Robert J. and Nancy D. Carney Institute for Brain Science

Michael Frank, Ph.D. directs the Lab for Neural Computation and Cognition, which develops computational models at multiple levels of description, from neural circuit implementations to higher-level algorithmic and computational levels. He uses models of motivated behavior to quantify and explain variation due to genetics and neural activity and how brain-behavior relationships are altered as a function of manipulations. He also uses ML methods for interrogating neural data to test theories and/or for classification of clinical populations and aberrant brain-behavioral relationships, helping to establish the nascent field of computational psychiatry. He and his students have also created online repositories and tutorials for using software available for the community at large, including neural models of various circuits and a hierarchical Bayesian parameter estimation toolbox (“HDDM”) for exploring quantitative relationships between neural and behavioral measures, which enjoys a vibrant listserv and has been adopted by various labs internationally and used in multiple publications.