EEG Artifact Removal in TMS Studies of Cortical Speech Areas

Research output: Contribution to journalArticle

Researchers

Research units

  • University of Helsinki
  • University of Glasgow

Abstract

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) is commonly applied for studying the effective connectivity of neuronal circuits. The stimulation excites neurons, and the resulting TMS-evoked potentials (TEPs) are recorded with EEG. A serious obstacle in this method is the generation of large muscle artifacts from scalp muscles, especially when frontolateral and temporoparietal, such as speech, areas are stimulated. Here, TMS–EEG data were processed with the signal-space projection and source-informed reconstruction (SSP–SIR) artifact-removal methods to suppress these artifacts. SSP–SIR suppressed muscle artifacts according to the difference in frequency contents of neuronal signals and muscle activity. The effectiveness of SSP–SIR in rejecting muscle artifacts and the degree of excessive attenuation of brain EEG signals were investigated by comparing the processed versions of the recorded TMS–EEG data with simulated data. The calculated individual lead-field matrix describing how the brain signals spread on the cortex were used as simulated data. We conclude that SSP–SIR was effective in suppressing artifacts also when frontolateral and temporoparietal cortical sites were stimulated, but it may have suppressed also the brain signals near the stimulation site. Effective connectivity originating from the speech-related areas may be studied even when speech areas are stimulated at least on the contralateral hemisphere where the signals were not suppressed that much.

Details

Original languageEnglish
JournalBrain Topography
Publication statusPublished - 1 Jan 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Broca’s area, Electroencephalography, Signal-space projection, Source-informed reconstruction, Transcranial magnetic stimulation, Wernicke’s area

Download statistics

No data available

ID: 35590028