Variability and stability of large-scale cortical oscillation patterns

Abstract

Individual differences in brain organization exist at many spatial and temporal scales, contributing to the substantial heterogeneity underlying human thought and behavior. Oscillatory neural activity is crucial for these behaviors, but how such rhythms are expressed across the cortex within and across individuals has not been thoroughly characterized. Combining electroencephalography (EEG) with representational similarity and multivariate classification techniques, we provide a systematic characterization of brain-wide activity across frequency bands and oscillatory features during rest and task performance. Results indicate that oscillatory profiles exhibit sizable group-level correspondences, indicating the presence of common templates of oscillatory organization. At the same time, we observed well-defined subject-specific network profiles that were discernible above and beyond the structure shared across individuals. These individualized patterns were sufficiently stable over time to allow successful classification of individuals several months later. Finally, our findings indicate that the network structure of rhythmic activity varies considerably across distinct oscillatory frequencies and features, suggesting the existence of multiple, parallel information processing streams embedded in distributed electrophysiological activity. Together, these findings affirm the richness of spatiotemporal EEG signals and emphasize the utility of multivariate network analyses for understanding the role of brain oscillations in physiology and behavior.