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Computational Model Reveals How the Brain Manages Short-Term Memories

neurosciencenews.com

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Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#21

Post by danielmarkbruce »

earthboundkid wrote: post #3

> Kim and Sejnowski found that good working memory required both that long-timescale neurons be prevalent, and that connections between inhibitory neurons–which suppress brain activity–be strong. When they altered the strength of connections between these inhibitory neurons in their model, the researchers could change how well the model performed on the working memory test as well as the timescale of the pertinent ne…

If you look at almost any complex phenomena that humans didn't actually create, you will see little actual knowledge. Neuroscience, much of biology and economics are examples.

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#23

Post by ohazi »

lamename wrote: post #11
earthboundkid wrote: post #3

> Kim and Sejnowski found that good working memory required both that long-timescale neurons be prevalent, and that connections between inhibitory neurons–which suppress brain activity–be strong. When they altered the strength of connections between these inhibitory neurons in their model, the researchers could change how well the model performed on the working memory test as well as the timescale of the pertinent ne…

As a neuroscientist, I can tell you with high confidence that many if not most neuroscientists would agree with you. You might also be interested in "Could a Neuroscientist Understand a Microprocessor?" https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

This paper was thoroughly entertaining. Thanks!

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#24

Post by longtom »

earthboundkid wrote: post #3

> Kim and Sejnowski found that good working memory required both that long-timescale neurons be prevalent, and that connections between inhibitory neurons–which suppress brain activity–be strong. When they altered the strength of connections between these inhibitory neurons in their model, the researchers could change how well the model performed on the working memory test as well as the timescale of the pertinent ne…

Most areas of the brain are rather homogenous. They've done experiments rewiring inputs going to the visual cortex to the auditive cortex in rodents and they could see. Further, artificial neural nets demonstrate that extremely simple repetitive structures can implement a vast function space simply by training them by stochastic gradient descent. The most complex structures in the brain may be hardwired social behaviors, including facial expression and recognition, but these may not be necessary for the intelligence part as individuals strongly impaired in hardwired social behavior (autists) are sometimes capable of complex thought.

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#25

Post by cortezdecoy »

trevyn wrote: post #14
h-1 wrote: post #6

Anyone can point out that autistic, schizophrenic or very old people lack certain inhibitions. But it's downright fascinating to think it may be explained by dulled inhibitory neurons or hypersensitive "regular" ones. That could be an easy fix!

> That could be an easy fix! Famous last words?

In one sense, almost certainly. But in another sense, any plausible fix is easy compared to the current situation.

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#27

Post by kkylin »

earthboundkid wrote: post #3

> Kim and Sejnowski found that good working memory required both that long-timescale neurons be prevalent, and that connections between inhibitory neurons–which suppress brain activity–be strong. When they altered the strength of connections between these inhibitory neurons in their model, the researchers could change how well the model performed on the working memory test as well as the timescale of the pertinent ne…

Being a mathematician who's dabbled in neuroscience a bit, I think that's essentially right (though perhaps I wouldn't have said "laughable"). But I also think this reflects the differences between how science and engineering progress -- our ability to exploit a natural phenomenon (or class of phenomena) often outstrips our ability to explain what's going on. As examples, I'd argue that for much of aviation history (and perhaps now too, I don't know), our ability to build flying machines far outstrips our understanding of how birds and insects (or even planes) fly.

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#28

Post by hackinthebochs »

mtrycz2 wrote: post #22

> Model reveals No, a model models, does not (and can not) reveal anything.

A model based on some core principles or constraints of the natural system will often solve the problem by discovering the same structure used by nature. And so facts of the model can reveal facts of the natural system. Of course such discoveries need to be validated against the real thing.

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#29

Post by subroutine »

bra-ket wrote: post #12
subroutine wrote: post #9

Earlier quoted context omitted.

I agree with this sentiment. To be fair though, the authors did attempt to generate a biologically plausible RNN, which they published in a previous article... https://www.pnas.org/content/pnas/116/45/22811.full.pdf I'm not fully sold on this model, but the article is fairly dense and I dont fully understand it. (Sejnowski, the senior author, was on my dissertation committee; he fell asleep during my defense lol)

Oh god, what he calls constraints are the "spiking nature of biological neurons", then he happily proceeds, just like you'd guess, to create this abomination of 'spiking RNN' and train this pretty much plain vanilla RNN via backpropagation, completely disregarding the energy spent, learning mechanism, and actual biological plausibility or relevance of this horrendous architecture as memory model. The first author kno…

Dropping a link below in case you're interested - I have a side-project that takes a more literal approach to modeling biologically plausible neural networks (MCMC simulations inside 3D models)...

https://github.com/bradmonk/plasticity

Re: Computational Model Reveals How the Brain Manages Short-Term Memories

#30

Post by trevyn »

cortezdecoy wrote: post #25
trevyn wrote: post #14

Earlier quoted context omitted.

> That could be an easy fix! Famous last words?

In one sense, almost certainly. But in another sense, any plausible fix is easy compared to the current situation.

The sense I intended was that it may indeed be an easy fix, but second- third- etc- order effects may actually make us all worse off in ways we never considered.
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