title: Inverse Stochastic Resonance in Cerebellar Purkinje Cells.
abstract: Purkinje neurons play an important role in cerebellar computation since their axons are the only projection from the cerebellar cortex to deeper cerebellar structures. They have complex internal dynamics, which allow them to fire spontaneously, display bistability, and also to be involved in network phenomena such as high frequency oscillations and travelling waves. Purkinje cells exhibit type II excitability, which can be revealed by a discontinuity in their f-I curves. We show that this excitability mechanism allows Purkinje cells to be efficiently inhibited by noise of a particular variance, a phenomenon known as inverse stochastic resonance (ISR). While ISR has been described in theoretical models of single neurons, here we provide the first experimental evidence for this effect. We find that an adaptive exponential integrate-and-fire model fitted to the basic Purkinje cell characteristics using a modified dynamic IV method displays ISR and bistability between the resting state and a repetitive activity limit cycle. ISR allows the Purkinje cell to operate in different functional regimes: the all-or-none toggle or the linear filter mode, depending on the variance of the synaptic input. We propose that synaptic noise allows Purkinje cells to quickly switch between these functional regimes. Using mutual information analysis, we demonstrate that ISR can lead to a locally optimal information transfer between the input and output spike train of the Purkinje cell. These results provide the first experimental evidence for ISR and suggest a functional role for ISR in cerebellar information processing.
authors.affiliation: Group for Neural Theory, Laboratoire des Neurosciences Cognitives, École Normale Supérieure, Paris, France.|Institute of Physics, Nanotechnology and Telecommunications, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia.|Center for Cognition and Decision Making, Department of Psychology, NRU Higher School of Economics, Moscow, Russia.
authors.forename: Anatoly
authors.identifier: 0000-0001-6284-9913
authors.initials: A
authors.lastname: Buchin
authors.affiliation: Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.
authors.forename: Sarah
authors.identifier: 0000-0003-0310-6647
authors.initials: S
authors.lastname: Rieubland
authors.affiliation: Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.
authors.forename: Michael
authors.initials: M
authors.lastname: Häusser
authors.affiliation: Group for Neural Theory, Laboratoire des Neurosciences Cognitives, École Normale Supérieure, Paris, France.|Center for Cognition and Decision Making, Department of Psychology, NRU Higher School of Economics, Moscow, Russia.
authors.forename: Boris S
authors.initials: BS
authors.lastname: Gutkin
authors.affiliation: Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom.
authors.forename: Arnd
authors.initials: A
authors.lastname: Roth
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D019295:Computational Biology; D008959:Models, Neurological; D011689:Purkinje Cells / Q000166:cytology* / Q000502:physiology*; D051381:Rats; D017207:Rats, Sprague-Dawley; D013269:Stochastic Processes