Literature DB >> 21331656

Removal of large muscle artifacts from transcranial magnetic stimulation-evoked EEG by independent component analysis.

Reeta J Korhonen1, Julio C Hernandez-Pavon, Johanna Metsomaa, Hanna Mäki, Risto J Ilmoniemi, Jukka Sarvas.   

Abstract

We present two techniques utilizing independent component analysis (ICA) to remove large muscle artifacts from transcranial magnetic stimulation (TMS)-evoked EEG signals. The first one is a novel semi-automatic technique, called enhanced deflation method (EDM). EDM is a modification of the deflation mode of the FastICA algorithm; with an enhanced independent component search, EDM is an effective tool for removing the large, spiky muscle artifacts. The second technique, called manual method (MaM) makes use of the symmetric mode of FastICA and the artifactual components are visually selected by the user. In order to evaluate the success of the artifact removal methods, four different quality parameters, based on curve comparison and frequency analysis, were studied. The dorsal premotor cortex (dPMC) and Broca's area (BA) were stimulated with TMS. Both methods removed the very large muscle artifacts recorded after stimulation of these brain areas. However, EDM was more stable, less subjective, and thus also faster to use than MaM. Until now, examining lateral areas of the cortex with TMS-EEG has been restricted because of strong muscle artifacts. The methods described here can remove those muscle artifacts, allowing one to study lateral areas of the human brain, e.g., BA, with TMS-EEG.

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Year:  2011        PMID: 21331656     DOI: 10.1007/s11517-011-0748-9

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  20 in total

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  24 in total

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6.  Parietal influence on temporal encoding indexed by simultaneous transcranial magnetic stimulation and electroencephalography.

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9.  Cortical modulation of short-latency TMS-evoked potentials.

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Journal:  Front Hum Neurosci       Date:  2013-01-09       Impact factor: 3.169

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Journal:  PLoS One       Date:  2013-02-27       Impact factor: 3.240

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