Temporospatial components of brain ERPs as biomarkers for Alzheimer's disease

0Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

Abstract

Introduction: Developing biomarkers that distinguish individuals with Alzheimer's disease (AD) from those with normal cognition remains a crucial goal for improving the health of older adults. We investigated adding brain spatial information to temporal event-related potentials (ERPs) to increase AD identification accuracy over temporal ERPs alone. Methods: With two-step principal components analysis, we applied multivariate analyses that incorporated temporal and spatial ERP information from a cognitive task. Discriminant analysis used temporospatial ERP scores to classify participants as belonging to either the AD or healthy control group. Results: Temporospatial ERPs produced a cross-validated area under the curve of 0.84. Adding spatial information through a formal procedure significantly improves classification accuracy. Discussion: A weighted combination of temporospatial ERP markers performs well in detecting AD. Because ERPs are noninvasive and inexpensive, they may be promising biomarkers for AD that can add functional information to other biomarker systems while providing the individual's probability of correct classification.

Cite

CITATION STYLE

APA

Chapman, R. M., Gardner, M. N., Klorman, R., Mapstone, M., Porsteinsson, A. P., Antonsdottir, I. M., & Kamalyan, L. (2018). Temporospatial components of brain ERPs as biomarkers for Alzheimer’s disease. Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 10, 604–614. https://doi.org/10.1016/j.dadm.2018.08.002

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free