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Journal of Undergraduate Research

Keywords

weak synchronization, inhibitory neuronal networks, nervous system

College

Physical and Mathematical Sciences

Department

Mathematics

Abstract

One ubiquitously observed dynamic phenomenon in the nervous system is that of weak synchronization or clustering, a behavior in which a large group of neurons in a population will all fire synchronously and then fall out of synchronization. When isolated to neurons that only form short-range connections, this behavior is typically referred to as “neuronal avalanches”, and is thought to be particularly important for robustness of information transmission as well as sensitivity to inputs. Given these potential computational benefits, avalanches have been a focus of theoretical biologists for the past 20 years. In particular, my project focused on the conditions, parameterizations and network topologies (structures) under which neuronal avalanches arise. During the course of the project, I also gave attention to comparisons between different neuronal network simulation platforms, as well as investigating more deeply the relation between neuronal avalanches and “criticality”, a quality of dynamics that is often hypothesized to be the optimal regime for computation.

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