title: Reliability of resting-state microstate features in electroencephalography.
abstract: BACKGROUND
  Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states ("microstates") that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis.
  
  
  METHODS
  We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach's α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes.
  
  
  RESULTS
  The approach of identifying a single set of "global" microstate maps showed the highest reliability (mean Cronbach's α > 0.8, SEM ≈ 10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach's α > 0.9). All features had high test-retest reliability with 19 and 8 electrodes.
  
  
  CONCLUSIONS
  High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain's neurophysiological health.
authors.affiliation: Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America.
authors.forename: Arjun
authors.initials: A
authors.lastname: Khanna
authors.affiliation: Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America.
authors.forename: Alvaro
authors.initials: A
authors.lastname: Pascual-Leone
authors.affiliation: Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
authors.forename: Faranak
authors.initials: F
authors.lastname: Farzan
mesh_terms: D000328:Adult; D001931:Brain Mapping; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D009482:Neurophysiology; D012146:Rest / Q000502:physiology