Biomarkers for Alzheimer's disease and mild cognitive impairment: Recent advances in task-based EEG
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Open Access
- 4 February 2026
- journal article
- review article
- Published by SAGE Publications in Journal of Alzheimer’s Disease
- Vol. 110 (1) , 58-73
Abstract
Background: Alzheimer's disease (AD) accounts for the majority of dementia-related disorders among aging populations. Given the irreversible nature of AD, early detection of cognitive impairment is critical for improving prognosis and facilitating timely interventions before individuals meet the clinical criteria for AD. Objective: The objective of this review is to provide a comprehensive summary of recent advances in task-based electroencephalography (EEG), such as using attention and inhibitory control tasks, which has recently emerged as a promising non-invasive biomarker for assessing neurophysiological alterations associated with AD and mild cognitive impairment (MCI). Methods: This systematic review evaluates the efficacy of task-based EEG biomarkers in distinguishing cognitively impaired individuals from those without impairment. A comprehensive literature search was conducted across PubMed, Semantic Scholar, and SpringerLink databases for studies published between 2017 and 2024. Results: Findings indicate consistent neurophysiological alterations in MCI and AD, particularly reductions in event-related potential amplitudes and prolonged latencies, with P3 abnormalities observed in about half of the studies assessing selective attention and inhibitory control. Similarly, a comparable number of studies using working memory tasks report disrupted functional connectivity patterns, increased low-frequency oscillations (delta and theta activity), and reduced fast oscillations (alpha and beta activity). Conclusions: These EEG-based indices demonstrate potential as objective biomarkers for detecting neural alterations associated with cognitive decline in both AD and preclinical dementia stages. Further research is needed to standardize EEG protocols and validate their clinical utility for early diagnosis and disease progression monitoring.Keywords
Funding Information
- AI-Cog DFG (BA 4695/4-1)
- Japan Science and Technology Agency (JPMJMS2237)
- Japan Science and Technology Agency (JPMJPF2101)
- Japan Science and Technology Agency AIP Trilateral AI Research (JPMJCR20G1)
- JSPS KAKENHI (JP22H00544)
- JSPS KAKENHI (JP22H04872)
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