Optimal inputs for phase models of spiking neurons

Jeff Moehlis, Eric Shea-Brown, Herschel Rabitz

Research output: Contribution to journalArticle

89 Scopus citations

Abstract

Variational methods are used to determine the optimal currents that elicit spikes in various phase reductions of neural oscillator models. We show that, for a given reduced neuron model and target spike time, there is a unique current that minimizes a squareintegral measure of its amplitude. For intrinsically oscillatory models, we further demonstrate that the form and scaling of this current is determined by the model's phase response curve. These results reflect the role of intrinsic neural dynamics in determining the time course of synaptic inputs to which a neuron is optimally tuned to respond, and are illustrated using phase reductions of neural models valid near typical bifurcations to periodic firing, as well as the Hodgkin-Huxley equations.

Original languageEnglish (US)
Pages (from-to)358-367
Number of pages10
JournalJournal of Computational and Nonlinear Dynamics
Volume1
Issue number4
DOIs
StatePublished - Oct 1 2006

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Applied Mathematics

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