ArticleAlzheimer's research & therapy2024
EEG biomarkers in Alzheimer's and prodromal Alzheimer's: a comprehensive analysis of spectral and connectivity features.
Article in Alzheimer's research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Electroencephalography in Subjective Cognitive Decline and Mild Cognitive Impairment: Systematic Review of Biomarkers, Classification, and Prognostic Evidence.Journal of medical Internet research · 2026Pooled it
- Effects of 40-Hz transcranial alternating current stimulation on cognition and neural markers in Alzheimer's disease: a randomized, sham-controlled trial.Alzheimer's research & therapy · 2026Trial
- The AHEPA EEG benchmark: setting the standard for machine learning in dementia diagnosis, a scoping review.Cognitive neurodynamics · 2026Article
- Electroencephalography Functional Network Responses to Immersive Virtual Reality in Alzheimer Disease and Mild Cognitive Impairment: Exploratory Single-Session 3-Group Repeated-Measures Study.JMIR serious games · 2026Article
- Technical system of electroencephalography-based brain-computer interface: Advances, applications, and challenges.Neural regeneration research · 2026Article
- Microglia-specific NLRP3 inhibition mitigates hippocampal neuroinflammation and cognitive deficits after hemorrhagic shock with resuscitation.Behavioral and brain functions : BBF · 2026Article
- EEG biomarkers can predict early-stage Alzheimer's disease and correlate with intracerebral pathology: a multimodal machine learning study.Alzheimer's research & therapy · 2026Article
- From brain waves to heartbeats: Exploring the combined role of electroencephalography and heart-rate variability in Alzheimer's disease diagnosis and management.Journal of Alzheimer's disease : JAD · 2026Review
- Restoration of gamma center frequency via personalized entrainment marks cognitive preservation in early Alzheimer's disease.GeroScience · 2026Article
- A deep-SVM hybrid framework with enhanced EEG feature engineering and SHAP-based explainability for Alzheimer's classification.Scientific reports · 2026Article
- Quantitative EEG signatures of power and functional connectivity alterations in Alzheimer's disease and frontotemporal dementia.Scientific reports · 2026Article
- Interpretable Feature-Transformer Framework for Cross-Subject MCI Detection Using Nonlinear Dynamical and Graph-Theoretic EEG Features.Research square · 2026Article
- Multi-dimensional EEG analysis reveals distinct neurophysiological patterns in Alzheimer's and frontotemporal dementia.Journal of neuroengineering and rehabilitation · 2026Article
- Alterations in Multidimensional Functional Connectivity Architecture in Preschool Children with Autism Spectrum Disorder.Brain sciences · 2026Article
- Beyond single-modality screening: toward an EEG-IoT dual-stream framework for early detection of mild cognitive impairment in community-dwelling older adults.Frontiers in aging neuroscience · 2026Article
- Restoring oscillatory dynamics in Alzheimer's disease: A laminar whole-brain model of serotonergic psychedelic effects.Network neuroscience (Cambridge, Mass.) · 2026Article
- The use of electroencephalography in neurodegenerative disease and its utility in dementia.NPJ dementia · 2026Review
- ScaleSpecter: a frequency-aware multi-scale patch framework for robust physiological classification under non-stationarity.Frontiers in human neuroscience · 2026Article
- Dissecting neuronal circuit function and dysfunction in Alzheimer's disease mouse models: from conventional calcium imaging analysis to machine learning-based approaches.Frontiers in aging neuroscience · 2026Review
- Fast Interneuron Dysfunction in Laminar Neural Mass Model Reproduces Alzheimer's Oscillatory Biomarkers.Human brain mapping · 2026Article
Corrections and comments
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11 authors.
Funding
Abstract
backgroundBiomarkers of Alzheimer's disease (AD) and mild cognitive impairment (MCI, or prodromal AD) are highly significant for early diagnosis, clinical trials and treatment outcome evaluations. Electroencephalography (EEG), being noninvasive and easily accessible, has recently been the center of focus. However, a comprehensive understanding of EEG in dementia is still needed. A primary objective of this study is to investigate which of the many EEG characteristics could effectively differentiate between individuals with AD or prodromal AD and healthy individuals.
methodsWe collected resting state EEG data from individuals with AD, prodromal AD, and normal cognition. Two distinct preprocessing pipelines were employed to study the reliability of the extracted measures across different datasets. We extracted 41 different EEG features. We have also developed a stand-alone software application package, Feature Analyzer, as a comprehensive toolbox for EEG analysis. This tool allows users to extract 41 EEG features spanning various domains, including complexity measures, wavelet features, spectral power ratios, and entropy measures. We performed statistical tests to investigate the differences in AD or prodromal AD from age-matched cognitively normal individuals based on the extracted EEG features, power spectral density (PSD), and EEG functional connectivity.
resultsSpectral power ratio measures such as theta/alpha and theta/beta power ratios showed significant differences between cognitively normal and AD individuals. Theta power was higher in AD, suggesting a slowing of oscillations in AD; however, the functional connectivity of the theta band was decreased in AD individuals. In contrast, we observed increased gamma/alpha power ratio, gamma power, and gamma functional connectivity in prodromal AD. Entropy and complexity measures after correcting for multiple electrode comparisons did not show differences in AD or prodromal AD groups. We thus catalogued AD and prodromal AD-specific EEG features.
conclusionsOur findings reveal that the changes in power and connectivity in certain frequency bands of EEG differ in prodromal AD and AD. The spectral power, power ratios, and the functional connectivity of theta and gamma could be biomarkers for diagnosis of AD and prodromal AD, measure the treatment outcome, and possibly a target for brain stimulation.
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