On the topochronic map of the human brain dynamics

Large-scale brain activity evolves dynamically over time across multiple time-scales. The structural connectome imposes a spatial network constraint since two structurally connected brain regions are more likely to coordinate their activity. It also imposes a temporal network constraint by virtue of time delays via signal transmission, which has modulatory effects on oscillatory signals. Specifically, the lengths of the structural bundles, their widths, myelination, and the topology of the structural connectome influence the timing of the interactions across the brain network. Together, they define a space-time structure (topochronic map) spanned by connection strengths (space) and signal transmission delays (time), which together establish the deterministic scaffold underlying the evolution of brain dynamics. We introduce a novel in vivo approach for directly measuring functional delays across the whole brain using magneto/electroencephalography and integrating them with the structural connectome derived from magnetic resonance imaging. We developed a map of the functional delays characterizing the connections across the human brain and a map of the corresponding functional velocities. This yields a topochronic map of the human brain dynamics. The functional delays are tightly regulated, with a trend showing, as expected, that larger structural bundles had faster velocities, with the delays varying much less than expected if they only depended upon distance. Then, we estimated the delays from magnetoencephalography (MEG) data in a cohort of multiple sclerosis patients, who have damaged myelin sheaths, and demonstrated that patients showed greater delays across the whole network than a matched control group. Furthermore, within each patient, individual lesioned connections were slowed down more than unaffected ones. Our technique provides a practical approach for estimating functional transmission delays in vivo at the single-subject and single-fiber level and, thus, opens the possibility for novel diagnostic and curative interventions as well as providing empirical, subject-specific constraints to tailor brain models.