title: Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models.
abstract: Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we demonstrate that, using a convex optimization procedure we previously introduced, a Generalized Integrate-and-Fire model can be accurately fitted with a limited amount of data. The model is capable of predicting both the spiking activity and the subthreshold dynamics of different cell types, and can be used for online characterization of neuronal properties. A protocol is proposed that, combined with emergent technologies for automatic patch-clamp recordings, permits automated, in vitro high-throughput characterization of single neurons.
authors.affiliation: Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Christian
authors.initials: C
authors.lastname: Pozzorini
authors.affiliation: Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Skander
authors.initials: S
authors.lastname: Mensi
authors.affiliation: Laboratory of Neural Microcircuitry (LNMC), Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Olivier
authors.initials: O
authors.lastname: Hagens
authors.affiliation: Department of Physics, University of Ottawa, Ottawa, Canada.
authors.forename: Richard
authors.initials: R
authors.lastname: Naud
authors.affiliation: Allen Institute for Brain Science, Seattle, Washington, USA.
authors.forename: Christof
authors.initials: C
authors.lastname: Koch
authors.affiliation: Laboratory of Computational Neuroscience (LCN), Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Wulfram
authors.initials: W
authors.lastname: Gerstner
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001921:Brain / Q000166:cytology; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004594:Electrophysiology; D057166:High-Throughput Screening Assays / Q000379:methods*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*