Publication
The relation between brain functional activity and the underlying structure is complex and varies depending on the specific brain region. Recently, we used graph signal processing to introduce the structural-decoupling index (SDI), a novel metric quantifying structure-function coupling in brain regions, based on graph spectral filtering of functional activity. At slow temporal scales accessible with resting-state functional magnetic resonance imaging, the SDI showed a meaningful spatial gradient from unimodal (more coupled) to transmodal regions (more liberal). It also showed to perform very well for brain fingerprinting; i.e., individuals could be classified with near perfect accuracy based on their SDI. Here, we investigate structure-function coupling at faster temporal scales and its specificity to individuals, by means of resting-state magnetoencephalography (MEG) of 84 healthy subjects. We found that the MEG SDI forms a cortical gradient from task-positive regions, more coupled, to task-negative regions, highly decoupled. Great specificity of the SDI to individuals was confirmed, with largest subject classification accuracies in the beta and alpha bands. We conclude that structure-function coupling changes across temporal scales of investigation and provides rich signatures of individual brain organization at rest.