title: Distribution-free graphical and statistical analysis of serial dependence in neuronal spike trains.
abstract: Two-dimensional 'joint' interval distributions of sequential interspike (ISIs) are a commonly used tool in neuronal spike train analysis. We present and evaluate here a modification of the joint interval plot using ranked ISIs. This modification provides clearer graphical evaluation of serial dependence in ISI sequences, a distribution-free basis for isolating changes in serial dependence across experimental treatments from changes in ISI distributions, and a basis for unambiguous statistical tests of serial dependence and stationarity. To validate this method and illustrate the advantages of its use we have applied it to both single-neuron spike trains recorded from cultured mammalian spinal cord neurons and artificial spike trains generated by stochastic models with defined burst envelopes and serial dependencies.
authors.affiliation: Center for Network Neuroscience, University of North Texas, Denton 76203, USA. brhoades@post.wesleyan.peachnet.edu
authors.forename: B K
authors.initials: BK
authors.lastname: Rhoades
authors.forename: J C
authors.initials: JC
authors.lastname: Weil
authors.forename: J M
authors.initials: JM
authors.lastname: Kowalski
authors.forename: G W
authors.initials: GW
authors.lastname: Gross
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D000818:Animals; D051379:Mice; D008959:Models, Neurological; D009433:Neural Inhibition; D009474:Neurons / Q000502:physiology*; D011188:Potassium / Q000378:metabolism; D011930:Reaction Time; D013116:Spinal Cord / Q000166:cytology / Q000502:physiology; D013269:Stochastic Processes; D013696:Temperature
chemical_list: D011188:Potassium