Abstract

Models in neuroscience, whether expressed in words or mathematics, inevitably involve simplifications. This approach has been extraordinarily successful in mathematical physics; for instance, the precise prediction of planetary orbits is achieved by representing planets as simple points of mass. However, can this strategy of simplification be equally effective in computational neuroscience, given the brain's immense complexity?

The philosopher Mazviita Chirimuuta explores this question in her book "The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience". The other panelist, the physicist Terry Sejnowski is a pioneer in computational neuroscience and has extensive practical experience in modelling neural systems at many different levels of detail.