An Existential Crisis in Neuroscience
m.nautil.us
An Existential Crisis in Neuroscience
1–10 of 112 posts
Re: An Existential Crisis in Neuroscience
#2"If the human brain were so simple that we could understand it, we would be so simple that we couldn't."
Re: An Existential Crisis in Neuroscience
#3If you've seen some of the high resolution videos of neural activity captures from even simple fish, the slightest motor movements activate hundreds of thousands of cells in a chaotic pattern. Neural circuitry is not neatly laid out like a silicon chip, its a forest of inter-connectivity that resists analysis even with extremely detailed visualization and data captures.
Re: An Existential Crisis in Neuroscience
#4What we need is a Newtonian model of the brain. A model that is incomplete and "wrong", but useful and generative. While Newtonian physics may be "wrong", is much easier to learn than quantum physics or relativity, etc.
Neuroscience usually focuses on precision details, but doesn't aim to tell big picture stories. There are a few exceptions, however, like Karl Friston's free energy reduction model.
Re: An Existential Crisis in Neuroscience
#5There is a good chance that complete brain mapping will be similar to whole genome sequencing. The result will be interesting but only answer a limited subset of questions.
Re: An Existential Crisis in Neuroscience
#6Generally too purple for its own good but a very interesting read! The Borges reference (and C. elegans conundrum) makes me as a layreader really appreciate how little we actually know about the endgame for all this data.
But there is such elegance in "rudimentary" DNN's giving us the ability to at all assemble this stuff.
Re: An Existential Crisis in Neuroscience
#7What we need is a Newtonian model of the brain. A model that is incomplete and "wrong", but useful and generative. While Newtonian physics may be "wrong", is much easier to learn than quantum physics or relativity, etc. Neuroscience usually focuses on precision details, but doesn't aim to tell big picture stories. There are a few exceptions, however, like Karl Friston's free energy reduction model.
Don't we have that in the model that describes what the parts of the brain do?
Proven to be wrong when you watch people with serious brain injuries re learn skills, but shown to have value by how it can predict what tumors or injuries will do to someone's ability.
Re: An Existential Crisis in Neuroscience
#8If you've seen some of the high resolution videos of neural activity captures from even simple fish, the slightest motor movements activate hundreds of thousands of cells in a chaotic pattern. Neural circuitry is not neatly laid out like a silicon chip, its a forest of inter-connectivity that resists analysis even with extremely detailed visualization and data captures.
If a highly structured action seems to be driven by system whose visualisation looks chaotic, perhaps we are using the wrong visualisation.
Re: An Existential Crisis in Neuroscience
#9What we need is a Newtonian model of the brain. A model that is incomplete and "wrong", but useful and generative. While Newtonian physics may be "wrong", is much easier to learn than quantum physics or relativity, etc. Neuroscience usually focuses on precision details, but doesn't aim to tell big picture stories. There are a few exceptions, however, like Karl Friston's free energy reduction model.
Don't we have that in the model that describes what the parts of the brain do? Proven to be wrong when you watch people with serious brain injuries re learn skills, but shown to have value by how it can predict what tumors or injuries will do to someone's ability.
I would equate our current understanding of the brain to the common knowledge that apples fall to the ground from trees; where else would they go? People knew that long before Newton.
Re: An Existential Crisis in Neuroscience
#10If you've seen some of the high resolution videos of neural activity captures from even simple fish, the slightest motor movements activate hundreds of thousands of cells in a chaotic pattern. Neural circuitry is not neatly laid out like a silicon chip, its a forest of inter-connectivity that resists analysis even with extremely detailed visualization and data captures.
Maybe it is DRM