2020
DOI: 10.1016/j.neuroimage.2020.116753
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Spatial suppression in visual motion perception is driven by inhibition: Evidence from MEG gamma oscillations

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Cited by 17 publications
(36 citation statements)
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“…The attenuation of the GR to moving high-contrast circular gratings caused by increasing their motion velocity (from 1.2 to 6.0 °/s) is a robust phenomenon that has been previously described in multiple studies [20][21][22]28,40 . To quantify this attenuation, we have previously introduced the Gamma Suppression Slope (GSS) index 28 .…”
Section: Meg Source Analysismentioning
confidence: 59%
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“…The attenuation of the GR to moving high-contrast circular gratings caused by increasing their motion velocity (from 1.2 to 6.0 °/s) is a robust phenomenon that has been previously described in multiple studies [20][21][22]28,40 . To quantify this attenuation, we have previously introduced the Gamma Suppression Slope (GSS) index 28 .…”
Section: Meg Source Analysismentioning
confidence: 59%
“…The second is the low rank-order consistency of the visual GR power measured in different stimulation conditions. Indeed, in a recent study we report a lack of signi cant correlation between the power of GRs induced by static and fast-moving (6 °/sec) visual gratings 20 , despite a high intra-individual reliability of the GRs to both types of stimuli 21 . In other words, an individual might have a relatively high-power GR in one experimental condition and an average or even low-power GR in another.…”
Section: Introductionmentioning
confidence: 73%
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“…In addition, our modelling approach can be extended to contribute to a better understanding of the origin of MEG and BOLD signals. Examples of MEG datasets that could be used for that purpose are from (Orekhova et al, 2020(Orekhova et al, , 2018, who show gamma power saturation and decay as a function of stimulus velocity, and our own previous work. Better models of gamma may also help in better understanding the relationship between gamma, spiking and BOLD and can constitute the building blocks of models of the BOLD signal (Dahlqvist, Thomsen, Postnov, & Lauritzen, 2019;Takata et al, 2015).…”
Section: Discussionmentioning
confidence: 99%