Tomoyuki Mizuno1, Tetsuya Takahashi2, Raymond Y Cho3, Mitsuru Kikuchi4, Tetsuhito Murata1, Koichi Takahashi5, Yuji Wada1. 1. Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan. 2. 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. 3. Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. 4. Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan. 5. Department of Informatics, Faculty of Science and Engineering, Kinki University, Higashi-Osaka, Japan.
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. SIGNIFICANCE: 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. 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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 ADpatients 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. SIGNIFICANCE: 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. 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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