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.

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

“…2) were selected as functional ICNs of interest, given that they best represented previously identified ICs from rs-EEG signals in terms of spatial and spectral patterns (Chen et al, 2013; Ding et al, 2014; Ponomarev et al, 2014; Yuan et al, 2012). Based on their distinct scalp potential maps (Fig.…”

“…To extract functional ICNs, a group-level time-frequency independent component analysis (tfICA) method was applied to disentangle EEG data into different component signals (i.e., ICs) (Ding et al, 2014; Shou et al, 2012), which represent concurrent electrical activities generated from strongly synchronized and spatially organized brain regions (Onton et al, 2006). All steps were shown in Fig.…”

“…1(B). Firstly, preprocessed data from individuals was normalized to z values (to account for inter-subject variations) and temporally concatenated across all subjects, which has been widely used in ICA to identify networked brain activity in group analysis (Chen et al, 2013; Ding et al, 2014; Nugent et al, 2015; Ponomarev et al, 2014; Ramkumar et al, 2014; Yuan et al, 2012), assuming spatial similarity across subjects. Secondly, power spectra in the range of 2 Hz to 30 Hz at a 1 Hz resolution were calculated via a short-time Fourier transform (STFT) on individual 1-s EEG epochs, and then obtained time-frequency EEG (epochs × power spectra) data were decomposed into 32 ICs using tfICA (Bingham and Hyvarinen, 2000; Shou et al, 2012) 1 , after an initial data reduction using principal component analysis (PCA).…”

“…Thereafter, components that represent distinct networked brain activity with distinguished spectral and spatial patterns (Shou and Ding, 2015), were selected as electrophysiological functional ICNs of interest (see the Functional ICNs section). For further details about tfICA, please see Ding et al (2014) and Shou et al (2012).…”

Double-Blind Sham-Controlled Crossover Trial of Repetitive Transcranial Magnetic Stimulation for Mal de Debarquement Syndrome

“…Ding et.al. used a protocol using a combination of 1Hz right and 10Hz left DLPFC stimulation in right-handed participants led to improvement in five out of 10 participants with MdDS (26). These studies point to short-term efficacy of rTMS on rocking dizziness, but none have evaluated long-term improvement in MdDS symptoms with rTMS.…”