Research Fellows Directory
Professor Stephen Furber CBE FREng
University of Manchester
The human brain remains as one of the great frontiers of science – how does this organ upon which we all depend so critically actually do its job? A great deal is known about the underlying technology – the neuron – and we can observe large-scale brain activity through techniques such as magnetic resonance imaging, but this knowledge barely starts to tell us how the brain works. Something is happening at the intermediate levels of processing that we have yet to begin to understand, but the essence of the brain's information processing function probably lies in these intermediate levels. To get at these middle layers requires that we build models of very large systems of spiking neurons, with structures inspired by the increasingly detailed findings of neuroscience, in order to investigate the emergent behaviours, adaptability and fault-tolerance of those systems.
Multi-core processors are now established as the way forward on the desktop, and highly-parallel systems have been the norm for high-performance computing for some time. In a surprisingly short space of time, industry has abandoned the exploitation of Moore’s Law through ever more complex uniprocessors, and is embracing the ‘new’ Moore’s Law: the number of processor cores on a chip will double roughly every 18 months.
Considering these two issues together draws us to two parallel, synergistic directions of enquiry, progress in either of which will represent a major scientific breakthrough:
• Can massively parallel computing resources accelerate our understanding of brain function?
• Can our growing understanding of brain function point the way to more efficient parallel, fault-tolerant computing?
Potential benefits from these lines of enquiry include better understanding and treatment of mental disorders and better, more reliable and more power-efficent computers.