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Exploring how local perturbations of cortical activity propagate across the brain network not only helps us understanding causal mechanisms of brain networks, but also offers a network insight into neurobiological mechanisms for transcranial magnetic stimulation (TMS) treatment response. The concurrent combination of TMS and electroencephalography (EEG) enables researchers to track the TMS-evoked activity, defined here as scalp-recorded electrical signals reflecting the brain's response to TMS, with millisecond-level temporal resolution. Based on this technique, we proposed a quantitative framework which combined sparse non-negative matrix factorization and stage-dependent effective connectivity methods to infer the causal pathways in TMS-evoked brain responses. We found that single-pulse TMS firstly induces local activity in the directly stimulated regions (left primary motor cortex, M1), and then propagates to the contralateral hemisphere and other brain regions. Finally, it propagates back from the contralateral region (right M1) to the stimulation region (left M1). This study provides preliminary evidence demonstrating how local perturbations propagate through brain networks to influence various cortical regions, and offers insights into the neural mechanism of TMS-evoked brain responses from a network perspective.
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http://dx.doi.org/10.1371/journal.pcbi.1013316 | DOI Listing |
CNS Neurosci Ther
September 2025
Department of Rehabilitation Medicine, Xuan Wu Hospital, Capital Medical University, Beijing, China.
Objective: To verify the effectiveness of the parietal repetitive transcranial magnetic stimulation (rTMS) and take advantage of TMS-EEG to assess cortical excitability in patients with minimally conscious states (MCS).
Methods: We enrolled 10 MCS patients who received 10 sessions of 10 Hz rTMS on the parietal cortex for 10 consecutive days and then 10 days of sham stimulation after a 14-day wash-out period. The Coma Recovery Scale-Revised (CRS-R) and TMS-EEG were used to assess the levels of consciousness and cortical excitability before and after active and sham stimulation, respectively.
Transcranial magnetic stimulation combined with intracranial EEG (TMS-iEEG) has emerged as a powerful approach for probing the causal organization and dynamics of the human brain. Despite its promise, the presence of TMS-induced artifacts poses significant challenges for accurately characterizing and interpreting evoked neural responses. In this study, we present a practical preprocessing pipeline for single pulse TMS-iEEG data, incorporating key steps of re-referencing, filtering, artifact interpolation, and detrending.
View Article and Find Full Text PDFJ Neural Eng
September 2025
Bioengineering Program, University of Kansas, Lawrence, KS, United States of America.
Functional near-infrared spectroscopy (fNIRS) has emerged as a promising brain imaging tool due to its cost-effectiveness and balance between spatial and temporal resolution. However, its reliance on the 10-20 EEG coordinate system for probe placement introduces potential inaccuracies in cortical localization. Despite concerns regarding its spatial precision, the integration of transcranial magnetic stimulation (TMS) with fNIRS for validating signal localization has not been systematically explored.
View Article and Find Full Text PDFSchizophr Res
August 2025
Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou), Guangzhou 510335, China; School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China. Electronic address:
Background: The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) (TMS-EEG) has become a pivotal tool for investigating neurophysiological mechanisms in schizophrenia (SZ), a disorder marked by pronounced clinical and neurobiological heterogeneity. However, conventional analyses of TMS-EEG data frequently neglect trial-to-trial neural variability, a critical dimension of dynamic brain responses that may reflect core pathophysiological features of SZ.
Methods: The TMS-EEG data and MCCB were collected from 45 SZ patients and 45 healthy controls (HC).