Nerve Cells Successfully Grown on Silicon

crabpeople writes "Researchers at the University of Calgary have found that nerve cells grown on a microchip can learn and memorize information which can be communicated to the brain. 'We discovered that when we used the chip to stimulate the neurons, their synaptic strength was enhanced,' said Naweed Syed, a neurobiologist at the University of Calgary's faculty of medicine."

Comments

Hasn't this been done before?

[nhaze]

I thought the Pine Lab at Caltech had done this several years ago. Neurochip Project

Re:Hasn't this been done before?

[kinnell]

No. You're right, growing neurons on silicon is nothing new, but the breakthrough here is that they have been able to stimulate the neurons into forming new connections, rather than just measuring the response of existing networks.

Re:Hasn't this been done before?

[NeuroKoan]

Quote from the above link
This particular chip has no electrodes. The grillwork design allows the neurons to grow, and contains them indefinitely. We are currently building full chips with this design, and with electrodes.

Keep an eye out for this page. Once we get fully functional chips, it shouldn't be long before I can show some real experiments and data.

I think the big news is that electrodes were on the silicon chip, and were actually able to "learn and memorize information which can be communicated to the brain" (as per the original article).

Also, the page looks like it hasn't been updated since 1995. I wonder what happened to this project. From the page Maher and Thorne seemed so close to what has just been acheived in Canada.

Re:The Future of Computing

[Illserve]

This is certainly not the future of computing!

The precise properties of individual Neurons are unpredictable and highly variable. Worse, they require constant life support just to stay alive. A 5 minute power interruption to your neural CPU and it's time to go shopping for a new one. You would certainly not want to build a practical computing tool out of them.

Neural computing will remain the domain of highly specialized research into AI and neural computing forever. We may develop neural analogs using nanotech or some other gee-whiz tech, but they will not be true neurons.

Re:Kinda cool: Neurons vs. Transistors

[G4from128k]

Neurons are much larger than transistors, but the two aren't really comparable. The main body of a neuron is usually around 25 microns (25000 nm) in diameter and runs at a clockspeed only in the kilohertz max.

A neuron is much more than a transistor-like switch. On the one side of the neuron's central body is a set of dendrites that connect to and gather input from other neurons. The average neuron might have a thousand of these dendrites.

The synapse at the end of each dendrite acts like part of a multiply-accumulate term -- taking the signal from an other neuron, multiplying it by a numerical coefficient and summing it into the total excitation level of the neuron's body. I suspect that the precision of this multiply -accumulate process is fairly low -- perhaps 8 to 16 bits.

Next, the body of the neuron has a long axon extending from it that sends the output of the neuron to other neurons (connecting to the dendrites of other neurons). This axon can be quite long, millimeters, even inches, in length. Thus, the axon is like an off-chip line driver with the potential to have a very high fanout (of a 1000 or more). (On a modern microchip, these off-chip connections are driven by much larger transistors than the small 65 nm ones used in computation).

Third, a neuron is not a static multiply-accumulate system. The coefficients on each synapse change in response to long-term adaptive processes. This process is computationally complex and includes cross-correlation of inputs between synapses and processing of other chemical signals in the brain. Cross-correlation alone could require the equivalent of several kilobytes to several megabyts of RAM. (We won't even get into the adaptive processes that include physical growth and removal of dendrites as this has no easy analog in hardware)

In summary, a neuron is more than a transistor-like switch. Its a free-running 1000 register multiply-accumulator with an off-chip line driver and a statistical processing engine that updates the coefficients on each of the multiply-accumulate terms. Thus, emulating a single neuron would require hundreds of thouands to millions of transistors.

Re:Kinda cool: Neurons vs. Transistors

[Welsh Dwarf]

This axon can be quite long, millimeters, even inches, in length.

Acutally, it can be over a meter in length (spinal cord to calf is one axone). Try that with a transistor

Re:Software version (more than Boolean)

[G4from128k]

Or, for a more software interpretation, it's a function that takes a bunch of boolean parameters and returns a boolean. Anyone who's ever done any programmation or computer architecture should see why you can easily process anything with this.

Excellent point. You are right about the computational flexibility of neurons. They can represent a wide range of logical functions, although I believe that the single neuron is incapable of doing an XOR.

But a neuron is more that a Boolean circuit. Although a neuron seems like a two-state device (its either quiesent or its firing), it is more of an N-state analog device in which the pulse-rate encodes a numerical quantity (probably the equivalent of an 8 to 16 bit floating point number). That is why the dendrite field is like a giant numerical multiply-accumulate.