ArticlePloS one2013
Characterizing Alzheimer's disease severity via resting-awake EEG amplitude modulation analysis.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 28 papers, 2 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The effects of different acetylcholinesterase inhibitors on EEG patterns in patients with Alzheimer's disease: A systematic review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Pooled it
- Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment.Disease markers · 2018Pooled it
- Imbalance in positive and negative acceleration ratio of alpha oscillation in patients with complex regional pain syndrome.Heliyon · 2024Article
- Monitoring Disease Severity of Mild Cognitive Impairment from Single-Channel EEG Data Using Regression Analysis.Sensors (Basel, Switzerland) · 2024Article
- EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs.Sensors (Basel, Switzerland) · 2023Article
- A holo-spectral EEG analysis provides an early detection of cognitive decline and predicts the progression to Alzheimer's disease.Frontiers in aging neuroscience · 2023Article
- Using CNN Saliency Maps and EEG Modulation Spectra for Improved and More Interpretable Machine Learning-Based Alzheimer's Disease Diagnosis.Computational intelligence and neuroscience · 2023Article
- Modulation Spectral Signal Representation for Quality Measurement and Enhancement of Wearable Device Data: A Technical Note.Sensors (Basel, Switzerland) · 2022Review
- A Comprehensive Review of Computer-Aided Diagnosis of Major Mental and Neurological Disorders and Suicide: A Biostatistical Perspective on Data Mining.Diagnostics (Basel, Switzerland) · 2021Review
- Adaptive Filtering for Improved EEG-Based Mental Workload Assessment of Ambulant Users.Frontiers in neuroscience · 2021Article
- Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes.Journal of Alzheimer's disease : JAD · 2021Article
- Variation of functional brain connectivity in epileptic seizures: an EEG analysis with cross-frequency phase synchronization.Cognitive neurodynamics · 2020Article
- Inter-band Bispectral Analysis of EEG Background Activity to Characterize Alzheimer's Disease Continuum.Frontiers in computational neuroscience · 2020Article
- Altered Patterns of Phase Position Connectivity in Default Mode Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment.Frontiers in neuroscience · 2020Article
- EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes.Neurobiology of aging · 2020Article
- Leveraging network analysis to support experts in their analyses of subjects with MCI and AD.Medical & biological engineering & computing · 2019Article
- EEG Window Length Evaluation for the Detection of Alzheimer's Disease over Different Brain Regions.Brain sciences · 2019Article
- Early Electrophysiological Disintegration of Hippocampal Neural Networks in a Novel Locus Coeruleus Tau-Seeding Mouse Model of Alzheimer's Disease.Neural plasticity · 2019Article
- Theta-Gamma Coupling and Working Memory in Alzheimer's Dementia and Mild Cognitive Impairment.Frontiers in aging neuroscience · 2018Article
- The Role of Cognitive Reserve in Alzheimer's Disease and Aging: A Multi-Modal Imaging Review.Journal of Alzheimer's disease : JAD · 2018Review
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Changes in electroencephalography (EEG) amplitude modulations have recently been linked with early-stage Alzheimer's disease (AD). Existing tools available to perform such analysis (e.g., detrended fluctuation analysis), however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD) showed significant differences in amplitude modulations between the three groups. Most notably, i) delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD), ii) delta modulation of the theta band appeared with an increase in severity, and iii) delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer's disease, but also to monitor its progression.
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