SOURCE by GENE OSTROVSKY on Jan 31, 2013


The human brain may be the most complex and mysterious system in the universe, so studying it requires some advanced tools. Of course, researchers have some of the best tools around – their own brains – but it’s going to take more than thinking to figure this organ out. To get a sufficiently nuanced picture of the brain, simulation and high power computing are going to play a role.

The Human Brain Project, an initiative to map and simulate the organ down to individual neurons, just won a commitment from the European Commission for €1 billion ($1.4 billion) worth of grants. The project hopes to bring together about 200 scientists from various fields and international institutions to first build a computational platform and then to use it to get a better understanding of the brain.

From the project’s info page:

HBP’s first goal is to build an integrated system of six ICT [Information and Communication Technology] based research platforms, providing neuroscientists, medical researchers and technology developers with access to highly innovative tools and services that can radically accelerate the pace of their research.

The second goal of the project is to trigger and drive a global, collaborative effort that uses the platforms to address fundamental issues in future neuroscience, future medicine and future computing.

The end result will be not just a new understanding of the brain but transformational new ICT. As modern computers exploit ever-higher numbers of parallel computing elements, they face a power wall: power consumption rises with the number of processors, potentially to unsustainable levels. By contrast, the brain manages billions of processing units connected via kilometres of fibres and trillions of synapses, while consuming no more power than a light bulb. Understanding how it does this – the way it computes reliably with unreliable elements, the way the different elements of the brain communicate – can provide the key not only to a completely new category of hardware (Neuromorphic Computing Systems) but to a paradigm shift for computing as a whole, moving away from current models of “bit precise” computing towards new techniques that exploit the stochastic behaviour of simple, very fast, low-power computing devices embedded in intensely recursive architectures.



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