Literature DB >> 28737503

Directional connectivity in the EEG is able to discriminate wakefulness from NREM sleep.

G Lioi1, S L Bell, D C Smith, D M Simpson.   

Abstract

A reliable measure of consciousness is of great interest for various clinical applications including sleep studies and the assessment of depth of anaesthesia. A number of measures of consciousness based on the EEG have been proposed in the literature and tested in studies of dreamless sleep, general anaesthesia and disorders of consciousness. However, reliability has remained a persistent challenge. Despite considerable theoretical and experimental effort, the neural mechanisms underlying consciousness remain unclear, but connectivity between brain regions is thought to be disrupted, impairing information flow.
OBJECTIVE: The objective of the current work was to assess directional connectivity between brain regions using directed coherence and propose and assess an index that robustly reflects changes associated with non-REM sleep. APPROACH: We tested the performance on polysomnographic recordings from ten healthy subjects and compared directed coherence (and derived features) with more established measures calculated from EEG spectra. We compared the performance of the different indexes to discriminate the level of consciousness at group and individual level. MAIN
RESULTS: At a group level all EEG measures could significantly discriminate NREM sleep from waking, but there was considerable individual variation. Across all individuals, normalized power, the strength of long-range connections and the direction of functional links strongly correlate with NREM sleep stages over the experimental timeline. At an individual level, of the EEG measures considered, the direction of functional links constitutes the most reliable index of the level of consciousness, highly correlating with the individual experimental time-line of sleep in all subjects. SIGNIFICANCE: Directed coherence provides a promising new means of assessing level of consciousness, firmly based on current physiological understanding of consciousness.

Mesh:

Year:  2017        PMID: 28737503     DOI: 10.1088/1361-6579/aa81b5

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  2 in total

1.  Validation of a new approach for distinguishing anesthetized from awake state in patients using directed transfer function applied to raw EEG.

Authors:  Bjørn E Juel; Luis Romundstad; Johan F Storm; Pål G Larsson
Journal:  J Clin Monit Comput       Date:  2020-10-16       Impact factor: 1.977

2.  A framework to quantify controlled directed interactions in network physiology applied to cognitive function assessment.

Authors:  Faezeh Marzbanrad; Negin Yaghmaie; Herbert F Jelinek
Journal:  Sci Rep       Date:  2020-10-28       Impact factor: 4.379

  2 in total

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