TY - JOUR
T1 - Metastable brain waves
AU - Roberts, James A.
AU - Gollo, Leonardo L.
AU - Abeysuriya, Romesh G.
AU - Roberts, Gloria
AU - Mitchell, Philip B
AU - Woolrich, Mark W.
AU - Breakspear, Michael
PY - 2019/3/5
Y1 - 2019/3/5
N2 - 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. 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. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. 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. By moving the study of functional networks from a spatially static to an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena across functional neuroimaging modalities and makes specific predictions for further experimentation.
AB - 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. 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. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. 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. By moving the study of functional networks from a spatially static to an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena across functional neuroimaging modalities and makes specific predictions for further experimentation.
KW - cognitive neuroscience
KW - computational neuroscience
UR - http://www.scopus.com/inward/record.url?scp=85062587384&partnerID=8YFLogxK
U2 - 10.1038/s41467-019-08999-0
DO - 10.1038/s41467-019-08999-0
M3 - Article
C2 - 30837462
AN - SCOPUS:85062587384
SN - 2041-1723
VL - 10
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1056
ER -