ArticleFrontiers in neuroscience2022
Enhanced temporal complexity of EEG signals in older individuals with high cognitive functions.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- What characterizes the exceptional cognition of superagers? A systematic review of multidomain biomarkers of successful cognitive aging.The Gerontologist · 2026Pooled it
- Explainable Machine Learning Reveals Time-Dependent Cognitive Risk in Minor Neurocognitive Disorder: Implications for Health Promotion and Early Risk Stratification.Biomedicines · 2026Article
- Spectrum and signals of medication-associated cognitive disorder: a comprehensive disproportionality analysis with cross-database validation.Frontiers in pharmacology · 2026Article
- Wavelet Entropy Analysis of EEG Signals During Wake and Sleep in Patients with Alzheimer's Disease: A Pilot Study.Neuropsychiatric disease and treatment · 2026Article
- Screening system for assessing suitability of cognitive behavioral therapy for chronic low back pain.Scientific reports · 2025Article
- Impact of visual distractors in virtual reality environments on sustained attention behavioral performance and EEG characteristics.Frontiers in human neuroscience · 2025Article
- Rewiring the aging brain: exergaming modulates brain complexity in older adults.Frontiers in aging neuroscience · 2025Article
- Structural inequality and temporal brain dynamics across diverse samples.Clinical and translational medicine · 2024Article
- Brain health in diverse settings: How age, demographics and cognition shape brain function.NeuroImage · 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
- Recent trends in multiple metrics and multimodal analysis for neural activity and pupillometry.Frontiers in neurology · 2024Article
- Editorial: Perspectives in brain-network dynamics in computational psychiatry.Frontiers in computational neuroscience · 2023Article
- Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals.Frontiers in aging neuroscience · 2023Article
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8 authors.
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Abstract
Recent studies suggest that the maintenance of cognitive function in the later life of older people is an essential factor contributing to mental wellbeing and physical health. Particularly, the risk of depression, sleep disorders, and Alzheimer's disease significantly increases in patients with mild cognitive impairment. To develop early treatment and prevention strategies for cognitive decline, it is necessary to individually identify the current state of cognitive function since the progression of cognitive decline varies among individuals. Therefore, the development of biomarkers that allow easier measurement of cognitive function in older individuals is relevant for hyperaged societies. One of the methods used to estimate cognitive function focuses on the temporal complexity of electroencephalography (EEG) signals. The characteristics of temporal complexity depend on the time scale, which reflects the range of neuron functional interactions. To capture the dynamics, composed of multiple time scales, multiscale entropy (MSE) analysis is effective for comprehensively assessing the neural activity underlying cognitive function in the brain. Thus, we hypothesized that EEG complexity analysis could serve to assess a wide range of cognitive functions in older adults. To validate our hypothesis, we divided older participants into two groups based on their cognitive function test scores: a high cognitive function group and a low cognitive function group, and applied MSE analysis to the measured EEG data of all participants. The results of the repeated-measures analysis of covariance using age and sex as a covariate in the MSE profile showed a significant difference between the high and low cognitive function groups (
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