Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer's disease Albert C. Yang a,b,c , Shuu-Jiun Wang d,e,f , Kuan-Lin Lai e,g , Chia-Fen Tsai a,b , Cheng-Hung Yang a,b , Jen-Ping Hwang a,b , Men-Tzung Lo c , Norden E. Huang c , Chung-Kang Peng h , Jong-Ling Fuh d,e,f, ⁎ a Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan b Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan c Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan d Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan e Division of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan f Institute of Brain Science, National Yang-Ming University, Taipei g Department of Neurology, Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan h Margret and H. A. Rey Institute for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA abstract article info Article history: Received 23 January 2013 Received in revised form 18 July 2013 Accepted 31 July 2013 Available online 13 August 2013 Keywords: Alzheimer's disease Complexity Electroencephalogram Multiscale entropy This study assessed the utility of multiscale entropy (MSE), a complexity analysis of biological signals, to identify changes in dynamics of surface electroencephalogram (EEG) in patients with Alzheimer's disease (AD) that was correlated to cognitive and behavioral dysfunction. A total of 108 AD patients were recruited and their digital EEG recordings were analyzed using MSE methods. We investigate the appropriate parameters and time scale factors for MSE calculation from EEG signals. We then assessed the within-subject consistency of MSE measures in dif- ferent EEG epochs and correlations of MSE measures to cognitive and neuropsychiatric symptoms of AD patients. Increased severity of AD was associated with decreased MSE complexity as measured by short-time scales, and with increased MSE complexity as measured by long-time scales. MSE complexity in EEGs of the temporal and occipitoparietal electrodes correlated significantly with cognitive function. MSE complexity of EEGs in various brain areas was also correlated to subdomains of neuropsychiatric symptoms. MSE analysis revealed abnormal EEG complexity across short- and long-time scales that were correlated to cognitive and neuropsychiatric assessments. The MSE-based EEG complexity analysis may provide a simple and cost-effective method to quantify the severity of cognitive and neuropsychiatric symptoms in AD patients. © 2013 Elsevier Inc. All rights reserved. 1. Introduction Alzheimer's disease (AD) is the most common form of dementia in the elderly population. The number of AD patients worldwide was estimated at 26.6 million in 2006, and is steadily increasing (Brookmeyer et al., 2007). In Taiwan, the prevalence of dementia is estimated to be between 1.7% and 4.3% in adults aged 65 years and older (Fuh and Wang, 2008). Currently, AD is diagnosed as possible or probable if a patient has insidious onset, clear-cut history of worsening of cognition by report or by observa- tion, and cognitive deficit either in amnestic or non-amnestic domains, and the symptoms are severe enough to interfere with the patient's nor- mal daily functioning. However, increasing interest is being directed to de- veloping an objective biomarker that could be used for both AD diagnosis and the assessment of symptom severity. The National Institute on Aging and Alzheimer's Association has proposed a biomarker in the clinical diag- nosis criteria for AD, such as brain amyloid-beta protein deposition or el- evated tau protein in cerebrospinal fluid (McKhann et al., 2011). Enhanced quantitative assessments of AD could therefore offer sub- stantial clinical utility, including the potential to provide a biomarker for AD diagnosis. Such assessments would be especially valuable if they were simple and inexpensive to conduct, as is electro-encephalogram (EEG) monitoring. Previous researchers observed that AD patients exhibit slowing of EEG waves, reduced complexity in EEG signals, and perturbations in EEG synchrony (Dauwels et al., 2011). Briefly, numerous literatures had demonstrated that AD and Mild Cognitive Impairment (MCI) were associated with an increase of power in low frequencies (i.e., delta and theta bands), and a decrease of power in higher frequencies (alpha and beta bands). Studies based on complexity analysis, such as the entropy method, generally showed that AD and MCI had reduced com- plexity compared to controls. Furthermore, the synchrony (i.e., statistical dependency between two signals, such as Pearson's correlation or coher- ence) of resting-state EEG signals of different brain regions may be re- duced in MCI and AD, compared to controls. However, inconsistency of Progress in Neuro-Psychopharmacology & Biological Psychiatry 47 (2013) 52–61 Abbreviations: AD, Alzheimer's disease; BPSD, Behavioral and psychological sysmptoms of dementia; CDR, Clinical dementia rating; EEG, Electroencephalogram; MCI, Mild cognitive impairment; MMSE, Mini-mental state examination; MSE, Multiscale entropy; NPI, Neuropsychiatric inventory. ⁎ Corresponding author at: The Neurological Institute, Taipei Veterans General Hospital, No. 201, Sec 2. Shi-Pai Rd., Taipei 11217, Taiwan. Tel./fax: +886 2 28765215. E-mail address: jlfuh@vghtpe.gov.tw (J.-L. Fuh). 0278-5846/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pnpbp.2013.07.022 Contents lists available at ScienceDirect Progress in Neuro-Psychopharmacology & Biological Psychiatry journal homepage: www.elsevier.com/locate/pnp