AIMRC Seminar: Proximity to Criticality Determines Learning Capacity and Predicts Alzheimer's

The Arkansas Integrative Metabolic Research Center (AIMRC) will host Dr. Woodrow Shew, a professor of physics at the U of A, at 11:50 a.m. on Wednesday, Sept. 23, in BELL 2269. Dr. Shew's research explores how brain function and behavior emerge from the coordinated activity of large populations of neurons by integrating experimental neuroscience, computational modeling and mathematical theory. In this seminar, he will discuss the brain criticality hypothesis and present evidence that neural dynamics near a critical state influence learning capacity and may provide an early indicator of Alzheimer's disease before symptoms appear.

Abstract: Myriad genetic, molecular and cellular properties impact brain function and dysfunction, but behavior ultimately emerges from the dynamic activity of large networks of neurons. How should these neural population dynamics be configured to optimize computation and maintain a healthy brain? This seminar will explore the brain criticality hypothesis, which posits that brain dynamics operate most effectively near a marginally stable state, at the edge of chaos. An overview of this hypothesis will be presented, along with recent findings suggesting that proximity to criticality influences learning speed and capacity, while deviations from criticality predict Alzheimer's disease even before symptoms become evident. The findings on learning speed are based on electrophysiology studies in mice and humans, whereas the findings on Alzheimer's are based on longitudinal fMRI experiments in humans.

Biography: Dr. Shew earned a B.A. in physics and mathematics from the College of Wooster in 1998 and a Ph.D. in physics from the University of Maryland in 2004. Following postdoctoral training in physics at the École Normale Supérieure in Lyon, France (2004-2006), and neuroscience at the National Institutes of Health (2006-2012), he joined the U of A faculty in 2012. His research examines how brain function emerges from the coordinated dynamics of large populations of neurons. Combining behavioral and electrophysiological experiments, computational modeling and mathematical theory, his laboratory studies the principles underlying neural computation and behavior. His team is recognized for expertise in high-density neural recordings, advanced motional tracking and innovative data analysis approaches. His work has advanced understanding of the critical brain hypothesis and has leveraged concepts from fundamental physics, including renormalization group theory, to investigate the organization and function of complex neural systems.

This event is supported by NIGMS of the National Institutes of Health under award number 2P20GM139768. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Pizza and beverages will be served. Please contact Kimberley Fuller, fullerk@uark.edu, for more information.

For those unable to attend in person, this seminar will also be available via Zoom.