Efficient estimation of phase-resetting curves in real neurons and its significance for neural-network modeling

Phys Rev Lett. 2005 Apr 22;94(15):158101. doi: 10.1103/PhysRevLett.94.158101. Epub 2005 Apr 19.


The phase-resetting curve (PRC) of a neural oscillator describes the effect of a perturbation on its periodic motion and is therefore useful to study how the neuron responds to stimuli and whether it phase locks to other neurons in a network. Combining theory, computer simulations and electrophysiological experiments we present a simple method for estimating the PRC of real neurons. This allows us to simplify the complex dynamics of a single neuron to a phase model. We also illustrate how to infer the existence of coherent network activity from the estimated PRC.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Computer Simulation
  • Electrophysiology
  • Membrane Potentials / physiology
  • Models, Neurological*
  • Nerve Net / physiology*
  • Neurons / physiology*
  • Synapses / physiology