August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Aperiodic and Periodic EEG predict performance in a double-flash fusion task
Author Affiliations
  • Michele Deodato
    New York University Abu Dhabi
  • David Melcher
    New York University Abu Dhabi
Journal of Vision August 2023, Vol.23, 5054. doi:https://doi.org/10.1167/jov.23.9.5054
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    • Get Citation

      Michele Deodato, David Melcher; Aperiodic and Periodic EEG predict performance in a double-flash fusion task. Journal of Vision 2023;23(9):5054. https://doi.org/10.1167/jov.23.9.5054.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

A longstanding hypothesis, which has received increased interest, posits that occipital alpha EEG oscillations (8-13 Hz) reflect a visual sampling rhythm. This idea has been corroborated by studies showing an association between alpha peak frequency and/or phase and the temporal resolution of perception. However, other recent studies have not replicated this relationship, raising the question of how, and whether, alpha and temporal sampling are related. Visual temporal acuity is commonly estimated with a two-flash fusion task, in which the ability to perceive two consecutive flashes depends on the inter-stimulus interval (ISI). Accuracy for each ISI is fitted with a psychometric function and its point of inflection is considered as an estimate of visual temporal resolution. However, the slope of the psychometric function, which may be highly informative of the amount of noise around the threshold estimate, has tended to be neglected. Here, we acquired EEG from a large sample (n=50) of participants during resting state and the double-flash task. We replicated the negative correlation between resting state peak alpha frequency and threshold. However, when more closely examining the psychophysical curves, we found that this relationship became highly significant only when considering participants with a steeper slope of the psychometric curve. Moreover, the slope was significantly correlated across participants with the aperiodic component of the occipital EEG, usually regarded as an index of the similarity of neural signals to white noise but recently linked to arousal and task engagement. Overall, these results show that periodic activity is related to the threshold while aperiodic EEG activity predicts the psychometric curve slope. These findings provide evidence for a direct relationship between neural noise and perceptual noise in visual temporal processing and suggest that the identification and exclusion of noisy estimates is important for replicating the key finding of the perceptual sampling hypothesis.

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