Single cortical neurons as deep artificial neural networks
sciencedirect.com
Single cortical neurons as deep artificial neural networks
1–10 of 135 posts
Re: Single cortical neurons as deep artificial neural networks
#2ANN neurons are Pitts-McCulloch neurons, an extremely stylized model of the 1940's understanding of neurons. Each neuron represents a dot product plus a function application.
A biological neuron is 6e17 Daltons[0], so on the order of quadrillions of atoms. A single synapse is a huge landscape studded with receptors of various kinds, and the whole thing is swimming in salt solution where chemicals diffuse stochastically. And then there's the glia.
This is why I dismiss any claims about the computational power of the human brain, most of which seem to begin with the assumption that "1 spike = 1 FLOP", and that'll all that goes on in the brain.
[0]: https://faculty.washington.edu/chudler/facts.html and https://www.wolframalpha.com/input/?i=1E-06+grams+in+dalton
Re: Single cortical neurons as deep artificial neural networks
#3This is trying to train a neural network to match the behaviour of various mathematical models of biological neurons.
Said models still don't seem to be very close to being able to predict the behaviour of biological neurons though.
If they did, then we'd have invented artificial human-level intelligence.
Re: Single cortical neurons as deep artificial neural networks
#45-8 layers but how many weights per layer? I can’t access the article but it says it’s a deep CNN so probably in the order of a few thousands weights per layer.
Re: Single cortical neurons as deep artificial neural networks
#5ANN neurons are Pitts-McCulloch neurons, an extremely stylized model of the 1940's understanding of neurons. Each neuron represents a dot product plus a function application. A biological neuron is 6e17 Daltons[0], so on the order of quadrillions of atoms. A single synapse is a huge landscape studded with receptors of various kinds, and the whole thing is swimming in salt solution where chemicals diffuse stochastical…
Transistors, while dramatically simpler than neurons, also have fairly complicated physics. It's quite hard to determine the computational power of a microprocessor when you only know roughly how transistors work and have no idea how microprocessors work.
Re: Single cortical neurons as deep artificial neural networks
#6ANN neurons are Pitts-McCulloch neurons, an extremely stylized model of the 1940's understanding of neurons. Each neuron represents a dot product plus a function application. A biological neuron is 6e17 Daltons[0], so on the order of quadrillions of atoms. A single synapse is a huge landscape studded with receptors of various kinds, and the whole thing is swimming in salt solution where chemicals diffuse stochastical…
Transistors, while dramatically simpler than neurons, also have fairly complicated physics. It's quite hard to determine the computational power of a microprocessor when you only know roughly how transistors work and have no idea how microprocessors work.
True, but transistors are designed by humans (for now), so you have an upper bound on complexity as well as a certain degree of modularity. Whereas biology has no such limitations because evolution doesn't care about the understandability of its designs.
So I tend to err on the side of biology being more complex than not.
But it's absolutely possible that the high-level behaviour is simple while the underlying implementation is complex and chaotic, as in the gas laws.
Re: Single cortical neurons as deep artificial neural networks
#75-8 layers but how many weights per layer? I can’t access the article but it says it’s a deep CNN so probably in the order of a few thousands weights per layer.
Up to 256.
Re: Single cortical neurons as deep artificial neural networks
#8ANN neurons are Pitts-McCulloch neurons, an extremely stylized model of the 1940's understanding of neurons. Each neuron represents a dot product plus a function application. A biological neuron is 6e17 Daltons[0], so on the order of quadrillions of atoms. A single synapse is a huge landscape studded with receptors of various kinds, and the whole thing is swimming in salt solution where chemicals diffuse stochastical…
Not to speak of all the 'weights' which are stored internaly in DNA methylation, among other memory forming mechanisms (proven recently).
(part of the quadrillion atoms system of course)
Re: Single cortical neurons as deep artificial neural networks
#9This is trying to train a neural network to match the behaviour of various mathematical models of biological neurons. Said models still don't seem to be very close to being able to predict the behaviour of biological neurons though. If they did, then we'd have invented artificial human-level intelligence.
That doesn't follow at all. Human neurons aren't much different from mouse neurons, maybe chicken neurons, mosquito neurons. After you faithfully model a neuron you still need untold myriads of them and their interconnects to get human brain.
Re: Single cortical neurons as deep artificial neural networks
#10This is trying to train a neural network to match the behaviour of various mathematical models of biological neurons. Said models still don't seem to be very close to being able to predict the behaviour of biological neurons though. If they did, then we'd have invented artificial human-level intelligence.
Modulo the HUGE computational cost of simulating these things, not to mention the non-trivial task of determining network parameters.
Surrogate models are a thing though, and it's going to be an interesting time as we gradually figure out what approximations and optimizations are 'acceptable', and what computations really are necessary for "intelligence" (whatever that might be).