Google X Health Verily

What is the vision ?

Doctor, I am depressed, sad, feel helpless, Despaired, what do I have doctor ? Pleas tell me

You have depression

Gee – isn’t that what I just told you

Can’t you give me any added value

?!?

Doctor, my stomach hurt, what do I have doctor ? Pleas tell me You have Appendecites Doctor, I am depressed, and sad, what do I have doctor ? Pleas tell me You have depression ? ? ? Place in the body What happend to it It is infected How to treat it Antybiotics

GastroenterologistCardiologistUrologist Psychiatrist

GastroenterologistCardiologistUrologist Psychiatrist

Cure psychiatric disorders

Three Strategic steps to get there 1 2 3

1 2 3 Objectivization of psychiatric phenomenology Discovery of the Etiology Brain Pacemaker RDoC

1 2 3 Objectivization of psychiatric phenomenology Discovery of the Etiology Brain Pacemaker Lets start from the end for a moment

These are NOT how brain pacemakers will look

Sensing-reacting Engine on a stickerNeuronal-modulating Nanoparticles Surprisingly they will look like this

A sticker on the forehead will control non-invasively and remotely activity of nanoparticles navigated to control PFC interneurons

Sensing arm Controlling arm Self-organizing module Brain-Pacing Sticker Loop device with sensing and controlling actions targeted to brain Hubs responsible for global brain optimization

1 2 3 Objectivization of psychiatric phenomenology Discovery of the Etiology Brain Pacemaker

Collects cyberactivity and generates trait profiles including personality cognition and psychiatric DSM- related phenomenology phenomenology

Collected is the totality of cyber- activity or as much as consented by the user, accuracy of profile depend on cyber activity Speech & Voice Content SMS Navigation cross- correlated Movement &Activity Face recogntion Incoming out—coming Logs Contents ( , Docs, sites ect..) Activity (open close speed typing) Social activity (social web) Gaming phenomenology

To generate growth the profiles will be used as psychological IDs that users will need to get insurance jobs ect… Commercial models Insurance Jobs HMO’s Banks Military phenomenology

Commercial models Insurance Jobs HMO’s Banks Military E g o B o o k AirB&B phenomenology Additional Commercial models To generate growth the profiles will be used as psychological IDs that users will need to get insurance jobs ect…

Commercial models Insurance Jobs HMO’s Banks Military E g o B o o k AirB&B Power of Big-data phenomenology Additional Commercial models To generate growth the profiles will be used as psychological IDs that users will need to get insurance jobs ect…

Woorlds

1 2 3 Objectivization of psychiatric phenomenology Discovery of the Etiology Brain Pacemaker RDoC (CBP)

Collects cyberactivity and generates trait profiles including personality cognition and psychiatric DSM- related phenomenology phenomenology Now that large-data phenomenology has been collected it is time to collect large data from brains and generate large data from brain imaging

Collects cyberactivity and generates trait profiles including personality cognition and psychiatric DSM- related phenomenology phenomenology Multiple devices already exist (there is room for development) EEG is probably the more feasible technologically

phenomenology Multiple devices already exist (there is room for development) EEG is probably the more feasible technologically

phenomenology Use it yourself NO FDA

phenomenology Large data Brain Imaging Large data Phenomenology What is Critically RELEVANT here is that the large-datasets are SYNCHRONIZED in real-time Synchronized Brain imaging

phenomenology Large data Brain Imaging Large data Phenomenology Now we are in a position to DISCOVER the causes of psychiatric disorders by discovering he relationships between brain dynamic organization and the phenomenology that emerges from it Synchronized Brain imaging BUT HOW ?

phenomenology Large data Brain Imaging Large data Phenomenology Now we are in a position to DISCOVER the causes of psychiatric disorders by discovering he relationships between brain dynamic organization and the phenomenology that emerges from it Synchronized Brain imaging Data Driven [Machine learning] ? Theory Driven ?

phenomenology Large data Brain Imaging Large data Phenomenology Now we are in a position to DISCOVER the causes of psychiatric disorders by discovering he relationships between brain dynamic organization and the phenomenology that emerges from it Synchronized Brain imaging Data Driven [Machine learning] ? Theory Driven ?

phenomenology There will be a place for THEORY-DRIVEN UNDERSTANDING of the data and here comes the RDoC Synchronized Brain imaging Negative valence systems Positive valence systems Cognitive systems Social processes systems Arousal regulatory systems Gene Molecules Cell Circuits Physiology Behavior

Negative valence systems Positive valence systems Cognitive systems Social processes systems Arousal regulatory systems Gene Molecules Cell Circuits Physiology Behavior CBP The RDoC effort should focus initially on one most promising level of brain organization – The Circuit level and here comes CBP Clinical Brain Profiling

Negative valence systems Positive valence systems Cognitive systems Social processes systems Arousal regulatory systems Gene Molecules Cell Circuits Physiology Behavior Explanatory power Brain-Pacing Intervention CBP This level is intermediate between molecular and whole brain levels thus has explanatory power going up the hierarchy and down the hierarchy. It is accessible to brain imaging. This level is also a suitable intervention level in a position to regulate lower-level and higher-level brain organizations Relevant for Imaging analysis Clinical Brain Profiling

Negative valence systems Positive valence systems Cognitive systems Social processes systems Arousal regulatory systems Gene Molecules Cell Circuits Physiology Behavior CBP phenomenology So now we are focused on finding the psychiatric phenomenological correlates of disturbances of brain network circuitry – or in other words, the disturbances of brain network circuitry causing psychiatric phenomenology or illness – i.e., the etiology of psychiatric disorders Clinical Brain Profiling

So what are the major issues that we know about brain circuitry and connectivity ? Those that can become disturbed in psychiatric illnesses

Synapto genesis Atrop hy CONNECTIVTY We know that Small World brain organization is optimal for modal-specific specialization and multimodal integration and Hierarchical processing H i e r a r c h yH i e r a r c h y Environment Action sensation INTERNAL REPRESENTATIONS The internal model determines how we view the psychosocial world and react to it, this is our personality style PLASTICTY The brain is Plastic. Neurons continually create (Synaptogenesis) and lose (Atrophy) connections PLASTICTY & ADAPTABILITY Plastic brains adapt reducing Free Energy updating internal representations and acting of the environment to adjust it to internal plans Free Energy reduction

Synapto genesis Atrop hy CONNECTIVTY We know that Small World brain organization is optimal for modal-specific specialization and multimodal integration and Hierarchical processing H i e r a r c h yH i e r a r c h y Environment Action sensation INTERNAL REPRESENTATIONS The internal model determines how we view the psychosocial world and react to it, this is our personality style PLASTICTY The brain is Plastic. Neurons continually create (Synaptogenesis) and lose (Atrophy) connections PLASTICTY & ADAPTABILITY Plastic brains adapt reducing Free Energy updating internal representations and acting of the environment to adjust it to internal plans Free Energy reduction Psychosis Schizophrenia spect’ Cognition Mood Depression & Anxiety Personality Disorders

Negative valence systems Positive valence systems Cognitive systems Social processes systems Arousal regulatory systems Gene Molecules Cell Circuits Physiology Behavior CBP Synapto genesis Atro phy H i e r a r c h yH i e r a r c h y Environment Action sensation Psychosis & Schizophrenia Mood disorders Personality Disorders

Cs Connectivity segregation Ci Connectivity integration Hbu Hierarchical bottom-up insufficiency Htd Hierarchical top-down shift O Optimization D De- Optimization CF Constraint frustration CF(b) Stimulus bound DMN Default Mode Network Delusi ons Halluc inatio ns Avolit ion Psycho sis Negati ve signs Mani a Depres sion Anxiet y Phobia Person ality disord er ConnectivityPlasticityPersonality C l i n i c a l B r a i n P r o f i l i n g

Cs Connectivity segregation Ci Connectivity integration Hbu Hierarchical bottom-up insufficiency Htd Hierarchical top-down shift O Optimization D De- Optimization CF Constraint frustration CF(b) Stimulus bound DMN Default Mode Network Delusi ons Halluc inatio ns Avolit ion Psycho sis Negati ve signs Mani a Depres sion Anxiet y Phobia Person ality disord er ConnectivityPlasticityPersonality C l i n i c a l B r a i n P r o f i l i n g

Cs Connectivity segregation Ci Connectivity integration Hbu Hierarchical bottom-up insufficiency Htd Hierarchical top-down shift O Optimization D De- Optimization CF Constraint frustration CF(b) Stimulus bound DMN Default Mode Network Delusi ons Halluc inatio ns Avolit ion Psycho sis Negati ve signs Mani a Depres sion Anxiet y Phobia Person ality disord er ConnectivityPlasticityPersonality C l i n i c a l B r a i n P r o f i l i n g

phenomenology So now we are in a position to predict personalized (large-data) brain disturbance and validate them with brain imaging CBP

phenomenology …… and validate them with brain imaging CBP Compare VALIDATE

phenomenology CBP Compare VALIDATE

1 2 3 Objectivization of psychiatric phenomenology Discovery of the Etiology Brain Pacemaker Back to the vision

phenomenology With validated theory we are in a position to start programing the corrective action of brain pacing CBP

Sensing arm Controlling arm Brain-Pacing Sticker 4. Network Hub activity optimizing whole-brain connectivity stabilizing perturbed brain 1. Remote signal 2. Nanoparticle action on calcium channel receptors and action potential 3. Regulatory action on layer IV pyramidal neurons, executing Network Hub effects CBP

Sampled Brain Organization Delta-controlled Signal delta Sampled organization Self-organization Optimization Deep-Learning like algorithms Brain-Pacing Sticker

Sampled Brain Organization Delta-controlled Signal delta Sampled organization Self-organization Optimization Deep-Learning like algorithms Brain-Pacing Sticker CBP