Fall 2016
Colloquia are held on Fridays at 11:30 a.m. in Cullimore Lecture Hall II, unless noted otherwise. Refreshments are served at 11:30 am. For questions about the seminar schedule, please contact Yassine Boubendir.
Date: November 18, 2016
Speaker: Horacio Rotstein
Department of Mathematical Sciences,
New Jersey Institute of Technology
Title: "Inhibition-Based Resonance in a Hippocampal CA1 Network: A Modeling Study"
Abstract:
Neuronal oscillations are ubiquitous in the nervous system and are believe to be implicated in various cognitive processes and motor behavior in both health and disease. A crucial issue in the understanding of neuronal oscillations is to elucidate the microcircuits that are the substrate to these rhythms in the different brain areas. This raises the question of whether rhythmic activity results solely from the properties of the network connectivity (e.g., excitation and inhibition) and topology or it involves the interplay of the latter with the intrinsic properties (e.g., ionic currents) of the participating neurons. In this project we address this issue theoretically in the context of the hippocampal area CA1 microcircuits, which include excitatory (PYR) and inhibitory (INT) cells. It has been observed that PYR exhibit a preferred subthreshold frequency response to oscillatory inptus at (4 - 10 Hz) frequencies (resonance) 'in vitro'. Contrary to expectation, these cells do not exhibit spiking resonance in response to 'in vivo' direct oscillatory optogenetic activation, but, surprisingly, spiking resonance in PYR occurs when INT are activated. We combine dynamical systems tools, biophysical modeling and numerical simulations to understand the underlying mechanisms of these rather unexpected results. We show that the low-pass filter results form a combination of post-inhibitory rebound (the ability of a cell to spike in response to inhibition) and the intrinsic properties of PYR. The band-pass filter requires additional timing mechanisms that prevent the occurrence of spikes at low frequencies. We discuss various possible, conceptually different scenarios. These results and tools contribute to building a general theoretical and conceptual framework for the understanding of preferred frequency responses to oscillatory inputs in neuronal networks.
This work is in collaboration with G. Buzsaki (NYU Medical School) and E. Stark (Tel Aviv University)