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Methods In Neuroscience At Dartmouth (MIND): Computational Summer School

Computational methods are rapidly transforming psychology and neuroscience research. However, traditional psychology and neuroscience training programs have not been able to keep pace with rapid development of methodological developments. Our vision is to help train the next generation of psychological and brain scientists in the latest mathematical modeling and analysis tools for studying the mind. Training students in computational techniques in graduate programs, workshops, and tutorials is an extraordinarily challenging endeavor due to high levels of variability in (a) mathematical and computer backgrounds, (b) interest in theory vs applications, and (c) computer operating systems and software packages. Many existing workshops provide hands on training in specific techniques, but this is largely introductory, merely providing superficial exposure to textbook “toy” problems, which is insufficient to allow students to apply these techniques to their own work. We strive to provide a comfortable, inclusive, diverse, nurturing, and exciting learning environment where all participants have the opportunity to further their science. Each year we select a general theme to help frame the lectures and tutorials included in the course. Importantly, these themes always include ties to psychological and neuroscientific questions at a broad range of scales, ranging from single neurons, to full brains, to interacting groups. For our 2020 MIND Computational Summer School, our theme will be how minds interacts. Past themes have included network dynamics, narratives and natural contexts, and cognitive maps.