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Neurons unexpectedly encode information in the timing of their firing

quantamagazine.org

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Re: Neurons unexpectedly encode information in the timing of their firing

#101

Post by samus »

solipsism wrote: post #73
rewq4321 wrote: post #58

Earlier quoted context omitted.

> there's evidence that at least some neurons "record" information about their activity in the form of RNA Source? I'm not a neuroscientist, but I'd have thought that I'd have heard of this if there were legit evidence. Are you saying that neurons might use RNA as a sort of "long-term" memory of activation patterns? This seems really unlikely! But again, I'm not a neuroscientist.

I'd have thought that I'd have heard of this if there were legit evidence Changes to DNA would be the long term changes, not RNA. But yes, look up epigenetics, and especially DNA methylation.

This might be a reason why the immune system is kept outside from the brain.

Re: Neurons unexpectedly encode information in the timing of their firing

#102

Post by hau »

tsimionescu wrote: post #93
hau wrote: post #89

Earlier quoted context omitted.

Richard Feynman describes such computation, that produces incorrect results on classic computer and correct one on quantum in "Simulating Physics with Computers"[0]. He follows one physical experiment detailing every step from start to finish and how it converges to incorrect result on classical computer. [0] - https://doi.org/10.1007/BF02650179

Thank you for the link! I have also found a free version for anyone else interested: http://physics.whu.edu.cn/dfiles/wenjian/1_00_QIC_Feynman.pd... However, Feynman does not claim what you say he claims. His whole article is about efficiently simulating QM on a classical computer, and he shows that is not possible given what we understand of quantum probability today, at least (he does this by explicitly asking for…

>"That's all. That's the difficulty. That's why quantum mechanics can't seem to be imitable by a local classical computer."

I don't think argument is about efficiency. "a classical computer can perfectly simulate a quantum system/computer" is not explicitily there, it's an argument against that. It seems to me you're saying anything that's not strictly proving BQP > BPP supports something else.

Re: Neurons unexpectedly encode information in the timing of their firing

#103

Post by tsimionescu »

hau wrote: post #102
tsimionescu wrote: post #93

Earlier quoted context omitted.

Thank you for the link! I have also found a free version for anyone else interested: http://physics.whu.edu.cn/dfiles/wenjian/1_00_QIC_Feynman.pd... However, Feynman does not claim what you say he claims. His whole article is about efficiently simulating QM on a classical computer, and he shows that is not possible given what we understand of quantum probability today, at least (he does this by explicitly asking for…

>"That's all. That's the difficulty. That's why quantum mechanics can't seem to be imitable by a local classical computer." I don't think argument is about efficiency. "a classical computer can perfectly simulate a quantum system/computer" is not explicitily there, it's an argument against that. It seems to me you're saying anything that's not strictly proving BQP > BPP supports something else.

At the very beginning he says:

> The rule of simulation that I would like to have is that the number of computer elements required to simulate a large physical system is only to be proportional to the space-time volume of the physical system. I don't want to have an explosion. That is, if you say I want to explain this much physics, I can do it exactly and I need a certain-sized computer. If doubling the volume of space and time means I'll need an exponentially larger computer, I consider that against the rules (I make up the rules, I'm allowed to do that).

He emphasizes this again in the section about computing the probabilities:

> We emphasize, if a description of an isolated part of nature with N variables requires a general function of N variables and if a computer stimulates this by actually computing or storing this function then doubling the size of nature (N->2N) would require an exponentially explosive growth in the size of the simulating computer. It is therefore impossible, according to the rules stated, to simulate by calculating the probability. [emphasis mine]

So when he uses the term 'computer' he doesn't mean 'abstract Turing machine', he explicitly means 'realizable/efficient Turing machine'.

Re: Neurons unexpectedly encode information in the timing of their firing

#104

Post by danielvf »

LeifCarrotson wrote: post #67

In my very different field (robotics and industrial automation), temporal coding is one of the most powerful ways to expand your IO. Nearly all PLCs, sensors, and robots make heavy use of digital IO. But this parallel interface is limited, especially with hard-wired signals, and even if you're using serial network protocols the typical fieldbus abstraction represents the network as fixed-size buffers of digital IO th…

This is cool hack! But boy does it terrify me!

I've spent so much time debugging weirdness getting into signals from things like lightning strikes, AM radio stations, and nearby switching power supplies....

Re: Neurons unexpectedly encode information in the timing of their firing

#105

Post by procgen »

mr_toad wrote: post #79
radicaldreamer wrote: post #6

Earlier quoted context omitted.

There’s a strong bias toward things that are model-able in neuroscience. The role of microtubules, for example, are mostly ignored even though they may explain the complexity of cognition displayed by relatively “simple” brains.

Microtubules are found in all eukaryotic cells. Even single celled organisms. If microtubules are responsible for cognition, what are brains for, and why aren’t amoeba intelligent?

Amoebas are intelligent. All living things are intelligent.

Re: Neurons unexpectedly encode information in the timing of their firing

#106

Post by kosievdmerwe »

tgbugs wrote: post #49

Rate coding vs temporal coding is literally a meme in neuroscience because the two camps seem to refuse to compromise. Everyone else has realized that both happen depending on how that particular part of the nervous system works, or even what particular kind of information is flowing through it. This title reads like it was written by a rate coder who woke up one day and was like "Woah, you mean ... there might be mo…

First rule about sufficiently evolved systems: They're more interconnected and involved than you likely first expect.

Re: Neurons unexpectedly encode information in the timing of their firing

#107

Post by sdwr »

HarHarVeryFunny wrote: post #55
sdwr wrote: post #51

Earlier quoted context omitted.

Fire together, wire together refers to the connection between two neurons strengthening. Firing just before the recipient neuron fires strengthens the bond, and firing afterwards/off tempo weakens the bond. It's an elegant concept, because it handles neural weights, a non-linear activation function, and clock speed with a simple, distributed rule.

Right, but first the "recipient" neuron needs to fire, which requires integrated synaptic inputs to cross some threshold, which requires input spikes to arrive close to the same time. This phase precession mechanism being discussed is what allows inputs arriving from different distances (i.e. with different signal travel times) to arrive close to the same time such that the recipient fires. Once it fires, then "fire…

After reading the article, I don't think that's what they're saying. My understanding is that place cells stand in for a literal location in space, and fire when they detect that location.

The phase precession is how place cell A overlaps firing with place cell B when the individual is moving from location A to B, strengthening the connection (to create a mental link/memory between the two?)

Re: Neurons unexpectedly encode information in the timing of their firing

#109

Post by mikewarot »

meroes wrote: post #98
tsimionescu wrote: post #97

Earlier quoted context omitted.

Random numbers are random numbers. You can calculate the probabilities (the wave function amplitudes, which are deterministic); or you can use any source of random noise to reproduce the data, once you adjust for the difference between quantum and classical probability.

For an extreme example, there are finite patterns behind the lava lamps at Cloudfare or the chaos of Jupiter's storms. These are sufficiently random for any current need I can currently imagine though. But then I also see that "classical computers can never be built big enough to explore more than 400, actually more than, probably 100 qubits, 100 qubits doesn’t seem like very much. No classical computer can do the ca…

A lava lamp is a chaotic system. The same initial conditions, no matter how precisely measured, will not result in the same outcome, it will diverge. It is non-deterministic in the real world.

Re: Neurons unexpectedly encode information in the timing of their firing

#110

Post by meroes »

mikewarot wrote: post #109
meroes wrote: post #98

Earlier quoted context omitted.

For an extreme example, there are finite patterns behind the lava lamps at Cloudfare or the chaos of Jupiter's storms. These are sufficiently random for any current need I can currently imagine though. But then I also see that "classical computers can never be built big enough to explore more than 400, actually more than, probably 100 qubits, 100 qubits doesn’t seem like very much. No classical computer can do the ca…

A lava lamp is a chaotic system. The same initial conditions, no matter how precisely measured, will not result in the same outcome, it will diverge. It is non-deterministic in the real world.

Wait, let's be clear. In the real world a lava lamp is basically impossible predict as it evolves. And that is due to chaos. So far so good.

But this chaos is deterministic. Chaos means highly sensitive to initial conditions and involves nonlinearity, but it is still entirely classical and deterministic. In the real world we do not measure things precise enough to keep track of a lava lamp's deterministic evolution, but it is there within the chaos.

So I am wondering if a quantum computer, which Susskind says takes only 100 qubits to outperform any Turing Machine constructable ever, may one day do better at picking out the deterministic patterns behind the chaos of things like lava lamps. And if that happens, we may need more extreme versions of chaotic systems to keep secrets. And since quantum randomness is the only true randomness in the universe, forever indiscernable in principle; will one day all deterministic, chaotic means of adding "randomness" be replaced with quantum sources of randomness, due to how powerful quantum computers are?

*Now you could say even the lava lamp involves quantum randomness because everything is ultimately quantum. But because it is so macroscopic, it behaves more classically the a smaller quantum system.

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