title: On a set of data for the membrane potential in a neuron.
abstract: We consider a set of data where the membrane potential in a pyramidal neuron is measured almost continuously in time, under varying experimental conditions. We use nonparametric estimates for the diffusion coefficient and the drift in view to contribute to the discussion which type of diffusion process is suitable to model the membrane potential in a neuron (more exactly: in a particular type of neuron under particular experimental conditions).
authors.affiliation: Institute of Mathematics, University of Mainz, Staudingerweg 9, D-55099 Mainz, Germany. hoepfner@mathematik.uni-mainz.de
authors.forename: Reinhard
authors.initials: R
authors.lastname: Höpfner
mesh_terms: D000200:Action Potentials / Q000187:drug effects / Q000502:physiology; D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology; D004594:Electrophysiology; D008564:Membrane Potentials / Q000187:drug effects / Q000502:physiology; D051379:Mice; D008959:Models, Neurological; D009431:Neural Conduction / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D011188:Potassium / Q000494:pharmacology; D017966:Pyramidal Cells / Q000187:drug effects / Q000502:physiology; D018709:Statistics, Nonparametric; D013269:Stochastic Processes; D013779:Tetrodotoxin / Q000494:pharmacology
chemical_list: D013779:Tetrodotoxin; D011188:Potassium