Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Neuroinformatics
Erschienen in: Neuroinformatics 2/2010

01.06.2010

Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production

verfasst von: De Maarten Vos, Stephanie Riès, Katrien Vanderperren, Bart Vanrumste, Francois-Xavier Alario, Van Sabine Huffel, Boris Burle

Erschienen in: Neuroinformatics | Ausgabe 2/2010

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

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.
Vorheriger Artikel iqr: A Tool for the Construction of Multi-level Simulations of Brain and Behaviour

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
Similar applications of BSS-CCA to other signals can be found in Hardoon et al. (2004), De Vos et al. (2007).
 
2
We use (:) to denote that all channels are involved.
 
Literatur
Alario, F.-X., & Ferrand, L. (1999). A set of 400 pictures standardized for french: Norms for name agreement, image agreement, familiarity, visual complexity, image variability, and age of acquisition. Behavior Research Methods, Instruments & Computers, 31(3), 531–552.
Alario, F.-X., Ferrand, L., Laganaro, M., New, B., Frauenfelder, U. H., & Segui, J. (2004). Predictors of picture naming speed. Behavior Research Methods Instruments & Computers, 36, 140–155.
Borga, M., & Knutsson, H. (2001). A canonical correlation approach to blind source separation. Tech. Rep. LiU-IMT-EX-0062, Dept. of Biomedical Engineering, Linköping University, Sweden.
Brooker, B. H., & Donald, M. W. (1980). Contribution of the speech musculature to apparent human eeg asymmetries prior to vocalization. Brain and Language, 9, 226–245.CrossRefPubMed
Chan, A., Englehart, K., Hudgins, B., & Lovely, D. (2002). Hidden markov model classification of myoelectric signals in speech. IEEE Engineering in Medicine and Biology Magazine, 21, 143–146.CrossRefPubMed
Comon, P. (1994). Independent component analysis, a new concept? Signal Process, 36, 287–314.CrossRef
Comon, P., & Jutten, C. (2010). Handbook of blind source separation, independent component analysis and applications. Academic Press.
Conway, B. A., Halliday, D. M., Farmer, S. F., Shahani, U., Maas, P., Weir, A. I., et al. (1995). Synchronization between motor cortex and spinal motoneuronal pool during the performance of a maintained motor task in man. Journal of Physiology (London), 489(3), 917–924.
Crespo-Garcia, M., Atienza, M., & Cantero, J. (2008). Muscle artifact removal from human sleep EEG by using independent component analysis. Journal of Biomedical Engineering, 36, 467–475.CrossRef
De Clercq, W., Vergult, A., Vanrumste, B., Van Paesschen, W., & Van Huffel, S. (2006). Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram. IEEE Transactions on Biomedical Engineering, 53, 2583–2587.CrossRefPubMed
De Vos, M., Laudadio, T., Simonetti, A., Heerschap, A., & Van Huffel, S. (2007). Fast nosologic imaging of the brain. Journal of Magnetic Resonance, 184, 292–301.CrossRefPubMed
Friedman, B. H., & Thayer, J. F. (1991). Facial muscle activity and eeg recordings: Redundancy analysis. Electroencephalography and clinical Neurophysiology, 79, 358–360.
Friman, O., Cedefamn, J., Lundberg, P., Borga, M., & Knutsson, H. (2001). Detection of neural activity in functional MRI using canonical correlation analysis. Magnetic Resonance in Medicine, 45, 323–330.CrossRefPubMed
Ganushchak, L. Y., & Schiller, N. O. (2008). Motivation and semantic context affect brain error-monitoring activity: An event-related brain potentials study. NeuroImage, 39, 395–405.CrossRefPubMed
Golub, G., Van Loan, C. F. (1996). Matrix computations (3rd ed.). Baltimore: John Hopkins University Press.
Goncharova, I. I., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2003). Emg contamination of eeg: Spectral and topographical characteristics. Clinical Neurophysiology, 114(9), 1580–1593.CrossRefPubMed
Gratton, G., Coles, M., & Donchin, E. (1983). A new method for offline removal of ocular artifacts. Electroencephalography and Clinical Neurophysiology, 55, 468–484.CrossRefPubMed
Hansen, P. C., & Jensen, S. H. (1998). Fir filter representations of reduced-rank noise reduction. IEEE Transactions on Signal Processing, 46, 1737–1741.CrossRef
Hardoon, D., Szedmak, S., & Shawe-Taylor, J. (2004). Canonical correlation analysis: An overview with application to learning methods. Neural Computation, 16, 2639–2664.CrossRefPubMed
Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28, 321–377.
Indefrey, P., & Levelt, W. J. M. (2004). The spatial and temporal signatures of word production components. Cognition, 92(1), 101–144.CrossRefPubMed
Jescheniak, J. D., Schriefers, H., Garrett, M. F., & Friederici, A. D. (2002). Exploring the activation of semantic and phonological codes during speech planning with event-related brain potentials. Journal of Cognitive Neuroscience, 14(6), 951–964.CrossRefPubMed
Jung, T., Makeig, S., Westerfield, M., Townsend, J., Courchesne, E., Sejnowski, T. (2001). Analysis and visualization of single-trial event-related potentials. Human Brain Mapping, 14, 166–85.CrossRefPubMed
Luck, S. L. (2005). An introduction to the event-related potential technique. MIT Press.
Masaki, H., Tanaka, H., Takasawa, N., & Yamazaki, K. (2001). Error-related brain potentials elicited by vocal errors. Neuroreport: For Rapid Communication of Neuroscience Research, 12(9), 1851–1855.
McAdam, D. W., & Whitaker, H. A. (1971). Language production: Electroencephalographic localization in the normal human brain. Science, 172(3982), 499–502.CrossRefPubMed
McMenamin, B., Shackman, A., Maxwell, J., Bachhuber, D., Koppenhaver, A., Greischar, L., et al. (2010). Validation of ica-based myogenic artifact correction for scalp and source-localized EEG. Neuroimage, 49, 2416–2432.CrossRefPubMed
McMenamin, B., Shackman, A., Maxwell, J., Greischar, L., & Davidson, R. (2009). Validation of regression-based myogenic correction techniques for scalp and source-localized EEG. Psychophysiology, 46, 578–592.CrossRefPubMed
Mima, T., & Hallett, M. (1999). Corticomuscular coherence: a review. Journal of Clinical Neurophysiology, 16(6), 501–511.CrossRefPubMed
Morrell, L. K., Huntington, D. A., McAdam, D. W., & Whitaker, H. A. (1971). Electrocortical localization of language production. Science, 174(4016), 1359–1360.CrossRefPubMed
Osterhout, L., McLaughlin, J., & Bersick, M. (1997). Event-related brain potentials and human language. Trends in Cognitive Sciences, 1, 203–209.CrossRef
Protopapas, A. (2007). Checkvocal: A program to facilitate checking the accuracy and response time of vocal responses from dmdx. Behavior Research Methods, 39, 859–862.PubMed
Riès, S., Janssen, N., Dufau, S., Alario, F.-X., & Burle, B. (2010). General purpose monitoring during speech production. Journal of Cognitive Neuroscience (in press).
Shackman, A., McMenamin, B., Slagter, H., Maxwell, J., Greischar, L., & Davidson, R. (2009). Electromyogenic artifacts and electroencephalographic inferences. Brain Topography, 22, 7–12.CrossRefPubMed
Stemmer, B., & Whitaker, H. (2008). Handbook of the neuroscience of language. Academic Press.
Urrestarazu, E., Iriarte, J., Alegre, M., Valencia, M., Viteri, C., & Artieda, J. (2004). Independent component analysis removing artifacts in ictal recordings. Epilepsia, 45(9), 1071–1078.CrossRefPubMed
van Turennout, M., Hagoort, P., & Brown, C. M. (1998). Brain activity during speaking: From syntax to phonology in 40 milliseconds. Science, 280, 572–574.CrossRefPubMed
Vergult, A., De Clercq, W., Palmini, A., Vanrumste, B., Dupont, P., Van Huffel, S., et al. (2007). Improving the interpretation of ictal scalp eeg: Bss-cca algorithm for muscle artifact removal. Epilepsia, 48, 950–958.CrossRefPubMed
Weidong, Z., & Gotman, J. (2004). Removal of emg and ecg artifacts from eeg based on wavelet transform and ica. In 26th annual international conference of the engineering in medicine and biology society (Vol. 1, pp. 392–395).
Whitham, E. M., Pope, K., Fitzgibbon, S. L. T., Clark, C., Loveless, S., Broberg, M. A. W., et al. (2007). Scalp electrical recording during paralysis: Quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG. Clinical Neurophysiology, 118, 1877–1888.CrossRefPubMed
Zarzoso, V., & Comon, P. (2008). Robust independent component analysis for blind source separation and extraction with application in electrocardiography. In 30th annual international conference of the ieee engineering in medicine and biology society (IEEE EMBS ’08) (pp. 3344–3347). Vancouver, Canada.
Metadaten
Titel
Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production
verfasst von
De Maarten Vos
Stephanie Riès
Katrien Vanderperren
Bart Vanrumste
Francois-Xavier Alario
Van Sabine Huffel
Boris Burle
Publikationsdatum
01.06.2010
Verlag
Humana Press Inc
Erschienen in
Neuroinformatics / Ausgabe 2/2010
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI
https://doi.org/10.1007/s12021-010-9071-0

Weitere Artikel der Ausgabe 2/2010

Neuroinformatics 2/2010 Zur Ausgabe

OriginalPaper

Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening

Editorial

Making Connections in the Connectome Era

OriginalPaper

The NIF DISCO Framework: Facilitating Automated Integration of Neuroscience Content on the Web

OriginalPaper

iqr: A Tool for the Construction of Multi-level Simulations of Brain and Behaviour

OriginalPaper

Cellular Dynamic Simulator: An Event Driven Molecular Simulation Environment for Cellular Physiology

Premium Partner

    Bildnachweise