4.1 Article

Non-parametric detection of temporal order across pairwise measurements of time delays

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE
卷 22, 期 1, 页码 5-19

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SPRINGER
DOI: 10.1007/s10827-006-9441-7

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cross correlation; phase offset; temporal-order code; transitivity; additivity

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Neuronal synchronization is often associated with small time delays, and these delays can change as a function of stimulus properties. Investigation of time delays can be cumbersome if the activity of a large number of neurons is recorded simultaneously and neuronal synchronization is measured in a pairwise manner (such as the cross-correlation histograms) because the number of pairwise measurements increases quadratically. Here, a non-parametric statistical test is proposed with which one can investigate (i) the consistency of the delays across a large number of pairwise measurements and (ii) the consistency of the changes in the time delays as a function of experimental conditions. The test can be classified as non-parametric because it takes into account only the directions of the delays and thus, does not make assumptions about the distributions and the variances of the measurement errors.

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