• DocumentCode
    3685548
  • Title

    Brain-computer interfacing in amyotrophic lateral sclerosis: Implications of a resting-state EEG analysis

  • Author

    Vinay Jayaram;Natalie Widmann;Christian Förster;Tatiana Fomina;Matthias Hohmann;Jennifer Müller vom Hagen;Matthis Synofzik;Bernhard Schölkopf;Ludger Schöls;Moritz Grosse-Wentrup

  • Author_Institution
    Max Planck Institute for Intelligent Systems, Spemannstr. 38, 72076 Tü
  • fYear
    2015
  • Firstpage
    6979
  • Lastpage
    6982
  • Abstract
    Despite decades of research on EEG-based brain-computer interfaces (BCIs) in patients with amyotrophic lateral sclerosis (ALS), there is still little known about how the disease affects the electromagnetic field of the brain. This may be one reason for the present failure of EEG-based BCI paradigms for completely locked-in ALS patients. In order to help understand this failure, we have recorded resting state data from six ALS patients and thirty-two healthy controls to investigate for group differences. While similar studies have been attempted in the past, none have used high-density EEG or tried to distinguish between physiological and non-physiological sources of the EEG. We find an ALS-specific global increase in gamma power (30-90 Hz) that is not specific to the motor cortex, suggesting that the mechanism behind ALS affects non-motor cortical regions even in the absence of comorbid cognitive deficits.
  • Keywords
    "Electroencephalography","Diseases","Electrodes","Sociology","Statistics","Neurophysiology"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319998
  • Filename
    7319998