ArticleScientific reports2021
Signal complexity indicators of health status in clinical EEG.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Global Trends in Research of Brain-Computer Interfaces in Neuroscience From 2014 to 2023: A Bibliometric Analysis.CNS neuroscience & therapeutics · 2026Review
- A principal component entropy metric for assessing global synchronicity in EEG signals.Scientific reports · 2026Article
- ReHA-Net: a ReVIN-hybrid attention network with multiscale convolution for robust EEG artifact removal in brain-computer interfaces.Scientific reports · 2025Article
- Time-Frequency Domain Analysis of Quantitative Electroencephalography as a Biomarker for Dementia.Diagnostics (Basel, Switzerland) · 2025Review
- Repetitive active and passive cognitive stimulations induce EEG changes in patients with Rett syndrome.Pediatric research · 2025Article
- Astrocytes induce desynchronization and reduce predictability in neuron-astrocyte networks cultured on microelectrode arrays.Royal Society open science · 2024Article
- Sex differences of signal complexity at resting-state functional magnetic resonance imaging and their associations with the estrogen-signaling pathway in the brain.Cognitive neurodynamics · 2024Article
- Article
- Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition.Brain topography · 2023Article
- Multiscale entropy of ADHD children during resting state condition.Cognitive neurodynamics · 2023Article
- Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics.Entropy (Basel, Switzerland) · 2022Article
- Electroencephalography-Based Measures to Understand Meditation and Mindfulness: Bibliometric Scoping Review of Randomized Controlled Trials.Global advances in integrative medicine and healthReview
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain signal variability changes across the lifespan in both health and disease, likely reflecting changes in information processing capacity related to development, aging and neurological disorders. While signal complexity, and multiscale entropy (MSE) in particular, has been proposed as a biomarker for neurological disorders, most observations of altered signal complexity have come from studies comparing patients with few to no comorbidities against healthy controls. In this study, we examined whether MSE of brain signals was distinguishable across patient groups in a large and heterogeneous set of clinical-EEG data. Using a multivariate analysis, we found unique timescale-dependent differences in MSE across various neurological disorders. We also found MSE to differentiate individuals with non-brain comorbidities, suggesting that MSE is sensitive to brain signal changes brought about by metabolic and other non-brain disorders. Such changes were not detectable in the spectral power density of brain signals. Our findings suggest that brain signal complexity may offer complementary information to spectral power about an individual's health status and is a promising avenue for clinical biomarker development.
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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.