ArticleFrontiers in human neuroscience2017
Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI).
Article in Frontiers in human neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.Schizophrenia bulletin · 2025Article
- Pattern Identification in Patients with Functional Dyspepsia Using Brain-Body Bio-Signals: Protocol of a Clinical Trial for AI Algorithm Development.Journal of clinical medicine · 2025Article
- Lifespan brain age prediction based on multiple EEG oscillatory features and sparse group lasso.Frontiers in aging neuroscience · 2025Article
- Predicting Subject Traits From Brain Spectral Signatures: An Application to Brain Ageing.Human brain mapping · 2024Article
- Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review.Bioengineering (Basel, Switzerland) · 2024Review
- A growth chart of brain function from infancy to adolescence based on EEG.EBioMedicine · 2024Article
- Brain-age estimation with a low-cost EEG-headset: effectiveness and implications for large-scale screening and brain optimization.Frontiers in neuroergonomics · 2024Article
- Multiplexity of human brain oscillations as a personal brain signature.Human brain mapping · 2023Article
- Application of bidirectional long short-term memory network for prediction of cognitive age.Scientific reports · 2023Article
- Unique spatiotemporal fMRI dynamics in the awake mouse brain.Current biology : CB · 2022Article
- Predicting age from resting-state scalp EEG signals with deep convolutional neural networks on TD-brain dataset.Frontiers in aging neuroscience · 2022Article
- Dyconnmap: Dynamic connectome mapping-A neuroimaging python module.Human brain mapping · 2021Article
- Temporal circuit of macroscale dynamic brain activity supports human consciousness.Science advances · 2020Article
- Typical and Aberrant Functional Brain Flexibility: Lifespan Development and Aberrant Organization in Traumatic Brain Injury and Dyslexia.Brain sciences · 2019Article
- Optimization of graph construction can significantly increase the power of structural brain network studies.NeuroImage · 2019Article
- Aberrant MEG multi-frequency phase temporal synchronization predicts conversion from mild cognitive impairment-to-Alzheimer's disease.NeuroImage. Clinical · 2019Article
- Modeling the Switching Behavior of Functional Connectivity Microstates (FCμstates) as a Novel Biomarker for Mild Cognitive Impairment.Frontiers in neuroscience · 2019Article
- How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters.Frontiers in neuroscience · 2018Article
- Eyes-Open and Eyes-Closed Resting States With Opposite Brain Activity in Sensorimotor and Occipital Regions: Multidimensional Evidences From Machine Learning Perspective.Frontiers in human neuroscience · 2018Article
- EEG Microstate Sequences From Different Clustering Algorithms Are Information-Theoretically Invariant.Frontiers in computational neuroscience · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The brain at rest consists of spatially and temporal distributed but functionally connected regions that called intrinsic connectivity networks (ICNs). Resting state electroencephalography (rs-EEG) is a way to characterize brain networks without confounds associated with task EEG such as task difficulty and performance. A novel framework of how to study dynamic functional connectivity under the notion of functional connectivity microstates (FCμstates) and symbolic dynamics is further discussed. Furthermore, we introduced a way to construct a single integrated dynamic functional connectivity graph (IDFCG) that preserves both the strength of the connections between every pair of sensors but also the type of dominant intrinsic coupling modes (DICM). The whole methodology is demonstrated in a significant and unexplored task for EEG which is the definition of an objective Chronnectomic Brain Aged index (CBAI) extracted from resting-state data (
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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.