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Analysis of Oscillations in a Reciprocally Inhibitory Network with Synaptic Depression

ataylor{at}ucsd.edu, University of California, San Diego, La Jolla CA 92093-0357, U.S.A.

Garrison W. Cottrell

gary{at}cs.ucsd.edu, University of California, San Diego, La Jolla CA 92093-0357, U.S.A.

William B. Kristan, Jr.

wkristan{at}ucsd.edu, University of California, San Diego, La Jolla CA 92093-0357, U.S.A.

We present and analyze a model of a two-cell reciprocally inhibitory network that oscillates. The principal mechanism of oscillation is short-term synaptic depression. Using a simple model of depression and analyzing the system in certain limits, we can derive analytical expressions for various features of the oscillation, including the parameter regime in which stable oscillations occur, as well as the period and amplitude of these oscillations. These expressions are functions of three parameters: the time constant of depression, the synaptic strengths, and the amount of tonic excitation the cells receive. We compare our analytical results with the output of numerical simulations and obtain good agreement between the two. Based on our analysis, we conclude that the oscillations in our network are qualitatively different from those in networks that oscillate due to postinhibitory rebound, spike-frequency adaptation, or other intrinsic (rather than synaptic) adaptational mechanisms. In particular, our network can oscillate only via the synaptic escape mode of Skinner, Kopell, and Marder (1994).

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