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

@article{Victor2007DynamicPA,
  title={Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments},
  author={Jonathan D. Victor and David H. Goldberg and Daniel Gardner},
  journal={Journal of Neuroscience Methods},
  year={2007},
  volume={161},
  pages={351-360}
}
Cost-based metrics formalize notions of distance, or dissimilarity, between two spike trains, and are applicable to single- and multineuronal responses. As such, these metrics have been used to characterize neural variability and neural coding. By examining the structure of an efficient algorithm [Aronov D, 2003. Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons. J Neurosci Methods 124(2), 175-79] implementing a metric for multineuronal responses… CONTINUE READING
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