Fig. 3: Removing recurrent connections to isolate the stimulated network suppresses late evoked potentials for high-order networks.

A Global mean field power (GMFP) for every stimulated network for model-generated high-density electroencephalography (hd-EEG) data run with both the intact (continuous line) and disconnected (dashed line) structural connectome. Findings show a more pronounced decrease in evoked late responses for high-order networks (LN Limbic Network, SN Salience Network, DAN Dorsal attention network, FPN Frontoparietal Network, DMN Default mode network). B Area under the curve (AUC) differences comparing the simulation run with the intact versus the lesioned structural connectome. The bar plot shows differences across three time windows (1st response: 0−37 ms, 2nd response: 37–78 ms, 3rd response: 78–373 ms). Data are presented as mean values ± standard error of the mean (SEM) (error bars), with individual subject data points overlaid (36 independent subjects, 323 stimulation sessions). A significant reduction in the AUC was found for late responses (78−373 ms) of high-order networks (LN, SN, DAN, FPN, and DMN) compared to low-order networks (Visual Network [VN] and Somatomotor Network [SMN]), indicated by asterisks (*P < 0.05). C Demonstration of the network recurrence-based theory for two representative sessions. Simulations of evoked dynamics are run using the intact (left) and lesioned (right) anatomical connectome. In the latter case, the connections were removed to isolate the stimulated networks for SMN (top) and DMN (bottom). In the case of the low-order network, this virtual dissection does not significantly impact the evoked potentials, while for the high-order network, a substantial reduction or disappearance of evoked components was observed.