title: Stochastic resonance in neuron models: endogenous stimulation revisited.
abstract: The paradigm of stochastic resonance (SR)-the idea that signal detection and transmission may benefit from noise-has met with great interest in both physics and the neurosciences. We investigate here the consequences of reducing the dynamics of a periodically driven neuron to a renewal process (stimulation with reset or endogenous stimulation). This greatly simplifies the mathematical analysis, but we show that stochastic resonance as reported earlier occurs in this model only as a consequence of the reduced dynamics.
authors: Max-Planck-Institut für Strömungsforschung and Fakultät für Physik, Universität Göttingen, Germany. hans.plesser@itf.nlh.no
authors: H E
authors: HE
authors: Plesser
authors: T
authors: T
authors: Geisel
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000222:Adaptation, Physiological / Q000502:physiology; D003198:Computer Simulation; D004056:Differential Threshold / Q000502:physiology*; D004558:Electric Stimulation; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology*