How to build a brain

Chris EliasmithCentre for Theoretical Neuroscience

Three views• Symbolicism

• Connectionism

• Dynamicism

A more synthetic approach to neuroscience (to complement the analytic approach)

large-scalecomplete behaviour

Just Scale Up!

State-of-the-art• IBM Cognitive Computing (Synapse)

• Dharmendra Mohda

• 109 simple, spiking neurons (now 5x1011)

Mohda’s slide

Some friction

• "...tremendous historic milestone" Modha

• "...a hoax and a PR stunt" - Markram

• "It is highly unethical of Mohda to mislead the public in making people believe they have actually simulated a cat's brain. Absolutely shocking." - Markram

State-of-the-art

• Blue Brain project - Henry Markram (EPFL)

• 10^6 ‘realistic’ neurons

• Concern: “It takes the established principles in neuroscience combined with mountains of data, shoving it all together to see what emerges” - nerd-alert.net

IBM Blue Gene

Cortical column activity

The deeper problem

Complexity without function

Just scale up

human - 30xmetabolism - 60x brain size - 300x

Tusko

Our recent attempt

• Spaun (Semantic Pointer Architecture Unified Network)

• 2.5 million neurons

• 8 different tasks

• Including basic perceptual tasks...

Eliasmith et al., Nov. 2012, Science.

And more cognitive tasks...

With no changes to Spaun between tasks...

(8 tasks include: recognition, copy drawing, reinforcement learning, counting, serial working memory, question answering, RVC, RPM)

http://nengo.ca/build-a-brain/spaunvideos

Bandit TaskDelay Approach Reward Return

Time (seconds)

Neu

ron

num

ber

Tria

l num

ber

Freq

uenc

y (s

pike

s/s)

V1 tuning

Response timesPeople 344±135, Spaun 419±10 ms/item

Working memory

Why is it brain-like?

How does it work?

How did we build it?

With the Neural Engineering Framework (NEF)

• A ‘neural compiler’

• Three principles

• General

• Unified

• Quantitative

Eliasmith & Anderson (2003) MIT Press

A useful toolNengo (http://nengo.ca/)

Model Construction Interactive Visualization

... and the Semantic Pointer Architecture (SPA)

• Specific functional claims:

• Working memory

• Action selection (BG)

• Motor/perception hierarchies

• Communication protocol:

• Semantic pointers

Eliasmith (2013), Oxford

Semantic Pointers• E.g. The pointer would be the activity of the top

level of a standard hierarchical visual model for object recognition

• This pointer can thensupport ‘symbol’manipulation

• It can also be used toreactivate a full visual representation

Serre et al., 2007 PNAS

SPA: Semantic Pointers• Semantic pointers are: Compressed, content-based

‘addresses’ to information in association cortices

• ‘Pointer’ because they are used to recall ‘deep’ semantic information (content-based pointer)

• ‘Semantic’ because they themselves define a ‘surface’ semantic space

Unified view

• Symbolicism

• Working with structure, SPs

• Connectionism

• Statistical categorization, SPs

• Dynamicism

• Brain/body dynamics, SPs & control

Still a long way to go...

...but I think the SPA/NEF/Nengo combination can help

(... btw, it’s a group effort, so everything here is open source and downloadable).

Further informationResearch, Papershttp://compneuro.uwaterloo.ca/

Nengo software, Tutorials, Demo videoshttp://www.nengo.ca

Spaun team: Terry Stewart, Xuan Choo, Travis Dewolf, Trevor Bekolay, Charlie Tang, Dan Rasmussen

CNRG lab: Eric Hunsberger, James Bergstra, Eric Crawford, Oliver Trujillo, Peter Blouw, Peter Suma, Brent Komer, Aaron Voelker, Youssef Zaky