An open discussion about low-dimensional representations in cognitive and systems neuroscience
By Dan Lurie, University of California, Berkeley
- Theme: Past, Present and Future of Open Science
- Format: Emergent session
Abstract
The brain is one of (if not the most) complex systems in the known universe. As such, it is natural for those of us studying brain structure, function, and mental processes to seek out simplified representations (networks, gradients, manifolds, cognitive concepts, diagnoses).
To what extent do these models accurately capture underlying mechanisms? How do we best map findings and concepts across models? Can a model be useful if it is "merely" descriptive?
In the tradition of previous OSR discussions of hot topics (time varying functional connectivity - 2017, theory in network neuroscience - 2019), please join us for an open discussion of these and related questions.
Feel free to comment below with points you'd like to raise during the conversation!
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