ArticleBioengineering (Basel, Switzerland)2022
Weighted Brain Network Analysis on Different Stages of Clinical Cognitive Decline.
Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 16 citations in OpenAlex.
- Functional and effective EEG connectivity patterns in Alzheimer's disease and mild cognitive impairment: a systematic review.Frontiers in aging neuroscience · 2025Pooled it
- The Importance of Subjective Cognitive Decline Recognition and the Potential of Molecular and Neurophysiological Biomarkers-A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Brain network analysis for the discrimination of dementia disorders using electrophysiology signals: A systematic review.Frontiers in aging neuroscience · 2023Pooled it
- Subjective cognitive decline in major depressive patients is associated with altered entropy and connectivity changes of temporal and insular region.Translational psychiatry · 2025Article
- Long-term risk of late-life depression in widowed elderly: a five-year follow-up study.BMC geriatrics · 2025Article
- Ten-words recall test: an effective tool to differentiate mild cognitive impairment from subjective cognitive decline.Frontiers in psychiatry · 2024Article
- ETMT: A Tool for Eye-Tracking-Based Trail-Making Test to Detect Cognitive Impairment.Sensors (Basel, Switzerland) · 2023Article
- Learning Causal Biological Networks with Parallel Ant Colony Optimization Algorithm.Bioengineering (Basel, Switzerland) · 2023Article
- Using shallow neural networks with functional connectivity from EEG signals for early diagnosis of Alzheimer's and frontotemporal dementia.Frontiers in neurology · 2023Article
- Electroencephalographic complexity and cognitive decline: Insights from approximate entropy across aging and dementia.Alzheimer's & dementia (New York, N. Y.)Article
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
This study addresses brain network analysis over different clinical severity stages of cognitive dysfunction using electroencephalography (EEG). We exploit EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients and Alzheimer's disease (AD) patients. We propose a new framework to study the topological networks with a spatiotemporal entropy measure for estimating the connectivity. Our results show that functional connectivity and graph analysis are frequency-band dependent, and alterations start at the MCI stage. In delta, the SCI group exhibited a decrease of clustering coefficient and an increase of path length compared to MCI and AD. In alpha, the opposite behavior appeared, suggesting a rapid and high efficiency in information transmission across the SCI network. Modularity analysis showed that electrodes of the same brain region were distributed over several modules, and some obtained modules in SCI were extended from anterior to posterior regions. These results demonstrate that the SCI network was more resilient to neuronal damage compared to that of MCI and even more compared to that of AD. Finally, we confirm that MCI is a transitional stage between SCI and AD, with a predominance of high-strength intrinsic connectivity, which may reflect the compensatory response to the neuronal damage occurring early in the disease process.
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