Abstract
Fine-grained understanding of dynamics in cortical networks is crucial in unpacking brain function. Here, we introduce a novel analytical method to characterize the dynamic interaction between distant brain regions, and apply it to data from the Human Connectome Project.
Resting-state fMRI results in time series recordings of the activity of different brain regions, which are aperiodic and lacking a base frequency. Cyclicity Analysis, a novel technique robust with respect to time-reparametrizations, is effective in recovering temporal ordering of such time series along a circular trajectory without assuming any time-scale. Our analysis detected slow cortical waves of activity propagating across the brain with consistent lead-lag relationships between specific brain regions. We also observed short bursts of task-modulated strong temporal ordering that dominate overall lead-lag relationships between pairs of regions in the brain. Our results suggest the possible role played by slow waves of information transmission between brain regions that underlie emergent cognitive function.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
edited for clarity