Training in Methods of Computational Neuroscience

点击翻译按钮获取中文摘要

 DESCRIPTION (provided by applicant): The Methods in Computational Neuroscience (MCN) course at the Marine Biological Laboratory in Woods Hole, MA provides a singular training opportunity to equip students with cutting edge skills and conceptual foundations of computational methods applied to understanding the dynamics and function of brain cells, circuits, and behavior. MCN is an intense lecture and laboratory course-targeted to a talented and diverse pool of students. MCN students interact one-on-one with internationally renowned scientists and carry out hands-on, project-based training with a wide variety of computational techniques and approaches. A foundational goal of the MCN course is to prepare students to carry out research leading to 1) new theoretical and data analysis tools, and 2) conceptual foundations for understanding of the biological basis of mental processes. These goals directly align with the scientific vision of the BRAIN Initiative. The course provides in-depth instruction on how to use computational approaches to solve fundamental problems in neurobiology, and bridge the wide range of scales probed by different experimental techniques. This is accomplished through hands-on training in the mathematical foundations and techniques for the model- based analysis of neural data, in the context of mechanistic descriptions of neurons, networks, and brain systems. The MCN course maintains its innovative edge by continually updating computational topics that are relevant to new experimental advances, such as the identification of cell types with distinct cellular properties, high-resolution anatomy that provids information about connectivity and structural properties of neurons, large-scale neuronal recordings with high-density electrical and optical techniques, and causal interventions such as optogenetics. New topics in the course include emerging computational approaches such as compressed sensing, advanced statistical inference, optimal experimental design, dimensionality reduction and analysis of large data sets. An additional innovation is an increased emphasis on computational approaches to understanding and addressing brain disorders, including schizophrenia, epilepsy, addiction, depression, and Parkinson's disease. The course is unique in providing students intensive interactions with a group of dedicated faculty, many of whom devote weeks or even the entire month to work with students. The course fosters a collegial, international environment that advances student careers by providing students with networking opportunities that lead to long-term interactions, mentorship, and collaborations.