Spike-centered jitter can mistake temporal structure

Jonathan Platkiewicz, Eran Stark, Asohan Amarasingham

Research output: Contribution to journalLetterpeer-review

Abstract

Jitter-type spike resamplingmethods are routinely applied in neurophysiology for detecting temporal structure in spike trains (point processes). Several variations have been proposed. The concern has been raised, based on numerical experiments involving Poisson spike processes, that such procedures can be conservative. We study the issue and find it can be resolved by reemphasizing the distinction between spike-centered (basic) jitter and interval jitter. Focusing on spiking processes with no temporal structure, interval jitter generates an exact hypothesis test, guaranteeing valid conclusions. In contrast, such a guarantee is not available for spike-centered jitter. We construct explicit examples in which spikecentered jitter hallucinates temporal structure, in the sense of exaggerated false-positive rates. Finally, we illustrate numerically that Poisson approximations to jitter computations, while computationally efficient, can also result in inaccurate hypothesis tests. We highlight the value of classical statistical frameworks for guiding the design and interpretation of spike resampling methods.

Original languageEnglish
Pages (from-to)783-803
Number of pages21
JournalNeural Computation
Volume29
Issue number3
DOIs
StatePublished - 1 Mar 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Massachusetts Institute of Technology.

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Cognitive Neuroscience

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