Title: Modeling adaptable behavior in neurons

Speaker: Dylan Shepardson

Date/Time: Wednesday, February 4, 2009, 9:30 AM MST

Location: CSRI Building, Room 90 (Sandia NM) to 915/S101 (CA)

Brief Abstract: Neurons are remarkably adaptable to their environment, rearranging themselves internally to keep functioning in a consistent manner in order to signal effectively to other parts of the nervous system.  Mathematical models are a valuable tool for uncovering the mechanisms behind a neuron’s ability to regulate its behavior, and understanding the relationship between a neuron’s internal state and its behavior is an important first step.  I will explore the kinds of mathematical models that have been used to represent neurons and some optimization-based analytical techniques being developed to understand their behavior.

Dylan is a PhD candidate in the Algorithms, Combinatorics, and Optimization group at the Georgia Institute of Technology.

CSRI POC: Jean-Paul Watson, (505) 845-8887