Data Driven Models in Neuroscience: A Mathematical Success Story
Arizona State University
Barton Lectures in Computational Mathematics
Date: Friday, January 24, 2020
Time: 4:00 pm - 5:00 pm
Location: Petty 150
Reception ∙ Petty 116∙3:30 – 4:00 PM
Building on early work that speculated on the nature of the electrical properties of neurons, Hodgkin and Huxley developed data-driven models for an excitable membrane that still serve as the basis of many neuroscience models today. A decade later, Rall extended these ideas in order to model how the spatial properties of neurons inform the dynamics of their electrical behavior. In this talk, I will discuss how these approaches are being used today to develop data-driven models that are appropriate for answering questions about the mechanisms underlying neural computation in the era of large-scale data. I will examine the issues that arise as novel technologies bring more and more data to the field, and I will introduce some of the tools the community is developing to deal with these issues.