ArticleHuman brain mapping2022
Unveiling whole-brain dynamics in normal aging through Hidden Markov Models.
Article in Human brain mapping, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.Human brain mapping · 2026Article
- Dynamic Brain State Alterations in Narcolepsy: A Hidden Markov Model Approach to Thalamocortical Instability and Symptom-Specific Neural Correlates.Brain and behavior · 2026Article
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.bioRxiv : the preprint server for biology · 2025Article
- Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest.GeroScience · 2025Article
- Revealing the Spatial Pattern of Brain Hemodynamic Sensitivity to Healthy Aging through Sparse Dynamic Causal Model.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Altered brain dynamics in post-stroke cognitive and motor dysfunction.Frontiers in aging neuroscience · 2025Article
- Brain activity dynamics after traumatic brain injury indicate increased state transition energy and preference of lower order states.NeuroImage. Clinical · 2025Article
- Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach.Translational psychiatry · 2024Article
- EEG microstate transition cost correlates with task demands.PLoS computational biology · 2024Article
- Controlling target brain regions by optimal selection of input nodes.PLoS computational biology · 2024Article
- Combination of static and dynamic neural imaging features to distinguish sensorineural hearing loss: a machine learning study.Frontiers in neuroscience · 2024Article
- Study of dynamic brain function in irritable bowel syndrome via Hidden Markov Modeling.Frontiers in neuroscience · 2024Article
- The dynamic functional connectivity fingerprint of high-grade gliomas.Scientific reports · 2023Article
- Compensatory Mechanisms in Early Alzheimer's Disease and Clinical Setting: The Need for Novel Neuropsychological Strategies.Journal of Alzheimer's disease reports · 2023Review
- A Hidden Markov Model reveals magnetoencephalography spectral frequency-specific abnormalities of brain state power and phase-coupling in neuropathic pain.Communications biology · 2022Article
- Unveiling whole-brain dynamics in normal aging through Hidden Markov Models.Human brain mapping · 2022Article
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5 authors.
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Abstract
During normal aging, the brain undergoes structural and functional changes. Many studies applied static functional connectivity (FC) analysis on resting state functional magnetic resonance imaging (rs-fMRI) data showing a link between aging and the increase of between-networks connectivity. However, it has been demonstrated that FC is not static but varies over time. By employing the dynamic data-driven approach of Hidden Markov Models, this study aims to investigate how aging is related to specific characteristics of dynamic brain states. Rs-fMRI data of 88 subjects, equally distributed in young and old were analyzed. The best model resulted to be with six states, which we characterized not only in terms of FC and mean BOLD activation, but also uncertainty of the estimates. We found two states were mostly occupied by young subjects, whereas three other states by old subjects. A graph-based analysis revealed a decrease in strength with the increase of age, and an overall more integrated topology of states occupied by old subjects. Indeed, while young subjects tend to cycle in a loop of states characterized by a high segregation of the networks, old subjects' loops feature high integration, with a crucial intermediary role played by the dorsal attention network. These results suggest that the employed mathematical approach captures the complex and rich brain's dynamics underpinning the aging process.
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