Spontaneous network activity accounts for variability in stimulus-induced gamma responses

Gamma range activity in human visual cortex is believed to play a major role in cognitive functions, such as selective attention. Although recent studies have revealed substantial variability in gamma activity, its origins are still unclear. We investigated whether variability in stimulus-induced gamma activity is related to the spontaneous dynamics of resting-state networks using Hidden Markov Modelling. The magnetoencephalogram (MEG) of 15 healthy participants was recorded at rest and while they were performing a task involving a visual stimulus inducing strong, narrow-band gamma activity. Brain states were inferred from the task9s baseline periods and from resting-state recordings, respectively. Our results show how network states are related to the amplitude of stimulus-induced gamma responses. Across trials, we found an association between the amplitude of gamma responses and the brain state occurring immediately prior to stimulus presentation. Strong gamma responses followed a state characterized by prominent delta/theta oscillations in parieto-occipital regions and comparably weak alpha activity. Across subjects, the overall probability of visiting this state in the baseline period, i.e. the individual preference for this state, correlated positively with the amplitude of the trial-averaged gamma response. Remarkably, this relationship persisted when states were inferred from resting-state recordings rather than the task9s baseline. In summary, both within- and across-subject variability in stimulus-induced gamma activity can in part be explained by the ongoing network dynamics. Fast, pre-stimulus modulations of brain states account for differences between trials while stable, individual state preferences account for differences between subjects.