title: Identification of scalp EEG circadian variation using a novel correlation sum measure.
abstract: OBJECTIVE
  In this paper, we propose a novel method to determine the circadian variation of scalp electroencephalogram (EEG) in both individual and group levels using a correlation sum measure, quantifying self-similarity of the EEG relative energy across waking epochs.
  
  
  METHODS
  We analysed EEG recordings from central-parietal and occipito-parietal montages in nine healthy subjects undergoing a 72 h ultradian sleep-wake cycle protocol. Each waking epoch (∼ 1 s) of every nap opportunity was decomposed using the wavelet packet transform, and the relative energy for that epoch was calculated in the desired frequency band using the corresponding wavelet coefficients. Then, the resulting set of energy values was resampled randomly to generate different subsets with equal number of elements. The correlation sum of each subset was then calculated over a range of distance thresholds, and the average over all subsets was computed. This average value was finally scaled for each nap opportunity and considered as a new circadian measure.
  
  
  RESULTS
  According to the evaluation results, a clear circadian rhythm was identified in some EEG frequency ranges, particularly in 4-8 Hz and 10-12 Hz. The correlation sum measure not only was able to disclose the circadian rhythm on the group data but also revealed significant circadian variations in most individual cases, as opposed to previous studies only reporting the circadian rhythms on a population of subjects. Compared to a naive measure based on the EEG absolute energy in the frequency band of interest, the proposed measure showed a clear superiority using both individual and group data. Results also suggested that the acrophase (i.e., the peak) of the circadian rhythm in 10-12 Hz occurs close to the core body temperature minimum.
  
  
  CONCLUSIONS
  These results confirm the potential usefulness of the proposed EEG-based measure as a non-invasive circadian marker.
authors.affiliation: Centre for Study and Treatment of Circadian Rhythms, Douglas Mental Health University Institute, McGill University, Montreal, QC, H4H 1R3, Canada.
authors.forename: Ali Shahidi
authors.initials: AS
authors.lastname: Zandi
authors.forename: Philippe
authors.initials: P
authors.lastname: Boudreau
authors.forename: Diane B
authors.initials: DB
authors.lastname: Boivin
authors.forename: Guy A
authors.initials: GA
authors.lastname: Dumont
mesh_terms: D000204:Activity Cycles / Q000502:physiology*; D000328:Adult; D000465:Algorithms; D002540:Cerebral Cortex / Q000502:physiology*; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D015203:Reproducibility of Results; D012535:Scalp / Q000502:physiology; D012680:Sensitivity and Specificity; D012894:Sleep Stages / Q000502:physiology*; D013223:Statistics as Topic