Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production
Research on the neural basis of language processing has often avoided investigating spoken language production by fear of the electromyographic (EMG) artifacts that articulation induces on the electro-encephalogram (EEG) signal. Indeed, such articulation artifacts are typically much larger than the...
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| Veröffentlicht in: | Neuroinformatics (Totowa, N.J.) N.J.), 2010-06, Vol.8 (2), p.135-150 |
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| creator | Vos, De Maarten Riès, Stephanie Vanderperren, Katrien Vanrumste, Bart Alario, Francois-Xavier Huffel, Van Sabine Burle, Boris |
| description | Research on the neural basis of language processing has often avoided investigating spoken language production by fear of the electromyographic (EMG) artifacts that articulation induces on the electro-encephalogram (EEG) signal. Indeed, such articulation artifacts are typically much larger than the brain signal of interest. Recently, a Blind Source Separation technique based on Canonical Correlation Analysis was proposed to separate tonic muscle artifacts from continuous EEG recordings in epilepsy. In this paper, we show how the same algorithm can be adapted to remove the short EMG bursts due to articulation on every trial. Several analyses indicate that this method accurately attenuates the muscle contamination on the EEG recordings, providing to the neurolinguistic community a powerful tool to investigate the brain processes at play during overt language production. |
| doi_str_mv | 10.1007/s12021-010-9071-0 |
| format | Article |
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Indeed, such articulation artifacts are typically much larger than the brain signal of interest. Recently, a Blind Source Separation technique based on Canonical Correlation Analysis was proposed to separate tonic muscle artifacts from continuous EEG recordings in epilepsy. In this paper, we show how the same algorithm can be adapted to remove the short EMG bursts due to articulation on every trial. 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| ispartof | Neuroinformatics (Totowa, N.J.), 2010-06, Vol.8 (2), p.135-150 |
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| subjects | Adult Algorithms Bioinformatics Biomedical and Life Sciences Biomedicine Brain - physiology Cognitive science Computational Biology/Bioinformatics Computer Appl. in Life Sciences Electroencephalography - methods Electromyography - methods Evoked Potentials Female Humans Language Male Muscle, Skeletal - physiology Neurology Neuroscience Neurosciences Signal Processing, Computer-Assisted Speech - physiology Time Factors Young Adult |
| title | Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production |
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