This proposal is to administer and further develop a successfully established two-week summer training course titled Mining and Modeling of Neuroscience Data which is held at UC Berkeley. The course teaches methods for analyzing neurophysiology data, that is, measurements of the neural activity over time, co-registered with behavior or stimuli. With the Obama BRAIN initiative in full swing, rich neurophysiology data will become available at a high rate. The course has the goal to help build a workforce for leveraging these data and is designed to fill in a significant gap in training opportunities in the intersection between neuroscience and computational methods (computer science, mathematics, statistics, physics, engineering). Specifically, attendees of the course will be individuals either with a quantitative background and interest in neuroscience or with a background in neuroscience who wish to learn cutting edge approaches for the analysis of neuroscience data. To recruit students from Computer Science and Mathematics the project is partnered with the Simons Institute of the Theory of Computing and the Mathematical Sciences Research Institute. The training provided by this course will help increase the pool of researches who can apply existing and develop novel methodology for analyzing and modeling large, complex neurophysiology data sets. Increasing this type of quantitative knowledge in neuroscience will be essential to enhancing the understanding of the brain and developing approaches to treat disorders of the brain.
This course teaches techniques for analyzing neuroscience data that include measurements of the simultaneous activity of many individual neurons to students with background in mathematics or in neuroscience. Investigation of this type of dynamical data is at the core of the BRAIN initiative and is necessary for a detailed understanding of brain function that could enable the developments of treatments for nervous system disorders or injuries.
