Systems and methods for detecting and alleviating neural deficits using brain imaging data

Abstract

Disclosed herein are systems and methods for assessing the molecular (e.g., brain reward system molecules) causes underlying depressive disorders and developing treatment plans based on the identified molecular causes. In one or more examples, the systems and methods described herein can utilize any combination of brain imaging techniques, subjective emotional data obtained from the patient, and / or one or more algorithms for converting emotional states into brain reward system molecules (e.g., neurotransmitters) to determine the molecular causes underlying a patient's depressive disorder. Once the molecular causes underlying a patient's depressive disorder have been determined, a treatment plan, including both behavioral and pharmacological aspects, can be selected based on the identity and level of deficiency of the reward system molecules determined to be deficient.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of U.S. Provisional Application No. 63 / 369,748, filed July 28, 2022, the entire contents of which are incorporated herein by reference.

[0002] The present disclosure relates to systems and methods for identifying the underlying molecular causes of depressive disorders using brain imaging technology, subjective emotional data, techniques for identifying distinct regions of interest that indicate distinct positive emotions, and techniques for translating recorded emotional states into brain reward system molecules. [Background technology]

[0003] Mental health is increasingly recognized as something that deserves the same level of consideration as physical health. Today, it is estimated that more than 80% of the world's population suffers from depression, anxiety, or addiction at least once in their lifetime. This poor mental health has significant implications for society as a whole. Mental health problems can lead to increased crime, higher suicide rates, and even reduced productivity. Therefore, improving the mental health of the entire population not only benefits individuals with improved mental health, but also benefits society.

[0004] Recognizing the importance of mental health, many approaches to improving it have been proposed and applied. For example, philosophical, psychological, technological, and neuroscientific approaches to improving mental health have been implemented individually, focusing only on a single aspect of the illness (rather than holistically), with mixed success. Many of these approaches have failed to improve mental health or provided only marginal improvements. The incidence and prevalence of depressive disorders have increased dramatically in recent years, affecting over 260 million people worldwide with a lifetime incidence rate exceeding 75%. The efficacy and effectiveness of available antidepressants has historically been very low, with over 70% of patients experiencing no improvement or even progressing to a more severe disease state. This problem is further exacerbated by significant deterioration of the condition after discontinuation of antidepressants and significantly higher suicide rates in certain patient groups. Basic research has provided evidence that depression is caused by one or more dysfunctional reward systems. However, precise methods for identifying the molecular basis for targeted interventions and leveraging it for personalized treatment are lacking. Therefore, available pharmacological and behavioral treatments cannot be adequately matched to the underlying causes of the disease, leading to ineffective treatment. Currently approved and used treatments often do not adequately address the underlying molecular disorder, and there is a significant risk that they may actually worsen the disease over time. Summary of the Invention

[0005] Accordingly, systems and methods are provided herein for assessing the molecular (e.g., brain reward system molecules) causes underlying depression and creating a treatment plan based on the identified molecular causes. In one or more examples, the systems and methods described herein can determine the molecular causes underlying a patient's depression using any combination of brain imaging techniques, subjective emotional data obtained from the patient, and / or one or more algorithms for converting emotional states into brain reward system molecules (e.g., neurotransmitters). In one or more examples, the subjective emotional data can be collected or received from the patient through an initial interview or other compilation of master data regarding the patient's current and / or past mental state. In one or more examples, the subjective emotional data can be systematically collected using, for example, one or more of the techniques described in U.S. Patent Application No. 17 / 389,023, the entire contents of which are incorporated herein by reference. In one or more examples, the initial interview or compilation of master data can include an assessment of the patient's actual emotional well-being state using a self-assessment questionnaire of subjective well-being. In one or more examples, the initial interview or compilation of master data can include an assessment of the patient's actual depression state using any clinical depression assessment questionnaire (e.g., HAMD17 or any other similar depression assessment questionnaire) that allows for classification of mental state. In one or more examples, the patient's answers to the questionnaire or interview questions can be used to determine a deficiency of one or more neurotransmitters (e.g., molecules) in the patient's brain.

[0006] In one or more examples, the systems and methods described herein can also include applying one or more algorithms to convert emotional data (e.g., subjectively reported emotional data) in a patient's recorded memories and responses to various events into neurotransmitter levels (e.g., reward system molecules), thus enabling identification of neurotransmitter deficiencies. In one or more examples, the algorithm inputs the patient's emotional responses to everyday events and activities and converts the events / responses into one or more neurotransmitter levels, thus allowing identification of one or more deficiencies in neurotransmitter levels.

[0007] In one or more examples, the systems and methods described herein may include using brain imaging techniques, such as functional magnetic resonance imaging (fMRI) and / or other similar techniques, to determine deficiencies in neurotransmitter levels in a patient's brain. In one or more examples, a patient's brain may be imaged in real time while the patient is randomly exposed to pictures and / or music that have emotional significance to the patient and are therefore likely to trigger reward center activity in the patient's brain. In one or more examples, signal intensity data and / or 3D location of brain activity from the brain scan may be used to identify distinct regions of interest in the brain that may correlate with distinct emotions and / or reward system molecules (e.g., neurotransmitters).

[0008] In one or more examples, once the underlying molecular causes of depression are identified (using any combination of the techniques described above), the systems and methods described herein can create personalized anti-depression prevention and / or treatment protocols specifically tailored to the identified neurotransmitter deficiencies.

[0009] In some embodiments, a first method for treating a neurological disorder is provided, the first method including: receiving information related to a patient, the received information including information regarding one or more past events involving the patient and one or more emotions associated with the one or more events; determining levels of one or more reward molecules in the patient based on the received information related to the patient; receiving one or more scans of the patient's brain; determining levels of one or more reward molecules in the patient based on the received one or more scans of the patient's brain; and determining one or more reward molecule deficiencies in the user based on the determined levels of one or more reward molecules in the patient based on the received information related to the patient and based on the determined levels of one or more reward molecules in the patient based on the received one or more scans of the patient.

[0010] In some embodiments of the first method, the method includes selecting a predetermined treatment regimen for the determined one or more reward molecule deficiencies based on the identity of each reward molecule deficiency.

[0011] In some embodiments of the first method, the identity of the reward molecule deficiency is selected from the group consisting of dopamine, serotonin, testosterone, oxytocin, cannabinoids, and opioids.

[0012] In some embodiments of the first method, determining levels of one or more reward molecules for the patient based on the received information related to the patient includes applying the received information related to the patient to a positive emotion versus neurotransmitter (PE-NT) matrix.

[0013] In some embodiments of the first method, the received one or more scans of the patient's brain include real-time functional magnetic resonance imaging (rt-fMRI) scans.

[0014] In some embodiments of the first method, the received one or more scans of the patient's brain include an electroencephalogram (EEG) scan.

[0015] In some embodiments of the first method, the received one or more brain scans are obtained using a method that includes exposing the patient to one or more stimuli, determining one or more locations in the brain where signals are produced in response to the stimuli, and determining a signal strength associated with each location in the brain where a signal is produced in response to the stimuli.

[0016] In some embodiments of the first method, determining one or more reward molecule levels in the patient based on the received one or more scans of the patient's brain includes associating the one or more determined locations in the brain where a signal is produced in response to the stimulus with one or more types of reward molecules, and determining the one or more reward molecule levels in the patient based on the determined signal strength associated with each location in the brain where a signal is produced in response to the stimulus.

[0017] In some embodiments of the first method, the one or more emotions associated with the one or more events of receiving the information related to the patient include emotions from a group including enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, attachment, amusement, joy, and gratitude.

[0018] In some embodiments of the first method, the received information related to the patient includes responses of the patient to one or more questionnaires configured to diagnose depression in the patient.

[0019] In some embodiments, a second method for identifying and treating a neurological deficiency is provided, the method being executed by a system comprising one or more processors, the second method including: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotional intensity for each of one or more emotions, respective temporal information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimuli to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters for the patient based on the measured brain activity of the patient; and identifying a neurological deficiency related to at least a first neurotransmitter in the patient based at least in part on the determined levels of the plurality of neurotransmitters for the patient.

[0020] In some embodiments, the second method includes identifying a subset of the plurality of patient memories associated with a positive neurological response indicated by the brain activity of the patient based on the memory information and based on the identified neurological deficiency; identifying a first aspect that is common across a plurality of memories based on the identified subset of the plurality of patient memories and based on the respective metadata indicative of an aspect of the identified subset; and generating and providing a personalized treatment plan for the patient that includes an indication of the first aspect.

[0021] In some embodiments of the second method, identifying the neurological deficiency includes generating a tentative indicator of the neurological deficiency based on the determined neurotransmitter levels of the patient, and applying one or more rule sets based on pharmacological and / or clinical biochemical information about the patient to determine that the tentative indicator of neurological deficiency should not be rejected. Provisional IndicatorsProvisional Indicators

[0022] In some embodiments of the second method, identifying the neurological deficiency includes generating a tentative indicator of neurological deficiency based on the determined neurotransmitter levels of the patient, and applying one or more rule sets based on the memory information about the patient, including by comparing emotional intensity information about the patient to emotional intensity threshold information to determine that the tentative indicator of neurological deficiency should not be rejected.

[0023] In some embodiments of the second method, identifying the neurological deficiency includes generating a tentative indicator of the neurological deficiency based on the determined neurotransmitter levels of the patient, and applying one or more rule sets based on the memory information of the patient, including by analyzing changes in emotional intensity information of the patient over time, to determine that the tentative indicator of the neurological deficiency should not be rejected.

[0024] In some embodiments of the second method, identifying the neurological deficiency includes generating a tentative indicator of neurological deficiency based on the determined neurotransmitter levels of the patient, and applying one or more rule sets based on the memory information for the patient, including by applying the memory information to a positive emotion versus neurotransmitter (PE-NT) matrix to determine that the tentative indicator of neurological deficiency should not be negated. Provisional IndicatorsProvisional Indicators

[0025] In some embodiments of the second method, the first neurotransmitter is selected from the group consisting of dopamine, serotonin, testosterone, oxytocin, a cannabinoid, and an opioid.

[0026] In some embodiments of the second method, measuring the patient's brain activity includes using functional magnetic resonance imaging (fMRI) scanning.

[0027] In some embodiments of the second method, the fMRI scan is a 7 Tesla fMRI scan.

[0028] In some embodiments of the second method, measuring the patient's brain activity includes using an electroencephalogram (EEG) scan.

[0029] In some embodiments of the second method, measuring brain activity of the patient includes using functional near-infrared spectroscopy (fNIRs).

[0030] In some embodiments of the second method, determining the plurality of neurotransmitter levels of the patient based on the measured brain activity of the patient includes: determining one or more locations in the brain from which signals are measured in response to the stimulation; determining one or more signal strengths associated with each of the one or more brain locations based on the measured brain activity of the patient; and determining the plurality of neurotransmitter levels based at least in part on the determined one or more locations and the determined one or more signal strengths.

[0031] In some embodiments of the second method, determining the plurality of neurotransmitter levels includes comparing the determined signal intensity for the determined location to a threshold signal intensity level for that location.

[0032] In some embodiments of the second method, the plurality of stimuli presented to the patient are analyzed based on the one or more emotions associated with the memories associated with the stimuli as indicated in the received information, and determining the one or more locations within the brain is based at least in part on the one or more emotions as indicated in the received information.

[0033] In some embodiments of the second method, the one or more emotions include emotions from the group including enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, affection, amusement, joy, and gratitude.

[0034] In some embodiments, a system for identifying and treating a neurological deficiency is provided, the system comprising one or more processors configured to cause the system to: receive information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotional intensity for each of one or more emotions, respective temporal information, and respective metadata indicative of an aspect of the memory; provide a plurality of stimuli to the patient, each of the plurality of stimuli respectively associated with one or more of the patient memories; measure brain activity of the patient while providing the stimuli to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determine levels of a plurality of neurotransmitters for the patient based on the measured brain activity of the patient; and identify a neurological deficiency related to at least a first neurotransmitter in the patient based at least in part on the determined levels of the plurality of neurotransmitters for the patient.

[0035] In some embodiments, a non-transitory computer-readable storage medium storing instructions for identifying and treating a neurological deficiency is provided, the instructions including instructions configured, when executed by one or more processors of a system, to cause the system to: receive information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotional intensity for each of one or more emotions, respective temporal information, and respective metadata indicative of an aspect of the memory; provide a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measure brain activity of the patient while providing the stimuli to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determine levels of a plurality of neurotransmitters for the patient based on the measured brain activity of the patient; and identify a neurological deficiency related to at least a first neurotransmitter in the patient based at least in part on the determined levels of the plurality of neurotransmitters for the patient.

[0036] Any one or more of the features of the above-listed embodiments may be combined, in whole or in part, with each other and / or with any other disclosure herein. [Brief explanation of the drawings]

[0037] [Figure 1] FIG. 1 illustrates an exemplary process for determining a molecular deficiency in a patient's brain, according to an example of the present disclosure.

[0038] [Figure 2] FIG. 2 illustrates an exemplary neurotransmitter level calculation according to an example of the present disclosure.

[0039] [Figure 3] FIG. 3 shows an illustrative process for determining neurotransmitter levels in a patient's brain, according to an example of the present disclosure.

[0040] [Figure 4] FIG. 4 illustrates an exemplary process for determining a treatment plan based on a determined molecular deficiency, according to an example of the present disclosure.

[0041] [Figure 5A] , [Figure 5B] 5A-5B illustrate an exemplary method for identifying and treating a neurological deficit.

[0042] [Figure 6A] , [Figure 6B] , [Figure 6C] , [Figure 6D] , [Figure 6E] , [Figure 6F] 6A-6F show exemplary brain scans showing regions of interest and correlated emotions, reward systems, and / or neurotransmitters.

[0043] [Figure 7A] , [Figure 7B] , [Figure 7C] 7A-C illustrate exemplary calculations performed on stored information.

[0044] [Figure 8] FIG. 8 illustrates an example of a computing device according to one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0045] In the following description of the present disclosure and embodiments, reference is made to the accompanying drawings, in which it is shown, by way of illustration, specific embodiments which may be practiced. It is to be understood that other embodiments and examples may be practiced and changes may be made without departing from the scope of the present disclosure.

[0046] It should further be understood that, as used in the following description, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that, as used herein, the term "and / or" refers to and encompasses any and all possible combinations of one or more of the associated listed items. It should also be understood that the terms "includes," "including," "comprises," and / or "comprising," as used herein, specify the presence of stated features, integers, steps, operations, elements, components, and / or units, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, units, and / or groups thereof.

[0047] Some portions of the detailed descriptions which follow are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self-consistent sequence of steps (instructions) leading to a desired result, the steps being those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical, magnetic, or optical signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It is sometimes convenient, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. Further, it is also convenient at times, without loss of generality, to refer to specific arrangements of steps requiring physical manipulations of physical quantities as modules or code devices.

[0048] However, all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless otherwise specified, as will be apparent from the description below, throughout the description, descriptions utilizing terms such as "processing," "computing," "calculating," "determining," "displaying," and the like, will be understood to refer to operations and processes of a computer system or similar electronic computing device that manipulate and transform data represented as physical (electronic) quantities in the computer system memory or registers or other such information storage, transmission, or display device.

[0049] Certain aspects of the present disclosure include process steps and instructions described herein in the form of algorithms. It should be noted that the process steps and instructions of the present disclosure may be implemented in software, firmware, or hardware, and if implemented in software, they may be downloaded to reside on and operate from different platforms for use by various operating systems.

[0050] This disclosure also relates to devices for performing the operations herein. The devices may be specially configured for the required purposes, or may include a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such computer programs may be stored on a non-transitory computer-readable storage medium, such as any type of disk, including, but not limited to, a floppy disk, an optical disk, a CD-ROM, a magneto-optical disk, a read-only memory (ROM), a random-access memory (RAM), an EPROM, an EEPROM, a magnetic or optical card, an application-specific integrated circuit (ASIC), or any type of medium suitable for storing electronic instructions, each coupled to a computer system bus. Furthermore, the computers referred to herein may include a single processor or may be architectures employing multiple processor designs to increase computing power.

[0051] The methods, devices, and systems described herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will appear from the following. Additionally, the present disclosure is not described with reference to any particular programming language. It will be understood that a variety of programming languages may be used to implement the teachings of the present disclosure as described herein.

[0052] Depression and other neurological disorders often result from a dysfunctional reward system in the patient's brain, which is often unable to produce the appropriate brain reward system molecules associated with a stable mood. Patients are often prescribed antidepressants to treat mood disorders, but such treatments often produce unsatisfactory results; patients often experience no improvement and, in some cases, their condition worsens when they eventually discontinue the medication. While it is known that a deficiency in specific brain reward system molecules can be the underlying cause of certain mood disorders, there is a lack of accurate identification of which neurotransmitters / molecules are deficient and then using such knowledge to develop a treatment plan for patients. This deficiency means that behavioral and pharmacological treatments for mood disorders cannot match the underlying cause of the mood disorder, resulting in poorer outcomes for patients with mood disorders.

[0053] As mentioned above, the first step in generating effective treatments (behavioral and pharmacological) for the treatment of mood disorders may be to accurately identify any deficiencies in reward molecules that may be the underlying cause of the mood disorder. For example, mood disorders (e.g., depression) can often be associated with deficiencies in various reward molecules in the brain, including, but not limited to, dopamine, serotonin, testosterone, oxytocin, cannabinoids, and opioids. Detecting deficiencies in these reward molecules can be difficult. Therefore, as described in detail below, a method for detecting reward molecule deficiencies is presented that can combine various diagnostic tools to accurately detect reward molecule deficiencies.

[0054] 1 shows an illustrative process for determining molecular deficiencies in a patient's brain, according to examples of the present disclosure. In one or more examples, process 100 of FIG. 1 can begin at step 102, in which information about the patient's psychiatric status is received. In one or more examples, the received information can include the patient's responses to one or more entry interviews, in which the patient is asked a series of questions (either verbal or written) regarding their emotional well-being, their actual state of depression through the use of a Hamilton Depression Rating Questionnaire, such as the Hamilton Depression Rating Scale (HAMD17) or any comparable diagnostic questionnaire, and their substance dependence / addiction / abuse or behavioral dependence / addiction / abuse.

[0055] In one or more examples, the entry interview / questionnaire responses received in step 102 can provide a first indication of potential reward system deficiencies and / or unsatisfied needs. In one or more examples, in step 102, the patient / participant can also be guided to assess and record the best positive memories of their life by assessing the full range of positive emotions and selecting representative pictures or music that trigger memory recall. In one or more examples, this range can include, but is not limited to, one or more of the following emotions: enthusiasm, sexual desire, pride / recognition, nurturing love (also called familial love), satisfaction, attachment love (also called friendship love), amusement, joy, and gratitude. In one or more examples, for each emotion, the patient / participant can be asked to record a predetermined number of best memories from their life that correlate with each emotion. In one or more examples, information about the patient's current memories can also be received in addition to past memories that correlate with the emotions. For example, in one or more examples, a patient may be asked to rate and record real-time memories for a predetermined period of time (e.g., 30 days) and may be asked to record memories that elicit emotions associated with emotional well-being. In one or more examples, a user may be asked to characterize the emotions felt (e.g., enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, recreational love, joy, and gratitude) and the level of intensity at which each emotion was felt.

[0056] In one or more examples, the information received in step 102 can be used to determine reward system molecule deficiencies. For example, using the information about the patient received in step 102, process 100 in step 104 can translate the user's experiences and emotional responses to one or more experiences into reward molecule and reward system activity using one or more algorithms specifically configured to translate emotions associated with the experiences into activity of reward system molecules, with the goal of identifying any gaps in the reward system molecules.

[0057] One exemplary algorithm that can be used to convert emotions recorded by a user (also referred to herein as a "patient") into neurotransmitter levels (e.g., reward system molecules) can include the use of a positive emotion versus neurotransmitter (PE-NT) matrix, which can convert the quantified positive emotions derived in step 102 into respective amounts of neurotransmitters associated with positive emotions. In one or more examples, for purposes of this disclosure, the term "neurotransmitter" can refer to specific neurotransmitters associated with the brain's reward system. In one or more examples, for purposes of this disclosure, the calculation can be based on the user information received in step 102.

[0058] FIG. 2 illustrates an exemplary neurotransmitter level calculation according to an example of the present disclosure. The example of FIG. 2 illustrates an exemplary PE-NT matrix 202 that can be used to calculate the amount of a particular neurotransmitter based on a patient's recorded emotions and the intensity of the emotion correlated with a particular memory or event. In one or more examples, the rows of the PE-NT matrix 102 can represent emotion categories such as enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, amusement, joy, and gratitude. In one or more examples, the columns of the PE-NT matrix 202 can represent brain reward system molecules associated with positive emotions (dopamine, testosterone, serotonin, oxytocin, cannabinoids, and opioids). A "1" in the matrix can indicate that a particular neurotransmitter is associated with that particular emotion. A "0" in the matrix can indicate that a particular neurotransmitter is not associated with that particular emotion.

[0059] In one or more examples, the PE-NT matrix 202 can be used to calculate the amount of neurotransmitters associated with an activity. Calculation 204 shows an example calculation. In one or more examples, calculation 204 can include a PE rating column indicating the ratings provided by the user in step 102 of FIG. 1 . For example, when rating emotions associated with a particular memory or event, the user can rate their enthusiasm during the event as mild (indicating lower than average, but still present), resulting in a quantified rating of 3. In the same example, in the PE rating column, the user can rate their satisfaction as 5, which is average. To calculate the amount of a neurotransmitter, the calculation can multiply the rating by the PE-NT matrix to generate a number (numeric value) associated with the amount of a particular neurotransmitter. For example, as shown in PE-NT matrix 202, enthusiasm can be associated with the release of dopamine. Looking at calculation 204, the PE rating for enthusiasm (provided by the user) is 3. That value is multiplied by 1 under the dopamine column, resulting in a value of 3. Thus, with respect to the enthusiasm felt by the user as represented by the PE rating, the dopamine levels associated with that enthusiasm are quantified at 3. In one or more instances, the remaining columns remain at 0 because these brain reward system molecules are not associated with enthusiasm.

[0060] In one or more examples, each and every positive emotion can be multiplied by the PE rating to arrive at a value for each neurotransmitter. For example, satisfaction was rated 5 by the user, and therefore, since satisfaction is associated with dopamine, oxytocin, and cannabinoids, each of those factors can be set to 5 (multiplying 5 x 1). Once a calculation is made for each emotion in each neurotransmitter, the calculation can add up the totals for each neurotransmitter. Referring to the example calculation 204 of FIG. 2, for dopamine, the dopamine levels for each emotion can be added up to 16. For serotonin, the calculation adds up to 4, and so on for each neurotransmitter.

[0061] Once each neurotransmitter is tallied, each tally can be multiplied by the duration of the event (assuming the user provided that information) to determine the total neurotransmitter activity associated with the event. Using the dopamine example, the sum would be 16 (as above), and multiplying that sum by 3.25 (e.g., 3.25 hours, the duration of the event indicated by the user) would result in a sum of 52 for dopamine. Individual levels for each neurotransmitter can be similarly calculated for a given memory. (In some embodiments, multiplication by time may not be used; in some embodiments, neurotransmitter levels may be normalized to 1 hour, e.g., multiplied by 1.)

[0062] The neurotransmitter level determinations for each memory may be aggregated. The aggregated neurotransmitter level data may be used to calculate a neurotransmitter deficiency. For example, a neurotransmitter deficiency may be identified by comparing neurotransmitter levels over time using the aggregated neurotransmitter level data.

[0063] In one or more examples, the exemplary algorithm described above with respect to Figure 2 for translating emotional responses to memories and events into reward molecule / neurotransmitter levels is for illustrative purposes only and should not be construed as limiting the present disclosure. In one or more examples, any algorithm capable of translating emotional experiences into neurotransmitter levels can be utilized in step 102 of process 100.

[0064] In one or more examples, returning to the example of FIG. 1 , to gather further data regarding reward molecule levels in the brain, process 100 may include step 106 of using brain imaging to determine whether there is a reward molecule deficiency associated with the patient. In one or more examples, as described in further detail below, the patient may be presented with various stimuli (e.g., music and pictures) known to elicit positive emotions from users. While the patient is being stimulated, in one or more examples, the patient's brain may be scanned to record their brain activity. In one or more examples, the brain activity observed in the scan may be used to determine the reward molecule deficiency. In one or more examples, the exemplary calculation described above with respect to FIG. 2 may be refined (improved) over time using feedback information from brain imaging scan data (described in further detail below), e.g., information gathered from the brain scan may be used to refine a multiplier used in the calculation.

[0065] FIG. 3 illustrates an exemplary process for determining (assessing) a molecular deficiency in a patient's brain using brain imaging, according to examples of the present disclosure. In one or more examples, process 300 of FIG. 3 can be utilized to identify a reward molecule deficiency from brain image data. In one or more examples, process 300 can be used in conjunction with, alternatively to, and / or in parallel with, determining a reward molecule deficiency based on self-reported patient data and / or other patient data other than brain scan data, as described in further detail below. In one or more examples, illustrated process 300 can begin at step 302, where a brain scan of the patient is initialized. In one or more examples, a "brain scan" can refer to multiple brain diagnostic tools configured to record brain activity in real time or near real time. For example, in one or more examples, brain scanning can include functional magnetic resonance imaging ("fMRI"), real-time functional magnetic resonance imaging ("rt-fMRI"), real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF), whole-scalp electroencephalography ("EEG"), and / or whole-scalp functional near-infrared spectroscopy (fNIRS). The above brain imaging procedures / tools are meant as examples only and should not be construed as limiting the present disclosure. Any tool / method configured to measure brain activity in response to a stimulus can be considered a "brain scan" within the scope of the present disclosure.

[0066] In one or more examples, once the brain scan is initialized in step 302, process 300 can proceed to step 304, where the patient is exposed to stimuli previously identified by the patient as eliciting positive emotions associated with the release of reward-active molecules in the brain. In one or more examples, the stimuli can include auditory verbal stimuli, such as spoken or recorded messages, displayed textual written verbal stimuli, music (e.g., audio stimuli), and / or photographs / videos (e.g., photos of people or places). The stimuli can be related to the patient's positive memories either directly or indirectly (e.g., by including common content (e.g., common people or places) as the patient's memories). In one or more examples, the stimuli applied in step 304 can be extracted from the patient data received in step 102 of process 100 of FIG. 1.

[0067] In one or more examples, the stimulation applied to the patient in step 304 can be designed to elicit the release of reward-related molecules in the brain. This, in turn, triggers brain activity that can be detected and measured by brain scanning in distinct regions of interest in the brain. Thus, in one or more examples, while the stimulation is being applied to the patient, a brain scanning tool can be used to measure the signal strength of the brain activity elicited by the stimulation in step 306. In one or more examples, in addition to measuring the signal strength, the three-dimensional location of the brain activity elicited by the stimulation can also be recorded in step 308. In one or more examples, the signal strength and three-dimensional location of the brain activity (extracted from the brain scan) can be used to identify activity in a predetermined reward center in the brain that can correlate with emotion and reward-related molecules. Thus, in one or more examples, the signal strength and signal location recorded in steps 306 and 308, respectively, can be translated to the reward-related molecule level. In this manner, the gaps in specific reward molecules determined by the algorithm described above with respect to FIG. 2 can be further confirmed by brain imaging data using process 300 of FIG. 3.

[0068] In one or more examples, brain studies configured to map emotional and reward system activity during memory retrieval to create a predictive map of the entire reward system landscape can be used to define brain regions correlated with or associated with various reward molecules. The reward map can be created through experiments. In one or more examples, brain studies can be performed on each individual patient to create a predictive map of the individual patient's reward system landscape. In one or more examples, brain studies can be performed on multiple control subjects (e.g., 1 to 5). In one or more examples, brain studies are performed on a subject (target) with a fully prepared memory and emotion database (memories associated with positive emotions), which can include multiple positive memories and can have one or more peak memories (e.g., memories that evoked the greatest emotional response), and selected to create the reward activity map. In one or more examples, each memory (e.g., audio / visual stimuli such as pictures and / or music) can be pre-rated by the patient for overall emotional intensity, as well as the intensity of the positive emotions mentioned above (e.g., enthusiasm, sexual desire, pride / recognition, nurturing, satisfaction, amusement, attachment, joy, and gratitude). For example, in one or more examples, memories can be rated on a scale of 0 to 8, with 0 meaning no emotion was experienced and 8 representing the highest experience of that emotion ever in the subject's life. In one example, before or during memory retrieval, the patient and / or control subject can be treated with chemical or biological agonists / antagonists specific to one or more reward system molecular pathways, thus allowing for selective enhancement or inhibition of each reward system pathway and better determining the causal role of neurotransmitters.

[0069] In one or more examples, a subject is shown a randomized collection of photographs / stimuli, some of which come from a predefined memory pool and others of which are control stimuli (e.g., in the form of white noise or blank photographs). In one or more examples, while the subject is viewing the randomized photographs, both the subject's EEG and fMRI brain scans are recorded to determine whether signals are detected in either scan in response to the stimuli. In one or more examples, any differences between EEG and fMRI signal intensities that correlate with a pre-assessed total emotional intensity can be detected. For example, differences between signal intensity levels of fMRI data compared to predicted fMRI signal intensity data based on subjective emotional intensity reports can be analyzed; differences between signal intensity levels of EEG data compared to predicted EEG signal intensity data based on subjective emotional intensity reports can be analyzed; and / or differences between fMRI signal intensity data and EEG signal intensity data (e.g., normalized based on typical respective signal intensities) can be analyzed. Furthermore, the scans can be analyzed to determine distinct signal patterns in both EEG and fMRI that correlate with pre-identified emotions. In one or more examples, patterns in the EEG data can be identified by examining a fast Fourier transform (FFT) of the epoched EEG signal. Additionally or alternatively, patterns can be identified by performing frequency band power analysis (theta, alpha, beta, and gamma) across brain regions, i.e., frontal, central, parieto-occipital, left temporal, right temporal, frontal midline, etc. Additionally or alternatively, power ratio analysis (theta / beta ratio, alpha / beta ratio) between frontal EEG electrodes can be used to detect patterns in the EEG that may help identify reward centers in the brain. Additionally or alternatively, power asymmetries between frontal electrodes (theta, alpha, beta, gamma) can be used to detect patterns in the EEG data. In one or more examples, additionally or alternatively, visual comparison can be used to compare signal strength across all emotions with a control stimulus.Additionally or alternatively, comparisons of stimuli for each emotion can be used to detect patterns, as well as comparisons of control stimuli (across all emotions and intensities) with positive emotion stimuli can be used to detect patterns.

[0070] In one or more examples, similar to EEG, fMRI data associated with patients receiving random stimuli can also be used to detect signal strength and locations within the brain that generate activity in response to stimuli provided to the patient during the study. In one or more examples, fMRI detection and analysis can be utilized according to techniques discussed in "Prefrontal Cortex Predict Individual Preferences across Reward Categories" by Gross et al. (The Journal of Neuroscience, May 28, 2014, 34(22):7580-7586). In one or more examples, fMRI can be performed at 3 Tesla (3T). In one or more examples, fMRI can be performed at 7 Tesla (7T) or higher. In one or more examples, fMRI can be performed at 14 Tesla (14T).

[0071] In one or more examples, process 300 can be utilized by itself or in conjunction with subjective data regarding emotional associations with various memories, such as self-reported data provided by the patient. Process 300 can be used in either manner to detect one or more gaps or deficiencies in the patient's brain that may be causing a depressive disorder. Returning to the example of FIG. 1 , in one or more examples, once the brain image analysis is completed in step 106, process 100 can move to step 108, where one or more molecular deficiencies are identified based on the results of steps 104 and / or 106 of process 100. In one or more examples, the gaps or deficiencies identified in step 106 based on the data collected from steps 102 and / or 104 can be used to create a personalized plan for treatment that can address the underlying causes of the patient's depression or mood disorder. Thus, in one or more examples, the gap analysis obtained from the subjective assessment and confirmed by brain imaging can be used to design a personalized depression prevention / treatment protocol. In one or more examples, protocols can cover the entire reward system landscape, going beyond the existing repertoire of currently used approved antidepressants and known behavioral treatments. In one or more examples, to reduce the risk of pharmacological dependence and disease relapse, each treatment created for a determined reward molecule deficiency can use behavioral and pharmacological components that address all identified reward system gaps. The former guides patients / participants toward behaviors that inherently fulfill distinct personal reward system gaps. Such behavioral corrective measures provide an anchor for long-term therapeutic effects. The latter can externally support patients / participants with missing active reward system molecules, thus accelerating improvement.

[0072] FIG. 4 illustrates an exemplary process for determining a treatment plan based on a determined molecular deficiency, according to examples of the present disclosure. In one or more examples, process 400 of FIG. 4 can begin at step 402, where one or more reward molecule deficiencies for a patient (e.g., ascertained using process 100 of FIG. 1) can be received. As noted above, in one or more examples, the reward molecules can include, but are not limited to, dopamine, serotonin, testosterone, oxytocin, cannabinoids, or opioids. Thus, in one or more examples, step 402 can include receiving information identifying one or more reward molecule deficiencies, but can also include receiving a quantification of the amount of deficiency so that the severity of the deficiency can also be assessed.

[0073] In one or more examples, once information related to a deficiency is received in step 402, in one or more examples, process 400 of FIG. 4 can move to step 404, where a treatment plan based on the identified deficiency can be selected. In one or more examples, as described above, the treatment plan can include both pharmacological and behavioral treatment plans that can be individually and / or collectively configured to ameliorate the reward molecule deficiency identified by step 402. In one or more examples, each reward molecule exhibits its own pharmacological and behavioral responses. In one or more examples, the treatment plan can be specifically tailored to the identified deficiency. A specifically tailored treatment plan that can be individualized for each individual patient provides a more effective treatment method than the generalized treatment plans currently implemented.

[0074] As an example, an exemplary treatment plan for dopamine deficiency is presented below. As a central cofactor of all positive emotions, a hallmark of dopamine deficiency may be a complete set of peak memories that equally encompass all emotions. The selected peak memories may be from the past few years, or they may span the subject's entire life, from recent memories (e.g., days or weeks ago) to memories from the past few years. In contrast, actual memories may show overall low and below-average ratings of emotional importance across all emotional intensities. A single highly rated memory indicates a high likelihood of an activity with a high adrenergic stimulant, given its synergistic effect on dopamine, e.g., bungee jumping, parachuting, and excessive partying. Among individuals with a dopamine gap, acute or past substance use or abuse primarily focuses on stimulants such as amphetamine (Adderall), methylphenidate (Ritalin), cocaine, or methamphetamine. Individuals suffering from dopamine deficiency often report periods of significant depression after using / abusing stimulants. High caffeine intake from dietary sources can be another indicator of dopamine deficiency. Acute or past behavioral abuse primarily centers around online gaming or gambling, which involves very short gaps between small digital rewards that trigger dopamine release.

[0075] Structural MRI (sMRI) shows lower rGMV in the rIC and rPC compared to controls. In response to past peak memories, functional MRI (fMRI) shows activity in all brain regions transmitting value signals, such as the right anterior medial prefrontal cortex (mPFC), right dorsal mPFC, right mPFC, left dorsal PFC, left mPFC, left anterior PFC, and anterior cingulate cortex. In contrast, in response to actual memories, signal intensity is significantly reduced across all these regions. The number of peak memories recorded under the support of stimulant drugs can provide an indication of the respective dopamine gap (e.g., by comparing fMRI intensity of peak memories with drug support versus peak memories without drug support).

[0076] Therefore, in one or more instances, given the problems associated with dopamine deficiency described above, behavioral treatment should include activities involving mental and / or physical learning components with small but rapid improvements and reward cycles (e.g., bouldering, any craft work, learning a new language in a local environment). If necessary, pharmacological treatment should focus on medical amphetamines or methylphenidate. Classic antidepressants of all classes, THC, and substances that stimulate the CB1 / 2 system are contraindicated in this patient population. In one or more instances, testosterone treatment may not be supportive or effective unless testosterone levels are below baseline. Combination treatment with amphetamines or methylphenidate and antidepressants should only be used if there is a gap in the serotonin reward system. In the case of recreational drug addiction to cocaine, methamphetamine, or similar, it is important to first complete rehabilitation to achieve complete withdrawal.

[0077] In one or more examples, an exemplary treatment plan for testosterone deficiency is provided below. The testosterone reward system activity gap can have two causes: (i) the threshold for triggering testosterone stimulation is normal, but available testosterone levels are too low due to impaired natural testosterone production (primarily due to stress or aging), or (ii) the threshold for triggering testosterone stimulation is abnormally high while testosterone levels are normal (primarily due to excessive pornography abuse, compulsive sexual behavior, hypersexual disorder, or sex addiction). To distinguish between the two causes and patient groups, the memory analysis described above can provide important insights. If a patient / participant's general sexual desire and behavior are low / zero (below the average number of peak memories and actual memories assessed for sexual desire) and pornography use is low / zero, testosterone blood testing should be initiated. In one or more examples, if testosterone blood levels are below baseline, supplementation with testosterone gel or injections can be initiated immediately, rapidly correcting the depressive disorder. Classical antidepressants of all classes, THC, and substances that stimulate the CB1 / 2 system or any stimulants are contraindicated in patients whose threshold for triggering testosterone stimulation is normal but whose available testosterone levels are too low due to impaired natural testosterone production. It should be noted that in this patient group, brain imaging results using fMRI, sMRI, EEG, or fNIRS are barely distinguishable from those in normal individuals and therefore cannot be used for differential diagnosis.

[0078] In contrast, patients with abnormally high thresholds for triggering testosterone stimulation but normal testosterone levels exhibit disturbed testosterone thresholds, but normal testosterone levels demonstrate an above-average number of peak memories covering sexual activity, accompanied by very high emotional ratings across all emotions for such activity. Depending on the level of depression, actual memories targeting sexual activity may be absent or few memories may be highly rated for experiencing sexual desire. Brain imaging using fMRI, sMRI, EEG, or fNIRS provides similar patterns in patients with a dopamine gap, thus providing limited input for differential diagnosis. In one or more instances, these patients may very likely benefit from classic antidepressants such as SSRIs. Stimulants of all kinds may be contraindicated. In one or more instances, behavioral treatment should initially focus patients on physical activity, primarily individual endurance sports such as running, cycling, hiking, and climbing, while strenuous weight training should be avoided. In severe cases, traditional addiction treatment can be applied in parallel.

[0079] In one or more examples, an exemplary treatment plan for serotonin deficiency is provided below. A hallmark of serotonin deficiency may be a complete set of peak memories that equally cover all emotions. However, memories with high ratings of pride / recognition are primarily recorded in childhood and are most often associated with positive feedback from parents. Actual memories show a very small number of memories involving experiences of pride / recognition, and those that show high ratings of pride / recognition are biased toward experiencing pride / recognition in others (children, friends) rather than in one's own pride / recognition.

[0080] In one or more instances, among individuals with a serotonin gap, acute or past recreational substance use or abuse may be centered on 3,4-methylenedioxymethamphetamine (ecstasy, MDMA), ketamine, and / or hallucinogens. Furthermore, these individuals may report significant withdrawal symptoms after using MDMA and ecstasy. In one or more instances, acute or past behavioral addiction may be primarily centered on social media. Additionally, this group has a higher incidence of sports addiction and eating disorders. In one or more instances, structural MRI (sMRI) may reveal significantly lower rGMV in the rIC and rPC compared to control groups. In one or more instances, in response to past peak memories, functional MRI (fMRI) may demonstrate activity in all brain regions transmitting value signals, such as the right anterior medial prefrontal cortex (mPFC), right dorsal mPFC, right mPFC, left dorsal PFC, left mPFC, left anterior PFC, and anterior cingulate cortex. In one or more examples, using a self-portrait ("Selfie") as a recall trigger for self-pride / recognition, a particularly strong activity response across all brain regions can be detected for selected highly valued memories. In one or more examples, this test can be an important discriminant for diagnosis. The number of peak memories recorded under the support of the aforementioned recreational drugs can provide an indication of the respective serotonin gap (e.g., by comparing fMRI intensity between drug-supported and non-drug-supported peak memories).

[0081] Based on the identified deficiencies in serotonin activity focused on play and playful learning, task-oriented, non-competitive group activities are indicated for behavioral treatment, e.g., group activities in and for nature, helping others, traveling, and nature conservation. Activities with a strong competitive focus are contraindicated unless they involve team tasks with a physical goal, such as whitewater rafting, rowing, climbing / rope teams, and scuba diving. Drama and orchestral performances are also indicated. If necessary, pharmacological treatment should focus on antidepressants that target only the serotonin reward system, such as SSRIs. These substances have high efficacy in this population. Medical ketamine, THC, and substances that stimulate the CB1 / 2 system should also be highly effective. In contrast, antidepressants and any stimulants that target dopamine pathways may be strictly contraindicated. Combination treatment with amphetamine or methylphenidate and antidepressants should only be used if there is a gap in the dopamine reward system. In one or more instances, in the case of recreational drug addiction to any substance, it is important to first complete rehabilitation to achieve complete withdrawal. In one or more instances, during treatment, monitoring focuses on experiencing pride / recognition and increasing fMRI intensity for actual memories, which increases the number of peak memories created without stimulating drug use. Over time, pharmacological treatment should be phased out in line with the progress of behavioral treatment. In one or more instances, monitoring can be used to provide ongoing guidance during the phase-out of pharmacological treatment. If fMRI indicators stagnate or worsen, phase-out can be reversed, slowed, or stopped.

[0082] In one or more instances, an exemplary treatment plan for oxytocin deficiency is provided below. Oxytocin deficiency may be characterized by a complete set of peak memories covering all emotions equally. However, memories high in nurturing love and satisfaction are primarily recorded in childhood and include pets more frequently than average. In actual memories (e.g., more recent memories), the number of memories involving experiences of nurturing love or satisfaction is very low. Memories rated high in nurturing love are often associated with pets or children. Among individuals with an oxytocin gap, acute or past recreational substance use or abuse is extremely rare, and, if present, experience with 3,4-methylenedioxymethamphetamine (ecstasy, MDMA) is rare. To differentiate between patients with a cannabinoid reward system gap, it may be important to note that patients with oxytocin disorders rarely use or abuse THC-containing recreational drugs, such as cannabis or marijuana. In one or more instances, acute or past behavioral addiction is also rare. However, low levels of oxytocin may be associated with higher incidence of autism and anorexia nervosa as confirmed at initial interview. Structural MRI (sMRI) shows lower rGMV in the rIC and rPC compared with controls. In response to past peak memories, functional MRI (fMRI) shows activity in all brain regions transmitting value signals, such as the right anterior medial prefrontal cortex (mPFC), right dorsal mPFC, right mPFC, left dorsal PFC, left mPFC, left anterior PFC, and anterior cingulate cortex. Recalling memories rated as high in nurturing affection detects particularly strong activity responses across key brain regions associated with trust and social interaction. This test serves as an important diagnostic criterion.

[0083] In one or more instances, treatment plans for identified oxytocin deficiency may focus on behavioral therapy, taking into account the limitations of available pharmacological treatments. (However, pharmacological treatments, including oxytocin sprays, can be used, for example, to improve symptoms of depression.) In behavioral treatment, activities should focus on nurturing, affectionate behaviors, which are highly effective, such as playing with pets / puppies, eating meals together, involving family members in treatment (if perceived positively by the patient), and team sports involving harmless physical contact (dancing, basketball, horseback riding, team ice skating, sailing, tandem parachuting). Pharmacological treatment for oxytocin deficiency may be limited to oxytocin nasal sprays, which have a rapid effect on depressive symptoms in this patient population. In one or more instances, all other antidepressants and stimulants may be strictly contraindicated because they may worsen symptoms. In one or more instances, monitoring may focus on increasing brain activity in brain regions associated with trust and social interaction, as detected by fMRI, and on increasing the number of actual memories with above-average ratings of nurturing affection and satisfaction.

[0084] In one or more examples, a treatment plan for cannabinoid deficiency is provided below. A hallmark of cannabinoid deficiency may be a complete set of peak memories covering all emotions. However, memories with high ratings for attachment, especially recreational, are primarily recorded in childhood or the past. In one or more examples, the absence of below-average ratings for recreational experiences may be an important indicator of cannabinoid disorders. In one or more examples, actual memories may show a very small number of memories involving attachment or recreational experiences. The number of memories recorded under the support of THC-containing drugs can provide an indicator of the respective cannabinoid gap (comparing the fMRI intensity of drug-supported peak memories with that of non-drug-supported peak memories).

[0085] Individuals with a cannabinoid gap are highly likely to have acute or past recreational substance use or abuse of THC-containing products, such as cannabis or marijuana. In one or more instances, this can be an important discriminant for differentiating them from patients with an oxytocin reward system gap. Acute or past behavioral addictions are focused on digital social media and games with deep and long-standing connections, such as multiplayer strategy games and professional forum activity. In one or more instances, structural MRI (sMRI) shows lower rGMV in the rIC and rPC compared to all other patient groups and control groups. This can be an important factor for differential diagnosis. In one or more instances, functional MRI (fMRI) in response to past peak memories can show activity in all brain regions that transmit value signals, such as the right anterior medial prefrontal cortex (mPFC), right dorsal mPFC, right mPFC, left dorsal PFC, left mPFC, left anterior PFC, and anterior cingulate cortex. Similar to patients with oxytocin gap, recalling memories rated as high in affection and enjoyment can detect particularly strong activity responses across key brain regions associated with trust and social interaction. In one or more instances, the above tests can be important diagnostic criteria for dopamine disorders, testosterone disorders, serotonin disorders, and opioid disorders.

[0086] In one or more examples, treatment for a determined cannabinoid deficiency may include activities focused on group activities that support experiences of laughter and camaraderie (e.g., attachment) and belonging. In one or more examples, play may be more important than competition and winning, but the competitive element may be focused on team sports, e.g., all (non-professional) team sports, all creative activities within a group / team, play, music together / orchestra, active group vacations and tasks, and small business activities with friends. Digital social media activities may be gradually reduced and replaced with physical interpersonal activities. Pharmacological treatments for cannabinoid deficiency are widely available in the form of medical and recreational cannabis and marijuana. Gradually reducing pharmacological treatment may be shown to eliminate long-term adverse effects on brain network structure. All other antidepressants and stimulants are strictly contraindicated because they stimulate self-focus and self-esteem (e.g., SSRIs) or competitiveness (stimulants), which may be counterproductive to successful treatment. Monitoring can focus on increased brain activity in brain regions associated with trust and social interaction, which, as detected by fMRI, increases the number of actual memories with above-average ratings in attachment and enjoyment. Structural MRI, focusing on increased rGMV in the rIC and rPC, is the most important monitoring indicator for patients undergoing treatment for cannabinoid disorders.

[0087] In one or more examples, an exemplary treatment plan for opioid deficiency is provided below. In one or more examples, a hallmark of opioid deficiency may be a full set of peak memories, but with fewer or lower intensity ratings for gratitude and pleasure, as a central output of activities involving positive emotions. A key differentiator may be that even peak memories are deficient in number and intensity. Actual memories may exhibit overall lower ratings for emotional importance and below-average ratings for gratitude and pleasure. In one or more examples, among individuals with an opioid gap, acute or past substance use or abuse focuses on THC-containing drugs, hallucinogens, ketamine, and anxiolytics, with less focus on stimulants such as amphetamines (e.g., Adderall), methylphenidate (e.g., Ritalin), cocaine, or methamphetamine. Concurrently, high use of medical painkillers such as NSAIDS may be observed and should be considered a differentiating factor. Acute or past behavioral abuse primarily focuses on passive movie and television viewing, eg, binge watching.

[0088]

[0088] With regard to brain scan data, structural MRI (sMRI) can show significantly lower rGMV in the rIC and rPC compared to control groups. In one or more examples, in response to past peak memories, functional MRI (fMRI) can show activity in all brain regions that transmit value signals, such as the right anterior medial prefrontal cortex (mPFC), right dorsal mPFC, right mPFC, left dorsal PFC, left mPFC, left anterior PFC, and anterior cingulate cortex. In contrast, in response to actual memories, signal intensity can be significantly reduced across all of these regions. The number of peak memories recorded under the support of a stimulant drug can provide an indication of the respective opioid gap (comparing fMRI intensity between drug-supported and non-drug-supported peak memories).

[0089] In one or more instances, behavioral treatment is central to the treatment of opioid disorders. In one or more instances, behavioral treatment can focus on experiencing gratitude rather than pleasure. This can be most effectively achieved through yoga, meditation, mindfulness coaching / training, and solitary activities in nature. In one or more instances, group activities or activities of a competitive nature may be contraindicated. In one or more instances, pharmacological treatment within the opioid class may be limited due to the high risk of substance addiction. If necessary, NSAIDs may be prescribed for an interim period to address pain-related issues. In one or more instances, antidepressants that target only the serotonin reward system, for example, may provide particular efficacy and may be used. Medical ketamine, THC, and substances that stimulate the CB1 / 2 system may also be used. In contrast, antidepressants and any stimulants that target dopamine pathways may be strictly contraindicated. Over time, pharmacological treatment should be reduced and discontinued. During treatment, monitoring can focus on increases in fMRI intensity for actual memories and an increase in the number of peak memories created without stimulating drug use. Structural MRI focusing on increased rGMV in rICs and rPCs may be an important monitoring indicator for patients undergoing treatment for opioid disorders.

[0090] As demonstrated above, treatments to combat reward molecule deficiencies can be highly specific to the exact reward system molecule found to be deficient. Thus, returning to the example of FIG. 4 , a treatment plan can be selected based on the identified deficiency found in the information received in step 402. In one or more examples, once a treatment plan is selected in step 404, in one or more examples, process 400 can proceed to step 406, where the treatment plan is administered to the patient. In one or more examples, administering the treatment plan to the patient can include engaging the patient in both behavioral and / or pharmacological treatments. In one or more examples, once a treatment is administered to the patient in step 406, the patient's progress can be monitored in step 408 to determine the effectiveness of the treatment.

[0091] In one or more examples, monitoring the progress of treatment can include daily monitoring and assessing positive memories and emotions, as well as observing derived reward system information. Additionally or alternatively, objective changes in brain structure and functionality via fMRI and EEG imaging can be monitored again after three months, and if necessary, six months, to confirm visible physiological improvements in the brain.

[0092] In one or more examples, one or more studies can be conducted to confirm the effectiveness of the methods described above with respect to FIGS. 1-4. For example, in one or more examples, a study can be conducted that can prove that individual fMRI-guided behaviors are effective in improving health and reducing depression symptoms. In one or more examples, the study can include conducting fMRI or other brain scans on multiple subjects and then generating a treatment plan for the patient, similar to process 400 described with respect to FIG. 4. In one or more examples, before the treatment plan is administered, the patient can be evaluated using one or more questionnaires or clinical depression assessments. In one or more examples, after a reward molecule deficiency has been identified according to the exemplary process 300 of FIG. 3 and a treatment plan has been selected and implemented according to the exemplary process 400 of FIG. 4, after a predetermined time has passed (e.g., three months), study participants can have changes in their health as manifested in biomarkers (blood biomarkers), structural brain data (sMRI, EEG), functional brain data (fMRI, EEG during memory recall), and health data (HAMD17, SWB) recorded to determine whether any improvements in health can be observed. In one or more examples, the study can detect improvements in HAMD17 and SWB scores through individual behaviors guided by individual memory / emotion data. Additionally or alternatively, the study can evaluate the correlation between biomarkers and / or brain imaging data and improvements in HAMD17 and SWB scores. Additionally or alternatively, the study can evaluate the correlation of fMRI data with predicted reward-emotion maps (post-event memory recall).

[0093] In one or more examples, another exemplary study validating the above-described method may include an intervention study of patients with mild / moderate depressive disorders prior to first-line pharmacological intervention. In one or more examples, a comparison may be made between standard treatment (antidepressant treatment, no diagnosis) and personalized pharmacological and behavioral interventions predicted by fMRI-guided reward-affect maps as described above. In one or more examples, the study may be configured to demonstrate the effectiveness of fMRI-guided personalized pharmacological and behavioral treatments in improving depressive symptoms beyond conventional standard treatment. In one or more examples, participants may include individuals who scored 10-17 on the HAMDD17 assessment. In one or more examples, all study participants may be evaluated using the above-described method to determine one or more reward molecule deficiencies. However, with regard to treatment, a blinded and randomized group of participants may receive a customized treatment plan (both behavioral and pharmacological) based on the identified deficiency, while another group may receive treatment according to conventional standard treatment.

[0094] In one or more examples, the outcomes of the two groups can be evaluated by determining whether there is a significant improvement in HAMD17 and SWB in patients treated with the individualized therapy compared to standard of care across all treatment groups. Additionally, correlations between biomarker and / or brain imaging data and improvement in HAMD17 and SWB scores can be evaluated.

[0095] 5A-B illustrate an exemplary method 500 for identifying and treating a neurological deficiency in a patient (or any human subject) according to some embodiments of the present disclosure. Method 500 may be performed automatically, in whole or in part, by a computerized system including one or more processors.

[0096] In step 502, the system may receive patient-related information, including memory information regarding a plurality of patient memories. The patient may input information regarding a plurality of memories and / or experiences, including memories from the distant past and / or recent past (e.g., everyday experiences), into the system. In some embodiments, the patient may input information only regarding positive memories. In some embodiments, one or more of the memories may be peak positive memories, i.e., memories that elicited a strong positive emotional response and / or memories quantitatively rated by the patient as one of the best memories of the patient's life. For each of the plurality of patient memories, the memory information provided by the patient (e.g., by providing one or more inputs to a graphical user interface configured to collect information for analysis by the system) may include a respective emotional intensity for each of one or more emotions. The one or more emotions may include, but are not limited to, enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, affection, amusement, joy, and gratitude. Emotion intensity data may be, for example, on a scale of 0 to 8, with 0 representing that the patient reported not experiencing the respective emotion at all and 8 representing that the patient reported experiencing the respective emotion with the highest intensity.

[0097] For each of the plurality of patient memories, the memory information may include respective time information. The respective time information may include a duration of an emotion felt during the memory. The respective time information may include a date and / or time when the memory occurred. The respective time information may include a date and / or time when the memory information was recorded by the system.

[0098] For each of the multiple patient memories, the memory information may include respective metadata indicative of aspects of the memory. Aspects of the memory may include, but are not limited to, information about a location associated with the memory, people associated with the memory, or activities associated with the memory. In some embodiments, the contents of the memory may be "tagged" with metadata labels indicative of people, groups, places, and / or activities, such that memories associated with overlapping or similar content may be grouped together by a common tag.

[0099] For each of the plurality of patient memories, the memory information may also include representative media associated with the memory (eg, audio / visual media such as photos, music, and / or video).

[0100] The system may store in a database information representing an association between each respective memory and other collected information associated with the memory, including, but not limited to, emotions and associated ratings, temporal information, aspects of the memory (e.g., the content of the memory), and / or media associated with the memory.

[0101] In step 504, the system may provide a plurality of stimuli to the patient. Each of the plurality of stimuli may be associated with one or more of the patient's memories. For example, after collecting memory information from the patient, stimuli selected based on the provided memory information may be provided to the patient. In some embodiments, the plurality of stimuli may include a randomized (or semi-randomized) collection of photographs, audio, and / or video containing media information associated with one or more of the patient's provided memories. When presented to the patient, the media information associated with the patient's memories may be intermixed with other random images, audio, and / or video, which may serve as a control. A control may also be provided by presenting noise and / or blank images to the patient. In some embodiments, the media may be presented in a predetermined time window, for example, by presenting multiple stimuli to the patient, and may be alternated with control stimuli. In some embodiments, the control stimuli may include one or more photographs and / or videos not known to be associated with any particular emotional response in the patient. Such photographs may be combined with white noise. After each stimulus, control, or emotional memory, there may be a re-baselining phase when the patient is presented with a black screen with a cross in the center to "wash away" all emotion before the next stimulus is presented. Emotional stimuli may be randomly alternated with control stimuli. After each stimulus (control or emotional), the patient may be emotionally reset to baseline (e.g., by presenting a black screen) before the next stimulus.

[0102] In step 505, the system can measure the patient's brain activity. The patient's brain activity can be measured while stimuli (including memory-related stimuli and control stimuli) are presented to the patient. Step 505 can be performed simultaneously with step 504 so that brain activity is measured when various stimuli from a plurality of stimuli are provided to the patient. Measuring brain activity can be performed by performing structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), real-time functional magnetic resonance imaging (rt-fMRI), real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF), whole-scalp electroencephalography (EEG), and / or whole-scalp functional near-infrared spectroscopy (fNIRS). The rt-fMRI scan can be a 3 Tesla rt-fMRI scan or a 7 Tesla rt-fMRI scan. Measuring brain activity can include measuring the intensity of brain activity while one or more stimuli are provided to the patient, for example, in the form of audio, images, and / or video. Measuring brain activity may also include recording locations of brain activity while one or more stimuli are provided to the patient. The locations of brain activity may refer to three-dimensional locations at which signals representative of brain activity (including respective signal strengths) are measured.

[0103] In step 506, the system can determine the patient's levels of multiple neurotransmitters based on the collected data indicating the location of brain activity and the associated intensity of the brain activity. The multiple neurotransmitters may include, but are not limited to, dopamine, testosterone, serotonin, oxytocin, cannabinoids, and / or opioids. The system can use the three-dimensional location and associated intensity of brain activity to identify activity in a predetermined reward center in the brain, which may be correlated with a particular emotion and a particular neurotransmitter. For example, brain activity in a particular region of the brain may be known to correspond to one or more emotions and / or neurotransmitters, e.g., based on an examination of the brain activity of a particular patient and / or based on background knowledge developed based on an examination of the brain activity of a population of subjects. The system can then detect activity in that particular region of the brain and, based on the detected activity in that region, determine that the patient is experiencing activity of the associated neurotransmitter (and / or associated emotion). The strength of the signal data measured in the region can be used to determine the strength of the neurotransmitter response (and / or the strength of the emotional experience), for example, based on a positive correspondence between the signal strength data and the strength of the neurotransmitter response.

[0104] In some embodiments, the system can use an algorithm to determine which neurotransmitters are associated with one or more emotions represented in the memory information. For example, the system can use the PE-NT matrix of FIG. 2. For example, by using the PE-NT matrix, dopamine can be associated with enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, amusement, attachment love, joy, or gratitude. Testosterone can be associated with sexual desire. Serotonin can be associated with pride / recognition. Oxytocin can be associated with nurturing love or satisfaction. Cannabinoids can be associated with satisfaction, amusement, or attachment love. Opioids can be associated with amusement, joy, or gratitude.

[0105] In some embodiments, the system may aggregate brain scan data by grouping them according to common neurotransmitters and / or common emotions. For example, brain scan data collected during presentation of stimuli associated with memories tagged with a particular emotion may be analyzed collectively, for example, by analyzing the total and / or average signal strength measured during all presentations of the memory.

[0106] In some embodiments, the brain scan data may be grouped according to memories associated with the same emotion (e.g., based on subjective emotional experience information provided by the user).

[0107] In some embodiments, brain scan data associated with different emotions may be grouped according to memories associated with the same neurotransmitter. For example, to obtain aggregated brain activity data associated with dopamine, the system may aggregate all brain activity data measured in response to stimuli meant to elicit enthusiasm. To obtain aggregated brain activity associated with serotonin, the system may aggregate brain activity data measured in response to stimuli meant to elicit pride / recognition.

[0108] The system may aggregate brain activity data associated with a particular neurotransmitter in a manner that minimizes the influence of other neurotransmitters on the brain activity data. For example, although dopamine is associated with multiple emotions, in some embodiments, dopamine is the only neurotransmitter (of the dopamine, testosterone, serotonin, oxytocin, cannabinoid, and opioid group) associated with enthusiasm, and therefore the system may aggregate only brain data measured in response to stimuli meant to elicit enthusiasm. In one or more examples, the system may process the aggregated brain data associated with dopamine to remove the effects of other neurotransmitters on the aggregated brain data, for example, to isolate brain activity signal responses attributable to dopamine activity.

[0109] The resulting aggregated brain activity data can be used to detect activity (or lack thereof) in predetermined reward centers of the brain. Based on the signal strength in these predetermined reward centers of the brain, the system can determine multiple neurotransmitters. In one or more examples, determining multiple neurotransmitters can be determined by comparing the signal strength in the predetermined reward centers to a threshold signal strength level for the predetermined reward center. The threshold level can be determined based on a historical analysis of a particular patient and / or a historical analysis of a subject population. For example, the system can analyze the aggregated brain activity data related to dopamine to determine whether it indicates activity in predetermined reward centers of the brain related to dopamine. If there is any activity in the predetermined reward centers of the brain related to dopamine, the system can determine the signal strength at these locations. Based on the determined signal strength in the predetermined reward centers related to dopamine, the system can determine the level of dopamine. The system can compare the determined signal strength in the predetermined reward centers related to dopamine to the threshold signal strength for those reward centers to determine the level of dopamine.

[0110] Brain regions of interest correlated with emotions and neurotransmitters can be determined using brain studies. The brain studies can be configured to map emotion and reward system activity while the brain is undergoing memory retrieval to create a predictive map of the brain's emotion (and corresponding reward center activity and / or neurotransmitter activity) landscape. In one or more examples, brain studies can be performed on each individual patient to create a predictive map of the individual patient's emotion and neurotransmitter landscape. In one or more examples, brain studies can be performed on multiple control subjects, which in some embodiments can include control subjects who are not known to have neurotransmitter deficiencies or who are positively believed not to have neurotransmitter deficiencies.

[0111] In one or more examples, a brain study is performed on a subject with a fully prepared memory and emotion database (memories associated with positive emotions), which may include multiple positive memories and may have one or more peak memories (e.g., memories that elicited the greatest emotional response). The brain study may include providing multiple stimuli associated with the memories and predefined emotions while performing a brain scan of the patient. The brain scan may be analyzed to determine distinct signal patterns, e.g., activity in specific brain regions of interest, which may be correlated with predefined emotions. The determined distinct signal patterns may then be used to determine brain regions of interest associated with specific emotions. The system may then use an algorithm, such as the PE-NT matrix of FIG. 2, to determine which regions of interest currently known to be associated with one or more specific emotions are associated with specific reward systems and / or neurotransmitters. For example, if a patient is exposed to a stimulus that has been predefined (e.g., by labeling by the patient) as eliciting an enthusiasm response, the system may determine that the activated brain region is a region of interest associated with enthusiasm, and therefore the system may further determine (e.g., using a PE-NT matrix) that the region of interest is associated with the neurotransmitter dopamine.

[0112] In some embodiments, the system may employ one or more alternative or additional techniques to determine brain regions of interest determined to be associated with specific emotions and / or specific neurotransmitter activity. As described above, one technique involves measuring brain activity and identifying active brain regions of interest that are triggered when stimuli associated with specific emotions are presented, thereby creating a biomarker brain map that associates brain regions with emotions. As described above, brain regions known to be associated with a given emotion may then be linked to one or more associated neurotransmitters using algorithms such as the PE-NT matrix. However, other techniques may additionally or alternatively be applied to link brain regions to one or more associated neurotransmitters.

[0113] In one additional or alternative approach, a subject / patient can be administered one or more known pharmacological agents that enhance or block one or more specific neurotransmitter pathways, and the subject's / patient's brain activity can then be measured under stimuli designed to elicit a specific emotional response (e.g., the same stimuli previously used without the pharmacological intervention). Differences in activity levels in one or more brain regions of interest can be measured as a comparison between (a) a state in which the patient / subject is not exposed to the pharmacological intervention and (b) a state in which the patient / subject is exposed to the pharmacological intervention. Thus, brain regions of interest in which statistically significant differences in activity levels are observed can be determined to be associated with the neurotransmitters that the pharmacological intervention is known to block.

[0114] Thus, any one or more of the approaches described above can be used to create a molecular fingerprint of the areas in the brain associated with a given emotion and / or a given neurotransmitter.

[0115] 6A-6F show exemplary aggregated brain activity data in which brain activity is concentrated in regions of interest correlated with various emotions, reward centers, and / or neurotransmitters. FIG. 6A shows aggregated brain activity in regions of interest associated with enthusiasm and correlated with dopamine. Region 602 indicates the region of interest associated with enthusiasm (and thus associated with dopamine). Regions in FIG. 6A with brighter colors indicate the location and intensity of brain activity. Because brain activity overlaps with region 602 and brightness indicates higher intensity of brain activity in region 602, the system calculates higher levels of dopamine. Brain activity overlaps with line graph 604, which shows percent signal change over time for a control stimulus, a non-dopamine-related stimulus (e.g., a stimulus not associated with enthusiasm, such as a stimulus more strongly associated with another neurotransmitter, or a stimulus rated low for enthusiasm), and a dopamine-related stimulus. In the illustrated example, brain activity was measured for the stimulus (or control) over a 20-second period, over which brain activity was measured. Line graph 604 shows that the difference between dopamine-related and non-dopamine-related brain activity is statistically significant.

[0116] FIG. 6B shows aggregated brain activity in regions of interest related to sexual desire and correlated with testosterone. Region 606 indicates the region of interest related to sexual desire (and thus related to testosterone). Areas in FIG. 6B with brighter colors indicate the location and intensity of brain activity. Although brain activity overlaps with region 606, brighter regions indicate lower intensity of brain activity in region 606, leading the system to calculate lower levels of testosterone. Line graph 608 shows the percent signal change over time for control stimuli, non-testosterone-related stimuli (e.g., stimuli not related to sexual desire, such as stimuli more strongly related to other neurotransmitters, or stimuli rated low for sexual desire), and testosterone-related stimuli. Line graph 608 indicates that the difference between testosterone-related and non-testosterone-related brain activity is statistically significant.

[0117] Figure 6C shows aggregated brain activity in regions of interest related to pride / recognition and correlated with serotonin. Regions 610 and 612 indicate regions of interest related to pride / recognition (and therefore related to serotonin). Regions in Figure 6C with lighter colors indicate the location and intensity of brain activity. Brain activity overlaps with region 612, and the lighter color indicates lower intensity of brain activity in region 612. Because brain activity does not overlap with region 610, the system calculates negligible levels of serotonin. Line graph 614 shows the percent signal change over time for control stimuli, non-serotonin-related stimuli (e.g., stimuli not related to pride / recognition, such as stimuli more strongly associated with other neurotransmitters, or stimuli rated low for pride / recognition), and serotonin-related stimuli. Line graph 614 indicates that the difference between serotonin-related and non-serotonin-related brain activity is statistically significant.

[0118] FIG. 6D shows aggregated brain activity in regions of interest associated with nurturing love and satisfaction and correlated with oxytocin. Region 616 indicates the region of interest associated with nurturing love and satisfaction (and thus associated with oxytocin). Regions in FIG. 6D with brighter colors indicate the location and intensity of brain activity. Because brain activity overlaps with region 616 and brightness indicates higher intensity of brain activity in region 616, the system calculates higher levels of oxytocin. Line graph 618 shows the percent signal change over time for control stimuli, stimuli not associated with oxytocin (e.g., stimuli not associated with nurturing love, such as stimuli more strongly associated with other neurotransmitters, or stimuli rated low for nurturing love), and stimuli associated with oxytocin. Line graph 618 indicates that the difference between oxytocin-related and non-oxytocin-related brain activity is statistically significant.

[0119] Figure 6E shows aggregated brain activity in regions of interest related to attachment and entertainment, and to a lesser extent satisfaction, and correlated with cannabinoids. Regions 620, 622, and 624 indicate regions of interest related to attachment, entertainment, and satisfaction (and thus related to cannabinoids). Regions in Figure 6E with bright colors indicate the location and intensity of brain activity. Brain activity overlaps with region 622, and the brightness indicates moderate brain activity intensity in region 622. Because there is no brain activity in regions 620 and 624, the system calculates negligible levels of cannabinoids. Line graph 626 shows the percent signal change over time for control stimuli, non-cannabinoid-related stimuli (e.g., stimuli not related to attachment, such as stimuli more strongly related to other neurotransmitters, or stimuli rated low for attachment), and cannabinoid-related stimuli. Line graph 626 indicates that the difference between cannabinoid-related and non-cannabinoid-related brain activity is statistically significant.

[0120] FIG. 6F shows aggregated brain activity in regions of interest associated with pleasure and gratitude and correlated with opioids. Region 628 indicates a region of interest associated with pleasure and gratitude (and thus associated with opioids). Regions in FIG. 6F with brighter colors indicate the location and intensity of brain activity. Because brain activity overlaps with region 628 and brightness indicates higher intensity of brain activity in region 628, the system calculates higher levels of opioids. Line graph 630 shows percent signal change over time for control stimuli, non-opioid-related stimuli (e.g., stimuli not associated with pleasure and / or gratitude, or stimuli rated low for pleasure and / or gratitude), and opioid-related stimuli. Line graph 630 indicates that the difference between opioid-related and non-opioid-related brain activity is statistically significant.

[0121] 5A-5B, in step 508, the system may identify a neurological deficiency in the patient with respect to neurotransmitters based at least in part on the plurality of neurotransmitter levels calculated in step 506. In some embodiments, the system may determine a neurological deficiency using only the plurality of neurotransmitter levels calculated in step 506. For example, using the neurotransmitter levels obtained from the example shown in FIGS. 6A-6F, the system may identify a neurological deficiency as shown in Table 1 below. [Table 1] Table 1: Examples of neurological deficiency identification based on neurotransmitter levels

[0122] Neurotransmitter levels, including quantification of levels and / or classification of levels (e.g., negligible, low, moderate, high, etc.), may be compared to one or more target values, expected values, historical values, and / or threshold values to determine whether a neurological deficiency of the respective neurotransmitter exists.

[0123] Optionally, in step 508a, the system may generate a provisional indicator of neurological deficiency using the plurality of neurotransmitter levels calculated in step 506. Optionally, in step 508b, the system may apply one or more rule sets based on pharmacological and / or clinical biochemical information about the patient to determine whether the provisional indicator of neurological deficiency should be rejected. For example, if the provisional indicator of neurological deficiency indicates testosterone deficiency, information about the patient's blood testosterone levels may be used to reject or verify the provisional indicator of testosterone deficiency. In another example, information about a history of ineffective selective serotonin reuptake inhibitor (SSRI) treatment may be used to reject the provisional indicator of serotonin deficiency.

[0124] Optionally, in steps 508c and 508d, the system can apply one or more rule sets based on the memory information to determine that the tentative indicators of neurological deficiency should not be rejected. Using the one or more rule sets, the system can analyze the memory information.

[0125] 7A-7C illustrate exemplary analyses performed on memory information. With reference to FIG. 7A, the system can aggregate the memory information into an emotional intensity distribution 702, which counts the number of memories for each emotional rating. In the illustrated example, emotional intensity distribution 702 indicates that the memory information included 10 memories with an enthusiasm rating of 8. The system can use emotional intensity distribution 702 to calculate the percentage of memories in each emotional rating category over the patient's lifetime, as seen in chart 704. The system can use emotional intensity distribution 702 to calculate the percentage of memories in each emotional rating category using only memories from the most recent 12 to 18 months, as seen in chart 706.

[0126] Referring back to FIG. 5A, in step 508c, the system can compare the patient's emotional intensity information over time to determine whether the provisional indicator of neurological deficiency should be rejected. For example, referring to FIG. 7B, the system can compare the percentage of memories in each emotional rating category from the patient's entire life (e.g., chart 704 in FIG. 7A) with the percentage of memories in each emotional rating category from the last 12 to 18 months of the patient's life (e.g., chart 706 in FIG. 7A) to obtain a delta emotional intensity distribution, such as that seen in delta emotional intensity distribution 708. The system can use this information to verify the provisional indicator of neurological deficiency. For example, delta emotional intensity distribution 708 may indicate that over time the patient has fewer memories with high ratings of family / attachment, verifying the provisional indicator of cannabinoid deficiency.

[0127] Referring back to FIG. 5A, in step 508d, the system can compare the patient's emotional intensity information with emotional intensity threshold information to determine that the provisional indicator of neurological deficiency should not be rejected. For example, referring to FIG. 7C, the system can use the percentage of memories in each emotional assessment category from the last 12 to 18 months of the patient's life (e.g., chart 706 in FIG. 7A) to create an emotional intensity map, such as that shown in emotional intensity map 710. The emotional intensity map can include a calculation of the percentage of peak memories to total memories for each emotion. The system can apply one or more threshold-based analyses or other data processing analyses to the emotional intensity map to determine neurological deficiency, and then use that determination to validate the provisional indicator of neurological deficiency determined based on the brain scan data. In the illustrated example, the percentage of peak recreational memories to total memories is below the threshold, indicating cannabinoid deficiency, thereby validating the provisional indicator of cannabinoid deficiency.

[0128] The neurological deficiencies obtained from the illustrated example following step 508d (which may be output as a final diagnosis of deficiency and / or a provisional diagnosis of deficiency) are summarized in Table 2 below. [Table 2] Table 2: Examples of neurological deficit identification based on brain activity and memory data

[0129] In some examples, the system may perform some or all of steps 508a-508d. The neurological deficiencies obtained from the illustrated example, as obtained by steps 508a-508c below, are summarized in Table 3 below. [Table 3] Table 3: Examples of neurological deficit identification based on brain activity, pharmacological data, clinical biochemical data, and memory data

[0130] Referring back to FIG. 5A, the method may proceed to steps 510-514, which may be used to generate and provide a treatment plan for the patient based on the identified neurological deficiencies, as described below.

[0131] The system may optionally perform step 510 by identifying a subset of the patient's memories associated with a positive neurological response based on the memory information and the identified neurological deficiency. For example, if the system identifies a cannabinoid deficiency, the system may identify all or some of the memories that showed a strong cannabinoid (and / or attachment) response when corresponding stimuli were presented to the patient. That is, even if the user's cannabinoid response was lower overall than expected, memories that elicited a strong cannabinoid response may be identified based on the brain scan data. The system may identify top memories that show a strong response to the deficient neurotransmitter, where the response exceeds a threshold signal intensity level, and / or identify a predetermined number of top memories with the strongest response to the deficient neurotransmitter.

[0132] Optionally, in step 512, the system may identify one or more aspects that are common across the identified subset of memories based on the metadata of each of the subset of memories. For example, if the metadata of a subset of potent cannabinoid (and / or attachment love) memories indicates that all (or most) of the memories are associated with a common person (e.g., a spouse, friend, or family member), the system identifies that person or people as a common aspect of the selected potent cannabinoid memories.

[0133] Optionally, in step 514, the system may generate and provide a treatment plan for the patient that includes the identified aspects of the subset of memories. For example, if the identified aspect from step 512 was a particular person or group of people, the system may generate a treatment plan configured to instruct the patient to spend more time with that person or group of people. In some embodiments, the treatment plan may include a data structure configured to provide instructions to the patient, to provide instructions to a physician, and / or to provide machine-executable instructions to a system configured to automatically implement the treatment plan. Automatic (e.g., automatic or semi-automatic) implementation of the treatment plan may include exposure to a subject-relevant stimulus that elicits a strong positive response in deficient neurotransmitters, such as providing the patient with a subject-relevant medium. In some embodiments, automatic implementation of the treatment plan may include automatically facilitating electronic communication between the patient (e.g., using a mobile application) and the subject (e.g., a person or activity) that elicits a strong positive response in deficient neurotransmitters; for example, implementation of the treatment plan may automatically open a chat for the cannabinoid-deficient patient to communicate with family members who will provide the patient with a strong cannabinoid response.

[0134] FIG. 8 illustrates an example of a computing device according to one embodiment. Device 800 may be a host computer connected to a network. Device 800 may be a client computer or a server. As illustrated in FIG. 8, device 800 may be any suitable type of microprocessor-based device, such as a personal computer, a workstation, a server, or a handheld computing device (portable electronic device) such as a phone or tablet. The device may include, for example, one or more of a processor 810, an input device 820, an output device 830, a storage device 840, and a communication device 860. Input device 820 and output device 830 may generally correspond to those described above and may be connectable to or integrated with the computer.

[0135] The input device(s) 820 may be any suitable device that provides input, such as a touchscreen, a keyboard or keypad, a mouse, or a voice recognition device. The output device(s) 830 may be any suitable device that provides output, such as a touchscreen, a tactile device, or a speaker.

[0136] The storage device 840 may be any suitable device that provides storage, such as electrical, magnetic, or optical memory, including RAM, a cache, a hard drive, or a removable storage disk. The communication device 860 may include any suitable device capable of sending and receiving signals over a network, such as a network interface chip or device. The components of a computer may be connected in any suitable manner, such as via a physical bus or wirelessly.

[0137] Software 850 that may be stored in memory device 840 and executed by processor 810 may include, for example, programs that embody functions of the present disclosure (e.g., embodied in a device such as those described above).

[0138] The software 850 may also be stored and / or transferred within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as those described above, that can fetch and execute instructions associated with the software from the instruction execution system, apparatus, or device. In the context of the present disclosure, a computer-readable storage medium may be any medium, such as storage device 840, that includes or can store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0139] The software 850 may also be propagated in any transmission medium for use by or in connection with an instruction execution system, apparatus, or device, such as those described above, that can fetch and execute instructions associated with the software from the instruction execution system, apparatus, or device. In the context of this disclosure, a transmission medium may be any medium that can communicate, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. Transmission-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, or infrared wired or wireless propagation media.

[0140] The device 800 may be connected to a network, which may be any suitable type of interconnected communication system. The network may implement any suitable communication protocol and may be protected by any suitable security protocol. The network may include any suitable configuration of network links capable of implementing the transmission and reception of network signals, such as a wireless network connection, a T1 or T3 line, a cable network, a DSL, or a telephone line.

[0141] Device 800 may implement any operating system suitable for operating on a network. Software 850 may be written in any suitable programming language, such as C, C++, Java, or Python. In various embodiments, application software embodying functionality of the present disclosure may be deployed in a variety of configurations, for example, in a client / server configuration or through a web browser as a web-based application or web service.

[0142] Below is a list of exemplary enumerated embodiments, which may be combined, in whole or in part, with each other and / or with any other disclosures herein. 1. A method for treating a neurological disorder, comprising: receiving information associated with a patient, the received information including information regarding one or more past events involving the patient and one or more emotions associated with the one or more events; determining a level of one or more reward molecules for the patient based on the received information associated with the patient; receiving one or more scans of the patient's brain; determining a level of one or more reward molecules in the patient based on the received one or more scans of the patient's brain; determining one or more reward molecule deficiencies in the user based on the determined one or more reward molecule levels of the patient based on the received information associated with the patient and the determined one or more reward molecule levels of the patient based on the received one or more scans of the patient's brain; A method comprising: 2. The method of embodiment 1, wherein the method comprises selecting a predetermined treatment regimen for the determined one or more reward molecule deficiencies based on the identity of each reward molecule deficiency. 3. The method of embodiment 2, wherein said identity of said reward molecule deficiency is selected from the group consisting of dopamine, serotonin, testosterone, oxytocin, cannabinoids, and opioids. 4. A method according to any one of embodiments 1 to 3, wherein determining the level of one or more reward molecules of the patient based on the received information associated with the patient comprises applying the received information associated with the patient to a positive emotion versus neurotransmitter (PE-NT) matrix. 5. The method of any one of embodiments 1 to 4, wherein the received one or more scans of the patient's brain include real-time functional magnetic resonance imaging (rt-fMRI) scans. 6. The method of any one of embodiments 1 to 5, wherein the received one or more scans of the patient's brain include an electroencephalogram (EEG) scan. 7. The received one or more brain scans include: exposing the patient to one or more stimuli; determining one or more locations in the brain where signals are produced in response to the stimulation; determining a signal strength associated with each location of the brain where a signal is generated in response to the stimulation; 7. The method of any one of embodiments 1 to 6, wherein the method is obtained using a method comprising: 8. Determining the level of one or more reward molecules in the patient based on the received one or more scans of the patient's brain includes: Associating the one or more determined locations in the brain where a signal is produced in response to the stimulus with one or more types of reward molecules; determining a level of the one or more reward molecules in the patient based on the determined signal strength associated with each location in the brain where a signal is produced in response to the stimulus; 8. The method of claim 7, comprising: 9. A method as described in any one of embodiments 1 to 8, wherein the one or more emotions associated with the one or more event reception information associated with the patient of the information associated with the patient include emotions from a group including enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, affection love, amusement, joy, and gratitude. 10. The method of any one of embodiments 1 to 9, wherein the received information associated with the patient includes the patient's responses to one or more questionnaires configured to diagnose depression in the patient. 11. A method for identifying and treating a neurological deficiency, said method being implemented by a system including one or more processors, said method comprising: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency with respect to at least a first neurotransmitter in the patient based at least in part on the determined plurality of neurotransmitter levels in the patient; A method comprising: 12. Identifying a subset of the plurality of patient memories associated with a positive neurological response indicated by the brain activity of the patient based on the memory information and based on the identified neurological deficit; identifying a first aspect that is common across a plurality of memories based on the identified subsets of the plurality of patient memories and based on the respective metadata indicative of an aspect of the identified subsets; generating and providing an individualized treatment plan for said patient including the indicator of said first aspect; 12. The method of claim 11, comprising: 13. Identifying the neurological deficiency comprises: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on pharmacological and / or clinical biochemical information about the patient to determine that the provisional indication of neurological deficit should not be rejected; 13. The method of any one of embodiments 11 to 12, comprising: 14. Identifying the neurological deficiency comprises: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the memory information about the patient, including by comparing emotional intensity information about the patient with emotional intensity threshold information to determine that the provisional indication of neurological deficit should not be rejected; 14. The method of any one of embodiments 11 to 13, comprising: 15. Identifying the neurological deficiency comprises: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the patient's memory information, including by analyzing changes in the patient's emotional intensity information over time, to determine that the provisional indicator of neurological deficit should not be rejected; and 15. The method of any one of embodiments 11 to 14, comprising: 16. Identifying the neurological deficiency comprises: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the memory information for the patient, including by applying the memory information to a positive emotion versus neurotransmitter (PE-NT) matrix to determine that the tentative indicator of neurological deficit should not be rejected; 16. The method of any one of embodiments 11 to 15, comprising: 17. The method of any one of embodiments 11 to 16, wherein the first neurotransmitter is selected from the group consisting of dopamine, serotonin, testosterone, oxytocin, cannabinoids, and opioids. 18. The method of any one of embodiments 11 to 17, wherein measuring the patient's brain activity comprises using functional magnetic resonance imaging (fMRI) scanning. 19. The method of any one of embodiments 11 to 18, wherein the fMRI scan is a 7 Tesla fMRI scan. 20. The method of any one of embodiments 11 to 19, wherein measuring the patient's brain activity comprises using electroencephalogram (EEG) scanning. 21. The method of any one of embodiments 11 to 20, wherein measuring the patient's brain activity comprises using functional near-infrared spectroscopy (fNIRs). 22. Determining the levels of the plurality of neurotransmitters in the patient based on the measured brain activity of the patient comprises: determining one or more locations in the brain where signals are measured in response to the stimulation; determining one or more signal strengths associated with each of one or more brain locations based on the measured brain activity of the patient; determining the plurality of neurotransmitter levels based at least in part on the determined one or more locations and the determined one or more signal strengths; 22. The method of any one of embodiments 11 to 21, comprising: 23. The method of claim 22, wherein determining the plurality of neurotransmitter levels comprises comparing the determined signal intensity for the determined location to a threshold signal intensity level for that location. 24. The plurality of stimuli presented to the patient are analyzed based on the one or more emotions associated with the memories associated with the stimuli as indicated in the received information; 24. A method according to any one of embodiments 11 to 23, wherein determining the one or more locations in the brain is based at least in part on the one or more emotions indicated in the received information. 25. The method of any one of embodiments 11 to 24, wherein the one or more emotions include emotions from the group including enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, affection, amusement, joy, and gratitude. 26. A system for identifying and treating neurological deficiencies, comprising: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency with respect to at least a first neurotransmitter in the patient based at least in part on the determined plurality of neurotransmitter levels in the patient; 10. A system comprising: one or more processors configured to cause the system to: 27. A non-transitory computer-readable storage medium storing instructions for identifying and treating a neurological deficiency, the instructions being executed by one or more processors of a system to provide the system with: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency with respect to at least a first neurotransmitter in the patient based at least in part on the determined plurality of neurotransmitter levels in the patient; A non-transitory computer-readable storage medium comprising instructions configured to cause

[0143] The foregoing description has been described with reference to specific embodiments for purposes of explanation. However, the illustrative discussion above is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. Many modifications and variations are possible in light of the above teachings. The embodiments have been chosen and described in order to best explain the principles of the technology and their practical application, thereby enabling those skilled in the art to best utilize the technology and various embodiments, with various modifications, as suited to the particular use contemplated.

[0144] Although the present disclosure and examples have been fully described with reference to the accompanying drawings, it should be noted that various changes and modifications will become apparent to those skilled in the art, and such changes and modifications are to be understood as being included within the scope of the present disclosure and examples as defined by the claims.

[0145] This application discloses several numerical ranges in the text and figures. The disclosed numerical ranges inherently support any range or value within the numerical range, including the disclosed endpoints, but since the disclosure can be practiced throughout the disclosed numerical ranges, no strict range limitations are stated literally herein.

[0146] The above description is presented to enable any person skilled in the art to make and use the disclosure, and it is provided in the context of a particular application and its requirements. Various modifications to the preferred embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein. Finally, the entire disclosures of the patents and publications mentioned in this application are incorporated herein by reference.

Claims

1. 1. A method for identifying and treating a neurological deficiency, the method being implemented by a system including one or more processors, the method comprising: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency in the patient with at least a first neurotransmitter based at least in part on the determined neurotransmitter levels in the patient; A method comprising:

2. identifying a subset of the plurality of patient memories associated with a positive neurological response indicated by the brain activity of the patient based on the memory information and based on the identified neurological deficiency; identifying a first aspect that is common across a plurality of memories based on the identified subsets of the plurality of patient memories and based on the respective metadata indicative of an aspect of the identified subsets; generating and providing an individualized treatment plan for said patient including the indicator of said first aspect; The method of claim 1 , comprising:

3. Identifying the neurological deficit includes: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on pharmacological and / or clinical biochemical information about the patient to determine that the provisional indication of neurological deficit should not be rejected; 3. The method of claim 1 or 2, comprising:

4. Identifying the neurological deficit includes: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the patient's memory information, including by comparing the patient's emotional intensity information with emotional intensity threshold information, to determine that the provisional indication of neurological deficit should not be rejected; 4. The method of claim 1, further comprising:

5. Identifying the neurological deficit includes: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the patient's memory information, including by analyzing changes in the patient's emotional intensity information over time, to determine that the provisional indicator of neurological deficit should not be rejected; and 5. The method of claim 1, comprising:

6. Identifying the neurological deficit includes: generating a provisional indicator of the neurological deficit based on the determined neurotransmitter levels of the patient; applying one or more rule sets based on the patient's memory information, including by applying the memory information to a positive emotion versus neurotransmitter (PE-NT) matrix to determine that the tentative indicator of neurological deficit should not be rejected; 6. The method of claim 1, comprising:

7. 7. The method of claim 1, wherein the first neurotransmitter is selected from the group consisting of dopamine, serotonin, testosterone, oxytocin, cannabinoids, and opioids.

8. 8. The method of claim 1, wherein measuring the patient's brain activity comprises using functional magnetic resonance imaging (fMRI) scanning.

9. 9. The method of claim 8, wherein the fMRI scan is a 7 Tesla fMRI scan.

10. 10. The method of claim 1, wherein measuring the patient's brain activity comprises using electroencephalogram (EEG) scanning.

11. 11. The method of claim 1, wherein measuring the patient's brain activity comprises using functional near-infrared spectroscopy (fNIRs).

12. Determining the plurality of neurotransmitter levels in the patient based on the measured brain activity of the patient includes: determining one or more locations in the brain where signals are measured in response to the stimulation; determining one or more signal strengths associated with each of the one or more locations of the brain based on the measured brain activity of the patient; determining the plurality of neurotransmitter levels based at least in part on the determined one or more locations and the determined one or more signal strengths; 12. The method of any one of claims 1 to 11, comprising:

13. 13. The method of claim 12, wherein determining the plurality of neurotransmitter levels comprises comparing the determined signal strength for the determined location to a threshold signal strength level for that location.

14. the plurality of stimuli presented to the patient are analyzed based on the one or more emotions associated with the memories associated with the stimuli as indicated in the received information; 14. The method of claim 1, wherein determining the one or more locations in the brain is based at least in part on the one or more emotions indicated in the received information.

15. 15. The method of any one of claims 1 to 14, wherein the one or more emotions include emotions from the group including enthusiasm, sexual desire, pride / recognition, nurturing love, satisfaction, affection, amusement, joy, and gratitude.

16. 1. A system for identifying and treating a neurological deficiency, comprising: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency in the patient with at least a first neurotransmitter based at least in part on the determined neurotransmitter levels in the patient; 10. A system comprising: one or more processors configured to cause the system to:

17. 1. A non-transitory computer-readable storage medium storing instructions for identifying and treating a neurological deficiency, the instructions being executable by one or more processors of a system to provide the system with: receiving information associated with a patient, the received information including memory information for a plurality of patient memories, wherein for each of the plurality of patient memories, the memory information indicates a respective emotion intensity for each of one or more emotions, respective time information, and respective metadata indicative of an aspect of the memory; providing a plurality of stimuli to the patient, each of the plurality of stimuli being respectively associated with one or more of the patient memories; measuring brain activity of the patient while providing the stimulation to the patient, wherein measuring brain activity includes collecting data indicative of a location of brain activity and an associated intensity of the brain activity; determining levels of a plurality of neurotransmitters in the patient based on the measured brain activity of the patient; identifying a neurological deficiency in the patient with at least a first neurotransmitter based at least in part on the determined neurotransmitter levels in the patient; A non-transitory computer-readable storage medium comprising instructions configured to cause

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