Cognitive processes in disorders of consciousness as revealed by EEG time-frequency analyses

Clin Neurophysiol. 2011 Nov;122(11):2177-84. doi: 10.1016/j.clinph.2011.03.004. Epub 2011 Apr 20.

Abstract

Objective: Although behavioral evaluation of awareness in disorders of consciousness is difficult it remains the clinical standard. We believe that the refinement of EEG and analyses techniques would improve our characterization of those patients.

Methods: We focused on cognitive processing in a sample of 12 control subjects, eight vegetative-state patients, and 13 patients in the minimally consciousness state using EEG. We used an 'active paradigm' which asks subjects to follow instructions, specifically to actively count own or other names as compared to passively listening to them. EEG data was then analyzed using an advanced EEG analysis technique.

Results: Results revealed that all groups exhibit a stronger theta-synchronization to their own names when forced to count them. We also observed a delay in theta power in response to targets relative to non-targets when participants were instructed to count their own name.

Conclusion: Active paradigms are able to induce a different oscillatory activity compared to passive paradigms. Differences between controls and the pathologic groups are prominent in the theta- and alpha-band.

Significance: Time-frequency analyses allow to focus on distinct cognitive processes in patients with disorders of consciousness and thereby contribute to a refined understanding of severely brain-injured patients.

Publication types

  • Controlled Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Awareness / physiology
  • Brain Waves / physiology
  • Cognition / physiology*
  • Consciousness / physiology
  • Electroencephalography / methods*
  • Evoked Potentials / physiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Persistent Vegetative State / diagnosis*
  • Persistent Vegetative State / physiopathology*
  • Reaction Time / physiology
  • Signal Processing, Computer-Assisted