ArticleCognitive neurodynamics2015
Transition dynamics of EEG-based network microstates during mental arithmetic and resting wakefulness reflects task-related modulations and developmental changes.
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 35 papers.
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35 citing papers in PubMed.
- Age-group differences between young and middle-aged adults in spatiotemporal EEG dynamics revealed by instantaneous frequency microstate analysis.Frontiers in aging neuroscience · 2026Article
- State-base dynamic functional connectivity analysis of fMRI data during facial emotional processing.Brain imaging and behavior · 2025Article
- Emotion Induction Modulates Neural Dynamics Related to the Originality of Ideational Creativity.Human brain mapping · 2025Article
- A New Method for Dynamic Brain Connectivity Analysis Based on Tensor Decomposition in Tinnitus Using High-density Electroencephalogram in Source Domain.Journal of medical signals and sensors · 2025Article
- How well do neural signatures of resting-state EEG detect consciousness? A large-scale clinical study.Human brain mapping · 2024Review
- Atypical instantaneous spatio-temporal patterns of neural dynamics in Alzheimer's disease.Scientific reports · 2024Article
- Evidence for modulation of EEG microstates by mental workload levels and task types.Human brain mapping · 2024Article
- A survey of brain network analysis by electroencephalographic signals.Cognitive neurodynamics · 2022Article
- Dyconnmap: Dynamic connectome mapping-A neuroimaging python module.Human brain mapping · 2021Article
- Graph Analysis of EEG Functional Connectivity Networks During a Letter-Speech Sound Binding Task in Adult Dyslexics.Frontiers in psychology · 2021Article
- EEG source-space synchrostate transitions and Markov modeling in the math-gifted brain during a long-chain reasoning task.Human brain mapping · 2020Article
- Medium- and long-term functional behavior evaluations in an experimental focal ischemic stroke mouse model.Cognitive neurodynamics · 2020Article
- Modeling the Switching Behavior of Functional Connectivity Microstates (FCμstates) as a Novel Biomarker for Mild Cognitive Impairment.Frontiers in neuroscience · 2019Article
- Automated detection of driver fatigue based on EEG signals using gradient boosting decision tree model.Cognitive neurodynamics · 2018Article
- Developmental trends of theta-beta interelectrode power correlation during resting state in normal children.Cognitive neurodynamics · 2018Article
- Arithmetic in the developing brain: A review of brain imaging studies.Developmental cognitive neuroscience · 2018Review
- Measures of entropy and complexity in altered states of consciousness.Cognitive neurodynamics · 2018Article
- Mitigation of stress: new treatment alternatives.Cognitive neurodynamics · 2018Review
- Reduction but no shift in brain activation after arithmetic learning in children: A simultaneous fNIRS-EEG study.Scientific reports · 2018Article
- Network dynamics in the healthy and epileptic developing brain.Network neuroscience (Cambridge, Mass.) · 2018Article
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3 authors.
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Abstract
We studied how maturation influences the organization of functional brain networks engaged during mental calculations and in resting state. Surface EEG measurements from 20 children (8-12 years) and 25 students (21-26 years) were analyzed. Interregional synchronization of brain activity was quantified by means of Phase Lag Index and for various frequency bands. Based on these pairwise estimates of functional connectivity, we formed graphs which were then characterized in terms of local structure [local efficiency (LE)] and overall integration (global efficiency). The overall data analytic scheme was applied twice, in a static and time-varying mode. Our results showed a characteristic trend: functional segregation dominates the network organization of younger brains. Moreover, in childhood, the overall functional network possesses more prominent small-world network characteristics than in early acorrect in xmldulthood in accordance with the Neural Efficiency Hypothesis. The above trends were intensified by the time-varying approach and identified for the whole set of tested frequency bands (from δ to low γ). By mapping the time-indexed connectivity patterns to multivariate timeseries of nodal LE measurements, we carried out an elaborate study of the functional segregation dynamics and demonstrated that the underlying network undergoes transitions between a restricted number of stable states, that can be thought of as "network-level microstates". The rate of these transitions provided a robust marker of developmental and task-induced alterations, that was found to be insensitive to reference montage and independent component analysis denoising.
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