Nonlinear effect on phase response curve of neuron model

Munenori Iida, Toshiaki Omori, Toru Aonishi, Masato Okada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the more useful tools for better understanding population dynamics is the phase response curve (PRC). Recent physiological experiments on the PRCs using real neurons showed that different shapes of the PRCs are generated depending on the perturbation, which has a finite amplitude. In order to clarify the origin of the nonlinear response of the PRCs, we analytically derived the PRCs from single neurons by using a spike response model. We clarified the relation between the subthreshold membrane response property and the PRC. Furthermore, we performed numerical simulations using the Hodgkin-Huxley model and their results have shown that a nonlinear change of the PRCs is generated. Our theory and numerical results imply that the nonlinear change of PRCs is due to the nonlinear element in spike time shift of firing neurons induced by the finite amplitude of the perturbation stimuli.

Original languageEnglish
Title of host publicationNeural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages240-250
Number of pages11
EditionPART 3
DOIs
Publication statusPublished - 2011 Nov 28
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China
Duration: 2011 Nov 132011 Nov 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7064 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Neural Information Processing, ICONIP 2011
CountryChina
CityShanghai
Period11/11/1311/11/17

Keywords

  • neuron model
  • phase response curve
  • spike response model

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Iida, M., Omori, T., Aonishi, T., & Okada, M. (2011). Nonlinear effect on phase response curve of neuron model. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings (PART 3 ed., pp. 240-250). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7064 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-24965-5_26