These metastable dynamics accord with empirical data from multiple imaging modalities, including electrical waves in cortical tissue, sequential spatiotemporal patterns in resting-state MEG data, and large-scale waves in human electrocorticography. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks.
Here we analyze the complex nonlinear dynamics that emerge from modeling large-scale spontaneous neural activity on a whole-brain network derived from human tractography.
Traveling patterns of neuronal activity-brain waves-have been observed across a breadth of neuronal recordings, states of awareness, and species, but their emergence in the human brain lacks a firm understanding.