CIMMS Lunchtime Series: Optimal Inputs for Phase Models of Spiking Neurons

Dr. Jeffrey M. Moehlis, University of California, Santa Barbara
Department of Mechanical Engineering

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 square-integral 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. This work is in collaboration with Eric Shea-Brown and Herschel Rabitz.