Multiple mechanisms link prestimulus neural oscillations to sensory responses

Spontaneous fluctuations of neural activity may explain why sensory responses vary across repeated presentations of the same physical stimulus. To test this hypothesis, we recorded electroencephalography in humans during stimulation with identical visual stimuli and analyzed how prestimulus neural oscillations modulate different stages of sensory processing reflected by distinct components of the event-related potential (ERP). We found that strong prestimulus alpha- and beta-band power resulted in a suppression of early ERP components (C1 and N150) and in an amplification of late components (after 0.4 s), even after controlling for fluctuations in 1/f aperiodic signal and sleepiness. Whereas functional inhibition of sensory processing underlies the reduction of early ERP responses, we found that the modulation of non-zero-mean oscillations (baseline shift) accounted for the amplification of late responses. Distinguishing between these two mechanisms is crucial for understanding how internal brain states modulate the processing of incoming sensory information.

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Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: This information can be found in the Statistical testing section of the Methods and in the Results. In this study we used cluster permutation test (Maris and Oostenveld, 2007) across the dimensions of the data under investigation to determine significant effects while correcting for multiple comparison. We reported the exact p-value of each significant cluster and we illustrated the average t-statistics within significant clusters in the time-frequency plots and topographies in Figures 2-6. Furthermore, we showed the variability of the data as shaded areas in the line plots in Figure 2 and 4 and as error bars in the quantile plots in Figures 3, 5 and 6. In Figure 3-figure supplement 1, we determined significant effects with t-tests and corrected for multiple comparisons using the False-Discovery-Rate (FDR) procedure. We reported the t-statistics and FDR-corrected p-values of this analysis in the Results and in the Supplementary Information.