In trying to brainstorm a list of unsolved problems in neuroscience, I read the a multitude of sources and asked around. This yields a predictable list ranging from ‘how can we cure psychiatric illness?’ to ‘what is consciousness?’. Asking Caltech faculty added entries about how networks function and what neural computation is. Caltech students had things figured out and got straight to the point (‘how can I sleep less?’, ‘how can we save our species?’, ‘can we become immortal?’). Next, I distill my own idiosyncratic list from all of this (admittedly biased towards cognitive neuroscience). Note that some future questions build on prior ones: we need to understand psychiatric illnesses before we can cure them, and whole-brain microscopic-resolution imaging of the zebrafish brain (100,000 neurons; done, although temporal resolution will improve) needs to come before we do the same for the mouse brain (70,000,000 neurons), let alone the human brain (80,000,000,000 neurons).
Some argue that we can only understand the brain once we know how it could be built. Both evolution and development describe temporally sequenced processes whose final expression looks very complex indeed, but the underlying generative rules may be relatively simple (for an interesting approach to discovering these rules). Perhaps knowing how to build a brain will enable us to glean general principles that cut across the many individual questions, and across species. Or might there instead be a huge diversity of specialized and baroque mechanisms, a giant ‘bag of tricks’, that serves each organism very well for specific problems in its niche, but that share no illuminating larger themes? Probably there are both general principles as well as specific constraints and local solutions, and an engineering view would force us to map this out. There is also the hope that understanding how evolution or engineering could build a brain would help us understand what problems brains are designed to solve: what is their proper function?
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