ArticleFrontiers in computational neuroscience2015
Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes.
Article in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Brain network disintegration as a final common pathway for delirium: a systematic review and qualitative meta-analysis.NeuroImage. Clinical · 2019Pooled it
- High-density EEG network analysis in MCI: an exploratory study of electrode density and cognitive performance.Frontiers in aging neuroscience · 2026Article
- Neurofeedback Training Modulates Brain Functional Networks and Improves Cognition in Amnestic Mild Cognitive Impairment Patients Aged 60-70 Years.Brain sciences · 2025Article
- Type-2 Diabetes Alters Hippocampal Neural Oscillations and Disrupts Synchrony between the Hippocampus and Cortex.Aging and disease · 2024Article
- Resting-state electroencephalographic characteristics related to mild cognitive impairments.Frontiers in psychiatry · 2023Article
- Phase Lag Index of Resting-State EEG for Identification of Mild Cognitive Impairment Patients with Type 2 Diabetes.Brain sciences · 2022Article
- Electroencephalogram microstates and functional connectivity of cybersickness.Frontiers in human neuroscience · 2022Article
- Intelligent Algorithm-Based Quantitative Electroencephalography in Evaluating Cerebral Small Vessel Disease Complicated by Cognitive Impairment.Computational and mathematical methods in medicine · 2022Article
- Exploring Network Properties Across Preclinical Stages of Alzheimer's Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study.Journal of Alzheimer's disease : JAD · 2022Article
- Enhanced temporal complexity of EEG signals in older individuals with high cognitive functions.Frontiers in neuroscience · 2022Article
- Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study.Frontiers in aging neuroscience · 2022Article
- Task aftereffect reorganization of resting state functional brain networks in healthy aging and mild cognitive impairment.Frontiers in aging neuroscience · 2022Article
- Functional brain changes using electroencephalography after a 24-week multidomain intervention program to prevent dementia.Frontiers in aging neuroscience · 2022Article
- Dyconnmap: Dynamic connectome mapping-A neuroimaging python module.Human brain mapping · 2021Article
- Complex networks and deep learning for EEG signal analysis.Cognitive neurodynamics · 2021Review
- A new era for executive function research: On the transition from centralized to distributed executive functioning.Neuroscience and biobehavioral reviews · 2021Review
- Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.Frontiers in computational neuroscience · 2021Article
- A Novel Connectome-Based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer's Disease by Using Resting-State High-Density EEG EGI GES 300.Brain sciences · 2020Article
- EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes.Neurobiology of aging · 2020Article
- Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks.Frontiers in computational neuroscience · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDiabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D).
methodIn this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed.
resultsMain findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band.
conclusionsThe brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track cognitive function of diabetic patients and provide a new diagnosis tool for aMCI.
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