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Phys Rev Lett. 2005 Apr 22;94(15):158101. Epub 2005 Apr 19.

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

Author information

1
Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA.

Abstract

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.

PMID:
15904191
PMCID:
PMC1410718
DOI:
10.1103/PhysRevLett.94.158101
[Indexed for MEDLINE]
Free PMC Article

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