Computational Challenges for Brain Science and Medicine

11 August 2014 / Warsaw, Poland

Richard Feynman

What I cannot create, I do not understand.

on his blackboard at the time of death in February 1988

Nature uses only the longest threads to weave her patterns, so each small piece of her fabric reveals the organization of the entire tapestry.

chapter 1, “The Law of Gravitation,” p. 34

Richard Feynman

Reinforcement learning,optimal control and utility theory

Information theory and minimum redundancy

Self-organisation, cybernetics, homoeostasis and autopoiesis

Bayesian brain, predictivecoding and active inference

Value

Surprise (free energy)

Entropy

Model evidence

Pavlov

Ashby

Helmholtz

ln ( | )

ln ( | )

[ ln ( | )]

( | )

t

p s m

p s m

E p s m

p s m

Barlow

Haken

( ) ( ) ln ( | )

( ) ( ) ln ( | )

r

a a

f s Q p s m

f s Q p s m

Perception

Action

Thorndike

If you can't explain it simply, you don't understand it...

( ) ( ) ln ( | )

( ) ( ) ln ( | )

r

a a

f s Q p s m

f s Q p s m

Perception

Action

If you can't explain it simply, you don't understand it...

In the hands of a Feynman the [variational] technique works like a Latin charm; with ordinary mortals the result is a mixed bag.

Forman S. Acton, Numerical Methods that Work (1970) p. 252

ln ( | )F p s m

The brain minimises [variational] free energy.