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Stimulus features, resetting curves, and the dependence on adaptation

Published: 01 June 2013 Publication History

Abstract

We derive a formula that relates the spike-triggered covariance (STC) to the phase resetting curve (PRC) of a neural oscillator. We use this to show how changes in the shape of the PRC alter the sensitivity of the neuron to different stimulus features, which are the eigenvectors of the STC. We compute the PRC and STC for some biophysical models. We compare the STCs and their spectral properties for a two-parameter family of PRCs. Surprisingly, the skew of the PRC has a larger effect on the spectrum and shape of the STC than does the bimodality of the PRC (which plays a large role in synchronization properties). Finally, we relate the STC directly to the spike-triggered average and apply this theory to an olfactory bulb mitral cell recording.

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Published In

cover image Journal of Computational Neuroscience
Journal of Computational Neuroscience  Volume 34, Issue 3
June 2013
176 pages

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 2013

Author Tags

  1. Adaptation
  2. Neural oscillator
  3. Perturbation
  4. Phase resetting curve
  5. Spike-triggered covariance

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