Literature DB >> 15649590

A measure of local variation of inter-spike intervals.

Shigeru Shinomoto1, Keiji Miura, Shinsuke Koyama.   

Abstract

It has been revealed in our recent study that cortical neurons are categorized into distinct types, according to a new measure of the local variation of inter-spike intervals, L(V). In this paper, we obtain values of the local variation L(V) and a conventional coefficient of variation C(V) for a variety of model point processes. While the value of C(V) undergoes large changes by rate fluctuation of the point processes, the value of L(V) does not undergo large changes by rate fluctuation, and is principally determined by the form of intrinsic interval distribution of the original model point process.

Mesh:

Year:  2005        PMID: 15649590     DOI: 10.1016/j.biosystems.2004.09.023

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  16 in total

1.  QUANTITATIVE MODELING OF SPATIO-TEMPORAL DYNAMICS OF INFERIOR OLIVE NEURONS WITH A SIMPLE CONDUCTANCE-BASED MODEL.

Authors:  Yuichi Katori; Eric J Lang; Miho Onizuka; Mitsuo Kawato; Kazuyuki Aihara
Journal:  Int J Bifurcat Chaos       Date:  2010-03       Impact factor: 2.836

2.  Comparison of local measures of spike time irregularity and relating variability to firing rate in motor cortical neurons.

Authors:  Adrián Ponce-Alvarez; Bjørg Elisabeth Kilavik; Alexa Riehle
Journal:  J Comput Neurosci       Date:  2009-05-16       Impact factor: 1.621

3.  Multiscale relevance and informative encoding in neuronal spike trains.

Authors:  Ryan John Cubero; Matteo Marsili; Yasser Roudi
Journal:  J Comput Neurosci       Date:  2020-01-28       Impact factor: 1.621

4.  A general method to generate artificial spike train populations matching recorded neurons.

Authors:  Samira Abbasi; Selva Maran; Dieter Jaeger
Journal:  J Comput Neurosci       Date:  2020-01-23       Impact factor: 1.621

5.  Emergent bimodal firing patterns implement different encoding strategies during gamma-band oscillations.

Authors:  B Sancristóbal; R Vicente; J M Sancho; J Garcia-Ojalvo
Journal:  Front Comput Neurosci       Date:  2013-03-26       Impact factor: 2.380

6.  Segmental Bayesian estimation of gap-junctional and inhibitory conductance of inferior olive neurons from spike trains with complicated dynamics.

Authors:  Huu Hoang; Okito Yamashita; Isao T Tokuda; Masa-Aki Sato; Mitsuo Kawato; Keisuke Toyama
Journal:  Front Comput Neurosci       Date:  2015-05-21       Impact factor: 2.380

7.  Information theoretic analysis of proprioceptive encoding during finger flexion in the monkey sensorimotor system.

Authors:  Claire L Witham; Stuart N Baker
Journal:  J Neurophysiol       Date:  2014-10-08       Impact factor: 2.714

8.  Robust transmission of rate coding in the inhibitory Purkinje cell to cerebellar nuclei pathway in awake mice.

Authors:  Samira Abbasi; Amber E Hudson; Selva K Maran; Ying Cao; Ataollah Abbasi; Detlef H Heck; Dieter Jaeger
Journal:  PLoS Comput Biol       Date:  2017-06-15       Impact factor: 4.475

9.  Classification of Neurons in the Primate Reticular Formation and Changes after Recovery from Pyramidal Tract Lesion.

Authors:  Boubker Zaaimi; Demetris S Soteropoulos; Karen M Fisher; C Nicholas Riddle; Stuart N Baker
Journal:  J Neurosci       Date:  2018-05-23       Impact factor: 6.167

10.  Probabilistic identification of cerebellar cortical neurones across species.

Authors:  Gert Van Dijck; Marc M Van Hulle; Shane A Heiney; Pablo M Blazquez; Hui Meng; Dora E Angelaki; Alexander Arenz; Troy W Margrie; Abteen Mostofi; Steve Edgley; Fredrik Bengtsson; Carl-Fredrik Ekerot; Henrik Jörntell; Jeffrey W Dalley; Tahl Holtzman
Journal:  PLoS One       Date:  2013-03-04       Impact factor: 3.240

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