Introducing the brain: structure studies (Introduction)

by David Turell , Thursday, October 28, 2021, 15:19 (901 days ago) @ David Turell

Careful anatomical studies don't tell us how the brain works:

https://nautil.us/issue/107/the-edge/neurosciences-existential-crisis

"Neuroscientists have made considerable progress toward understanding brain architecture and aspects of brain function. We can identify brain regions that respond to the environment, activate our senses, generate movements and emotions. But we don’t know how different parts of the brain interact with and depend on each other. We don’t understand how their interactions contribute to behavior, perception, or memory. Technology has made it easy for us to gather behemoth datasets, but I’m not sure understanding the brain has kept pace with the size of the datasets.

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"Some serious efforts, however, are now underway to map brains in full. One approach, called connectomics, strives to chart the entirety of the connections among neurons in a brain. In principle, a complete connectome would contain all the information necessary to provide a solid base on which to build a holistic understanding of the brain. We could see what each brain part is, how it supports the whole, and how it ought to interact with the other parts and the environment. We’d be able to place our brain in any hypothetical situation and have a good sense of how it would react.

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"It’s just there’s so much going on at the same time. That’s what a human brain is. It’s millions of things happening simultaneously among different types of cells, neuromodulators, genetic components, things from the outside. There’s no point when you can suddenly say, ‘I now understand the brain,’ just as you wouldn’t say, ‘I now get New York City.’ ”

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"Scientists still need to understand the relationship between those minute anatomical features and dynamical activity profiles of neurons—the patterns of electrical activity they generate—something the connectome data lacks. This is a point on which connectomics has received considerable criticism, mainly by way of example from the worm: Neuroscientists have had the complete wiring diagram of the worm C. elegans for a few decades now, but arguably do not understand the 300-neuron creature in its entirety; how its brain connections relate to its behaviors is still an active area of research. (my bold)

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“'A strong intuition among many neuroscientists is that individual neurons are exquisitely complicated: They have all of these back-propagating action potentials, they have dendritic compartments that are independent, they have all these different channels there. And so a single neuron might even itself be a network. To caricature that as a rectified linear unit”—the simple mathematical model of a neuron in DNNs—“is clearly missing out on so much.” [DNNs: deep neural networks]

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"It seems likely that Lichtman’s two exabytes of brain slices, and even my 48 terabytes of rat brain data, will not fit through any individual human mind. Or at least no human mind is going to orchestrate all this data into a panoramic picture of how the human brain works. As I sat at my office desk, watching the setting sun tint the cloudless sky a light crimson, my mind reached a chromatic, if mechanical, future. The machines we have built—the ones architected after cortical anatomy—fall short of capturing the nature of the human brain. But they have no trouble finding patterns in large datasets. Maybe one day, as they grow stronger building on more cortical anatomy, they will be able to explain those patterns back to us, solving the puzzle of the brain’s interconnections, creating a picture we understand."

Comment: we've invented fantastic ways of analyzing the brain and don't have a way of understanding how it really works. A reductionism approach won't work. Will anything? The designer is laughing.