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February 26, 2007

Towards real-time, mouse-scale cortical simulations

Last week, we presented a poster on a fascinating new result at the CoSyNe 2007 conference:

Neurobiologically realistic, large-scale cortical and sub-cortical simulations are bound to play a key role in computational neuroscience and its applications to cognitive computing. One hemisphere of the mouse cortex has roughly 8,000,000 neurons and 8,000 synapses per neuron. Modeling at this scale imposes tremendous constraints on computation, communication, and memory capacity of any computing platform.

We have designed and implemented a massively parallel cortical simulator with (a) phenomenological spiking neuron models; (b) spike-timing dependent plasticity; and (c) axonal delays.  

We deployed the simulator on a 4096-processor BlueGene/L supercomputer with 256 MB per CPU. We were able to represent 8,000,000 neurons (80% excitatory) and 6,300 synapses per neuron in the 1 TB main memory of the system. Using a synthetic pattern of neuronal interconnections, at a 1 ms resolution and an average firing rate of 1 Hz, we were able to run 1s of model time in 10s of real time!

I believe that such cortical simulators are the linear accelerators of neuroscience. We are already able to study extremely large-scale cortical dynamics. This is a developing story...please stay tuned in!

Reference:

James Frye, Rajagopal Ananthanarayanan, and Dharmendra S. Modha, "Towards real-time, mouse-scale cortical simulations," CoSyNe: Computational and Systems Neuroscience, Salt Lake City, Utah, Feb 22-25, 2007 PDF

February 19, 2007

Google and AI

The programming language of humans, if you will, would include the workings of your brain, said Google co-founder Larry Page, who offered his hypothesis Friday night during a plenary lecture here at the annual American Association for the Advancement of Science conference. His guess, he said, was that the brain's algorithms weren't all that complicated and could be approximated, eventually, with a lot of computational power. Specifically, Page said "When AI happens, it's going to be a lot of computation, not so much ... clever algorithms." Given the size of DNA (~600 MB compressed), the algorithms of the brain are "probably not that complicated."

"...artificial intelligence...I don't think it's that far off as people think."

Links:

  1. Press article
  2. Video

February 01, 2007

Walter Freeman turns 80!

Walter Freeman 

Professor Walter Freeman one of whose academic grandfathers was Nobelist Charles Sherrington and one of whose great great academic grandfathers was Nobelist Thomas Huxley turned 80 years old!

In his honor, his friends, students, and colleagues organized a wonderful "Conference on Brain Network Dynamics". The conference was incredible, and full of intellectual stimulation. Professor Freeman is intellectually as vigorous as ever. They are hoping to have a similar conference when he turns 100!