Literature DB >> 20804383

A fast L(p) spike alignment metric.

Alexander J Dubbs1, Brad A Seiler, Marcelo O Magnasco.   

Abstract

The metrization of the space of neural responses is an ongoing research program seeking to find natural ways to describe, in geometrical terms, the sets of possible activities in the brain. One component of this program is spike metrics-notions of distance between two spike trains recorded from a neuron. Alignment spike metrics work by identifying "equivalent" spikes in both trains. We present an alignment spike metric having L(p) underlying geometrical structure; the L(2) version is Euclidean and is suitable for further embedding in Euclidean spaces by multidimensional scaling methods or related procedures. We show how to implement a fast algorithm for the computation of this metric based on bipartite graph matching theory.

Mesh:

Year:  2010        PMID: 20804383     DOI: 10.1162/NECO_a_00026

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  3 in total

1.  A metric space approach to the information channel capacity of spike trains.

Authors:  James B Gillespie; Conor J Houghton
Journal:  J Comput Neurosci       Date:  2010-10-23       Impact factor: 1.621

2.  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

3.  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

  3 in total

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