BACKGROUND: Successful early detection of mild cognitive impairment (MCI) and Alzheimer's disease demands the identification of biomarkers capable of distinguishing individuals with prodromal or early cognitive impairment from healthy aging adults. Many laboratories are engaged in the discovery and validation of a wide array of potential genetic, proteomic, cognitive, and other types of biomarkers. METHODS: This review focuses on the application of quantitative electroencephalography (qEEG) and event-related potential (ERP) technologies as markers of prodromal impairment and early disease progression. It is the aim of this review to critically assess where this field currently stands, as well as future directions for EEG biomarker development. RESULTS: As a neuroimaging tool that is relatively inexpensive, potentially portable, and capable of providing high-density spatial mapping, qEEG offers a noninvasive, rapid, and replicable method for assessing age-related and disease-related neurophysiologic change. CONCLUSIONS: As different signature changes associated with particular stages of disease burden are identified and validated, we anticipate expanded application of qEEG as a reliable and sensitive biomarker(s) of MCI and early Alzheimer's disease.
BACKGROUND: Successful early detection of mild cognitive impairment (MCI) and Alzheimer's disease demands the identification of biomarkers capable of distinguishing individuals with prodromal or early cognitive impairment from healthy aging adults. Many laboratories are engaged in the discovery and validation of a wide array of potential genetic, proteomic, cognitive, and other types of biomarkers. METHODS: This review focuses on the application of quantitative electroencephalography (qEEG) and event-related potential (ERP) technologies as markers of prodromal impairment and early disease progression. It is the aim of this review to critically assess where this field currently stands, as well as future directions for EEG biomarker development. RESULTS: As a neuroimaging tool that is relatively inexpensive, potentially portable, and capable of providing high-density spatial mapping, qEEG offers a noninvasive, rapid, and replicable method for assessing age-related and disease-related neurophysiologic change. CONCLUSIONS: As different signature changes associated with particular stages of disease burden are identified and validated, we anticipate expanded application of qEEG as a reliable and sensitive biomarker(s) of MCI and early Alzheimer's disease.
Authors: Mark R Trusheim; Breon Burgess; Sean Xinghua Hu; Theresa Long; Steven D Averbuch; Aiden A Flynn; Alfons Lieftucht; Abhijit Mazumder; Judy Milloy; Peter M Shaw; David Swank; Jian Wang; Ernst R Berndt; Federico Goodsaid; Michael C Palmer Journal: Nat Rev Drug Discov Date: 2011-10-31 Impact factor: 84.694
Authors: Robert M Chapman; Anton P Porsteinsson; Margaret N Gardner; Mark Mapstone; John W McCrary; Tiffany C Sandoval; Maria D Guillily; Lindsey A Reilly; Elizabeth DeGrush Journal: Curr Alzheimer Res Date: 2013-09 Impact factor: 3.498
Authors: Robert M Chapman; Margaret N Gardner; Mark Mapstone; Rafael Klorman; Anton P Porsteinsson; Haley M Dupree; Inga M Antonsdottir; Lily Kamalyan Journal: Clin Neurophysiol Date: 2016-03-16 Impact factor: 3.708
Authors: Annamaria Painold; Peter Anderer; Anna K Holl; Martin Letmaier; Gerda M Saletu-Zyhlarz; Bernd Saletu; Raphael M Bonelli Journal: J Neural Transm (Vienna) Date: 2010-10-08 Impact factor: 3.575
Authors: Robert M Chapman; Anton P Porsteinsson; Margaret N Gardner; Mark Mapstone; John W McCrary; Tiffany C Sandoval; Maria D Guillily; Elizabeth DeGrush; Lindsey A Reilly Journal: J Alzheimers Dis Date: 2013 Impact factor: 4.472