Gamma activity is thought to serve several cognitive processes, including attention and memory. Even for the simplest stimulus, the occurrence of gamma activity is highly variable, both within and between individuals. The sources of this variability, however, are largely unknown.
In this paper, we address one possible cause: the cross-frequency influence of spontaneous, whole-brain network activity on visual stimulus processing. By applying Hidden Markov modelling to MEG data, we reveal that the trial-averaged gamma response to a moving grating depends on the individual network dynamics, inferred from slower brain activity (<35 Hz) in the absence of stimulation (resting-state and task baseline). In addition, we demonstrate that modulations of network activity in task baseline influence the gamma response on the level of trials.
In summary, our results reveal a cross-frequency and cross-session association between gamma responses induced by visual stimulation and spontaneous network activity. These findings underline the dependency of visual stimulus processing on the individual, functional network architecture.
