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by lambdaloop
2335 days ago
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As a counterpoint, I am a computational neuroscientist who transitioned form working in human cognition to fruit fly motor control. Fruit fly neuroscience in the past decade has advanced tremendously. With the latest tools, we can record activity from specific genetically labeled neurons while stimulating others. We have identified specific groups of neurons to stimulate to get the fly to groom, walk, turn, and even walk backwards. The full fly brain has been scanned with similar techniques and the connectome is beginning to be mapped out (e.g. see this very recent post from Google AI research https://ai.googleblog.com/2020/01/releasing-drosophila-hemib... ). I find that as we gain new tools to study the nervous system more specifically, both data and models of how neurons are organized at the circuit level become more important. To advance on an analogy in the article, it's like trying to explore the dynamics of NYC without a map. For instance, it's hard to tell how/why people interact with central park if you don't even know where they live. The more specifically you are able to pin down people, the more it matters where exactly they live to understand. Granted, the fly is much simpler than humans or even mice, and it will likely take decades and new tools for us to study humans in this way. However, when we get there, mapping out the brain connections will be crucial to make sense of it all. |
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Similar tricks can be played with the human brain, things we have been able to do for decades, while people are undergoing brain surgery, and now later, with TMS. However, being able to elicit limb movements or bits of speech, or even emotional qualia is different from having a dynamic understanding of the brain in vivo in everyday life.
Certainly having an understanding of detailed circuitry is interesting and important, but to me there's a forest for the trees problem.