Literature DB >> 2357472

Recurring discharge patterns in multiple spike trains. I. Detection.

R D Frostig1, Z Frostig, R M Harper.   

Abstract

We present a procedure to detect recurring discharge patterns in multiple spike trains. Such recurring patterns can include many spikes and involve from three to many spike trains. The pattern detection procedure is based on calculating the exact probability of randomly obtaining each individually recurring pattern. The statistical evaluation is based on the use of 2 x 2 contingency tables and the application of Fisher's exact test. Several simulations are applied to evaluate the method. Findings based on applying the procedure to simultaneously recorded spike and event trains are described in a companion paper (Frostig et al. 1990).

Mesh:

Year:  1990        PMID: 2357472     DOI: 10.1007/bf00205110

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  14 in total

1.  Nerve-impulse patterns: a quantitative display technique for three neurons.

Authors:  D H Perkel; G L Gerstein; M S Smith; W G Tatton
Journal:  Brain Res       Date:  1975-12-19       Impact factor: 3.252

2.  Recurring discharge patterns in multiple spike trains. II. Application in forebrain areas related to cardiac and respiratory control during different sleep-waking states.

Authors:  R D Frostig; R C Frysinger; R M Harper
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

3.  Information trains. The technique and its uses in spike train and network analysis, with examples taken from the nucleus parabrachialis medialis during sleep-waking states.

Authors:  R D Frostig; Z Frostig; R M Harper
Journal:  Brain Res       Date:  1984-11-19       Impact factor: 3.252

4.  The neurochrome. An identity preserving representation of activity patterns from neural populations.

Authors:  W Epping; H van den Boogaard; A Aertsen; J Eggermont; P Johannesma
Journal:  Biol Cybern       Date:  1984       Impact factor: 2.086

Review 5.  Do neurons process information by relative intervals in spike trains?

Authors:  W R Klemm; C J Sherry
Journal:  Neurosci Biobehav Rev       Date:  1982       Impact factor: 8.989

6.  Bursts and recurrences of bursts in the spike trains of spontaneously active striate cortex neurons.

Authors:  C R Legéndy; M Salcman
Journal:  J Neurophysiol       Date:  1985-04       Impact factor: 2.714

7.  Favored patterns in spike trains. II. Application.

Authors:  J E Dayhoff; G L Gerstein
Journal:  J Neurophysiol       Date:  1983-06       Impact factor: 2.714

8.  Favored patterns in spike trains. I. Detection.

Authors:  J E Dayhoff; G L Gerstein
Journal:  J Neurophysiol       Date:  1983-06       Impact factor: 2.714

9.  Stochastic properties of spontaneous unit discharges in somatosensory cortex and mesencephalic reticular formation during sleep-waking states.

Authors:  M Yamamoto; H Nakahama
Journal:  J Neurophysiol       Date:  1983-05       Impact factor: 2.714

10.  The quantification and graphic display of correlations among three spike trains.

Authors:  M Abeles
Journal:  IEEE Trans Biomed Eng       Date:  1983-04       Impact factor: 4.538

View more
  9 in total

1.  Cellular mechanisms contributing to response variability of cortical neurons in vivo.

Authors:  R Azouz; C M Gray
Journal:  J Neurosci       Date:  1999-03-15       Impact factor: 6.167

Review 2.  Conditional modeling and the jitter method of spike resampling.

Authors:  Asohan Amarasingham; Matthew T Harrison; Nicholas G Hatsopoulos; Stuart Geman
Journal:  J Neurophysiol       Date:  2011-10-26       Impact factor: 2.714

3.  Recognition of visual stimuli from multiple neuronal activity in monkey visual cortex.

Authors:  J D Becker; J Krüger
Journal:  Biol Cybern       Date:  1996-04       Impact factor: 2.086

4.  Recurring discharge patterns in multiple spike trains. II. Application in forebrain areas related to cardiac and respiratory control during different sleep-waking states.

Authors:  R D Frostig; R C Frysinger; R M Harper
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

5.  Replay and time compression of recurring spike sequences in the hippocampus.

Authors:  Z Nádasdy; H Hirase; A Czurkó; J Csicsvari; G Buzsáki
Journal:  J Neurosci       Date:  1999-11-01       Impact factor: 6.167

6.  Discovering spike patterns in neuronal responses.

Authors:  Jean-Marc Fellous; Paul H E Tiesinga; Peter J Thomas; Terrence J Sejnowski
Journal:  J Neurosci       Date:  2004-03-24       Impact factor: 6.167

7.  STDP allows fast rate-modulated coding with Poisson-like spike trains.

Authors:  Matthieu Gilson; Timothée Masquelier; Etienne Hugues
Journal:  PLoS Comput Biol       Date:  2011-10-27       Impact factor: 4.475

8.  Detecting multineuronal temporal patterns in parallel spike trains.

Authors:  Kai S Gansel; Wolf Singer
Journal:  Front Neuroinform       Date:  2012-05-22       Impact factor: 4.081

9.  Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains.

Authors:  Timothée Masquelier; Rudy Guyonneau; Simon J Thorpe
Journal:  PLoS One       Date:  2008-01-02       Impact factor: 3.240

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.