Description:

Neuronal activity patterns provide the physical substrates for perception, cognition, and behavior. This activity in turn emerges from the network of interactions between neurons. A mechanistic understanding of brain function thus requires that neuroscientists be able to link functional patterns of neuronal activity to structural patterns of synaptic connectivity. Here I will describe my lab’s efforts to link neural network structure and function by building and characterizing mathematical ensembles of neural network models. Our approach embraces the fact that many different patterns of synaptic connectivity could underlie the same functional response properties. By figuring out what is shared by all possibilities, we make experimental predictions that rigorously test neural network models. By comparing the possibilities to available connectivity data, we build biologically realistic neural network models. And by hypothesizing that biology dynamically explores its possibilities, we develop novel theories of learning and memory. This talk will explain each of these applications to illustrate how ensemble modeling provides a general framework for understanding how brains work.

 James Fitzgerald, Associate Professor, Department of Neurobiology, Northwestern University

Host: John Marko