The visual cortex produces gamma band echo in response to broadband visual flicker

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Authors

Abstract

The aim of this study is to uncover the network dynamics of the human visual cortex by driving it with a broadband random visual flicker. We here applied a broadband flicker (1–720 Hz) while measuring the MEG and then estimated the temporal response function (TRF) between the visual input and the MEG response. This TRF revealed an early response in the 40–60 Hz gamma range as well as in the 8–12 Hz alpha band. While the gamma band response is novel, the latter has been termed the alpha band perceptual echo. The gamma echo preceded the alpha perceptual echo. The dominant frequency of the gamma echo was subject-specific thereby reflecting the individual dynamical properties of the early visual cortex. To understand the neuronal mechanisms generating the gamma echo, we implemented a pyramidal-interneuron gamma (PING) model that produces gamma oscillations in the presence of constant input currents. Applying a broadband input current mimicking the visual stimulation allowed us to estimate TRF between the input current and the population response (akin to the local field potentials). The TRF revealed a gamma echo that was similar to the one we observed in the MEG data. Our results suggest that the visual gamma echo can be explained by the dynamics of the PING model even in the absence of sustained gamma oscillations.

Bibliographic note

Funding Information: The work was supported by the following funding: James S. McDonnell Foundation, Understanding Human Cognition Collaborative Award, grant number 220020448, www.jsmf.org, to O.J.; the Wellcome Trust Investigator Award in Science, grant number 207550, wellcome.org, to O.J.; Biotechnology and Biological Sciences Research Council, grant BB/R018723/1, bbsrc.ukri. org, to O.J.; Wolfson Research Merit Award, Royal Society, royalsociety.org, to O.J. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2021 Zhigalov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Details

Original languageEnglish
Article numbere1009046
JournalPLoS Computational Biology
Volume17
Issue number6
Publication statusPublished - 1 Jun 2021

Keywords

  • Biology and life sciences, Medicine and health sciences, Physical sciences, Research Article, Research and analysis methods, Social sciences