Scientists to Build 'Brain Box'

lee1 writes "Researchers at the University of Manchester are constructing a 'brain box' using large numbers of microprocessors to model the way networks of neurons interact. They hope to learn how to engineer fail-safe electronics. Professor Steve Furber, of the university school of computer science, hopes that biology will teach them how to build computer systems. He said: 'Our brains keep working despite frequent failures of their component neurons, and this "fault-tolerant" characteristic is of great interest to engineers who wish to make computers more reliable. [...] Our aim is to use the computer to understand better how the brain works [...] and to see if biology can help us see how to build computer systems that continue functioning despite component failures.'"

Fault tolerance with fuzzy logic already done

[EmbeddedJanitor]

In an interesting experiment in the 80s, a controller based on fuzzy chips degraded gracefully.

The system was designed around a set of fuzzy computing boards. When one of the boards was removed, the control degraded, but still continued to function. Of course if some critical boards (eg direct attached to outputs) were removed, the system would fail immediately.

Academia dupe?

[shib71]

Since when is this a new idea? I heard about people doing stuff like this years ago.

http://neuralnets.web.cern.ch/NeuralNets/nnwInHepH ard.html [web.cern.ch]
http://www.particle.kth.se/~lindsey/elba2html/sect ion3_5.html [particle.kth.se]
http://www.cs.ucl.ac.uk/staff/D.Gorse/research/pRA M.html [ucl.ac.uk]
http://www.kcl.ac.uk/neuronet/about/roadmap/hardwa re.html [kcl.ac.uk]

Re:some amusing calculations

[Stuntmonkey]

so how fast do we think? well i couldn't find anything on this so lets get a quick estimate. the average neuron is .1m in length .1 / c = 3.3x10^-10 or 333 picoseconds. now lets add in some delay for the chemicals in the neurons to do their thing, this is probably much slower than the electrical impulse, so lets say 3.3 nanoseconds.

This is a drastic underestimate of the computational timescale for neurons in the brain. The error on the back of your envelope is that chemical diffusion is a fundamental part of the process, and chemical diffusion (i.e. random walking) is very slow relative to the speed of light. For neural computation, diffusion is required for both the propagation of action potentials within single neurons (ions diffusing across the cell membrane), as well as the propagation of signals between neurons (neurotransmitter chemicals diffusing across the synapse).

A better generic estimate for computational timescale would be a few milliseconds, so you are about 10^6 off in your subsequent estimates.

Re:some amusing calculationst

[Procyon101]

yup. The neurons have alot of chemical work to do before being able to fire again. Most soures I've seen measure the neurons rate of fire in Hz, not even kHz as you suggest, and certainly not the GHz of the OP.

Re:some amusing calculations

[giafly]

so how fast do we think?

When I was studying experimental psychology, I calculated the brain's effective "clock speed" as about one tick per 10ms, or 100Hz. Within a factor of two. Of course the brain is immensely parallel and every nerve cell is like a separate "core", so it's still very powerful. What slows it down is using chemical diffusion to pass signals across junctions (synapses). Back in the day, some of our potential protozoan ancestors already had light receptors and emitters - if only they'd used these instead!

Re:some amusing calculations

[Illserve]

There are so many unfounded or incorrect assumptions in this post that I'm forced to comment.

  A synapse is not a FLOP. Dendrites are computational devices in themselves, and a synaptic activation at one point along the dendritic branch will affect how a synaptic activation elsewhere affects the soma. Also, when neurons fire, the spikes propagate backwards down the dendrite to allow the synapses to learn. Simulating this to even a crude degree of accuracy requires a compartmental model of the dendritic tree as a series of compartments. The equations involved in doing this are expensive to say the least.

The computer needed to do this at a brain level would probably be about the size of the moon.

And even if you built such a thing, you still wouldn't understand how it works, it would just be an equally mysterious human intelligence implemented in a moon sized computer. Also, we are nowwhere near understanding the anatomy of the brain to a degree that would permit us to make our moon-sized replication.

So really, reproducing the function of the brain is going to come from an understanding of its principles of organization and function, not from a piecemeal replication at a cellular level. There are substantially complicated bits of brain function that can be replicated with a single Dell desktop if you abstract yourself away from the neural implementation.

The point being, these comparisons between number of synapses and CPU's as a metric of us simulating a brain are uninformative and terribly misleading.

Although I have to say from a selfish perspective, for the degree to which ideas like this excite public interest and generate funding in my field of research, knock yourself out.

Teramac, by Hewlett-Packard

[mosel-saar-ruwer]

This sort of thing [highly parallelizable, highly fault-tolerant computing] was done more than a decade ago, at Hewlett-Packard, in the old Teramac group.

Background here [hp.com], here [kinetic.org], here [byu.edu], etc.