title: A benchmark test for a quantitative assessment of simple neuron models.
abstract: Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activity of neurons under temporally structured current injection. It is, however, difficult to compare the advantages of various models and algorithms since each model is designed for a different set of data. Here, we report about one of the first attempts to establish a benchmark test that permits a systematic comparison of methods and performances in predicting the activity of rat cortical pyramidal neurons. We present early submissions to the benchmark test and discuss implications for the design of future tests and simple neurons models.
authors.affiliation: Center for Psychiatric Neuroscience, University of Lausanne, 1015 Lausanne, Switzerland. renaud.jolivet@a3.epfl.ch
authors.forename: Renaud
authors.initials: R
authors.lastname: Jolivet
authors.forename: Ryota
authors.initials: R
authors.lastname: Kobayashi
authors.forename: Alexander
authors.initials: A
authors.lastname: Rauch
authors.forename: Richard
authors.initials: R
authors.lastname: Naud
authors.forename: Shigeru
authors.initials: S
authors.lastname: Shinomoto
authors.forename: Wulfram
authors.initials: W
authors.lastname: Gerstner
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology; D003627:Data Interpretation, Statistical; D004594:Electrophysiology; D005260:Female; D008297:Male; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D017966:Pyramidal Cells / Q000502:physiology; D051381:Rats; D017208:Rats, Wistar; D012044:Regression Analysis