title: EEG Synchronization Evaluation: A New Diagnostic Tool for Predicting the Progression of Alzheimer's disease.
abstract: Alzheimer's disease (AD) is known as a leading cause of dementia in elderly persons. It is a chronic neurodegenerative disorder characterized by progressive cognitive dysfunction. AD can disrupt functional connectivity in distributed cortical networks. The S-estimator, which is a measure of multivariate intraregional synchronization, was analyzed in this study. Twenty patients with AD and 20 age-matched controls were tested at baseline and after 1 year to evaluate the potential of synchronization to be a possible marker of AD progression. All the subjects had clinical evaluations and electroencephalography (EEG) at baseline and post 1 year. Hyposynchronization had an important effect in the medial temporal and frontal regions, while there were no significant effects for hypersynchronization. Hypersynchronized clusters changed more slowly with time (P = .067), whereas hyposynchronized clusters changed more quickly (P = .032). Hyposynchronized cluster-averaged S-estimator correlated negatively with progression of AD (r = -0.98769, P = .0103). In conclusion, the present study provides a whole-brain, AD-specific phenotype of temporal coordination in distributed cortical networks, which is an early diagnostic tool for progression of AD.
authors.affiliation: Department of Endocrinology and Metabolism, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
authors.forename: Ran
authors.initials: R
authors.lastname: Yi
authors.affiliation: Department of Endocrinology and Metabolism, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
authors.forename: Xiao-Rong
authors.initials: XR
authors.lastname: Zhan
authors.affiliation: Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
authors.forename: Jing
authors.initials: J
authors.lastname: Tang
authors.affiliation: Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
authors.forename: Li-Ming
authors.initials: LM
authors.lastname: Zhang
authors.affiliation: Department of Endocrinology and Metabolism, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China.
authors.forename: Xiao-Min
authors.initials: XM
authors.lastname: Liu
authors.affiliation: Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China dongqidoctor2010@yeah.net liuxiaomm@sina.com.
authors.forename: Qi
authors.initials: Q
authors.lastname: Dong
mesh_terms: D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000503:physiopathology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D018450:Disease Progression; D004569:Electroencephalography / Q000379:methods*; D058407:Electroencephalography Phase Synchronization; D005260:Female; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000503:physiopathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Alzheimer’s disease; diagnosis; electroencephalography; hypersynchronization; hyposynchronization