Bridging theory and experiment in (statistical) learning

Abstract

Statistical learning and neuroplasticity have been studied extensively over the past decades by theorists and experimentalists working in animal and human experimental models, with neurobiologists, cognitive neuroscientists, and theorists each offering complementary inputs to the field. While there are collaborations between theorists and each of experimentalists working in animal and human models, there are more limited interactions across the experimental groups, with these fields remaining largely siloed. Here, we discuss the challenges for cross-disciplinary collaboration, as well as offer suggestions for ways to facilitate it in the future. We propose that theorists are in a key position to facilitate interactions between experimentalists working in animal and human models by developing theories or working models that span these two fields to enable cross-disciplinary collaboration. Increasing training for early career researchers to become skilled cross-disciplinary collaborators may also help facilitate future interactions in these fields.