Intrinsic correlations of electroencephalography rhythms with cerebral hemodynamics during sleep transitions

Mariko Uchida-Ota, Naoki Tanaka, Hiroki Sato, Atsushi Maki

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

To examine the correlation between electroencephalography fluctuations (EEGF) and cerebral hemodynamics during sleep after eliminating influences from cardiovascular activity, we simultaneously measured EEGF, the cerebral hemoglobin concentration change, and mean arterial blood pressure (MAP) during the sleep of healthy human adults. The cerebral hemoglobin concentration change was measured at 88 positions covering the whole head, by optical topography. We extracted the intrinsic correlation between EEGF and the cerebral hemoglobin concentration change without MAP contributions through cross-correlation and partial correlation analyses considering time lags. We found that increases in the power of the alpha rhythm in EEGF were correlated with increases in oxygenated hemoglobin (oxy-Hb) and decreases in deoxygenated hemoglobin (deoxy-Hb) and that increases in the power of the sigma rhythm in EEGF were correlated with decreases in oxy-Hb and increases in deoxy-Hb. The former correlations tended to appear in the transition from sleep stage 2 to sleep stage 1, and the latter correlations tended to appear in the transition from sleep stage 1 to sleep stage 2. The former correlations were found in the inferior frontal and middle temporal gyri and the latter correlations were found in the superior frontal, middle frontal, and angular gyri.

Original languageEnglish
Pages (from-to)357-368
Number of pages12
JournalNeuroImage
Volume42
Issue number1
DOIs
Publication statusPublished - 2008 Aug 1

Keywords

  • Alpha rhythm
  • Cerebral hemodynamics
  • Cross-correlation
  • EEG fluctuation
  • Non-rapid eye movement sleep
  • Partial correlation
  • Sleep spindle

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

Fingerprint Dive into the research topics of 'Intrinsic correlations of electroencephalography rhythms with cerebral hemodynamics during sleep transitions'. Together they form a unique fingerprint.

  • Cite this