December 10, 2012. Researchers from the University of Waterloo report that they have 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 behavior 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 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 behavior.
“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 can be found here.