Lasting modulation effects of rTMS on neural activity and connectivity as revealed by resting-state EEG

Abstract

The long-lasting neuromodulatory effects of repetitive transcranial magnetic stimulation (rTMS) are of great interest for therapeutic applications in various neurological and psychiatric disorders, due to which functional connectivity among brain regions is profoundly disturbed. Classic TMS studies selectively alter neural activity in specific brain regions and observe neural activity changes on nonperturbed areas to infer underlying connectivity and its changes. Less has been indicated in direct measures of functional connectivity and/or neural network and on how connectivity/network alterations occur. Here, we developed a novel analysis framework to directly investigate both neural activity and connectivity changes induced by rTMS from resting-state EEG (rsEEG) acquired in a group of subjects with a chronic disorder of imbalance, known as the mal de debarquement syndrome (MdDS). Resting-state activity in multiple functional brain areas was identified through a data-driven blind source separation analysis on rsEEG data, and the connectivity among them was characterized using a phase synchronization measure. Our study revealed that there were significant long-lasting changes in resting-state neural activity, in theta, low alpha, and high alpha bands and neural networks in theta, low alpha, high alpha and beta bands, over broad cortical areas 4 to 5 h after the last application of rTMS in a consecutive five-day protocol. Our results of rsEEG connectivity further indicated that the changes, mainly in the alpha band, over the parietal and occipital cortices from pre- to post-TMS sessions were significantly correlated, in both magnitude and direction, to symptom changes in this group of subjects with MdDS. This connectivity measure not only suggested that rTMS can generate positive treatment effects in MdDS patients, but also revealed new potential targets for future therapeutic trials to improve treatment effects. It is promising that the new connectivity measure from rsEEG can be used to understand the variability in treatment response to rTMS in brain disorders with impaired functional connectivity and, eventually, to determine individually tailored stimulation parameters and treatment procedures in rTMS.

Fig. 1

Block diagram of the analysis process: (a) preprocessing steps from raw rsEEG to artifacts-rejected rsEEG epochs for individual subjects, (b) steps to calculate spatial patterns and spectral dynamics of ICs of interest using a group-level ICA, and (c) group-level analyses examining the effects of rTMS treatment on neural activity and connectivity.

Fig. 2

Summary of VAS score changes over ten subjects.

Fig. 3

Scalp maps of 13 ICs of interest.

Fig. 4

Grand averaged spectral powers of 13 ICs over ten subjects for pre-and post-TMS sessions. Red lines denote the frequency bands of significant power differences (p < 0.05). Solid lines: mean powers; shaded areas: SEM.

Fig. 5

Scatter plots of significant cross-subject correlations between spectral power changes and VAS score changes from pre- to post-TMS sessions: (a) significant correlations in high alpha and beta bands from IC2, and (b) significant correlations in beta band from IC9. Red crosses denote coordinate origins; black lines are regressed lines; and blue, black, and red dots indicate subjects from positive, neutral, and negative groups, respectively.

Fig. 6

Significant ICPCs (p < 0.01, corrected) in the four frequency bands from both pre-TMS (a) and post-TMS (b) sessions.

Fig. 7

Significant ICPC differences (p < 0.05) between pre- and post-TMS sessions identified in (a) theta band, (b) low alpha band, (c) high alpha band, and (d) beta band. Circles mark sensory function related ICs. Dashed lines: reduced connections; solid lines: enhanced connections.

Fig. 8

Significant cross-subject correlations (p < 0.05) between ICPC changes and VAS score changes from pre- to post-TMS sessions in (a) theta, (b) low alpha, and (c) high alpha bands.

Fig. 9

Directions of ICPC changes in subjects from positive (blue dots), neutral (black dots), and negative groups (red dots) using two metrics: 1) x-axis: number of negative significant ICPC changes over total number of significant ICPC changes; 2) y-axis: sum of all significant ICPC changes.