ArticleScientific reports2024
Differentiating neurodegenerative diseases based on EEG complexity.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Aperiodic Neural Activity in Clinical Investigations.The European journal of neuroscience · 2025Pooled it
- An Interpretable Framework for Identifying EEG Spectral Biomarkers of Pathological Brain Aging.Diagnostics (Basel, Switzerland) · 2026Article
- Mechanical Ventilation-Associated Changes in Hippocampal Electroencephalogram: A Cross-Species Study in Humans and Rats.CNS neuroscience & therapeutics · 2026Article
- Early aperiodic EEG changes in preclinical and prodromal Alzheimer's disease.Alzheimer's research & therapy · 2026Article
- The correlation between physical exercise and cognitive function in older adults with cognitive impairment mediated by inhibitory control and possible cognitive processing mechanisms.Frontiers in public health · 2026Article
- From clinical phenotypes to molecular precision: multimodal biomarkers for progressive supranuclear palsy.Frontiers in neuroscience · 2026Review
- Management and Prevention of Neurodegenerative Disorders: Can Antioxidant-Rich Dietary Interventions Help?Antioxidants (Basel, Switzerland) · 2025Review
- The Role of Quantitative EEG in the Diagnosis of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2025Review
- A dual path graph neural network framework for dementia diagnosis.Scientific reports · 2025Article
- Development of Neurodegenerative Disease Diagnosis and Monitoring from Traditional to Digital Biomarkers.Biosensors · 2025Review
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Authors and funding
11 authors.
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Abstract
Neurodegenerative diseases are common causes of impaired mobility and cognition in the elderly. Among them, tauopathies and α-synucleinopathies were considered. The neurodegenerative processes and relative differential diagnosis were addressed through a qEEG non-linear analytic method. Study aims were to test accuracy of the power law exponent β applied to EEG in differentiating neurodegenerative diseases and to explore differences in neuronal connectivity among different neurodegenerative processes based on β. N = 230 patients with a diagnosis of tauopathy or α-synucleinopathy and at least one artifact-free EEG recording were selected. Periodogram was applied to EEG signal epochs from continuous recordings. Power law exponent β was determined by the slope of the signal power spectrum versus frequency in logarithmic scale. A data-driven clustering based on β values was performed to identify independent subgroups. Data-driven clustering based on β differentiated tauopathies (overall lower β values) from α-synucleinopathies (higher β values) with high sensitivity and specificity. Tauopathies also presented lower values in the correlation coefficients matrix among frontal sites of recording. In conclusion, significant differences in β values were found between tauopathies and α-synucleinopathies. Hence, β is proposed as a possible biomarker of differential diagnosis and neuronal connectivity.
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