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Pierre-Emmanuel Jabin "Complexity of some models of interacting biological neurons."
Start Date: 4/18/2018Start Time: 3:00 PM
End Date: 4/18/2018End Time: 4:00 PM
Event Description:
Speaker: Pierre-Emmanuel Jabin, University of Maryland, College Park

Abstract: We study some models of for the dynamics of large groups of biological neurons: Those typically consist of large coupled systems of ODE's or SDE's, usually implementing some simple form of integrate and fire. The main question that we wish to address concerns the behavior of such networks as the number of neurons increases. Many particle systems (as they are used in physics, or multi-agent systems in general) naturally come to mind, as it is well known in such cases that propagation of chaos (i.e. the almost independence of each agent) can lead to a reduction in complexity through the direct calculation of various macroscopic densities. However the system under consideration here can be seen as multi-agent system with positive reinforcement so that correlations between neurons never vanish. In an ongoing work with D. Poyato, we first study the case where neurons are essentially fully connected. We show that in spite of this simple topology, the networks may exhibit different measures of complexity which can be characterized through the type of initial connections between neurons.
Location Information:
Homewood - Shaffer
Room: 304
Mathematics Department
Data Analysis Seminar

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