Undergraduate and Graduate Training in Computational Neuroscience and Data Analysis

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Project Summary The goal of this training program entitled “Training in Computational Neuroscience and Data Analysis” is to help undergraduate and predoctoral students gain the knowledge, skills, and attitudes they need to flourish in a scientific career that brings quantitative approaches to the study of neuroscience and behavior. This new program arises from a prior training program in Computational Neuroscience at Brandeis University that expired recently after 10 years of NIDA support. Given the increasing importance of machine learning in data analysis and solving of data-rich scientific problems, coupled with recent Brandeis hires in the field, our new program will include more participation from computer science faculty with expertise in the field. Also, given the recent introduction of an applied mathematics major at Brandeis and associated new faculty in the field, we have doubled the number of training labs with students working on mathematical modeling in neuroscience. The proposed program requests funding to support 6 undergraduates, 4 NRSA eligible graduate students, and 2 non-NRSA eligible graduate students each year. We will target two cohorts of prospective trainees: 1) Individuals with strong prior experience with quantitative methods who wish to work in neuroscience. 2) Individuals with backgrounds in psychology, neuroscience and biology who wish to learn to employ quantitative and computational methods to tackle important problems in neuroscience. We will continue prioritizing outreach activities aimed at ensuring trainees from underrepresented populations are included in our program. Students will have two complementary mentors so they participate in labs with both quantitative and experimental approaches to neuroscience. The 26 training faculty have research expertise ranging from human cognition to cellular and molecular neuroscience, so a wide variety of research problems, at numerous levels of analysis are available to trainees. The training faculty were chosen based on demonstrated commitment to the use of theoretical and computational methods and interdisciplinary collaboration to understand the nervous system in health and disease. Students will take courses in statistics, data analysis, computational neuroscience, obtain skills in building models of neurons, synapses, and networks, and employ these in a variety of independent research projects. In addition to course work and laboratory research, students and trainees will be engaged in a large number of other activities designed to enhance their speaking skills, writing skills, and ability to collaborate with other scientists. All students and trainees will receive training in the responsible conduct of science and will interact with senior scientists at other institutions.