Literature DB >> 12706847

Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons.

Dmitriy Aronov1.   

Abstract

Spike train metrics quantify the notion of dissimilarity, or distance, between spike trains and between multineuronal responses (J. Neurophysiol. 76 (1996) 1310, Network 8 (1997) 127). We present a new algorithm for the implementation of a metric based on the timing of individual spikes and on their neurons of origin. This algorithm surpasses the earlier approach in speed by a factor that grows exponentially with the number of neurons, substantially extending the applicability of metric space methods to the study of coding in larger neuronal populations.

Mesh:

Year:  2003        PMID: 12706847     DOI: 10.1016/s0165-0270(03)00006-2

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  9 in total

1.  Temporal and rate code analysis of responses to low-frequency components in the bird's own song by song system neurons.

Authors:  Makoto Fukushima; Peter L Rauske; Daniel Margoliash
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2015-08-30       Impact factor: 1.836

Review 2.  Spike train metrics.

Authors:  Jonathan D Victor
Journal:  Curr Opin Neurobiol       Date:  2005-10       Impact factor: 6.627

3.  Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments.

Authors:  Jonathan D Victor; David H Goldberg; Daniel Gardner
Journal:  J Neurosci Methods       Date:  2006-12-15       Impact factor: 2.390

4.  A new multineuron spike train metric.

Authors:  Conor Houghton; Kamal Sen
Journal:  Neural Comput       Date:  2008-06       Impact factor: 2.026

5.  Spike train analysis toolkit: enabling wider application of information-theoretic techniques to neurophysiology.

Authors:  David H Goldberg; Jonathan D Victor; Esther P Gardner; Daniel Gardner
Journal:  Neuroinformatics       Date:  2009-05-28

6.  Approaches to Information-Theoretic Analysis of Neural Activity.

Authors:  Jonathan D Victor
Journal:  Biol Theory       Date:  2006

7.  An information-geometric framework for statistical inferences in the neural spike train space.

Authors:  Wei Wu; Anuj Srivastava
Journal:  J Comput Neurosci       Date:  2011-05-17       Impact factor: 1.621

8.  Estimating summary statistics in the spike-train space.

Authors:  Wei Wu; Anuj Srivastava
Journal:  J Comput Neurosci       Date:  2012-10-05       Impact factor: 1.621

9.  A novel, jitter-based method for detecting and measuring spike synchrony and quantifying temporal firing precision.

Authors:  Ariel Agmon
Journal:  Neural Syst Circuits       Date:  2012-05-02
  9 in total

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