Shaping Cortical Networks-Activity by Mutual Learning of Brains and Machines

Eilon Vaadia (eilon.vaadia@elsc.huji.ac.il)The Hebrew University, Edmond and lily Safra Center for Brain Science, (Founding Director)

Acknowledgments

• Hagai Bergman (ELSC)• Zvi Israel (Hadassah)• David Hanzel (CNRS Paris & HUJI• Ran Darshan (Ph.D. ELSC)• Larry Abbott (Columbia, USA)• Andrew B. Schwartz (Pittsburg, USA)

Collaborations:The MotorCortex lab• Hagai lalazar (Columbia U/)• Lavi Shpigelman (IBM)• Ben Engelhard (Princeton)• Nofar Ozeri (Princeton)• Oren Peles (Ph.D. ELSC)• Dr. Uri Werner Reiss (Lab Manager)

Support:ADELIS, BSF, ISF, MAFAT, Rosetrees Trust, Skirball Chair and Research fund

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Technical Help:• Dr. Sharon Freeman (retired)• Dr. Uri Werner Reiss• (The late) Dmitry Davidov

Take home Message

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The Brain – the enigma

• The brain is an Adaptive-Predictive State-machine

• Brain inspired BMIs, are efficient and promising

Action-Perception:Adaptive-Predictive Internal Model

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Adaptive Predictor

Goal

Updated Prediction Prediction(based on the past)

KalmanGain Prediction ErrorNeural

State

Action

State(sensory, World)

Adaptive Controller

Efference Copy

ŷt ŷt-1

(Kalman Filter)

BRAIN MACHINE INTERPHASES (BMI)

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Pred. Err.

Adaptive Predictor

State(sensory, World)

Adaptive Controller

Efference Copy

ŷt ŷt-1

BRAIN

Action

Machine learningAlgorithm

Goal

Machine

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The experiments: Spikes of 180 Neurons

1. The Machine learns the Brain Activity and generates actions

BMI Type 1

q N

euro

ns

redu

ce

Spike times

1

Last s bins

r bins

=new state estimate

positionvelocity

acceleration

Shpigelman et al 2006, 2008

previous state estimate

(Real time “action-Perception” autoregressive loop)

KARMA: An Efficient BMI Algorithm:

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(PAST) (FUTURE)

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3-D BMI (KARMA)

Shpigelman, Lalazar, & Vaadia, NIPS, 2008

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BMI Experiments in Humans (Pittsburgh, 2012)

A.B Schwartz, M.L. BoningerE. Tyler-Kabara & W. Wang

NINDS, DARPA

Movements BMIBack to the Monkeys (Movements vs. BMI)

Lalazar , Abbott, Vaadia, Cosyne 2016, In prep 2018 11

Hagai Lalazar

Units

(N=1

94)

Targets (27 locations 3-D) Targets (27 locations 3-D)

Norm

Firi

ng R

ate

min

max

PronationSupinationBMIResting

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Activity of neurons in motor cortex is dynamically adapted, from “Movement-state” warping into a new neuronal state-space “BMI State”

Neuronal state spaceArm movements vs. BMI

Lalazar , Abbott, Vaadia Cosyne 2016, In prep 2018

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During BMI the activity of the local circuit reaches a newneuronal state adapting to the BMI state.

Interim Summary

the next type of BMI:Direct modulations of Brain Activity

Oren Peles Uri Werner-ReissBen EngelhardNofar Ozeri

BMI control of a single unit’s firing rateSpikes/sec

Time (sec)14

POSTConditioning

CONDITIONINGPSEUDOConditioning

PREConditioning

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• Pre-movement• Post Movement• Pseudo• BMI

Method:Gaussian-process factor analysisYu et al 2008

A BMI Neuronal State has evolved!

Engelhard et alIn Prep, 2018

During BMI, the activity evolves from the pseudo subspace and gradually moves, farther away from the “movement subspace” to the newly acquired “BMI state”

BMI Control of Oscillatory Activity

Engelhard et al , Neuron, 2013

Nanorobots

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Interim Summary

• The brain learns rapidly to increase the firing rate of a “target neuron”, and more generally; to change the spatiotemporal pattern of activity of the network.

• The changing patterns of activity reflects a learning process, evolving rapidly to the required new state space (BMI state)

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Manipulation of Beta Oscillations byClosed-loop Electrical Stimulation

• 8 bi-phasic (initial negative) pulses• Phase width: 100usec• Intensity: 80uA

UP

Down

100usec

50msec

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Oren Peles Uri Werner-Reiss

Modulations of Oscillatory patterns

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UP DN

LFP(OSC norm)

Spikes(PC1 -OSC)

4mm

Oren Peles and Uri Werner-Reiss (MAFAT supported project)

Conclusions

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• The experiments show that a local brain’s circuit can rapidly Travel among neuronal states, as required by the new action-perception behavioral state.

• Cortical closed-loop stimulations facilitate BMI control of state transitions.

• Hopeful note; Controlling brain states presents attractive applications and solutions to medical conditions like Epilepsy, Schizophrenia, ADHD, and others.

POTENTIAL AND RISK

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There lies before us, if we choose, continual progress in happiness, knowledge, and wisdom.

We appeal as human beings to human beings: Remember your humanity, and forget the rest.

If you can do so, the way lies open to a new Paradise;

If you cannot, there lies before you the risk of universal death.

Einstein-Raussell Manifesto 1955

Thank youProf. Eilon VaadiaThe Edmond and Lily Safra Center for Brain Sciences, and theThe Hebrew University of Jerusalem

Mail Addressees:

1. email: eilon.vaadia@elsc.huji.ac.il

24Jerusalem, Feb-17-2019