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Updated: Jun 16, 2025

Combined Transcranial Magnetic Stimulation and Electroencephalography of the Dorsolateral Prefrontal Cortex
Published on: August 17, 2018
Quantifying task-locked information transmission between cortical areas with TMS-EEG
Zhaohuan Ding1, Wenbo Ma2, Leixiao Feng3
1Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou 510640, China.
Objective:
This study aims to develop TMS-EEG (Transcranial magnetic stimulation combined with EEG) technology to detect task-locked neural network activation and dynamically quantify information transmission.
Approach:
30 participants performed visually guided gap saccade tasks while TMS-EEG data were recorded, with the TMS pulses delivered to prefrontal cortex (PFC) and posterior parietal cortex (PPC) at different task stages. The directed transfer function (DTF) method was applied to TMS-EEG data to indicate the information flow. By analyzing the channel combinations associated with the PFC and PPC, we calculated differences in information flow within the alpha, beta, and gamma frequency bands to determine whether TMS-EEG could quantitatively characterize the direction of information flow between cortical areas.
Main Results:
Analysis of eye tracker data revealed that all participants successfully performed the saccade task, with a correct rate exceeding 90 %. The mean saccade latency was 132.25 ± 22.59 ms after target appearance. Stimulation of the PFC and PPC revealed significant differences in information flow in the gamma bands at different time points. Specifically, during the preparatory period, the C3 electrode acts as a hub for incoming information from O1, later transitioning to send information towards F4 and O1 post-target. Then, P3 emerges as a hub, sending data towards P4, with connectivity between them intensifying post 100 ms from the target's appearance.
Significance:
This study utilized DTF values derived from TMS-EEG to characterize information flow between cortical areas during the gap saccade task. This approach provides a novel method for quantifying dynamic changes in connectivity and causality between cortical areas during task processing.
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