Musical improvisation offers an excellent experimental paradigm for the study of real-time human creativity. It involves moment-to-moment decision-making, monitoring of one's performance, and utilizing external feedback to spontaneously create new melodies or variations on a melody. Recent neuroimaging studies have begun to study the brain activity during musical improvisation, aiming to unlock the mystery of human creativity. What brain resources come together and how these are utilized during musical improvisation are not well understood. To help answer these questions, we recorded electroencephalography (EEG) signals from 19 experienced musicians while they played or imagined short isochronous learned melodies and improvised on those learned melodies. These four conditions (Play-Prelearned, Play-Improvised, Imagine-Prelearned, Imagine-Improvised) were randomly interspersed in a total of 300 trials per participant. From the sensor-level EEG, we found that there were power differences in the alpha (8–12 Hz) and beta (13–30 Hz) bands in separate clusters of frontal, parietal, temporal, and occipital electrodes. Using EEG source localization and dipole modeling methods for task-related signals, we identified the locations and network activities of five sources: the left superior frontal gyrus (L SFG), supplementary motor area (SMA), left inferior parietal lobule (L IPL), right dorsolateral prefrontal cortex, and right superior temporal gyrus. During improvisation, the network activity between L SFG, SMA, and L IPL was significantly less than during the prelearned conditions. Our results support the general idea that attenuated cognitive control facilitates the production of creative output.

Generating movement rhythms is known to involve a network of distributed brain regions associated with motor planning, control, execution, and perception of timing for the repertoire of motor actions. What brain areas are bound in the network and how the network activity is modulated by rhythmic complexity have not been completely explored. To contribute to answering these questions, we designed a study in which nine healthy participants performed simple to complex rhythmic finger movement tasks while undergoing simultaneous functional magnetic resonance imaging and electroencephalography (fMRI-EEG) recordings of their brain activity during the tasks and rest. From fMRI blood oxygenation-level dependent (BOLD) measurements, we found that the complexity of rhythms was associated with brain activations in the primary motor cortex (PMC), supplementary motor area (SMA), and cerebellum (Cb), and with network interactions from these cortical regions to the cerebellum. The spectral analysis of single-trial EEG source waveforms at the cortical regions further showed that there were bidirectional interactions between PMC and SMA, and the complexity of rhythms was associated with power spectra and Granger causality spectra in the beta (13–30 Hz) frequency band, not in the alpha (8–12 Hz) and gamma (30–58 Hz) bands. These results provide us new insights into the mechanisms for movement rhythm complexity.