ArticleCognitive neurodynamics2015
Power spectral density and coherence analysis of Alzheimer's EEG.
Article in Cognitive neurodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 2 of them syntheses that pooled it.
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Who cites it
76 citing papers in PubMed, 2 syntheses or guidelines pooled it, 195 citations in OpenAlex.
- Functional and effective EEG connectivity patterns in Alzheimer's disease and mild cognitive impairment: a systematic review.Frontiers in aging neuroscience · 2025Pooled it
- Systematic Review on Resting-State EEG for Alzheimer's Disease Diagnosis and Progression Assessment.Disease markers · 2018Pooled it
- qEEG and Functional Connectivity as a Translational Bridge Between Humans and Dogs in Epilepsy and Associated Disorders: From Spontaneous Model to Automatic Classification-An Integrative Review.Veterinary sciences · 2026Review
- Transcranial pulse stimulation modulates spectral signatures of Alzheimer's disease in the 3×Tg-AD mouse model.Alzheimer's research & therapy · 2026Article
- Machine learning-based stratification of chagas heart failure severity using ECG power spectral biomarkers.Medical & biological engineering & computing · 2026Article
- Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity.Communications biology · 2026Article
- Decoding the mechanisms of amyloid-β in synaptic toxicity.Journal of Alzheimer's disease : JAD · 2026Review
- Quantitative EEG signatures of power and functional connectivity alterations in Alzheimer's disease and frontotemporal dementia.Scientific reports · 2026Article
- Comparison of electroencephalogram waveforms in older patients with/without dementia after administration of midazolam: a prospective, observational comparative study.Journal of dental anesthesia and pain medicine · 2026Article
- Divergence of cortical neurophysiology across different neurodegenerative disorders compared to healthy ageing.Progress in neurobiology · 2026Article
- Role of Electroencephalographic Biomarkers as Predictors of Post-Stroke Cognitive Outcomes in Patients with Cerebral Infarction: Literature Review.Neuropsychiatric disease and treatment · 2026Review
- Interpretable self-supervised transformers for resting-state EEG analysis in Alzheimer's disease.Frontiers in neuroinformatics · 2026Article
- Fast Interneuron Dysfunction in Laminar Neural Mass Model Reproduces Alzheimer's Oscillatory Biomarkers.Human brain mapping · 2026Article
- Restoring oscillatory dynamics in Alzheimer's disease: A laminar whole-brain model of serotonergic psychedelic effects.Network neuroscience (Cambridge, Mass.) · 2026Article
- EEG biomarkers for Alzheimer's disease: A novel automated pipeline for detecting and monitoring disease progression.Journal of Alzheimer's disease : JAD · 2025Article
- Transparent EEG Analysis: Leveraging Autoencoders, Bi-LSTMs, and SHAP for Improved Neurodegenerative Diseases Detection.Sensors (Basel, Switzerland) · 2025Article
- EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.Scientific reports · 2025Article
- Motor activity in gamma and high gamma bands recorded with a Stentrode from the human motor cortex in two people with ALS.Journal of neural engineering · 2025Article
- Towards predicting posttraumatic stress symptom severity using portable EEG-derived biomarkers.Scientific reports · 2025Article
- Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
16 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer's disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pair-wise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.