title: Linking the computational structure of variance adaptation to biophysical mechanisms.
abstract: In multiple sensory systems, adaptation to the variance of a sensory input changes the sensitivity, kinetics, and average response over timescales ranging from < 100 ms to tens of seconds. Here, we present a simple, biophysically relevant model of retinal contrast adaptation that accurately captures both the membrane potential response and all adaptive properties. The adaptive component of this model is a first-order kinetic process of the type used to describe ion channel gating and synaptic transmission. From the model, we conclude that all adaptive dynamics can be accounted for by depletion of a signaling mechanism, and that variance adaptation can be explained as adaptation to the mean of a rectified signal. The model parameters show strong similarity to known properties of bipolar cell synaptic vesicle pools. Diverse types of adaptive properties that implement theoretical principles of efficient coding can be generated by a single type of molecule or synapse with just a few microscopic states.
authors.affiliation: Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
authors.forename: Yusuf
authors.initials: Y
authors.lastname: Ozuysal
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Baccus
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000222:Adaptation, Physiological / Q000502:physiology*; D025042:Amacrine Cells; D000818:Animals; D055592:Biophysical Phenomena / Q000502:physiology*; D003198:Computer Simulation; D008959:Models, Neurological; D009474:Neurons / Q000145:classification / Q000502:physiology*; D010775:Photic Stimulation; D012160:Retina / Q000166:cytology*; D051245:Retinal Bipolar Cells; D012165:Retinal Ganglion Cells; D014562:Caudata; D014795:Visual Pathways / Q000502:physiology