Evidence that dendrites actively process information in the brain • Hacker News Board

Re: Evidence that dendrites actively process information in the brain

#31

Post by bl » Wed, Oct 30, 2013, 10:57 PM UTC

PeterisP wrote: post #28

bl wrote: post #23

Earlier quoted context omitted.

"[I]t looks I could design a dendritic tree geometry for almost any boolean function of the inputs". That's my outlook on the structure-function link between dendritic morphology and dendritic information processing, with the modification that I'd not restrict it to boolean functions. There are very many more types of functions, linear and non-linear, that can conceivably be built out of neuronal dendrites. And I lik…

Well, AFAIK you don't need anything more than boolean functions, since if we're talking about single spikes (not spike frequency), then there either is or isn't a spike, you don't get some spikes larger than other. The linear/nondigital functions IMHO seem to be used as implementation details - for example, a neuron "fire iff 1+ VIP-input fires or 3+ normal inputs fire" can be implemented in wetware by having 'vip-in…

I hope no one interpreted my statements to suggest that anything you said was wrong. Just trying to fill in details.

I merely want to avoid prematurely narrowing the range of functions that are possible. If we, for the moment, think of the neural computation of a single neuron as a neural network, then the spike/no-spike decision would be in the last layer and a whole host of linear/non-linear (some not necessarily boolean) functions could be implemented by the dendrites. And some single neuron processing we already know behaves in a non-boolean manner.

Be aware, just because arbitrarily powerful logic could be constructed solely out of boolean components (I don't even know if this is true. Isn't this kinda what is going on in an FPGA?) doesn't mean that neural hardware is purposed the same way. They may very well may be analog, at least for some computations.

And to speak to your second paragraph, I should declare my personal biases. As a dendritic physiologist, I wasn't much interested in whole-cell firing characteristics, but in the dendrite's sub-threshold behavior.

How do a smattering of synaptic inputs, each with varying strengths, interact within the complex electrophysiological scaffolding provided by a branched dendrite layered with non-uniform, non-linear ion channel distributions?

So my perspective is somewhat inverted: To me, neuron firing is the implementation detail!

Re: Evidence that dendrites actively process information in the brain

#32

Post by pkroll » Wed, Oct 30, 2013, 11:12 PM UTC

jostmey wrote: post #25

groovy2shoes wrote: post #21

Earlier quoted context omitted.

The problem is that our knowledge is limited. Once we have a better understanding of certain biological processes, we may be able to find the right abstractions.

You might be missing the point. Biological systems are the result of Natural selection, and the processes of Natural selection are fundamentally irrational. Any biological system, including our own brain, is essentially the outcome of a random, irrational process. There may be cases where we can arrive at some abstractions, but such cases may be the exception, not the norm.

In that irrational assumes sentience, OK. The randomness being "we can't possibly predict all the elements that went into X happening" OK. But neither of those matters in making an abstraction: the biological components didn't evolve outside of chemistry and physics. We can argue about how much detail would be needed, but is there really anything we can't abstract?

Re: Evidence that dendrites actively process information in the brain

#33

Post by floobynewb » Thu, Oct 31, 2013, 12:02 AM UTC

akavi wrote: post #11

This is the very sort of interaction that leads me to be very, very unoptimistic about ever seeing Moore's Law style runaway advancement in biotechnology. Biology, it seems, is deeply unabstractable . Ie, as one moves up the levels of organization, one rarely (never?) reaches a point where a higher level can be fully modeled without also fully modeling each of the lower levels. This is in sharp contrast to computer e…

I suppose the question is: Are there appropriate abstractions which would bring conceptual simplicity to these systems? I find it hard to believe that there is not. A system which does not have such a property is more difficult for natural selection to operate upon. The changes which are likely to happen to a lineage over the course of time are likely to have evolved to be likely to move the lineage closer to a locally optimal phenotype. I do not think that a system which is incompressible, would display such dynamics, the system would be chaotic and small changes in the genotype would lead to divergent phenotypes wrt the fitness landscape. Perhaps the appropriate abstractions are spread out both temporaly and spatially.