Two computational regimes of a single-compartment neuron separated by a planar boundary in conductance space

Authors:
Brian Nils Lundstrom;Sungho Hong;Matthew H. Higgs;Adrienne L. Fairhall
Affiliations:
Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, U.S.A. lundbr@u.washington.edu;Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, U.S.A. shhong@u.washington.edu;Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, and Veterans Affairs Puget Sound Health System, Seattle, WA 98108, U.S.A. higgsm@u.washington.edu;Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, U.S.A. fairhall@u.washington.edu
Venue:
Neural Computation
Year:
2008

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Abstract

Recent in vitro data show that neurons respond to input variance with varying sensitivities. Here we demonstrate that Hodgkin-Huxley (HH) neurons can operate in two computational regimes: one that is more sensitive to input variance (differentiating) and one that is less sensitive (integrating). A boundary plane in the 3D conductance space separates these two regimes. For a reduced HH model, this plane can be derived analytically from the V nullcline, thus suggesting a means of relating biophysical parameters to neural computation by analyzing the neuron's dynamical system.