Recurrence analysis of the EEG during sleep accurately identifies subjects with mental health symptoms

David E. McCarty, Naresh M. Punjabi, Paul Y. Kim, Clifton Frilot, Andrew A. Marino

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Analysis of brain recurrence (ABR) is a novel computational method that uses two variables for sleep depth and two for sleep fragmentation to quantify temporal changes in non-random brain electrical activity. We postulated that ABR of the sleep-staged EEG could identify an EEG signature specific for the presence of mental health symptoms. Using the Mental Health Inventory Questionnaire (MHI-5) as ground truth, psychological distress was assessed in a study cohort obtained from the Sleep Heart Health Study. Subjects with MHI-5 <50 (N=34) were matched for sex, BMI, age, and race with 34 subjects who had MHI-5 scores > 50. Sixteen ABR markers derived from the EEG were analyzed using linear discriminant analysis to identify marker combinations that reliably classified individual subjects. A biomarker function computed from 12 of the markers accurately classified the subjects based on their MHI-5 scores (AUROC=82%). Use of additional markers did not improve classification accuracy. Subgroup analysis (20 highest and 20 lowest MHI-5 scores) improved classification accuracy (AUROC=89%). Biomarker values for individual subjects were significantly correlated with MHI-5 score (r=0.36, 0.54 for N=68, 40, respectively). ABR of EEGs obtained during sleep successfully classified subjects with regard to the severity of mental health symptoms, indicating that mood systems were reflected in brain electrical activity.

Original languageEnglish (US)
Pages (from-to)335-340
Number of pages6
JournalPsychiatry Research - Neuroimaging
Issue number3
StatePublished - Mar 21 2014
Externally publishedYes


  • Biomarker
  • Brain recurrence
  • Electroencephalography
  • MHI-5
  • Mental disorders

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Psychiatry and Mental health


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