A statistical significance test for spatio-temporal receptive field estimates obtained using spike-triggered averaging of binary pseudo-random sequences

Murat Okatan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Spatio-temporal receptive fields (STRF) of visual neurons are often estimated using spike-triggered averaging of binary pseudo-random stimulus sequences. The spike train of a visual neuron is recorded simultaneously with the stimulus presentation. The neuron’s STRF is estimated by averaging the stimulus frames that coincide with spikes at fixed latencies. Although this is a widely used technique, an analytical method for determining the statistical significance of the estimated value of the STRF pixels seems to be lacking. Such a significance test would be useful for identifying the significant features of the STRF and investigating their relationship with experimental variables. Here, the distribution of the estimated STRF pixel values is derived for given spike trains, under the null hypothesis that spike occurrences and stimulus values are statistically independent. This distribution is then used for computing amplitude thresholds to determine the STRF pixels where the null hypothesis can be rejected at a desired two-tailed significance level. It is also proposed that the size of the receptive field may be inferred from the significant pixels. The application of the proposed method is illustrated on spike trains collected from individual mouse retinal ganglion cells.

Original languageEnglish
Pages (from-to)3759-3766
Number of pages8
JournalSignal, Image and Video Processing
Volume17
Issue number7
DOIs
Publication statusPublished - Oct 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

Keywords

  • Amplitude thresholding
  • Computational neuroscience
  • Extracellular neural recording
  • Sensory neuron
  • Spike train

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