Waterloo researchers create world's largest functioning model of the brain
Professor Chris Eliasmith
November 29, 2012
WATERLOO, Ont. (Thursday, Nov. 29, 2012) – A team of researchers from the University of Waterloo has built the
world's largest simulation of a functioning brain. It can help scientists understand how the complex activity of the brain gives
rise to the complex behaviour exhibited by animals, including humans.
The model is called Spaun, which stands for Semantic Pointer Architecture Unified Network. It consists of 2.5 million simulated
neurons. The model captures biological details of each neuron, including which neurotransmitters are used, how voltages are
generated in the cell, and how they communicate. Spaun uses this network of neurons to process visual images in order to control
an arm that draws Spaun's answers to perceptual, cognitive and motor tasks. The research team's findings appear in this week's
issue of the journal Science.
"This is the first model that begins to get at how our brains can perform a wide variety of tasks in a flexible manner—how the
brain coordinates the flow of information between different areas to exhibit complex behaviour," said Professor Chris Eliasmith,
Director of the Centre for Theoretical Neuroscience at Waterloo. He is Canada Research Chair in Theoretical Neuroscience, and
professor in Waterloo's Department of Philosophy and Department of Systems Design Engineering.
Unlike other large brain models, Spaun can perform several tasks. Researchers can show patterns of digits and letters the model's
eye, which it then processes, causing it to write its responses to any of eight tasks. And, just like the human brain, it can
shift from task to task, recognizing an object one moment and memorizing a list of numbers the next. Because of its biological
underpinnings, Spaun can also be used to understand how changes to the brain affect changes to behaviour.
"In related work, we have shown how the loss of neurons with aging leads to decreased performance on cognitive tests,"
said Eliasmith. "More generally, we can test our hypotheses about how the brain works, resulting in a better understanding of
the effects of drugs or damage to the brain.”
In addition, the model provides new insights into the sorts of algorithms that might be useful for improving machine intelligence.
For instance, it suggests new methods for controlling the flow of information through a large system attempting to solve
challenging cognitive tasks.
Professor Eliasmith has written a book on the research. How To Build A Brain will be on shelves this winter.
Videos on the project are at
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