title: Direct control of firing rate gain by dendritic shunting inhibition.
abstract: The firing rate gain of neurons, defined as the slope of the relation between input to a neuron and its firing rate, has received considerable attention in the past few years. This has been largely motivated by the many experimental demonstrations of behavior related gain changes in a variety of neural circuits of the CNS. A surprising result was that a prime candidate, shunting inhibition, apparently does not change the firing rate gain of neurons. However, in this paper, we show a physiologically plausible mechanism by which shunting inhibition in the dendritic tree does, in a simple and direct manner, modulate the firing gain of neurons. The effect is due to a strong attenuation of the dendritic current arriving at the soma by shunting dendritic inhibition. Increasing the dendritic inhibitory conductance enhances the attenuation of current flowing from the dendritic to the somatic compartment and thus reduces firing gain. This mechanism relies on known physiological and anatomical properties of CNS neurons and does not require special features such as tunable neural noise inputs. Gain control by the proposed mechanism may prove to be a ubiquitous feature of neural circuit operations and it is readily verifiable experimentally.
authors.affiliation: Brain & Movement Laboratory, Department of Anatomy and Physiology, Laval University, CRULRG F6500, 2601 de la Canardiere Québec City G1J 2G3, Canada. charles.capaday@anm.ulaval.edu
authors.forename: Charles
authors.initials: C
authors.lastname: Capaday
authors.forename: Carl
authors.initials: C
authors.lastname: van Vreeswijk
mesh_terms: D000200:Action Potentials / Q000502:physiology* / Q000528:radiation effects; D000818:Animals; D003712:Dendrites / Q000502:physiology* / Q000528:radiation effects; D004307:Dose-Response Relationship, Radiation; D004553:Electric Conductivity; D004558:Electric Stimulation / Q000379:methods; D008959:Models, Neurological; D009433:Neural Inhibition / Q000502:physiology* / Q000528:radiation effects; D016571:Neural Networks, Computer; D009474:Neurons / Q000145:classification / Q000166:cytology* / Q000502:physiology* / Q000528:radiation effects