A deep learning framework for neuroscience
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Re: A deep learning framework for neuroscience
#2Anyone up for a summary? I didn't get much from the abstract.
Re: A deep learning framework for neuroscience
#3Anyone up for a summary? I didn't get much from the abstract.
any article containing the word "framework" right in the title is either philosophical mumbo-jumbo, or an incomplete documentation for an over-engineered first project of a recent CS graduate.
Re: A deep learning framework for neuroscience
#4I'm not sure, but I think it's trying to say that deep learning as it stands is modeled on one aspect of a model of the brain, by developing out the 3 aspects they identify and having them act in unison would be potentially a good thing, disclaimer, I am neither a neuroscientist nor deep learning expert!
Re: A deep learning framework for neuroscience
#5Anyone up for a summary? I didn't get much from the abstract.
they're arguing that articifial neural nets are useful models of brain function and anatomy.
a lot of people in the field of neuroscience strongly disagree, hence their attempt to outline the utility of ANNs.
Re: A deep learning framework for neuroscience
#6Anyone up for a summary? I didn't get much from the abstract.
they're arguing that articifial neural nets are useful models of brain function and anatomy. a lot of people in the field of neuroscience strongly disagree, hence their attempt to outline the utility of ANNs.
I also tend to be skeptical that ANNs are very useful as a model for brain function. In vivo neural networks are so complex and so dynamic when compared ANNs.
In my opinion, the fact that even such a massively simplified model of one specific subtype neural processing has been able to give as powerful results as we have seen from Deep Learning should give us an appreciation for how much there still is for us to learn about this staggeringly complex system.
I would guess that the next great advancements will come from using better understandings of the brain to build better ANNs, not the other way around.
Re: A deep learning framework for neuroscience
#7I'm not sure, but I think it's trying to say that deep learning as it stands is modeled on one aspect of a model of the brain, by developing out the 3 aspects they identify and having them act in unison would be potentially a good thing, disclaimer, I am neither a neuroscientist nor deep learning expert!
What I understood is that they're saying deep learning relies on understanding neural processing in 3 parts: objective functions (activation functions maybe?), learning rules (I guess like back-prop/gradient descent?) and architecture (I assume network structure)?
So it sounds like they want to use this componentization of neural processing to try to understand biological neural networks better.
Re: A deep learning framework for neuroscience
#8Earlier quoted context omitted.
they're arguing that articifial neural nets are useful models of brain function and anatomy. a lot of people in the field of neuroscience strongly disagree, hence their attempt to outline the utility of ANNs.
I also tend to be skeptical that ANNs are very useful as a model for brain function. In vivo neural networks are so complex and so dynamic when compared ANNs. In my opinion, the fact that even such a massively simplified model of one specific subtype neural processing has been able to give as powerful results as we have seen from Deep Learning should give us an appreciation for how much there still is for us to learn…
Learning's likely to be bidirectional. ANN (as a mathematical analogue) is independent to the biological function (the original and key inspiration). Advances in network architecture (e.g. the recent trend towards skip connections and parallel processes) is likely to give insight to how an underlying, more complex system is likely to operate. In particular, systematic errors made by ANNs under given frameworks have a tendency for existing in some form in psychology and biology. Since conceptual thinking from both domains can directly feed towards each other, it's a rare bootstrap moment with the potential for rapid advances in both directions.
Re: A deep learning framework for neuroscience
#9Earlier quoted context omitted.
I also tend to be skeptical that ANNs are very useful as a model for brain function. In vivo neural networks are so complex and so dynamic when compared ANNs. In my opinion, the fact that even such a massively simplified model of one specific subtype neural processing has been able to give as powerful results as we have seen from Deep Learning should give us an appreciation for how much there still is for us to learn…
Learning's likely to be bidirectional. ANN (as a mathematical analogue) is independent to the biological function (the original and key inspiration). Advances in network architecture (e.g. the recent trend towards skip connections and parallel processes) is likely to give insight to how an underlying, more complex system is likely to operate. In particular, systematic errors made by ANNs under given frameworks have a…
> Advances in network architecture (e.g. the recent trend towards skip connections and parallel processes) is likely to give insight to how an underlying, more complex system is likely to operate.
Maybe. The thing about these advances in ANNs is, so we have any reason to believe they have anything to do with the way biological neural networks work? It might be the case that these kinds of advances correlate to a more accurate understanding of how our brains process information, or it might also be the case that these are just optimizations on a mathematical model which is fundamentally different to biological intelligence.
To me advances in the other direction are much more compelling. We actually know quite a lot about how biological neural networks work. The way that electrical and chemical signals are transmitted is quite well understood, and can be accurately modeled through mathematical models derived from physics and physical chemistry. At the moment, the problem seems more to be more about how to accurately model this system at scale which we already have tons of data on.
It's not that I think these innovations in ANNS have no value, it's just that it seems that ANNs are quite tangential to neuroscience.
Re: A deep learning framework for neuroscience
#10Anyone up for a summary? I didn't get much from the abstract.