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Do the maths: HAL 9000 by 2018?

There's a new science in town: connectomics. A specialised form of neuroanatomy, connectomics is in the business of mapping out the brain's networks – in particular, how the various functional modules already identified connect to each other.
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Written by Rupert Goodwins on

There's a new science in town: connectomics. A specialised form of neuroanatomy, connectomics is in the business of mapping out the brain's networks – in particular, how the various functional modules already identified connect to each other. While this has always been of interest to brain researchers, it's only recently that the IT's been good enough to embark on seriously detailed mapping – and fascinating new results are already turning up.

For example, work at Indiana University, University of Lausanne, Switzerland, Ecole Polytechnique Fédérale de Lausanne, Switzerland, and Harvard Medical School has uncovered a "superhub", a structure between the two halves of the brain where many networks converge, and that's active all the time. Exactly what it's doing and what happens when it goes wrong are two very interesting questions.

Connectomics has a higher aim, to produce a complete map of the brain's networks akin to the sequenced information from the human genome projects. That's ambitious, but by combining new extremely high resolution scanning technologies with computational analysis that pulls structures out of the data it seems entirely realisable.

Meanwhile, other intensive data crunching is cogitating away with IBM's Blue Brain project, where the team has built "a rat-scale cortical model (55 million neurons, 442 billion synapses) in 8TB memory of a 32,768-processor BlueGene/L" That's a long way from the ten billion or so neurons of the human brain – 180 times smaller, in fact – but in Moore's Law terms, that's around ten years. And the researchers are most definitely looking ahead: "Our long-term goals are to develop novel brain-like cortex size computing architectures along with appropriate programming paradigms, and to evolve C2 into a cortex-like universal computational platform that integrates and operationalizes existing quantitative neuroscientific data to build simulation of large networks of spiking neurons and a powerful learning machine: a cognitive computer" (from their report Anatomy of a Cortical Simulator - pdf).

You know what that means. Doesn't matter if you don't - it will know..

A lot of that work is going on in the same places as the connectomics research – so no prizes for guessing where that's all heading. We may have missed the starting gun, but the race to produce a full working model of the human brain has most certainly started.

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