Google X Health Verily What is the vision

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

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

Urologist Cardiologist Gastroenterologist Psychiatrist

Urologist Cardiologist Gastroenterologist Psychiatrist

Cure psychiatric disorders

3 Three Strategic steps to get there 2 1

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

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

These are NOT how brain pacemakers will look

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

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

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

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

phenomenology Collects cyberactivity and generates trait profiles including personality cognition and psychiatric DSMrelated phenomenology

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

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

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

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

Woorlds https: //www. youtube. com/watch? v=_Rdf. M_po. Gnk

Brain Pacemaker 3 Discovery of the Etiology 2 1 Objectivization of psychiatric phenomenology RDo. C (CBP)

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

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

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

Use it yourself NO FDA phenomenology

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

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 Brain imaging Synchronized phenomenology Large data Phenomenology Large data Brain Imaging Data Driven [Machine learning] ? Theory Driven ?

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 Brain imaging Synchronized phenomenology Large data Phenomenology Large data Brain Imaging P R Data Driven OB [Machine A B learning] ? L Y BO Theory Driven. T ? H

There will be a place for THEORY-DRIVEN UNDERSTANDING of the data and here comes the RDo. C Synchronized Brain imaging Mo Be ha Ph ys vio r iol Cir og cu y its Ce ll lec ule s Ge ne phenomenology stems Negative valence sy stems Positive valence sy Cognitive systems Social processes sy stems Arousal regulatory sy

The RDo. C effort should focus initially on one most promising level of brain organization – The Circuit level and here comes CBP Mo Ci Ph Be ha ys iol vio og r y rc ui ts Ce ll lec ule s Ge ne stems Negative valence sy stems Positive valence sy Cognitive systems Social processes sy stems Arousal regulatory sy CBP Clinical Brain Profiling

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 Explanatory power Relevant for Imaging analysis Mo Ci Ph Be ha ys iol vio og r y rc ui ts Ce ll Brain-Pacing Intervention lec ule s Ge ne stems Negative valence sy stems Positive valence sy Cognitive systems Social processes sy stems Arousal regulatory sy CBP Clinical Brain Profiling

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 Mo Ci Ph Be ha ys iol vio og r y rc ui ts Ce ll lec ule s Ge ne stems Negative valence sy systems phenomenology Positive valence Cognitive systems Social processes sy stems Arousal regulatory sy CBP 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

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

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

Disturbances to connectivity and hierarchy Disturbances to To plasticity Optimization Disturbances to Internal representations Action h y c r r a e H i Synaptogenesis Environment Atrophy sensation Mo Ph Be ha ys vio r iol og y Ci rc ui ts Ce ll lec ule s Ge n Psychosis & Schizophrenia e stems Negative valence sy Mood disorders stems Positive valence sy Cognitive systems Personality Disorders stems Social processes sy stems Arousal regulatory sy CBP

Clinical Brain Profiling Connectivity Htd Hierarchical top-down shift Hbu Hierarchical bottom-up insufficiency n s s on tion olitio i s a Av lu De llucin Ha Plasticity Ci Connectivity integration s y Ps si cho Cs Connectivity segregation ve ati g Ne s n sig O Optimization nia a M D De. Optimization D re ep on ssi Personality CF Constraint frustration ty xie An CF(b) Stimulus bound bia o Ph DMN Default Mode Network y alit n rso Pe order dis

Clinical Brain Profiling Personality y g o l o n i m r e t / y m o n o x a t d e t a l e Brain–r Connectivity Plasticity d e z i l a n Perso Htd Hierarchical top-down shift Hbu Hierarchical bottom-up insufficiency n s s on tion olitio i s a Av lu De llucin Ha Ci Connectivity integration s y Ps si cho Cs Connectivity segregation ve ati g Ne s n sig O Optimization nia a M D De. Optimization D re ep on ssi CF Constraint frustration ty xie An CF(b) Stimulus bound bia o Ph DMN Default Mode Network y alit n rso Pe order dis

Clinical Brain Profiling Connectivity Htd Hierarchical top-down shift Hbu Hierarchical bottom-up insufficiency n s s on tion olitio i s a Av lu De llucin Ha Plasticity Ci Connectivity integration s y Ps si cho Cs Connectivity segregation ve ati g Ne s n sig O Optimization nia a M D De. Optimization D re ep on ssi Personality CF Constraint frustration ty xie An CF(b) Stimulus bound bia o Ph DMN Default Mode Network y alit n rso Pe order dis

http: //neuroanalysis. org. il/cbp/index. php http: //neuroanalysis. org. il/? page_id=114

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 VALIDATE CBP Compare phenomenology

Correlation analysis (nonlinear) Graph analysis (small-world) VALIDATE CBP Compare phenomenology SPM, DCM Entropy measures

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

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

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

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

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