Advanced Computational Analysis for Behavioral and Neurophysiological Recordings

This summer school will expose participants to state-of-the-art computational methods for visualizing, analyzing and interpreting high-dimensional neurophysiological and behavioral data. The recent years have seen the explosion of high-throughput neural recording methods: hundreds of individual neurons can now be monitored simultaneously using large-scale functional imaging or multisite electrode arrays. A comparable trend is observed in behavioral studies where new imaging technology produces high-resolution imaging of complex behaviors. In order to extract meaningful information from these high-dimensional datasets, neurobiologists need to develop and use robust computational tools. This workshop aims at addressing this need by offering theoretical as well as direct practical exposure to advanced data processing tools in the particular context of neuroscience. The workshop, intended for PhD students and post-docs in experimental neurobiology, will consist in presentations by experts in the field on the foundations of these computational techniques, from image analysis, to dimensionality reduction methods and machine learning approaches. These techniques will then be effectively implemented by the participants during practical hands-on sessions, using actual datasets - behavioral, neuroimaging or electrophysiological on mice and zebrafish - provided to them.