any session (705). The baseline metrics may be associated with a user (e.g., user 210) who is at risk for, diagnosed with, or suffering from a condition. In some cases, the user's condition may include multiple sclerosis (MS), with or without mobility limitations due to muscle weakness or spasticity, fatigue, or loss of balance. A user with multiple sclerosis may have relapsed and been steroid-free for at least a period of time (e.g., between 3 days and 3 weeks) prior to the session. In other cases, the user's condition may include cancer, such as lung cancer, colorectal cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, or gastric cancer. In other cases, the condition may include a psychogenic chronic pain condition, such as fibromyalgia, rheumatoid arthritis, or IBS.

[0124] "Cancer," also referred to herein as "tumor," is medically known as the uncontrolled division of abnormal cells in a part of the body, and can be benign or malignant. In one embodiment, cancer refers to malignant neoplasms, a broad group of diseases involving unregulated cell division and growth, and invasion of nearby parts of the body. Non-limiting examples of cancer include carcinomas, sarcomas, leukemias, and lymphomas, such as colon cancer, colorectal cancer, rectal cancer, gastric cancer, esophageal cancer, head and neck cancer, breast cancer, brain cancer, lung cancer, stomach cancer, liver cancer, gallbladder cancer, or pancreatic cancer. In one embodiment, the term "cancer" refers to solid tumors, which are abnormal masses of tissue that do not usually contain cysts or fluid, including, but not limited to, sarcomas, carcinomas, and certain lymphomas (such as non-Hodgkin's lymphoma). In another embodiment, the term "cancer" refers to liquid cancers, which are cancers that exist in bodily fluids (such as blood or bone marrow), such as leukemia (cancer of the blood) and certain lymphomas.

[0125] Additionally or alternatively, cancer may refer to localized cancer (an invasive malignant cancer that is entirely confined to the organ or tissue in which it originated), metastatic cancer (referring to cancer that has spread from the site of origin to another part of the body), non-metastatic cancer, primary cancer (a term referring to the cancer that first affects a subject), secondary cancer (referring to a metastasis from a primary cancer or a second cancer unrelated to the original cancer), advanced cancer, unresectable cancer, or recurrent cancer. As used herein, advanced cancer refers to cancer that has progressed after receiving one or more of the following treatments: first-line, second-line, and third-line treatments.

[0126] The user may also be taking medication to address the user's condition at least partially in parallel with the session. For multiple sclerosis, the medication may include beta interferon, glatiramer, cladribine, dimethyl fumarate, diroximel fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponesimod, siponimod, teriflunomide, alemtuzumab, mitoxantrone, or natalizumab. For cancer, the user may have completed chemotherapy, radiation therapy, or immunotherapy at least some period (e.g., between 3 days and 18 months) prior to the session. The user may be of any demographic or characteristic, such as by age (e.g., adult (18 years or older), late adolescent (between 18-24 years old)) or gender (e.g., male, female, or non-binary).

[0127] The user may have one or more symptoms associated with attention bias resulting from a condition that affects the user's cognitive function. Condition-related symptoms may include chronic pain, fatigue, affect (e.g., depressed mood), and the like. Condition-affected cognitive function may include, among others, chronic neurological disease and cognitive impairment due to multiple sclerosis, and cognitive impairment due to cancer or cancer treatment. Attention bias may include, for example, avoidance of stimuli or activities associated with the condition, anxiety induced from stimuli associated with the condition, multiple sclerosis, or cancer, or depression, and the like.

[0128] The baseline measurements may be obtained (e.g., by a computing system such as the user device 110 or the session management service 105, or a clinician separate from the computing system) before any of the sessions are provided to the user via the digital therapeutic application (e.g., the application 125 or the research app described herein). The baseline measurements may identify or indicate the severity of symptoms associated with attention bias due to a condition affecting the user's cognitive function. Specific types of metrics or metrics may be used for both multiple sclerosis and cancer. For both conditions, baseline metrics may include, for example, Patient-Reported Outcomes Measurement Information System (PROMIS) values ​​(e.g., PROMIS-29), Brief Pain Questionnaire (BPI) values, Pain Catastrophizing Scale (PCS) values, Global Rating of Change (GRC) values, User Experience Questionnaire values, and computerized assessment values. Specific types of metrics may be used for either multiple sclerosis or cancer. Baseline metrics for multiple sclerosis may include Symbol Digit Modalities Test (SDMT) scores, and baseline metrics for cancer may include Functional Assessment of Cancer Treatment-Cognitive (FACT-Cog) scores.

[0129] The method 700 may include identifying or selecting a set of visual stimuli (e.g., visual stimuli 175) for the session (710). The computing system may select the set of visual stimuli based on settings (e.g., settings 205 identifying a list of words for identifying visual stimuli) of the user's user profile (e.g., user profile 170) and previous sessions, if any, provided to the user. The visual stimuli may include text, images, or videos and may be selected according to Attention Bias Modification Training (ABMT). The set of visual stimuli may include at least one visual stimulus associated with a pathology (or a symptom associated with the pathology) and at least one other visual stimulus. The first visual stimulus (e.g., first visual stimulus 175A) may be, for example, a pain-related visual stimulus, a threat-related visual stimulus, a pathology-related visual stimulus, or other negatively-related visual stimulus, etc. The second visual stimulus (e.g., second visual stimulus 175B) may be a neutral visual stimulus, a positive visual stimulus, etc.

[0130] The method 700 may include displaying, rendering, or otherwise presenting (715) the set of visual stimuli. Upon selection of the set of visual stimuli, the computing system may present on the display a first visual stimulus at least partially overlapping with a second visual stimulus. The user may be prompted or instructed (e.g., via the display) to perform at least one interaction (e.g., interaction 220) with one of the first or second visual stimuli presented to the user. For example, the computing system may display an indicator identifying which side of the display the device should be oriented toward to select the visual stimulus. The computing system may monitor an interaction with one of the visual stimuli. The interaction may include an orientation (e.g., tilt or movement) of the device display to a side corresponding to one of the visual stimuli or a contact (e.g., a contact or click event) with one of the visual stimuli. Once detected, the computing system may identify (e.g., from the response 215) a visual stimuli from the set of visual stimuli with which the user has performed an interaction.

[0131] The method 700 can include presenting, outputting, or otherwise playing an auditory stimulus (e.g., auditory stimulus 180) (720). The computing system can generate the auditory stimulus to provide feedback to the user based on the response. The computing system can determine whether the response is correct based on which visual stimulus the user performed the interaction based on. If the response identifies the interaction was with a first visual stimulus associated with the pathology, the computing system can determine that the response is incorrect. If the response is incorrect, the computing system can generate the auditory stimulus to provide negative reinforcement (e.g., by removing one or more portions 310). If the response identifies the interaction was with a second visual stimulus, the computing system can determine that the response is correct. If the response is correct, the computing system can generate the auditory stimulus to provide positive reinforcement (e.g., by adding one or more portions 310). In some embodiments, the computing system can present the auditory stimulus at least partially simultaneously with the presentation of the set of visual stimuli. The auditory stimuli may include stereo audio, where audio played to one ear of a user differs from audio played to the other ear of the same user to achieve binaural perception. In response to the binaural beats in the auditory stimuli, a user may experience an improvement in fatigue symptoms associated with a medical condition.

[0132] The method 700 can include determining, identifying, or otherwise obtaining a session metric (725). The session metric may be obtained (e.g., by a computing system such as the user device 110 or the session management service 105, or by a clinician separate from the computing system) after at least one of the sessions is provided to the user via the digital therapeutic application. The session metric can identify or indicate the severity of symptoms associated with attention bias due to a condition affecting the user's cognitive function. The session metric can be of the same type of measurement as the baseline metric. Specific types of metrics or metrics can be used for both multiple sclerosis and cancer. For both conditions, the baseline metric can include, for example, Patient-Reported Outcomes Measurement Information System (PROMIS) values ​​(e.g., PROMIS-29), Brief Pain Questionnaire (BPI) values, Pain Catastrophizing Scale (PCS) values, Global Rating of Change (GRC) values, User Experience Questionnaire values, and computerized assessment values. Specific types of metrics can be used for either multiple sclerosis or cancer. Baseline metrics for multiple sclerosis may include Symbol Digit Modalities Test (SDMT) scores, and baseline metrics for cancer may include Functional Assessment of Cancer Treatment-Cognitive (FACT-Cog) scores.

[0133] Method 700 may include a step of determining (730) whether to continue. This determination may be based on a set length of the test (e.g., days, weeks, or years) or a set number of sessions provided to the user. For example, the set number of time instances may range from two weeks to eight weeks relative to obtaining baseline metrics. If the amount of time since obtaining baseline metrics exceeds the set length, the decision may be to stop providing additional sessions. Method 700 may select the set of visual stimuli for the next session and repeat from step 710. The visual stimuli presented for the subsequent session may be changed, varied, or otherwise modified based on responses in the current session. In some embodiments, the computing system may determine, identify, or otherwise select a difficulty level based on responses from the user in the current or previous session. This selection may cause the computing system to modify visual features (e.g., opacity or degree of overlap) of the set of visual stimuli for the next session based on the difficulty level.

[0134] The method 700 may include determining whether the session metric is an improvement over the baseline metric (735). The improvement may correspond to an improvement or reduction in symptoms associated with attention bias due to a condition affecting the user's cognitive function. The improvement may be determined (e.g., by a computing system or by a clinician examining the user) to have occurred when the session metric has increased by a first predetermined margin compared to the baseline metric, or when the session metric has decreased by a second predetermined margin compared to the baseline metric. The margin identifies or defines a difference in values ​​between the baseline metric and the session metric for determining that the user has exhibited a reduction in the symptom or its severity. Whether the improvement is indicated by an increase or a decrease may depend on the type of metric used to measure the user with respect to the condition or symptom. The margin may also depend on the type of metric used, and may generally correspond to a difference in values ​​that indicates a noticeable difference to a clinician or user with respect to the symptom, or a statistically significant result in the difference in values ​​between the baseline metric and the session metric.

[0135] The method 700 may include determining that a symptom reduction has occurred if the session metric is determined to improve over the baseline metric by a first or second predetermined margin (740). In some embodiments, the symptom may be reduced when the session PROMIS value increases from the baseline PROMIS value by a first predetermined margin. In some embodiments, the symptom may be reduced when the session BPI value decreases from the baseline BPI value by a first predetermined margin. In some embodiments, the symptom may be reduced when the session PCS value decreases from the baseline PCS value by a first predetermined margin. In some embodiments, the symptom may be reduced when, for a computerized cognitive assessment value, the session metric value increases from the baseline metric value by a second predetermined margin. In some embodiments, the symptom may be reduced when, for a user with multiple sclerosis, the session SDMT value increases from the baseline SDMT value by a second predetermined margin. In some embodiments, the symptoms may be reduced for a user with cancer when a session FACT-Cog value increases from a baseline FACT-Cog value by a second predetermined margin, in some embodiments, the symptoms may be reduced after a session of FACIT-Fatigue, FACT-G and / or HADS.

[0136] The method 700 may include determining that no symptom reduction has occurred if it is determined that the session metric does not improve over the baseline metric by a first or second predetermined margin (745). In some embodiments, the symptoms may not be reduced if the session PROMIS value does not increase from the baseline PROMIS value by a first predetermined margin. In some embodiments, the symptoms may not be reduced if the session BPI value does not decrease from the baseline BPI value by a first predetermined margin. In some embodiments, the symptoms may not be reduced if the session PCS value does not decrease from the baseline PCS value by a first predetermined margin. In some embodiments, the symptoms may not be reduced for a computer cognitive assessment value when the session metric value does not increase from the baseline metric value by a second predetermined margin. In some embodiments, the symptoms may not be reduced for a user with multiple sclerosis when the session SDMT value does not increase from the baseline SDMT value by a second predetermined margin. In some embodiments, symptoms may not be alleviated for a user with cancer when the session FACT-Cog value does not increase from the baseline FACT-Cog value by a second predetermined margin.

[0137] Example 1: A randomized controlled exploratory basket study evaluating multimodal multistable modification of attentional biases to normalize and improve cognition in adult patients with multiple sclerosis, breast cancer, and lung cancer 1. Overview Indications: Multiple sclerosis (MS), breast cancer, lung cancer

[0138] Introduction and Study Rationale: CT-100 (e.g., Application 125) is a platform that provides interactive, software-based therapeutic components that may be used as part of a multimodal treatment in future software-based prescriptive digital therapeutics. One class of CT-100 components is the Digital Neural Activation and Modulation (DiNaMo®) components. DiNaMo components target key nervous systems (including, but not limited to, systems related to sensation, perception, emotion, pain, attention, cognitive control, sociality, and self-processing) to optimally improve participants' health.

[0139] Multimodal multistable modification of bias (or multimodal multistable bias modification or MMBM) is a targeted cognitive training using the principles of multimodal neural reinforcement tasks (M-NET) to reduce symptoms associated with multiple sclerosis (MS) and cancer. Bias to direct attention towards or away from specific stimuli can exacerbate various symptoms in various indications. For example, in chronic pain states, patients may direct more attention towards pain-related stimuli, which can lead to hypersensitivity. Similarly, hypersensitivity to threat-related stimuli exacerbates anxiety.

[0140] In multimodal multistable modification of bias, users are trained to redirect attention to positive stimuli instead of potentially distressing stimuli, such as pain- or threat-related stimuli. This is done in a novel format that utilizes multistable perception. Visual multistable perception, in the form of monocular rivalry, is used to implicitly retrain attentional bias. At the same time, auditory multistable perception, in the form of binaural beats, works synergistically to target fatigue symptoms while improving components of attentional bias.

[0141] OBJECTIVE:To assess trends in effect compared with a digital control group on pain interference, cognition, and related outcomes (attentional bias and general quality of life [QoL]).

[0142] Evaluation criteria

[0143] Exploratory Endpoints Change from baseline to week 4 in quality of life as measured by PROMIS-29+2 (Patient-Reported Outcomes Measurement Information System) Change from baseline to week 3 in pain severity and pain interference as measured by the Brief Pain Inventory (BPI) Change from baseline to week 4 in the Pain Catastrophizing Scale (PCS) Change from baseline to week 4 in indication-specific measures: Symbol Digit Modalities Test (SDMT) in MS, Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) in cancer Change from baseline to week 4 in computerized cognitive assessment Percentage of participants who saw improvement as measured by Global Rating Change (GRC) score at week 4 ● Engagement with research apps, measured by metrics such as daily research app usage and daily time spent using research apps. Experience with the study app assessed through a user experience survey and optional qualitative interviews after the end of the treatment period

[0144] Study design

[0145] Referring now to Figure 8, a timeline is shown for a randomized controlled exploratory basket study to evaluate multimodal multistable modification of attentional biases aimed at normalizing attentional biases and improving cognition in adults with multiple sclerosis, breast cancer, and lung cancer.

[0146] Screening period (day -14 to day -1) Participants were screened over a period of up to 14 days, including electronic informed consent. Assessments during this period were carried out remotely according to a Schedule of Activities and Assessments (SoA). • Participants were considered eligible if they met all inclusion criteria and did not fall under any exclusion criteria, based on the investigators' assessment. • Screening and baseline visits sometimes occurred on the same day.

[0147] Baseline (Day 1) Participants were contacted for a baseline visit to screen and verify eligibility and conduct identity verification. Assessments were conducted in accordance with the SoA. ● Eligible participants were randomized during a virtual study visit on Day 1. Participants were randomized 1:1 (study app:control) within four cohorts: MS patients with no mobility limitations, MS patients with mobility limitations, breast cancer patients, and lung cancer patients. Participants randomized to the study app treatment arm downloaded and activated the app on their personal primary smartphone.

[0148] Intervention period (Day 1-Day 28) ● Participants in the research app group completed the app-based brain exercises for seven minutes per day for four weeks. ● Participants in the control group received digital controls and did not receive the study intervention. ● During the intervention period, both groups were assessed weekly according to the SoA. ● Participants assigned to the study app group completed a user experience survey at the end of the intervention period.

[0149] Follow-up period (up to 1 week) • Participants completed follow-up assessments according to the SoA. ● Participants did not perform any activities within the study app. ● A subset of participants participated in optional qualitative interviews between days 29 and 35.

[0150] Planned Number of Participants: 189 participants were enrolled in the study. • A total of 107 participants with MS were included, with at least 53 in the DiNaMo 4 group and at least 54 in the control group. • There were 82 patients in the BC group, at least 41 in the DiNaMo 4 group, and at least 41 in the control group.

[0151] Research participation criteria

[0152] Inclusion criteria: Participants were eligible to participate in this study if they met all of the following criteria: 1. Fluent in written and spoken English and able to read, understand, and sign an informed consent form. 2. You are a resident of the United States. 3. Adults aged 22 to 65 years old. 4. Meet the indication-specific inclusion criteria as reported by the study participant with appropriate clinical documentation (provided to the study team upon request). 5. Have a valid email address and are willing and able to receive and reply to emails. 6. Internet access will be available for the duration of this study. 7. Have or be willing to open a valid bank account to receive research remuneration. 8. Willing and able to comply with study protocols and evaluations. 9. During the exam period, you will use your smartphone alone and will not share it with others. 10. Willingness and ability to receive Short Message Service (SMS) text messages and notifications on your smartphone. 11. You have headphones that work properly.

[0153] Exclusion Criteria: Participants who met any of the following criteria were deemed ineligible to participate in the study. 1. Have severe vision, dexterity, or cognitive deficits that, in the opinion of the researchers, would prevent them from participating in response time-based activities using the app. 2. Severe mental disorders with a history of psychiatric illness (e.g., schizophrenia, bipolar disorder, severe personality disorder). 3. History of psychiatric hospitalization in the past 6 months. 4. Participated in any research study (including studies of psychotherapy, mindfulness, cognitive training, or pharmacological treatment) in the past 3 months. 5. Initiation or change of disease-specific primary medication within 30 days prior to study entry. 6. The participant plans to introduce a new treatment (including research on psychotherapy, mindfulness, cognitive training, and pharmacological therapy) during the study period (6 weeks). 7. Anticipating any changes to current pharmacological or psychotherapeutic treatment regimens during the study period (6 weeks). 8. Self-reported substance use disorder within the past year. 9. Severe neurological disorder compromising brain function (e.g., history of stroke, dementia, primary brain dysfunction, brain metastases, Alzheimer's disease, Parkinson's disease, history of significant head trauma with subsequent persistent neurological impairment, or known structural brain abnormality). 10. Mild, moderate, severe or significant unilateral or bilateral hearing loss.

[0154] Test product and application method DiNaMo 004

[0155] Eligible participants will download and install the study app onto their smartphone at the baseline visit (Day 1).

[0156] Treatment Regimen: Study App: Daily use for 3 weeks (7 minutes per day)

[0157] Study Duration: Participation in this study will last a maximum of six weeks. ● Screening period: up to 2 weeks ● Intervention period: 3 weeks ● Follow-up: up to 1 week

[0158] Sample sizes: 107 in MS, at least 53 in DiNaMo 4, and at least 54 in control; at least 80 in BC, at least 41 in DiNaMo 4, and at least 41 in control. These sample sizes were sufficient to measure change relatively precisely.

[0159] Statistical Analysis: Changes from baseline to week 3 for all PROMIS-29+2 domains, BPI pain severity, BPI pain interference, PCS subcategory and total scores, and computerized cognitive assessment were summarized using descriptive statistics. Analysis of covariance (ANCOVA) models were performed to assess differences between the two treatment groups. The models included change from baseline as the dependent variable and treatment group, indication, and baseline value as covariates. 95% confidence intervals (CIs) and two-sided p-values ​​for the null hypothesis of no difference between the two groups were given. Least squares means (LS) of the treatment effects were given. In addition, LS means, 95% CIs, and p-values ​​for the null hypothesis of no change from baseline were given for each treatment group.

[0160] For SDMT and FACT-Cog, indication-specific changes from baseline were summarized using descriptive statistics. In addition, 95% CIs and two-sided p-values ​​for the null hypothesis of no difference between treatment groups were given for the change from baseline to week 3 in each treatment group. CIs and p-values ​​were based on two-sample t-distributions.

[0161] The 95% CI for the change from baseline to week 3 in each group was given, along with a two-sided p-value for the null hypothesis of no change from baseline using a one-sample (before and after) t-distribution.

[0162] Number and percentage of GRC-measured improvements (improvement was a score of ≥1) were summarized by treatment group. Comparisons between treatment groups were performed using the Cochran-Mantel-Haenszel test with indication-specific stratification.

[0163] For the remaining exploratory endpoints and safety parameters, only descriptive statistics were used.

[0164] 2. Individual Indications A. Multiple sclerosis without movement limitations Indications: Multiple sclerosis (MS)

[0165] Evaluation criteria

[0166] Other Disease-Specific Scales ● Symbol Digit Modality Test (SDMT)

[0167] Research participation criteria

[0168] Selection Criteria 1. Self-reported clinical diagnosis of multiple sclerosis accompanied by appropriate clinical records (provided to the study team upon request). 2. No relapse or steroid use for 30 days prior to screening. 3. Have self-reported pain for at least the past 3 months and the pain began after diagnosis of MS.

[0169] Exclusion criteria: 1. Self-reported cancer diagnosis 2. Unable to walk 300 m (328 yards) unassisted.

[0170] B. Multiple sclerosis with movement limitations Indications: Multiple sclerosis (MS)

[0171] Evaluation criteria

[0172] Other disease-specific scales: ● Symbol Digit Modality Test (SDMT)

[0173] Research participation criteria

[0174] Selection Criteria 1. Self-reported clinical diagnosis of multiple sclerosis with appropriate clinical documentation (to be provided to the study team upon request) 2. No relapse or steroid use for 30 days prior to screening. 3. Unable to walk 300 m (328 yards) unassisted. 4. Have self-reported pain for at least the past 3 months and the pain began after diagnosis of MS.

[0175] Exclusion criteria

[0176] 1. Self-reported cancer diagnosis C. Breast cancer Indications: Breast cancer

[0177] Evaluation criteria

[0178] Other disease-specific scales: ● Functional Assessment of Cognitive Function in Cancer Treatment (FACT-Cog)

[0179] Study participation criteria Selection criteria 1. Study participant reported history of breast cancer (any stage) with appropriate clinical records (to be provided to the study team upon request). 2. Patients have completed at least 3 months of chemotherapy within 9 months to 5 years prior to screening. 3. Have had self-reported pain for at least the past 3 months and the pain began after cancer treatment.

[0180] Exclusion criteria 1. Self-reported clinical diagnosis of multiple sclerosis

[0181] D. Lung cancer Indications: Lung cancer

[0182] Evaluation criteria

[0183] Other disease-specific scales: ● Functional Assessment of Cognitive Function in Cancer Treatment (FACT-Cog)

[0184] Study participation criteria Selection criteria 1. Study participant reported a medical history of lung cancer (any stage) with appropriate clinical records (to be provided to the study team upon request). 2. Patients have completed at least 3 months of chemotherapy within 9 months to 5 years prior to screening. 3. Have had self-reported pain for at least the past 3 months and the pain began after cancer treatment.

[0185] Exclusion criteria 1. Self-reported clinical diagnosis of multiple sclerosis 3. Schedule of activities and evaluations

[0186] [Table 1] JPEG2025041526000003.jpg229166 JPEG2025041526000004.jpg195166

[0187] 4. Introduction A. Multimodal multistable correction of bias Multimodal multistable modification of bias (or multimodal multistable bias modification or MMBM) is targeted cognitive training using the principles of multimodal neural reinforcement tasks (M-NET) to reduce symptoms associated with multiple sclerosis (MS) and cancer, including fatigue, pain, and mood-related symptoms. In multimodal multistable modification of bias, users are trained to redirect attention to positive stimuli, instead of potentially distressing ones, such as pain- or threat-related stimuli, via a multistable perceptual phenomenon called monocular rivalry. At the same time, binaural beats are used to target fatigue symptoms, working synergistically by providing a second modality of multistable perception.

[0188] B. Attentional bias Individuals with various indications, such as MS and various types of cancer, tend to present with both pain and mood problems. These problems may be exacerbated by attentional biases associated with pain and threat-related stimuli. Individuals with chronic pain tend to pay more attention to pain-related stimuli, which may further exacerbate their condition through fear avoidance. Avoiding stimuli or activities that are perceived to cause pain can derail the individual, which may progress the disability and worsen the condition. With threat-related stimuli, anxious individuals often unconsciously seek out signs of the threat. This threat triggers a feedback loop that perpetuates feelings of anxiety. This includes indication-related stimuli. For example, cancer survivors who fear a recurrence of their cancer may have a bias for cancer-related stimuli. Similarly, pain and anxiety are highly comorbid, and because alterations in neural circuitry are similar in both, targeting biases associated with both is likely to be synergistic. Finally, depressed individuals often show attentional biases for negative emotional information, which may foster rumination and exacerbate symptoms. The overlap of these various attentional biases can be quite debilitating for patients.

[0189] Common symptoms of MS include pain and mood disorders, two targets of this treatment, and there is a significant relationship between high levels of pain and anxiety, for which multimodal multistable correction of bias may be particularly effective.

[0190] Both cancer patients and survivors show attentional biases toward cancer-related words. Many studies also find evidence of biases toward threat and negative emotions. Attempts to change these unconscious associations have met with some success. Because cancer patients also experience pain and mood symptoms, multimodal, multistable modification of biases is expected to be highly relevant and meaningful to this patient population.

[0191] C. Cognitive impairment Cognitive impairment is common in several physical and psychiatric disorders. This may be due to presenting symptoms associated with the disease / disorder, or associated with the treatment of a specific disease (e.g., chemotherapy for cancer), or both. Cognitive impairment is also frequently associated with problems with emotion regulation and mood problems. The combination of cognitive deficits and mood symptoms can cause distress and disability for patients, negatively impact quality of life, and increase healthcare utilization.

[0192] For example, in multiple sclerosis (MS), a chronic central nervous disease, cognitive impairment is very common, with up to 70% of MS patients experiencing cognitive deficits. The cognitive deficits affect several cognitive domains, with attention and processing speed being commonly affected. MS patients experience these cognitive deficits as a disability and stress, and currently there are insufficient treatment options to improve these challenges. Computer-based cognitive training has repeatedly proven effective in correcting cognitive impairments in MS. This training can be expected to have a broader effect outside of the cognitive domain. For example, cognitive training has shown beneficial effects on memory, semantic fluency, processing speed, and executive function. It can also have benefits beyond cognitive improvement. For example, other studies have found beneficial effects on depression, activities of daily living, Expanded Disability Status Scale scores, and fatigue.

[0193] In cancer patients, tumor activity and associated inflammatory processes, and / or cancer-related treatments can affect cognitive function. Cancer-related cognitive impairment is seen in up to 75% of cancer patients, and in up to 35% of patients who experience impairment, this can persist for months to years after treatment. As the number of cancer survivors increases, persistent cognitive impairment due to cancer and cancer treatment is likely to increase. As with MS, computer-based cognitive training has been shown to be effective in general cancer patients, breast cancer patients, and cancer survivors.

[0194] Fatigue is also a debilitating symptom for both indications, and contributes greatly to cognitive problems. Up to 97% of MS patients have significant fatigue, and up to 40% state that fatigue is the most disabling symptom of their disease. In fact, fatigue is the first symptom patients report to their healthcare provider in one in three diagnosed patients. Fatigue is one of the most common cancer symptoms, and is often the first symptom patients report to their healthcare provider. Fatigue can result from both treatments, such as chemotherapy (which is administered to 75-100% of patients), or the disease itself, especially in the final stages. One study found that 37% of cancer survivors had not regained a satisfactory level of energy even after several years.

[0195] D. Binaural Beats In binaural beats, one tone frequency is played in each ear, and the detectable frequency difference between these two is called the "beat." The theory behind binaural beats is that rhythmic sensory stimulation may entrain neural oscillations, similar to non-invasive techniques such as transcranial magnetic stimulation and transcranial direct current stimulation. Previous studies have found that binaural beats have beneficial effects on depression and anxiety symptoms, memory, attention, cognition, fatigue, and pain sensation.

[0196] E. Research Applications (Apps) Multimodal multistable bias correction CT-100 Digital Neural Activation and Modulation (DiNaMo) components (e.g., Application 125) use implicit training to redirect and strengthen attention processes. This intervention not only helps improve cognitive performance, but also redirects attention bias and helps participants desensitize to painful stimuli. Preliminary studies have shown the success of computerized cognitive training in MS and cancer, and of retraining attention bias in pain, threat, and mood. Multimodal multistable correction of bias is likely to improve not only cognitive performance, but also attention biases seen in multiple sclerosis and cancer.

[0197] F. Digital Control The digital control group downloaded the digital control app and completed a version of the task designed to be inactive in the study application, which only involved selecting from a set of neutral words based on personal preference and did not include the attention-biasing capture stimulus. Additionally, all instances of multistable perception were removed, including the removal of all auditory components.

[0198] G. Study Rationale Multimodal multistable modification of bias is a novel intervention that uses the principles of the multimodal neural enrichment task (M-NET) to reduce symptoms related to MS and cancer. Attentional bias towards different attention-capturing stimuli can exacerbate different symptoms in many different indications. For example, in some pathologies, patients may pay more attention to pain-related stimuli, which can lead to hypersensitivity. Similarly, hypersensitivity to threat-related stimuli exacerbates anxiety.

[0199] In multimodal multistable modification of bias, users are trained to redirect attention to positive stimuli instead of potentially distressing stimuli, such as pain- or threat-related stimuli. This is done in a novel format that utilizes multistable perception. Visual multistable perception, in the form of monocular rivalry, is used to implicitly retrain attentional bias. At the same time, auditory multistable perception, in the form of binaural beats, works synergistically to target fatigue symptoms while improving components of attentional bias.

[0200] The aim of this study is to evaluate the initial effects of DiNaMo components (the research app) on measures of attentional bias, attentional disorders, and related outcomes (general quality of life [QOL]) in various pathologies, including MS, breast cancer, and lung cancer. Findings from this study may be used as components for future digital therapeutics.

[0201] H. CT-100 Platform The CT-100 platform offers interactive, software-based therapeutic components that may be used as part of multimodal treatments in future software-based prescriptive digital therapeutics. One class of CT-100 components are the DiNaMo components. The DiNaMo components target key nervous systems (including but not limited to systems related to sensation, perception, emotion, pain, attention, cognitive control, sociality, and self-processing) to optimally improve participants' health.

[0202] 3. Purpose and Endpoints The objectives of this study were as follows: • To assess trends in effects compared with a digital control group on pain interference, cognition and related outcomes (attentional bias and general quality of life [QoL]). • To explore the feasibility of delivering a digital multimodal multistable bias-corrected visual search task (study app) at home, including participants’ engagement with and experience of the study app. ● Evaluating the safety of investigational apps.

[0203] Study endpoints supporting these objectives are listed in Table 2.

[0204] [Table 2] JPEG2025041526000006.jpg80166

[0205] 4. Study design A. Scientific basis for study design The present study was designed to evaluate the initial effects of a multimodal multistable bias-correcting CT-100 component (a research app) on attentional bias and cognitive deficits compared to a digital control.

[0206] Participants were assessed based on validated standard participant assessment outcomes. Participant engagement with the study app was assessed based on participant usage data captured within the study app. Participants were assessed for safety throughout the duration of the study. Measures and assessments are described herein.

[0207] B. Definition of End of Study The end of the study was defined as the date of last contact or last attempted contact of the last participant who completed or withdrew from the study. In this study, participants who completed the study assessments on Day 21 (+3) (Week 3) were defined as study completers.

[0208] 6. Study interventions and concomitant therapies A. Study interventions implemented The CT-100-D-004 study app (e.g., Application 125) was given to participants along with the study intervention.

[0209] B. CT-100 The study intervention to be evaluated is the multimodal multistable bias correction CT-100 component, a digital mobile application. Participants randomized to this group will download and install the study app on their smartphone at the baseline visit (day 1) and will use the study app daily for multimodal multistable bias correction training over the 3-week intervention period.

[0210] C. Control The digital control group downloaded the digital control app and completed a version of the task designed to be inactive in the study application, which only involved selecting from a set of neutral words based on personal preference and did not include the attention-biasing capture stimulus. Additionally, all instances of multistable perception were removed, including the removal of all auditory components.

[0211] D. Preparation / Handling / Storage / Accountability

[0212] Detailed instructions for downloading, installing, activating, using, and disposing of the Research App are provided in CT-100-D-004 Research App Site Instructions for Use.

[0213] In general: 1. Only participants enrolled in the study received the study intervention. 2. Site staff made sure to download and activate the study app. 3. The study app was automatically disabled after week 3. Site staff notified participants who completed the study or terminated early to uninstall the study app.

[0214] E. Concomitant Therapy Participants continued to use prescribed treatments while enrolled in the study. Participants self-reported any changes in all primary indication-related or psychoactive concomitant medications through the end of the follow-up period.

[0215] 7. Study Assessment and Procedures Study assessments and procedures, including their timing, are summarized in the SoA. Adherence to study design requirements, including those specified in the SoA, is a mandatory and necessary condition for the conduct of the study. No exemptions or waivers of the protocol will be permitted. Every effort should be made to ensure that assessments and procedures requested in the protocol are completed as described. All clinician-administered measures (where applicable) were performed by appropriately trained personnel. Study assessments are described below.

[0216] The following efficacy measures were used in this study at the times described in the SoA. A description of all endpoint measures and their respective scoring algorithms will be described in the Statistical Analysis Plan (SAP).

[0217] A. Patient-Reported Outcomes Measurement Information System-29+2 (PROMIS-29+2) Profile v2.1 PROMIS-29 is part of the Patient-Reported Outcomes Measurement Information System (PROMIS). PROMIS-29 is a short-form assessment that includes four items from each of the seven PROMIS domains (anxiety, physical function, pain interference, fatigue, sleep problems, depression, and ability to participate in social roles and activities), plus one pain intensity question (on a 0-10 numeric rating scale) and two questions about cognitive function. PROMIS-29 is universal, not disease-specific (i.e., it can assess a patient's health regardless of disease or condition), and is intended for adults (ages 18 and older). Scores were generated for all seven domains. The domains were assessed over the past 7 days. PROMIS-29 has been widely administered and validated in a variety of populations and settings. The electronic questionnaire was completed by the participants. It took approximately 7 minutes to complete.

[0218] PROMIS 29+2 also allows for the calculation of the PROMIS Preference (PROPr) score, which allows the PROMIS subscales to be used to calculate a single quality of life summary score on a scale ranging from 0 (death) to 1 (perfect health).

[0219] B. Brief Pain Inventory (BPI) The BPI is a self-report measure used in clinical trials. It has 32 items and uses a numeric rating scale (NRS 0-10) to assess pain severity and interference, location of pain, analgesics, and amount of pain relief in the past 24 hours. The scale has good test-retest reliability and internal consistency in chronic pain studies. The questionnaire was completed electronically by participants. It took approximately 5 minutes to complete.

[0220] The BPI Interference subscale has seven items, each rated using a numeric rating scale (NRS 0-10). The purpose of the BPI Interference subscale is to assess the extent to which pain affects daily functioning. This scale was used for both acute and chronic pain. The questionnaire was completed electronically by participants using a standard 24-hour questionnaire. It took approximately 1 minute to complete.

[0221] C. Pain Catastrophizing Scale (PCS) The PCS is a reliable and valid 13-item self-report measure used to assess pain-related catastrophizing in adults (18-64 years). It consists of a 5-point Likert scale across three subscales: rumination (4 items), exaggeration (3 items), and helplessness (6 items). These subscales can be scored separately or summed to produce a total score. The questionnaire is a survey that participants complete electronically. It took approximately 5 minutes to complete.

[0222] D. Global Rating of Change (GRC) The GRC is a self-report, 10-point Likert scale used to assess participants' overall improvement in adjustment following the study intervention. This item was completed electronically by participants.

[0223] E. User Experience Surveys and Optional Qualitative Interviews The user experience survey was a questionnaire to understand participants' experience with the study app during the intervention phase. The survey asked questions related to perceived enjoyment, difficulties, and related user experiences and did not include questions related to clinical outcomes. The survey was completed electronically by participants and took approximately 7 minutes to complete.

[0224] Additionally, a subset of participants may have participated in telephone or video conference-based qualitative user interviews that collected additional information about users' experiences with the app, such as preferred app features, ease of use of features, difficulties related to the intervention, or other feedback gained from regular interaction with the app.

[0225] 8. Statistical considerations A. Statistical Hypothesis This study is exploratory and no formal statistical hypotheses were stated.

[0226] B. Determining sample size There were at least 100 participants with MS, at least 50 with no physical activity limitations, and at least 50 with physical activity limitations, at least 80 participants with oncology, at least 40 with breast cancer, and at least 40 with lung cancer.

[0227] C. Analysis Population For the analysis, the following analysis populations were defined:

[0228] [Table 3]

[0229] D. Statistical analysis The SAP was finalized before database lock and included a more technical and detailed description of the statistical analyses described in this section, which summarizes the planned statistical analyses of the most important endpoints.

[0230] E. General Considerations Descriptive statistics included mean, standard deviation, median, minimum, and maximum for continuous variables. For categorical variables, numbers and percentages were reported for all variables when applicable. Descriptive statistics were compiled by combined treatment group and by treatment group within each indication.

[0231] All analyses were exploratory in nature. For several efficacy endpoints, 95% confidence intervals and statistical tests were performed and detailed as part of the description of the planned analyses for each endpoint.

[0232] Data collection methods were programmed to minimize missing data (e.g., responses were required to proceed to the next assessment question). SAP also accommodated handling of incomplete questionnaires with missing domains or total scores. When complete questionnaires or visits were missing, no imputation was performed and only observed data were included in the analysis. No adjustment for multiplicity was planned.

[0233] F. Participant Allocation The analyses were performed on the enrolled population. Numbers of enrolled participants, screening failures, randomized participants, and participants who completed the study were presented. The number of subjects in each analysis population was presented by treatment group within each indication cohort.

[0234] G. Demographics and Baseline Characteristics Demographic and baseline characteristic data were summarized by treatment group to assess baseline comparability of the two groups. These summaries were presented for the mITT population. If there was a difference of ≥6 participants in total between the mITT and safety, and ITT and PP populations, summaries were presented for these populations.

[0235] H. Exploratory Endpoints This was an exploratory study. Specific endpoints were applied to all participants: PROMIS-29+2, BPI, PCS, and GRC. Analyses of these endpoints were performed by treatment group using the mITT population. This analysis was repeated in the PP population.

[0236] For PROMIS, absolute values ​​and change from baseline to week 3 in the seven core domains, pain intensity questions, cognitive function domain, and PROPr summary scores were descriptively summarized. Furthermore, to estimate differences between the two treatment groups, the change from baseline to week 3 was analyzed using an analysis of covariance (ANCOVA) model. The model included the change from baseline as the dependent variable, and treatment group, indication, and baseline value were included in the model as covariates. 95% confidence intervals (CIs) and two-sided p-values ​​for the null hypothesis of no difference between the two groups were given. Least squares means (LS) of the treatment effects were given. Furthermore, LS means, 95% CIs, and p-values ​​for the null hypothesis of no change from baseline were given for each treatment group.

[0237] In the BPI, absolute values ​​and changes from baseline to week 3 for four questions about pain intensity and seven questions about pain interference were summarized descriptively for all visits. In addition, confidence intervals (CIs) and tests within and between treatment groups were performed using the same approach as described in PROMIS. In the PCS, absolute values ​​and changes from baseline to week 3 for three domains (helplessness, magnification, and rumination) and their sum were summarized descriptively for all visits. Confidence intervals (CIs) and tests within and between treatment groups were performed using the same approach as described in PROMIS.

[0238] Graphs of mean (standard error [SE]) changes from baseline over time by treatment group and within indication were generated for the above endpoints using the mITT set. For GRC, the number and percentage of subjects with improvement (score >1) were summarized by treatment group. Comparisons between treatment groups were performed using the Cochran-Mantel-Haenszel test stratified by indication.

[0239] I. Other Exploratory Endpoints Endpoints considered in this section are either indication-specific or are endpoints completed only by participants in the investigational app arm. For the former (SDMT and FACT-Cog), changes from baseline are summarized using descriptive statistics. Changes from baseline to week 3 within each treatment group, 95% confidence intervals (CIs), and two-sided p-values ​​for the null hypothesis of no difference between treatment groups are given. CIs and p-values ​​are based on two-sample t-distributions. 95% CIs for changes from baseline to week 3 in each group and two-sided p-values ​​for the null hypothesis of no change from baseline using a one-sample (before-after) t-distribution are given.

[0240] For endpoints where only the study app arm was completed, analyses were stratified by indication and overall (MS and cancer patients combined). Analyses of these endpoints were performed using the mITT population and include only descriptive statistics.

[0241] 9. Results Applicant conducted a remote, randomized, single-blind, exploratory basket trial to evaluate the feasibility and acceptability of a smartphone app-based multimodal multistable bias-modified (MMBM) intervention in multiple sclerosis (MS) and breast cancer (BC). The results of this study provide strong evidence to support the advancement of MMBM in BC, particularly with respect to fatigue and mood. They also provide strong evidence to support the advancement of MMBM in MS, particularly with respect to anxiety and pain catastrophizing.

[0242] I. Patient-Reported Outcomes: PROMIS Patients were assessed with the Patient-Reported Outcomes Measurement Information System (PROMIS). For anxiety, depression, fatigue, sleep disturbance, and pain interference, lower scores indicate greater improvement. For cognitive function, physical function, and social function, higher scores indicate greater improvement. The results of patient-reported outcomes recorded by PROMIS are described below and shown in Figure 10-18.

[0243] A. Fatigue As shown in Figure 10, breast cancer shows the superiority of DiNaMo over controls. In BC, both DiNaMo and controls improved significantly over time, while only DiNaMo exceeded the minimal clinically important change threshold. The more stringent criterion of half a standard deviation (5 points) for clinically important change was also met only by DiNaMo in the BC group. In MS, both DiNaMo and controls improved significantly over time and exceeded the minimal clinically important change threshold.

[0244] B. Depression As shown in Figure 11, BC shows superiority of DiNaMo over control, with the difference exceeding the minimal clinically important change threshold. In MS, both DiNaMo and control improved significantly over time, exceeding the minimal clinically important change threshold.

[0245] C. Anxiety As shown in Figure 12, BC showed significant superiority of DiNaMo over controls and MS showed a trend toward superiority. This difference is above the threshold for minimal clinically important change. In MS, only DiNaMo significantly improved over time and above the threshold for minimal clinically important change. In BC, both DiNaMo and controls significantly improved over time and above the threshold for minimal clinically important change. The more stringent criterion of half a standard deviation (5 points) for a clinically important change was also met only by DiNaMo in the BC group.

[0246] D. Pain interference As shown in Figure 13, in MS, only DiNaMo shows a trend towards improvement over time. In BC, only DiNaMo significantly improved over time, above the minimal clinically important change threshold.

[0247] E. Pain Score As shown in Figure 14, both DiNaMo and control showed significant improvement over time in MS. Only DiNaMo showed significant improvement over time in MS.

[0248] F. Sleep Disorders As shown in FIG. 15, in MS and BC, only DiNaMo significantly improved over time, above the minimal clinically important difference threshold.

[0249] G. Physical functions In MS, both DiNaMo and control significantly improved over time, as shown in Figure 16. In BC, only DiNaMo significantly improved over time, above the minimal clinically important change threshold.

[0250] H. Cognitive Function As shown in Figure 17, in BC, only DiNaMo shows a trend of improvement over time.

[0251] I. Social Functions As shown in Figure 18, in MS, only DiNaMo significantly improved over time. In BC, both DiNaMo and control improved significantly over time, above the minimal clinically important change threshold.

[0252] II. Patient-related outcomes: Pain-related Pain-related outcomes were assessed via patient-reported outcomes. Self-reported assessments of pain interference and pain severity for MS and BC patients are described below and shown in Figures 19-23. Lower scores indicate greater improvement.

[0253] A. Brief Pain Questionnaire - Interference As shown in Figure 19, in MS, DiNaMo improved over time. In BS, both DiNaMo and control improved over time.

[0254] B. Brief Pain Questionnaire - Worst Pain Severity As shown in Figure 20, both DiNaMo and control improved over time in MS. DiNaMo showed a trend towards improvement over time in MS.

[0255] C. Brief Pain Questionnaire - mildest pain As shown in Figure 21, in BC, DiNaMo shows a trend of improvement over time.

[0256] D. Brief Pain Questionnaire - Average Pain Severity As shown in Figure 22, DiNaMo tends to be superior to the control group in MS. DiNaMo significantly improved over time in both MS and BS.

[0257] E. Brief Pain Questionnaire - Current Pain Severity As shown in Figure 23, in BC, DiNaMo demonstrates a significant advantage over control. In MS, DiNaMo shows a trend for improvement over time. In BC, DiNaMo shows significant improvement over time.

[0258] F. Pain Catastrophism Scale Self-reported pain catastrophizing scores were significantly improved in MS patients compared to controls (Figure 24). DiNaMo also showed significant improvement in BC patients.

[0259] III. Patient-Reported Outcomes – Other A. Cognition As shown in FIG. 25, there was a statistically and clinically meaningful improvement in cognition in MS patients in both DiNaMo and controls.

[0260] IV. Overall Change Assessment Patients were asked how they felt at the end of the study compared to when they began. As shown in Figure 26, the DiNaMo group tended to have a higher rate of improvement compared to the control group.

[0261] V. Objective Outcomes Patients were assessed via a dot-probe assessment to measure attentional bias. The goal for the attentional bias index was to approach or be less than 0 (no bias).

[0262] As shown in Figure 27, the BC control group significantly worsens over time on the attention bias depression index, whereas the BC DiNaMo group does not. As shown in Figure 28, the MS DiNaMo group shows a trend toward superiority in the attention bias index for anxiety, which corresponds well with the superiority of the MS DiNaMo group over the control group on the PROMIS-anxiety domain (indication-specific words may trigger anxiety about one's condition).

[0263] VI. Conclusion The above data relate to a remote, randomized, single-blind, exploratory basket trial to evaluate the feasibility and acceptability of a smartphone app-based multimodal multistable bias-corrected (MMBM) intervention in multiple sclerosis (MS) and breast cancer (BC), designed to treat fatigue, mood, and pain symptoms.

[0264] The results contain strong evidence supporting the development of MMBM in BC. With regard to fatigue, as measured by PROMIS-29+2 (Patient-Reported Outcomes Measurement Information System), DiNaMo shows a statistically and clinically significant advantage over the control group. The relevant PROMIS cognitive function domain also shows a trend for improvement over time only in the DiNaMo group. With regard to mood, the PROMIS depression and anxiety domains show a statistically and clinically significant advantage over the DiNaMo group in the PROMIS pain interference and pain intensity domains. With regard to pain, the PROMIS pain interference and pain intensity domains show improvement over time only in the DiNaMo group. All pain severity scores on the Brief Pain Questionnaire also show a trend for improvement or a statistically significant improvement in the DiNaMo group but not in the control group. The current pain severity score also shows a significant advantage over the DiNaMo group. Only the DiNaMo group improves significantly over time on the pain catastrophizing scale. Finally, the relevant PROMIS physical function domain also showed statistically and clinically significant improvements over time.

[0265] Furthermore, the results provide strong evidence supporting the development of MMBM in MS. On the PROMIS-29+2, there is a trend for a statistically significant advantage in the DiNaMo group over the control group for anxiety, with a clinically significant advantage. On the objective attention bias assessment, the MS DiNaMo group shows a trend for an improvement advantage over the control group for anxiety and adjustment-related words. On pain, there is a statistically significant advantage in the DiNaMo group over the control group for pain catastrophizing. On the PROMIS pain interference, only the DiNaMo group shows a trend for improvement. On the Brief Pain Questionnaire, pain interference scores improved significantly over time only in the DiNaMo group. On the mean pain severity score, there is a trend for a DiNaMo group over the control group. On the current pain severity score, only the DiNaMo group shows a trend for improvement.

[0266] The DiNaMo 004 intervention (MMBM) showed statistically and clinically significant improvements in breast cancer (BC) patients, suggesting that different diseases may respond differently to treatment, a hypothesis supported by direct EEG (electroencephalography) evidence, which should further strengthen this already compelling argument.

[0267] The results described herein indicate that BC (and cancer in general) may be particularly amenable to MMBM interventions, possibly because it directly impacts fronto-parietal functional connectivity, which has been linked to both chemotherapy-associated cognitive impairment and the development of cancer itself, and not least because studies have shown that functional brain changes prior to chemotherapy are a stronger predictor of post-treatment fatigue than chemotherapy itself.

[0268] The rapidity of response observed in breast cancer compared to multiple sclerosis (MS) may further support this hypothesis, since in MS, cognitive impairment and fatigue are primarily driven by structural damage and inflammation, with the subsequent recruitment of maladaptive networks contributing to fatigue. In other words, MMBM in MS may not be targeting the root cause, but downstream events, which may explain the slower or less pronounced effect compared to breast cancer. This mechanism of action (MOA) of MMBM can be further investigated through EEG recordings to assess changes in resting-state functional connectivity and neural oscillations within the frontoparietal cortex and network transmission.

[0269] overview Example 2: A randomized controlled exploratory basket study evaluating multimodal multistable modification of attentional bias to normalize and improve cognition in adult patients with cancer or chronic psychogenic pain. Indications: Cancer and psychogenic chronic pain conditions

[0270] OBJECTIVE:To assess trends in effect compared with care as usual (CAU) or digital control groups on pain interference, cognition and related outcomes (attentional bias and general quality of life [QoL]).

[0271] Evaluation criteria

[0272] Exploratory Endpoints Change from baseline to weeks 2-8 in quality of life as measured by PROMIS-29+2 (Patient-Reported Outcomes Measurement Information System) Change from baseline to weeks 2-8 in pain severity and pain interference as measured by the Brief Pain Inventory (BPI) Change from baseline to weeks 2-8 in the Pain Catastrophizing Scale (PCS) Change from baseline to weeks 2-8 in indication-specific measures: Functional Assessment of Cancer Treatment-Cognitive Function in Cancer (FACT-Cog) Change from baseline to weeks 2-8 in computerized cognitive assessment Percentage of participants who saw improvement as measured by Global Rating Change (GRC) scores at weeks 2-8 ● Engagement with research apps, measured by metrics such as daily research app usage and daily time spent using research apps. Experience with the study app assessed through a user experience survey and optional qualitative interviews after the end of the treatment period Other exploratory endpoints may include the Functional Assessment of Chronic Illness Therapy-Fatigue scale (FACIT-Fatigue), the Functional Assessment of Cancer Therapy-General (FACT-G), and / or the Hospital Anxiety and Depression Scale (HADS). The FACIT-Fatigue is a 13-item scale with 5-point Likert-type scale questions. Scores are summed (2 questions are reverse scored). To account for missing scores, they are multiplied by 13 and divided by the number of questions answered. Higher scores indicate better quality of life. The FACT-G is a 27-item questionnaire with a 5-point Likert-type scale that assesses health-related quality of life in cancer patients with physical, social, emotional, and functional subscales. Values ​​are summed and some are reverse scored (all social and functional subscales and one question for the emotional subscale). All subscales are added together to obtain a total FACT-G score, with higher scores indicating better quality of life. The HADS is a 14-item questionnaire used to assess depression and anxiety, with higher scores in each subdomain indicating greater symptom severity.

[0273] Study design

[0274] Referring now to Figure 8 , a timeline is presented for a randomized controlled exploratory basket study to evaluate multimodal multistable modification of attentional biases aimed at normalizing attentional biases and improving cognition in adults with cancer or chronic psychogenic pain conditions.

[0275] Screening period (day -14 to day -1) Participants will be screened over a period of up to 14 days, including electronic informed consent. Assessments during this period will be carried out remotely according to the Schedule of Activities and Assessments (SoA). • Participants will be considered eligible if they meet all inclusion criteria and do not fall under any exclusion criteria, based on the investigator's assessment. • Screening and baseline visits may occur on the same day.

[0276] Baseline (Day 1) ● Participants will be contacted for a baseline visit to screen and verify eligibility and conduct identity verification. Assessment will be done as per the SoA. ● Eligible participants will be randomized at the virtual study visit on Day 1. Participants will be randomized 1:1 (study app:control) within cancer or psychogenic chronic pain condition cohorts. Participants randomized to the study app treatment arm will download and activate the app on their personal primary smartphone.

[0277] Intervention period ● Participants in the research app group will complete the app-based brain exercises for one to 30 minutes at least three times a week for two to eight weeks. ● Participants in the control group will receive either care as usual (CAU) or digital control and will not receive the study intervention. ● During the intervention period, both groups will be assessed weekly according to the SoA. ● Participants assigned to the study app group will complete a user experience survey at the end of the intervention period.

[0278] Follow-up period (up to 1-8 weeks) ● Participants complete follow-up assessments according to the SoA. ● Participants do not perform any activities within the study app. ● A portion of participants will participate in optional qualitative interviews between days 22 and 28.

[0279] Planned Number of Participants: At least 40 participants will be enrolled in this study.

[0280] Research participation criteria

[0281] Selection Criteria: Participants were eligible to take part in this study if they met all of the following criteria: 1. Fluent in written and spoken English and able to read, understand, and sign an informed consent form. 2. You reside in the United States. 3. Adults aged 22 to 65 years old. 4. Meet the indication-specific inclusion criteria as reported by the study participant with appropriate clinical documentation (provided to the study team upon request). 5. Have a valid email address and are willing and able to receive and reply to emails. 6. Internet access will be available for the duration of this study. 7. Have or be willing to open a valid bank account to receive research remuneration. 8. Willing and able to comply with study protocols and evaluations. 9. During the exam period, you will use your smartphone alone and will not share it with others. 10. Willingness and ability to receive Short Message Service (SMS) text messages and notifications on your smartphone. 11. You have headphones that work properly.

[0282] Exclusion Criteria: Participants who meet any of the following criteria are not eligible to participate in the study. 1. Have severe vision, dexterity, or cognitive deficits that, in the opinion of the researchers, would prevent them from participating in response time-based activities using the app. 2. Severe mental disorders with a history of psychiatric illness (e.g., schizophrenia, bipolar disorder, severe personality disorder). 3. History of psychiatric hospitalization in the past 6 months. 4. Participated in any research study (including studies of psychotherapy, mindfulness, cognitive training, or pharmacological treatment) in the past 3 months. 5. Initiation or change of disease-specific primary medication within 30 days prior to study entry. 6. Plan to introduce new treatments (including psychotherapy, mindfulness, cognitive training, and pharmacological therapy) during the study period (1-12 weeks). 7. Anticipating any changes to current pharmacological or psychotherapeutic treatment regimens during the study period (1-12 weeks). 8. Self-reported substance use disorder within the past year. 9. Severe neurological disorder compromising brain function (e.g., history of stroke, dementia, primary brain dysfunction, brain metastases, Alzheimer's disease, Parkinson's disease, history of significant head trauma with subsequent persistent neurological impairment, or known structural brain abnormality). 10. Mild, moderate, severe or significant unilateral or bilateral hearing loss.

[0283] Test product and application method DiNaMo 004

[0284] Eligible participants will download and install the study app onto their smartphone at the baseline visit (Day 1).

[0285] Treatment Regimen: Study App: Use at least 3 times per week for at least 2 weeks (1 to 30 minutes per day)

[0286] Study Duration: Participation in this study will last a maximum of six weeks. ● Screening period: up to 2 weeks ● Intervention period: 2-8 weeks ● Follow-up: up to 1-3 weeks

[0287] Sample size: At least 40 subjects with cancer and / or chronic psychogenic pain conditions. These sample sizes were sufficient to measure change relatively precisely.

[0288] Statistical Analysis: Changes from baseline to week 3 for PROMIS-29+2 all domains, BPI pain severity, BPI pain interference, PCS subcategory and total scores, and computerized cognitive assessment are summarized using descriptive statistics. Analysis of covariance (ANCOVA) models are performed to assess differences between the two treatment groups. The models include change from baseline as the dependent variable and treatment group, indication, and baseline value as covariates. 95% confidence intervals (CIs) and two-sided p-values ​​for the null hypothesis of no difference between the two groups are given. Least squares means (LS) of the treatment effects are given. In addition, LS means, 95% CIs, and p-values ​​for the null hypothesis of no change from baseline are given for each treatment group.

[0289] For SDMT and FACT-Cog, indication-specific, changes from baseline are summarized using descriptive statistics. In addition, 95% CIs and two-sided p-values ​​for the null hypothesis of no difference between treatment groups are given for the change from baseline to week 3 in each treatment group. CIs and p-values ​​are based on two-sample t-distributions.

[0290] The 95% CI for the change from baseline to week 3 in each group is given, as well as two-sided p-values ​​for the null hypothesis of no change from baseline using a one-sample (before and after) t-distribution.

[0291] Number and percentage of GRC-measured improvements (improvement is a score of ≥1) will be summarized by treatment group. Comparisons between treatment groups will be made using the Cochran-Mantel-Haenszel test stratified by indication.

[0292] For the remaining exploratory endpoints and safety parameters, only descriptive statistics will be used.

[0293] 2. Individual indications: Pathology of cancer and psychogenic chronic pain Evaluation criteria

[0294] Other disease-specific scales: ● Functional Assessment of Cognitive Function in Cancer Treatment (FACT-Cog)

[0295] Study participation criteria Selection criteria 1. Study participant reported a medical history of cancer (any stage) with appropriate clinical records (to be provided to the study team upon request). 2. Patients have completed at least 3 months of chemotherapy within 9 months to 5 years prior to screening. 3. Have had self-reported pain for at least the past 3 months and the pain began after cancer treatment.

[0296] Exclusion criteria 1. Self-reported clinical diagnosis of multiple sclerosis or breast cancer

[0297] 3. Activity and evaluation schedule The schedule of activities is given in Example 1.

[0298] 4. Introduction A. Multimodal multistable correction of bias As described above in Example 1, we utilize multimodal multistable correction of bias (or multimodal multistable bias correction, or MMBM).

[0299] B. Attentional bias Individuals with various indications, such as various types of cancer, tend to exhibit both pain and mood problems. These problems may be exacerbated by attentional biases associated with pain and threat-related stimuli. Individuals with chronic pain tend to pay attention to pain-related stimuli, which may further exacerbate their condition through fear avoidance. Avoiding stimuli or activities that are perceived to cause pain can destabilize the body, which may progress the disability and worsen the condition. With threat-related stimuli, anxious individuals often unconsciously seek out signs of the threat. This threat triggers a feedback loop that perpetuates feelings of anxiety. This includes indication-related stimuli. For example, cancer survivors who fear a recurrence of their cancer may have a bias for cancer-related stimuli. Similarly, pain and anxiety are highly comorbid, and because neural circuit changes are similar in both, targeting biases associated with both is likely to be synergistic. Finally, depressed individuals often exhibit attentional biases for negative emotional information, which may foster rumination and exacerbate symptoms. The overlap of these various attentional biases can be quite debilitating for patients.

[0300] Both cancer patients and survivors show attentional biases toward cancer-related words. Many studies also find evidence of biases toward threat and negative emotions. Attempts to change these unconscious associations have met with some success. Because cancer patients also experience pain and mood symptoms, multimodal, multistable modification of biases is expected to be highly relevant and meaningful to this patient population.

[0301] C. Cognitive impairment Cognitive impairment is common in several physical and psychiatric disorders. This may be due to presenting symptoms associated with the disease / disorder, or associated with the treatment of a specific disease (e.g., chemotherapy for cancer), or both. Cognitive impairment is also frequently associated with problems with emotion regulation and mood problems. The combination of cognitive deficits and mood symptoms can cause distress and disability for patients, negatively impact quality of life, and increase healthcare utilization.

[0302] In cancer patients, tumor activity and associated inflammatory processes, and / or cancer-related treatments can affect cognitive function. Cancer-related cognitive impairment occurs in up to 75% of cancer patients, and in up to 35% of patients who experience impairment, this can persist for months to years after treatment. As the number of cancer survivors increases, persistent cognitive impairment due to cancer and cancer treatment is likely to increase.

[0303] Fatigue is also a debilitating symptom for both indications and contributes greatly to cognitive problems. Fatigue is one of the most common cancer symptoms and is often the first symptom patients report to their healthcare provider. Fatigue can result from both treatments such as chemotherapy (which occurs in 75-100% of patients) or the disease itself (especially in the later stages). One study found that 37% of cancer survivors had not regained a satisfactory level of energy even after several years.

[0304] D. Binaural Beats In binaural beats, one tone frequency is played in each ear, and the detectable frequency difference between these two is called the "beat." The theory behind binaural beats is that rhythmic sensory stimulation may entrain neural oscillations, similar to non-invasive techniques such as transcranial magnetic stimulation and transcranial direct current stimulation. Previous studies have found that binaural beats have beneficial effects on depression and anxiety symptoms, memory, attention, cognition, fatigue, and pain sensation.

[0305] E. Research Applications (Apps) Multimodal multistable bias correction CT-100 Digital Neural Activation and Modulation (DiNaMo) components (e.g., Application 125) use implicit training to redirect and strengthen attention processes. This intervention not only helps improve cognitive performance, but also redirects attention bias and helps participants desensitize to painful stimuli. Preliminary studies have shown the success of computer cognitive training in cancer and retraining attention bias in pain, threat, and mood. Multimodal multistable correction of bias is likely to improve not only cognitive performance but also attention bias seen in cancer.

[0306] F. Care as Usual (CAU) or Digital Control The care as usual (CAU) control group will only undergo the assessment and will not use the study app. The digital control app group will download the digital control app. They will complete a version of the task designed to be inactive in the study application, which only involves selecting from a set of neutral words based on personal preference and does not include any attention-biasing capture stimuli. Additionally, all instances of multistable perception will be removed, including the removal of all auditory components.

[0307] G. Study Rationale Multimodal multistable modification of bias is a novel intervention that uses the principles of the multimodal neural reinforcement task (M-NET) to reduce symptoms related to cancer. Attentional bias towards different attention-capturing stimuli can exacerbate various symptoms in many different indications. For example, in some pathologies, patients may pay more attention to pain-related stimuli, which can lead to hypersensitivity. Similarly, hypersensitivity to threat-related stimuli exacerbates anxiety.

[0308] In multimodal multistable modification of bias, users are trained to redirect attention to positive stimuli instead of potentially distressing stimuli, such as pain- or threat-related stimuli. This is done in a novel format that utilizes multistable perception. Visual multistable perception, in the form of monocular rivalry, is used to implicitly retrain attentional bias. At the same time, auditory multistable perception, in the form of binaural beats, works synergistically to target fatigue symptoms while improving components of attentional bias.

[0309] The aim of this study is to evaluate the initial effects of DiNaMo components (investigative apps) on measures of attentional bias, attention disorders, and related outcomes (general quality of life [QOL]) in various pathologies, including cancer. Findings from this study may be used as components for future digital therapeutics.

[0310] H. CT-100 Platform The CT-100 platform offers interactive, software-based therapeutic components that may be used as part of multimodal treatments in future software-based prescriptive digital therapeutics. One class of CT-100 components are the DiNaMo components. The DiNaMo components target key nervous systems (including but not limited to systems related to sensation, perception, emotion, pain, attention, cognitive control, sociality, and self-processing) to optimally improve participants' health.

[0311] 3. Purpose and Endpoints The objectives of this study are as follows: To assess trends in effects compared with care as usual (CAU) or digital control groups on pain interference, cognition and related outcomes (attentional bias and general quality of life [QoL]). • To explore the feasibility of delivering a digital multimodal multistable bias-corrected visual search task (study app) at home, including participants’ engagement with and experience of the study app. ● Evaluating the safety of investigational apps.

[0312] Study endpoints correspond to those presented in Example 1.

[0313] 4. Study design A. Scientific basis for study design This study is designed to evaluate the initial effects of the multimodal multistable bias-correcting CT-100 component (a research app) on attentional bias and cognitive deficits compared to care as usual (CAU) or digital control.

[0314] Participants will be assessed based on validated standard participant assessment outcomes. Participant engagement with the study app will be assessed based on participant usage data captured within the study app. Participants will be assessed for safety throughout the duration of the study. Measures and assessments are described herein.

[0315] B. Definition of End of Study The end of the study is defined as the date of last contact or last attempted contact of the last participant who completed or withdrew from the study. In this study, participants who completed study assessments on Day 21 (+3) (Week 3) are defined as study completers.

[0316] 6. Study interventions and concomitant therapies A. Study interventions implemented The CT-100-D-004 study app (e.g., application 125) will be given to participants along with the study intervention.

[0317] B. CT-100 The study intervention to be evaluated is the multimodal multistable bias correction component of the CT-100, a digital mobile application. Participants randomized to this group will download and install the study app on their smartphone at the baseline visit (Day 1) and will use the study app daily for multimodal multistable bias correction training over the 2-8 week intervention period.

[0318] C. Control Participants randomized to the CAU or digital control group will complete only the study assessments over the 2-8 week intervention period. The digital control group will download the digital control app. They will complete a version of the task designed to be inactive in the study application, which only involves selecting from a set of neutral words based on personal preference and does not include attention-biasing capture stimuli. Additionally, all instances of multistable perception will be removed, including the removal of all auditory components.

[0319] D. Preparation / Handling / Storage / Accountability Detailed instructions for downloading, installing, activating, using, and disposing of the Research App are provided in CT-100-D-004 Research App Site Instructions for Use.

[0320] In general: 1. Only participants enrolled in the study will receive the study intervention. 2. Site staff made sure to download and activate the study app. 3. The research app will be automatically disabled after weeks 2-8. Site staff will inform participants who complete the study or terminate early to uninstall the study app.

[0321] E. Concomitant Therapy Participants will continue to use prescribed treatments while enrolled in the study, and will self-report any changes in all primary indication-related or psychoactive concomitant medications through the end of the follow-up period.

[0322] 7. Study Assessment and Procedures Study assessments and procedures, including their timing, are summarised in the SoA and previously described for Example 1.

[0323] 8. Statistical considerations The statistical considerations correspond to those discussed above in connection with Example 1.

[0324] 9. Conclusion Based on the results of Example 1, individuals receiving the treatment are expected to show improvement in at least one adaptation-related symptom as measured by the performance criteria described herein. The improvement in at least one adaptation-related symptom in the recipients is expected to be statistically significant compared to any improvement observed in the corresponding adaptation-related symptom in individuals receiving the digital control or CAU.

[0325] C. Network and Computing Environment Various operations described herein may be implemented on a computer system. FIG. 9 shows a simplified block diagram of a representative server system 900, a client computer system 914, and a network 926 that may be used to implement certain embodiments of the present disclosure. In various embodiments, the server system 900 or a similar system may implement the services or servers described herein, or portions thereof. The client computer system 914 or a similar system may implement the clients described herein. The system 100 described herein may be similar to the server system 900. The server system 900 may have a modular design incorporating many modules 902 (e.g., blades in a blade server embodiment), and although two modules 902 are shown, any number may be provided. Each module 902 may include one or more processing units 904 and local storage 906.

[0326] The one or more processing units 904 may include a single processor, which may have one or more cores, or multiple processors. In some embodiments, the one or more processing units 904 may include a general-purpose primary processor as well as one or more special-purpose co-processors, such as a graphics processor, digital signal processor, etc. In some embodiments, some or all of the processing units 904 may be implemented using customized circuitry, such as an application specific integrated circuit (ASIC) or a customer programmable grid array (FPGA). In some embodiments, such integrated circuits execute instructions stored within the circuitry itself. In other embodiments, the one or more processing units 904 may execute instructions stored in a local storage device 906. Any combination of any type of processor may be included in the one or more processing units 904.

[0327] The local storage 906 may include volatile storage media (e.g., DRAM, SRAM, SDRAM, etc.) and / or non-volatile storage media (e.g., magnetic or optical disks, flash memory, etc.). The storage media incorporated in the local storage 906 may be fixed, removable, or upgradeable, as desired. The local storage 906 may be physically or logically divided into various subunits, such as system memory, read-only memory (ROM), and permanent storage. The system memory may be a readable / writeable memory device, or a volatile readable / writeable memory, such as a dynamic random access memory. The system memory may store some or all of the instructions and data required by the one or more processing units 904 during execution. The ROM may store static data and instructions required by the one or more processing units 904. The permanent storage may be a non-volatile readable / writeable memory device that may store instructions and data even when the module 902 is powered down. As used herein, the term "storage medium" includes any medium that is capable of storing data indefinitely (albeit through overwriting, electrical disturbance, power loss, etc.) and does not include carrier waves or ephemeral electronic signals propagated over wireless or wired connections.

[0328] In some embodiments, local storage 906 may store one or more software programs executed by one or more processing units 904, such as an operating system and / or programs that implement various server functions, such as the functionality of system 100 or any other system described herein, or any other server(s) associated with system 100 or any other system described herein.

[0329] "Software" generally refers to a sequence of instructions that, when executed by one or more processing units 904, cause the server system 900 (or portions thereof) to perform various operations, thus defining one or more specific machine embodiments that execute and perform the operations of the software program. The instructions can be stored as firmware resident in a read-only memory for execution by one or more processing units 904, and / or as program code stored in a non-volatile storage medium that can be loaded into a volatile working memory. The software can be implemented as a single program or a collection of separate programs or program modules that interact as desired. From the local storage device 906 (or non-local storage device, described below), the one or more processing units 904 can retrieve program instructions to execute and data to process in order to perform the various operations described above.

[0330] In some server systems 900, multiple modules 902 may be interconnected via a bus or other interconnect 908 to form a local area network that supports communications between the modules 902 and other components of the server system 900. The interconnect 908 may be implemented using a variety of technologies, including server racks, hubs, routers, etc.

[0331] A wide area network (WAN) interface 910 may provide data communication capabilities between a local area network (e.g., via interconnect 908) and a network 926, such as the Internet. Other technologies may be used to communicatively couple the server system to the network 926, including wired technologies (e.g., Ethernet, IEEE 802.3 standard) and / or wireless technologies (e.g., Wi-Fi, IEEE 802.11 standard).

[0332] In some embodiments, the local storage device 906 is intended to provide working memory for one or more processing units 904, providing fast access to programs and / or data being processed while reducing traffic on the interconnect 908. Storage for larger amounts of data can be provided on a local area network by one or more mass storage subsystems 912 connectable to the interconnect 908. The mass storage subsystems 912 can be based on magnetic, optical, semiconductor, or other data storage media. Direct attached storage, storage networks, network attached storage, etc. can be used. Any data storage mechanism or other collection of data described herein as generated, consumed, or maintained by a service or server can be stored in the mass storage subsystem 912. In some embodiments, additional data storage resources are accessible (albeit potentially with increased latency) via the WAN interface 910.

[0333] The server system 900 may operate in response to requests received via the WAN interface 910. For example, one of the modules 902 may implement a management function and assign individual tasks to other modules 902 in response to received requests. Work allocation techniques may be used. Once a request is processed, a result may be returned to the requester via the WAN interface 910. Typically such operations may be automated. Additionally, in some embodiments, the WAN interface 910 may connect multiple server systems 900 together to provide a scalable system capable of managing large volumes of activity. Other techniques for managing server systems and server farms (collections of server systems collaborating with each other) may be used, including dynamic resource allocation and reallocation.

[0334] The server system 900 can interact with a variety of user-owned or user-operated devices over a wide area network such as the Internet. One example of a user-operated device is shown in Figure 9 as client computing system 914. The client computing system 914 can be implemented as a consumer device, such as, for example, a smartphone, other mobile phone, tablet computer, wearable computing device (e.g., smart watch, glasses), desktop computer, laptop computer, etc.

[0335] For example, client computing system 914 may communicate over a WAN interface 910. Client computing system 914 may include computer components such as one or more processing units 916, storage devices 918, network interfaces 920, user input devices 922, and user output devices 924. Client computing system 914 may be computing devices implemented in a variety of form factors, such as desktop computers, laptop computers, tablet computers, smartphones, other computing devices, wearable computing devices, etc.

[0336] The processing unit 916 and storage device 918 may be similar to the one or more processing units 904 and local storage device 906 described above. Appropriate devices may be selected based on the demands placed on the client computing system 914. For example, the client computing system 914 may be implemented as a "thin" client having limited processing capabilities or as a high performance computing device. The client computing system 914 may comprise program code executable by the one or more processing units 916 to enable various interactions with the server system 900.

[0337] The network interface 920 may provide a connection to a network 926, such as a wide area network (e.g., the Internet) to which the WAN interface 910 of the server system 900 is also connected. In various embodiments, the network interface 920 may include a wired interface (e.g., Ethernet) and / or a wireless interface implementing various wireless data communication standards, such as Wi-Fi, Bluetooth, or cellular data network standards (e.g., 3G, 4G, LTE, etc.).

[0338] User input device 922 may include any device (or devices) by which a user can send signals to client computing system 914 that can be interpreted by client computing system 914 as indicating a particular user request or information. In various embodiments, user input device 922 may include any or all of a keyboard, a touchpad, a touchscreen, a mouse or other pointing device, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, a microphone, and the like.

[0339] The user output devices 924 may include any device that enables the client computing system 914 to provide information to a user. For example, the user output devices 924 may include display-to-display shared images generated by or transmitted to the client computing system 914. Displays may incorporate a variety of image generating technologies, such as, for example, liquid crystal displays (LCDs), light emitting diode (LED) displays including organic light emitting diodes (OLEDs), projection systems, cathode ray tubes (CRTs), along with supporting electronics (e.g., digital-to-analog or analog-to-digital converters, signal processors, etc.). Some embodiments may include devices such as touch screens that function as both input and output devices. In some embodiments, other user output devices 924 may be provided in addition to or instead of a display. Examples include indicator lights, speakers, tactile "display" devices, printers, etc.

[0340] Some embodiments include electronic components, such as a microprocessor, storage devices, and memory, that store computer program instructions on a computer-readable storage medium. Many of the features described herein can be implemented as a process specified as a set of program instructions encoded on a computer-readable storage medium. These program instructions, when executed by one or more processing units, cause the one or more processing units to perform various operations indicated in the program instructions. Examples of program instructions or computer code include machine code produced by a compiler, or files containing higher level code that are executed by a computer, electronic component, or microprocessor using an interpreter. With appropriate programming, the one or more processing devices 904 and 916 can provide various functions to the server system 900 and the client computing system 914, including any of the functions described herein as being performed by a server or client, or other functions.

[0341] It will be understood that the server system 900 and the client computing system 914 are exemplary and that variations and modifications are possible. Computer systems used in connection with embodiments of the present disclosure may have other functionality not specifically described herein. Additionally, while the server system 900 and the client computing system 914 are described with reference to certain blocks, it should be understood that these blocks are defined for convenience of explanation and are not intended to imply a particular physical arrangement of components. For example, different blocks may be located in the same facility, in the same server rack, or on the same motherboard, but need not be so located. Furthermore, such blocks need not correspond to physically separate components. The blocks may be configured to perform various operations, for example, by programming a processor or providing appropriate control circuitry, and the various blocks may be reconfigurable or non-reconfigurable depending on how the initial configuration is obtained. The embodiments of the present disclosure may be realized in a variety of apparatuses, including electronic devices implemented using any combination of circuitry and software.

[0342] Although the present disclosure has been described with respect to specific embodiments, those skilled in the art will recognize that many variations are possible. The embodiments of the present disclosure can be implemented using a variety of computer systems and communication technologies, including but not limited to the specific examples described herein. The embodiments of the present disclosure can be implemented using any combination of dedicated components and / or programmable processors and / or other programmable devices. The various processes described herein can be performed by any combination of the same or different processors. Where a component is described as being configured to perform a particular operation, such configuration can be achieved, for example, by designing an electronic circuit to perform the operation, by programming a programmable electronic circuit (such as a microprocessor) to perform the operation, or by any combination thereof. Furthermore, while the above-described embodiments may refer to specific hardware and software components, those skilled in the art will recognize that different combinations of hardware and / or software components can also be used, and that a particular operation described as being implemented in hardware can also be implemented in software, or vice versa.

[0343] A computer program incorporating various features of the present disclosure can be encoded and stored on various computer-readable storage media. Suitable media include magnetic disks or tapes, optical storage media such as compact disks (CDs) or digital versatile disks (DVDs), flash memory, and other non-transitory media. A computer-readable medium encoded with a program code may be packaged with a compatible electronic device, or the program code may be provided separately from the electronic device (e.g., via internet download or as a separately packaged computer-readable storage medium).

[0344] Thus, although the disclosure has been described in terms of specific embodiments, it will be understood that the disclosure is intended to cover all modifications and equivalents that fall within the scope of the following claims.

Claims

1. 1. A method of presenting multimodal stimuli to address symptoms associated with a pathology, comprising: identifying, by a computational system, (i) a first visual stimulus associated with a medical condition and (ii) a second visual stimulus to address a medical condition of the user; presenting, by the computing system via a display, the first visual stimulus at least partially overlaid with the second visual stimulus to prompt the user to interact with the display; detecting, by the computing system, a response identifying an interaction associated with either the first visual stimulus or the second visual stimulus; generating, by the computing system, an auditory stimulus that includes one or more portions indicative of feedback based on the response; and playing, by the computing system, the auditory stimuli via a transducer to provide the feedback to the user about the response.

2. determining, by the computing system, that the response is correct based on the interaction associated with the second visual stimulus to distract the user from the pathological condition; 2. The method of claim 1, wherein the step of generating an auditory stimulus by the computing system further comprises the step of adding at least one portion to the auditory stimulus to provide positive reinforcement in response to the determination that the response is correct.

3. determining, by the computing system, that the response is incorrect based on the interaction associated with the first visual stimulus associated with the disease state; 2. The method of claim 1, wherein the step of generating an auditory stimulus by the computing system further comprises removing at least one portion from the auditory stimulus to provide a negative attenuation in response to the determination that the response is incorrect.

4. (i) assigning, by the computing system, the first visual stimuli to a first type of interaction and (ii) assigning, by the computing system, the second visual stimuli to a second type of interaction; 2. The method of claim 1, wherein the step of presenting via a display further comprises: (i) presenting the first visual stimulus along with a first indicator for identifying the first type of interaction; and (ii) presenting the second visual stimulus along with a second indicator for identifying the second type of interaction.

5. selecting, by the computing system, a difficulty level from a plurality of difficulty levels based on a rate of correct responses from a previous presentation of a visual stimulus, each of the plurality of difficulty levels defining one or more visual features; and modifying, by the computing system, the presentation of the first visual stimulus and the second visual stimulus according to the one or more visual features and in accordance with the one difficulty level.

6. generating, by the computing system, an auditory stimulus further comprises generating the auditory stimulus to include (i) a first element played to a first ear of the user and (ii) a second element played to a second ear of the user; 2. The method of claim 1, wherein the step of playing the auditory stimuli via a transducer further comprises presenting the first element to the first ear of the user via a first speaker and presenting the second element to the second ear via a second speaker.

7. 2. The method of claim 1, wherein the interaction includes orienting the display toward a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus.

8. The method of claim 1 , further comprising modifying, by the computing system, visual features of one of the first visual stimulus or the second visual stimulus based on the response.

9. 2. The method of claim 1 , wherein the step of playing the auditory stimulus via a transducer further comprises playing at least one portion of the one or more portions of the auditory stimulus at least partially simultaneously with the presentation of the first visual stimulus and the second visual stimulus.

10. receiving, by the computing system via an interface, a user selection of at least one property from a plurality of properties for the auditory stimulus; The method of claim 1 , wherein the step of playing the auditory stimulus via a transducer further comprises generating the auditory stimulus according to the at least one property.

11. receiving, by the computing system via an interface, a list identifying a plurality of words, the plurality of words including a first subset of words and a second subset of words associated with the disease condition; 2. The method of claim 1, wherein the step of identifying by a computational system to address a pathology further comprises selecting the first visual stimulus from the first subset of words and the second visual stimulus from the second subset of words.

12. The method of claim 1 , wherein the user is taking a medication to address the condition associated with at least one of cancer or multiple sclerosis at least partially concurrently with the session.

13. 1. A system for presenting multimodal stimulation to reduce symptoms associated with a pathology, comprising: A computing system having one or more processors coupled to a memory, the computing system comprising: identifying (i) a first visual stimulus associated with a medical condition and (ii) a second visual stimulus to address a medical condition of the user; presenting the first visual stimulus via a display at least partially superimposed on the second visual stimulus to instruct the user to interact with the display; detecting a response identifying an interaction associated with either the first visual stimulus or the second visual stimulus; generating an auditory stimulus including one or more portions indicative of feedback based on the response; a system configured to play the auditory stimuli via a transducer to provide the user with the feedback on the response.

14. The computing system further comprises: determining that the response is correct based on the interaction associated with the second visual stimulus to direct the user away from the pathological condition; 14. The system of claim 13, configured to add at least one portion to the auditory stimulus to provide positive reinforcement in response to the determining that the response is correct.

15. The computing system further comprises: determining that the response is incorrect based on the interaction associated with the first visual stimulus associated with the medical condition; 14. The system of claim 13, configured to remove at least one portion from the auditory stimulus to provide a negative attenuation in response to the determination that the response is incorrect.

16. The computing system further comprises: (i) assigning the first visual stimulus to a first type of interaction and (ii) assigning the second visual stimulus to a second type of interaction; 14. The system of claim 13, configured to: (i) present the first visual stimulus along with a first indicator for identifying the first type of interaction; and (ii) present the second visual stimulus along with a second indicator for identifying the second type of interaction.

17. The computing system further comprises: selecting a difficulty level from a plurality of difficulty levels based on a percentage of correct responses from a previous presentation of the visual stimulus, each of the plurality of difficulty levels defining one or more visual features; 14. The system of claim 13, configured to modify presentation of the first visual stimulus and the second visual stimulus according to the one difficulty level using the one or more visual features.

18. The computing system further comprises: generating the auditory stimuli to include (i) a first element played to a first ear of the user and (ii) a second element played to a second ear of the user; 14. The system of claim 13, configured to present the first element to the first ear of the user via a first speaker and the second element to the second ear via a second speaker.

19. 14. The system of claim 13, wherein the interaction includes orienting the display toward a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus.

20. 14. The system of claim 13, wherein the computing system is further configured to modify visual features of one of the first visual stimulus or the second visual stimulus based on the response.

21. 14. The system of claim 13, wherein the computing system is further configured to play at least a portion of the one or more portions of the auditory stimulus at least partially simultaneously with the presentation of the first visual stimulus and the second visual stimulus.

22. The computing system further comprises: receiving, via the interface, a selection by a user of at least one property from a plurality of properties for the auditory stimulus; The system of claim 13 , configured to generate the auditory stimulus according to the at least one property.

23. The computing system further comprises: receiving, via an interface, a list identifying a plurality of words including a first subset of words and a second subset of words associated with the condition; 14. The system of claim 13, configured to select the first visual stimulus from the first subset of words and the second visual stimulus from the second subset of words.

24. 14. The system of claim 13, wherein the user is taking a medication to address the condition associated with at least one of cancer or multiple sclerosis at least partially concurrently with the session.

Images