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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."
But what's the size of a neuron vs the size of a transistor in a 65nm process CPU?
-- *My* journal is more interesting than *yours*...
But this is very exciting. The idea that we could grow neurons on silicon is one of those big steps that looks to lead us into the Johnny Mnemonic world that Gibson was talking about just a couple stories prior to this one.
There is a song that says, "It only takes a spark to get a fire going". So too is it true that it only takes a couple neurons to start synapsing. As these true neural webs become more complicated, it would be interesting to see if any kind of emergent behavior was evident.
Also, with the current political and scientific climate as it is, this could be the first step to replicating a nervous system without having to rely on fetuses for stem cells. It requires no human cloning and holds immense promise.
It would definitely be cool to have a couple of these chips implanted to enhance the base memory that we are kitted with at birth, that's for sure!
I have been pwned because my
Will this make computers more human or otherwise ?.
... Forty Two ... naah... doesn't work) ... Of course, nature did a better job making us humans than we would have achieved ... :)
Maybe it's time to admit that nature does a better job bruteforcing (OK , what else do you call SEX and EVOLUTION) the secrets of this world than all our mathematical precision.. (E=MC2
Quidquid latine dictum sit, altum videtur
If only they could find out how did the strength increase and wether we can do the same to the human body we can find a cure for most of the nervous system degradation diseases. Anybody have link to a more verbose article?
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a.k.a Neal Stephenson and his uncle.
Chip embedded in politician's brain after a stroke - he goes on to be president.... v. spooky.
I would love to see alzheimer's patients helped with this. If it's a genetic disease, I'm up the creek and dropped me paddle a while back.
- Lnr
You know I had read somewhere that our brains (individual processes) run at around 200MHz (as it is all electro-chemically done), now if you say that we have hundreds of billions of neurons, so do we have billions of transistors on chips.
The difference here is that our brains use the 3rd dimension effectively (and also work in parallel, I think). Now I'm not sure if the latest breakthrough uses electro-chemical processes to communicate, but if it's faster than 200MHz, it definitely has huge potential.
A quote i read somewhere
"The danger from computers is not that they will eventually get as smart as men, but we will meanwhile agree to meet them halfway." -Bernard Avishai
Yes, Neural Networks by there very nature are really nothing more than adaptive filters, aka classifiers. The eye does a great deal of preprocessing such as edge detection, motion detection, etc ?aka classifying? to reduce the work load on the brain. Neural Networks could perform similary preprocessing to reduce the work load for cpu based image reconition systems.
Actually the idea of "reflexes" is the same as electro-robots which can since objects by electrical load. That hot plate is nothing more than an over threshold input that cause electro-motor response. An electrical circuit could also be easily designed to include a little bit of fussy logic via a simple anolog circuit to achive the same thing.
So, equivalent mechanisms are not readily available for cpu based computing, but there are for ANN based computing. If we ever hope to match the basic capabilities of animals we can not just rely on cpu based computing, we also need ANN based computing for sensor preprocessing and feed back controlled motor function
Thanks for the reply, very enlightening.
But it clearly would be folly to try to emulate a neuron using purely digital computing techniques. You're dealing with an analog mechanism that is pretty much a wire-or of many inputs feeding into a capacitor. This is very much an analog computing circuit; now the question is how efficiently you can do A/D-D/A conversion on this scale.
(And as I recall, the sciatic nerve running down your leg is a single cell with an axon over 1 foot long. Definitely some impressive stuff Mother Nature has concocted...)
-- *My* journal is more interesting than *yours*...
It's kinda funny, a few years ago (back in the 80s) my dad actually did this. Believe it or not, he was the first one to grow a neuron on silicon (a Motorola chip for those interested). The poster with the electon micrograph of it was absolutly everywhere (we had 1000s of the posters in the basement). I even rememeber going to highschool science and, sure enough, there was my dad's poster. :)
The hype surrounding this was insane mostly due to fact that everyone thought this was the true start to cybernetics. In the end, the hype died down, My dad's lab got a ton of grants and he got back to doing more research. Ironically enough, the most publicisied research that he did (the neuron on a chip) probably had the least impact.
Such is the world of science at times
So, yes, it's nothing new. Just repackaged.
I think parent (along with some other posts) are confusing the biological neuron and the perceptron, which is a simplified mathematical model. While the perceptron can't cope with linearly inseperable problems (like XOR), there is no consensus on the computational limits of the neuron. In fact, very little is known for certain about the learning algorithm used by the nervous system. The neuron may learn not only through the weights of its inputs, but also through chemical interactions with glial cells. Really, the neuron is still too much of a mystery for us to know its limitations.