I’ve no great resources in mind for this. Off the top of my head, a few examples of ideas that are common in comp neuro that might have bought mech interp some time if more people in mech interp were familiar with them when they were needed: - Polysemanticity/distributed representations/mixed selectivity - Sparse coding - Representational geometry I am not sure about what future mech interp needs will be, so it’s hard to predict which ideas or methods that are common in neuro will be useful (topological data analysis? Dynamical systems?). But it just seems pretty likely that a field that tackles such a similar problem will continue to be a useful source of intuitions and methods. I’d love if someone were to write a review or post on the interplay between the parallel fields of comp neuro and mech interp. It might help flag places where there ought to be more interplay.
I’m wondering if you have any other pointers to lessong/methods you think are valuable from neuroscience?
I’ve no great resources in mind for this. Off the top of my head, a few examples of ideas that are common in comp neuro that might have bought mech interp some time if more people in mech interp were familiar with them when they were needed:
- Polysemanticity/distributed representations/mixed selectivity
- Sparse coding
- Representational geometry
I am not sure about what future mech interp needs will be, so it’s hard to predict which ideas or methods that are common in neuro will be useful (topological data analysis? Dynamical systems?). But it just seems pretty likely that a field that tackles such a similar problem will continue to be a useful source of intuitions and methods. I’d love if someone were to write a review or post on the interplay between the parallel fields of comp neuro and mech interp. It might help flag places where there ought to be more interplay.