Evaluation of brain functional states based on projections of electroencephalographic spectral parameters on 2-dimensional canonical space

Seung Hee Won, Hwan Soo Jang, Ho Won Lee, Il Sung Jang, Maan Gee Lee

Research output: Contribution to journalArticlepeer-review

Abstract

Electroencephalographic (EEG) activities reflect the functional state of the brain, but it is difficult to objectively describe functional brain states. Here, we describe two statistical divergence measures, Mahalanobis distance and Hellinger distance of projections to the reference spaces, to evaluate their state-discriminating ability. Last, divergence measures of 30-min segments after caffeine treatment were compared to evaluate the dose- and time-dependent arousal effects of caffeine to the best reference space. EEG was recorded from Sprague-Dawley rats during pre- and post-administration of caffeine. Several two-dimensional reference spaces were constructed from subsets of the normalized 7 relative band powers pooled from the pre-drug period of all recordings for each cortex: two reference spaces from data sets of the frontal and parietal cortex, and four reference spaces from data sets of active wake, slow-wave sleep, paradoxical sleep state, and all states. Sleep-wake states used as test states were plotted onto the reference spaces, and then, two divergence measures were derived to measure state-discriminating ability of each reference space. First, the reference space of the same cortex as test data was better for discriminating test states than another cortical reference space. Second, the one reference space constructed from data of all states was better for discriminating test states than the other reference spaces. Third, divergence measures were well correlated with sleep-wake durations after caffeine administration and showed the temporal trends of caffeine-induced arousal effect. These results suggest that two statistical measures can objectively describe brain functional states and drug-induced states.

Original languageEnglish
Pages (from-to)40-48
Number of pages9
JournalJournal of Neuroscience Methods
Volume211
Issue number1
DOIs
StatePublished - 15 Oct 2012

Keywords

  • Canonical correlation analysis
  • EEG spectral analysis
  • Factor analysis
  • Hellinger distance
  • Mahalanobis distance

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