Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons

Song, Z., Zhou, Y. and Juusola, M. orcid.org/0000-0002-4428-5330 (2017) Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons. Physiological Reports, 5. e13306 . ISSN 2051-817X

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society. This is an open access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: vision; neural adaptation; Drosophila; large dynamic range; fly photoreceptor; quantal 28 sampling; stochasticity; quantum bump
Dates:
  • Accepted: 4 May 2017
  • Published (online): 8 June 2017
  • Published: 8 June 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Biological Sciences (Sheffield) > Department of Biomedical Science (Sheffield)
Funding Information:
FunderGrant number
BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL (BBSRC)BB/M009564/1
JANE & AATOS ERKKO FOUNDATIONNONE
LEVERHULME TRUST (THE)RPG-2012-567
Depositing User: Symplectic Sheffield
Date Deposited: 10 May 2017 14:17
Last Modified: 07 Jul 2017 12:00
Published Version: https://doi.org/10.14814/phy2.13306
Status: Published
Publisher: Wiley
Refereed: Yes
Identification Number: https://doi.org/10.14814/phy2.13306

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