Mathematical Modeling ofSpontaneous Brain Activity
and Psychiatry

ATR Computational Neuroscience
Labs
Mitsuo Kawato
Discovery Channel

Neuroscience: Tilting Against aMajor Theory of Movement Control

Reconstruction of Firing Frequency for
Different Stimulus Speeds and Durationf(t): firing frequency

(t): eye movement

ÝÝt     BÝt     K t     ff t   M
bias

Squared Correlation Coefficient 0.78

Shidara M, Kawano K, Gomi H, Kawato M: Inverse‐dynamics model eye movement control bypurkinje cells in the cerebellum. Nature, 365, 50‐52 (1993).

Behavioral and Imaging Datafor Learning Sessions

Imamizu H, Miyauchi S, Tamada T, Sasaki Y, Takino R, Puetz B, Yoshioka T, Kawato M:
Human cerebellar activity reflecting an acquired internal model of a new tool.
Nature 403 192-195(2000)

DB Air Hockey by Reinforcement Learning,Learning by Watching and Skill Learning••Learn appropriate actions and sub‐goals for theobserved situation.
– Database initialized with supervised data;
observes human player.
– Actions: Right bank shot, left bank shot, etc.
Learn by adjusting the distance to the query point
within the database.
– Data is retrieved using locally weighted
learning (LWL) techniques.
– Weights are updated using Q learningtechniques.

• Agent receives feedback (reward andpenalty) while playing.

Air Hockey
Darrin C. Bentivegna (darrin@atr.jp)

Haruno M, Kuroda T, Doya K, Toyama K, Kimura M, Samejima K, Imamizu H, Kawato M: A neural correlate of reward-based behavioral
learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task. Journal of Neuroscience 24, 1660-1665(2004)

Reconstruction of Black and White
General Images from V1 fMRI Signal

Miyawaki, Uchida, Yamashita, Sato, Tanabe, Sadato, Kamitani Neuron (2008)7

Dream Reading

Neural decoding of visual imagery during sleep. T. Horikawa, M. Tamaki, Y. Miyawaki,
8
Y. Kamitani, Science, 340, 639‐642 (2013)

ROI fMRI real-time neurofeedback;pain, Parkinson’s disease, anxiety

NeuroImage. 2003 Jul;19(3):577-86.Physiological self-regulation of regional brain activity
using real-time functional magnetic resonance imaging (fMRI): methodology andexemplary data . Weiskopf N, Veit R, Erb M, Mathiak K, Grodd W, Goebel R, Birbaumer N.

ACC for Pain; De Charms RC et al. (2005) PNAS 102, 18626
SMA for Parkinson; Subramanian L. et al. (2011) J Neurosci. 31, 16309
OFC for OCD; Scheinost D, et al. (2013) Translational psychiatry 3:e250.

Are V1/V2 plastic enough toaccommodate visual perceptual
learning?
Perceptual learning

Behavioral performance

Conventional way:
Correlation

Before trainingAfter training

Our goal:
Causality

Shibata K, Watanabe T, Sasaki Y, Kawato M: Perceptual learning incepted by decoded
fMRI neurofeedback without stimulus presentation. Science, 334 1413‐1415 (2011)

Behavioral pre- and post-test
Stimuluspresentation

Behavioral
pre‐test

Reportorientation

FMRI Decoder
construction

TimeOrientation
Decoded fMRI
neurofeedback

Behavioral
Post‐test

10 deg70 deg130 deg

Noiselevel
Hard

Easy

fMRI decoder construction
Behavioral
pre‐test
10 deg70 degFMRI Decoder
construction

130 deg

Likelihoods
21%

Decoded fMRI
neurofeedback

Decoder

V1 & V2

Behavioral
Post‐test

MultinomialSparse
LogisticRegression

61%

18%Multinomial Sparse Logistic Regression
Yamashita et al., NeuroImage, 2008

Sparseness prior10-day Decoded fMRI neurofeedback
Behavioral
pre‐test

Visual stimulus to subjects
Induction Period

Reward feedback

FMRI Decoder
construction
TimeTarget
Orientation

Decoded fMRI
neurofeedback

Decoder61%

Behavioral
Post‐test

V1 & V2

Neurofeedback system

Accuracies only in target
orientation improved in post-tests
compared with pre-tests
3‐way ANOVA: Day * Orientation * S/N ratio, P = 0.02
100Target−60 deg+60 deg

80*60

P < 0.01
Pre‐test
Post‐test

40468124 6 812S/N ratio [%]46812

Conclusions of Perceptual
Learning induced by decoded
Neurofeedback• Mere induction of spatial pattern of neuralactivity is sufficient to cause visual perceptual
learning without visual stimulus presentation.
• V1/V2 are locus of visual perceptual learning:demonstrating V1/V2 plasticity in adulthood• Subjects were not aware of what theneurofeedback signal represents and which is
the target orientation.
• Minimal information leak outside V1/V216

Correlation vs Cause-and-Effect;
From neural codes to mind
(3) Decoded neurofeedback∝(1) Correlation (fMRI, unit activity)

decoder

Physical and/or
mental variable(2) Lesion (Patient,pharmacological, TMS)

Stimuli,
Reward,etc

decodedinformation

lesionloss or deteriorationof functions• Necessary condition• No neural code examined

Induction of a specific neuralcode is sufficient to cause a
specific function

Kawato M: From “understanding the brain by creating the brain” toward manipulative
neuroscience. Philosophical Transactions of the Royal Society B, 363, 2201-2214 (2008)17

Why DecNef works out?
• Brain activity always fluctuates.
• If activity happens to fluctuate in a desired
direction, the decoder detects it and a reward
feedback is given to a subject and the brain.
• Synaptic plasticity is induced dependent onneuromodulators such as dopamine.
• Reinforcement learning without action but
essentially the same as that for sensorymotor learning
occurs in basal ganglia and cerebellum.
• Billions of synapses and millions of neurons
fluctuate their activities to induce voxel fluctuation.
• Activated synapses in conjunction with reward
may be potentiated, and depressed with penalty.
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Independent Component Analysis of Big Data
(30,000 sub., 10,000 exp., and 2,000 papers)

Laird AR et al.(2011) J.
Cog. Neurosci. 4022

DMN

16 components out of 18
correspond well to thoseobtained from restingstates

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ICA from resting state activity of
306 subjects; rs-fcMRI

lM

PDMN

1Biswal BB et al.
(2010) PNAS,4734

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