title: Assessment of EEG dynamical complexity in Alzheimer's disease using multiscale entropy.
abstract: OBJECTIVE
  Multiscale entropy (MSE) is a recently proposed entropy-based index of physiological complexity, evaluating signals at multiple temporal scales. To test this method as an aid to elucidating the pathophysiology of Alzheimer's disease (AD), we examined MSE in resting state EEG activity in comparison with traditional EEG analysis.
  
  
  METHODS
  We recorded EEG in medication-free 15 presenile AD patients and 18 age- and sex-matched healthy control (HC) subjects. MSE was calculated for continuous 60-s epochs for each group, concurrently with power analysis.
  
  
  RESULTS
  The MSE results from smaller and larger scales were associated with higher and lower frequencies of relative power, respectively. Group analysis demonstrated that the AD group had less complexity at smaller scales in more frontal areas, consistent with previous findings. In contrast, higher complexity at larger scales was observed across brain areas in AD group and this higher complexity was significantly correlated with cognitive decline.
  
  
  CONCLUSIONS
  MSE measures identified an abnormal complexity profile across different temporal scales and their relation to the severity of AD.
  
  
  CONCLUSIONS
  These findings indicate that entropy-based analytic methods with applied at temporal scales may serve as a complementary approach for characterizing and understanding abnormal cortical dynamics in AD.
authors.affiliation: Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
authors.forename: Tomoyuki
authors.initials: T
authors.lastname: Mizuno
authors.affiliation: Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address: takahash@u-fukui.ac.jp.
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Takahashi
authors.affiliation: Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Raymond Y
authors.initials: RY
authors.lastname: Cho
authors.affiliation: Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Kikuchi
authors.affiliation: Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
authors.forename: Tetsuhito
authors.initials: T
authors.lastname: Murata
authors.affiliation: Department of Informatics, Faculty of Science and Engineering, Kinki University, Higashi-Osaka, Japan.
authors.forename: Koichi
authors.initials: K
authors.lastname: Takahashi
authors.affiliation: Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
authors.forename: Yuji
authors.initials: Y
authors.lastname: Wada
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000503:physiopathology*; D000704:Analysis of Variance; D016022:Case-Control Studies; D004569:Electroencephalography / Q000379:methods; D019277:Entropy; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D013223:Statistics as Topic
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