MechSE Master Calendar

Abstract:  Many brain functions require neural activity with a broad repertoire of time scales, from the fleeting response to brief sensory signals, to the moderate time scales of motor control and body movement, to even longer time scales of memory.  How the brain generates such a wide range of time scales is crucial to understanding cognitive computation.  In this talk I will discuss the hypothesis that the brain tunes itself near criticality and, by doing so, tunes its repertoire of intrinsically generated time scales.  I'll introduce the criticality hypothesis and new data analytic tools to measure proximity to criticality.  I will show applications of these tools in the context of sleep and the arousal system.

Bio:  I received my PhD in Physics in 2004 from University of Maryland, building experiments to study fluid turbulence and geophysical magnetohydrodynamics.  I did my first postdoc at Ecole Normale Superieure in Lyon, France, studying fluid dynamics of bubbles and tiny robots.  I switched fields to neuroscience in 2006, doing systems neuroscience at NIH in Dietmar Plenz's lab (following in John Beggs' footsteps).  I started my own lab in 2012 at University of Arkansas.  We do high density electrophysiology in awake behaving rodents (mostly) and theory to investigate the critical brain hypothesis (mostly).