Random noise stimulation (tRNS) applied to the dorsolateral prefrontal cortex (DLPFC) enhances fluency and originality in verbal divergent thinking tasks. However, the underlying neural mechanisms of this behavioral change remain unclear. Given that the DLPFC is a key node of the executive control network (ECN) and that creativity is a two-stage process in which the ECN is primarily involved in the final idea selection stage, application of tRNS to this region shall not only result in an increase of originality and flexibility but also in a modulation of EEG activity. To test these assumptions, we collected 256-channel EEG of 40 participants before and after tRNS/sham applied to the DLPFC, during which participants performed two verbal creativity tasks. To assess stimulation-induced connectivity changes and to capture large-scale cortical communication, a source space alpha (8–12 Hz) imaginary coherence was calculated. We found that the tRNS-induced improvements in originality and flexibility were associated with bilateral DLPFC alpha coherence changes. From a large-scale networks perspective, these results suggest that tRNS-induced ECN activity is associated with increased originality and flexibility, potentially by enhancing selectivity in the idea evaluation phase. This study, for the first time, indicates a link between neurophysiological activity and tRNS-induced changes in verbal creativity. Author Summary This study investigates the impact of transcranial random noise stimulation (tRNS) on alpha coherence and the link between neurophysiological and tRNS-induced effects on creativity. Given the dorsolateral prefrontal cortex’s (DLPFC) role in creativity’s final idea selection stage, 40 participants underwent 256-channel EEG recordings immediately before and after tRNS applied to the DLPFC. Using a within-subject design with active and sham tRNS sessions, we found that the tRNS-induced changes in originality and flexibility were linked to changes in alpha coherence in both left and right DLPFCs, analyzed in source space. These results suggest a network-level impact of tRNS on creativity, potentially enhancing executive control network activity for improved idea evaluation and indicate that the effect of tRNS is explained by task-related brain activity.

Learning new motor skills through training, also termed motor learning, is central for everyday life. Current training strategies recommend intensive task-repetitions aimed at inducing local activation of motor areas, associated with changes in oscillation amplitudes (“event-related power”) during training. More recently, another neural mechanism was suggested to influence motor learning: modulation of functional connectivity (FC), that is, how much spatially separated brain regions communicate with each other before and during training. The goal of the present study was to compare the impact of these two neural processing types on motor learning. We measured EEG before, during, and after a finger-tapping task (FTT) in 20 healthy subjects. The results showed that training gain, long-term expertise (i.e., average motor performance), and consolidation were all predicted by whole-brain alpha- and beta-band FC at motor areas, striatum, and mediotemporal lobe (MTL). Local power changes during training did not predict any dependent variable. Thus, network dynamics seem more crucial than local activity for motor sequence learning, and training techniques should attempt to facilitate network interactions rather than local cortical activation. Author Summary Both, local and network processing mechanisms support motor sequence learning. The aim of the present study was to compare the impact of these two processing types on motor learning. We measured EEG before, during, and after a finger-tapping task (FTT) in 20 healthy subjects. The results showed that only network dynamics, measured with functional connectivity, could predict learning, long-term expertise, and consolidation. Conversely, local activity, measured with event-related power decrease, did not predict any dependent measure. Specifically, network interactions of the primary motor area, the striatum, and the medial temporal lobe correlated with learning performance. Therefore, network dynamics seem more crucial than local activity for motor sequence learning and training techniques should facilitate network interactions rather than local cortical activation.