ArticleFrontiers in neuroscience2023
Triple-network analysis of Alzheimer's disease based on the energy landscape.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 6 citations in OpenAlex.
- Neuromodulation techniques targeting neurotransmitter dysfunction: Innovation in treatments for Alzheimer's disease.Neural regeneration research · 2026Article
- Whole-Brain Structural Connectivity Alterations in Chronic Subjective Tinnitus: An Exploratory Diffusion Tensor Imaging Study.Brain sciences · 2026Article
- Cortical synchrony is reduced in Alzheimer's disease and relates to arousal state.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Bilateral Angular Gyrus 810-nm Transcranial Near-Infrared Stimulation Reshapes Brain Network: Ameliorate Alzheimer's Disease Cognitive Deficits.BME frontiers · 2026Article
- From microstates to macroscales: A Critical Review of Maximum Entropy Modeling and Energy Landscape Analysis in functional MRI.Research square · 2025Article
- Energy landscape analysis based on the Ising model: Tutorial review.PLOS complex systems · 2025Article
- The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks.Sleep · 2024Article
- Energy landscape analysis of brain network dynamics in Alzheimer's disease.Frontiers in aging neuroscience · 2024Article
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Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Research on the brain activity during resting state has found that brain activation is centered around three networks, including the default mode network (DMN), the salient network (SN), and the central executive network (CEN), and switches between multiple modes. As a common disease in the elderly, Alzheimer's disease (AD) affects the state transitions of functional networks in the resting state. Methods: Energy landscape, as a new method, can intuitively and quickly grasp the statistical distribution of system states and information related to state transition mechanisms. Therefore, this study mainly uses the energy landscape method to study the changes of the triple-network brain dynamics in AD patients in the resting state. Results: AD brain activity patterns are in an abnormal state, and the dynamics of patients with AD tend to be unstable, with an unusually high flexibility in switching between states. Also , the subjects' dynamic features are correlated with clinical index. Discussion: The atypical balance of large-scale brain systems in patients with AD is associated with abnormally active brain dynamics. Our study are helpful for further understanding the intrinsic dynamic characteristics and pathological mechanism of the resting-state brain in AD patients.
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