ArticleNeuroImage. Clinical2019
Abnormal dynamic properties of functional connectivity in disorders of consciousness.
Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 59 citations in OpenAlex.
- Both Transcutaneous Auricular Vagus Nerve Stimulation and Great Auricular Nerve Stimulation Modulate Functional and Structural Connectivity of Brainstem Nuclei in Chronic Low Back Pain.Neuromodulation : journal of the International Neuromodulation Society · 2026Trial
- Transcutaneous auricular nerve stimulation modulates the functional connectivity of the descending pain modulation system and reward network in patients with chronic low back pain.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Trial
- Psychedelics and disorders of consciousness: a new frontier in neurotherapeutics.Molecular psychiatry · 2026Review
- Multimodal Assessment of Consciousness with Brain-Computer Interfaces and Artificial Intelligence: From Acquired Brain Injury to Neurodegenerative Disease.Journal of clinical medicine · 2026Review
- Neuroimaging of Disorder of Consciousness: From Brain Network Mechanisms to Clinical Translation.Journal of clinical neurology (Seoul, Korea) · 2026Review
- A dynamical systems framework for precision psychiatry.NPJ digital medicine · 2025Review
- Transition and dynamic reconfiguration in late-life depression based on hidden Markov model.Npj mental health research · 2025Article
- Identification of brain-like complex information architectures in embryonic tissue ofCommunicative & integrative biology · 2025Article
- Revolutionizing treatment for disorders of consciousness: a multidisciplinary review of advancements in deep brain stimulation.Military Medical Research · 2024Review
- Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden markov models.Journal of translational medicine · 2024Article
- Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation.PLoS computational biology · 2024Article
- Neuroimaging in Disorders of Consciousness and Recovery.Physical medicine and rehabilitation clinics of North America · 2024Review
- Article
- Distinct Spectral Profiles of Awake Resting EEG in Disorders of Consciousness: The Role of Frequency and Topography of Oscillations.Brain topography · 2024Article
- Brain state identification and neuromodulation to promote recovery of consciousness.Brain communications · 2024Review
- Deciphering network dysregulations and temporo-spatial dynamics in disorders of consciousness: insights from minimum spanning tree analysis.Frontiers in psychology · 2024Article
- Improved dynamic functional connectivity estimation with an alternating hidden Markov model.Cognitive neurodynamics · 2023Article
- Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness.NeuroImage · 2023Article
- The dynamic functional connectivity fingerprint of high-grade gliomas.Scientific reports · 2023Article
- The lack of temporal brain dynamics asymmetry as a signature of impaired consciousness states.Interface focus · 2023Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to research abnormal functional connectivity (FC) in patients with disorders of consciousness (DOC). However, most studies assumed steady spatial-temporal signal interactions between distinct brain regions during the scan period. The aim of this study was to explore abnormal dynamic functional connectivity (dFC) in DOC patients. After excluding 26 patients' data that failed to meet the requirements of imaging quality, we retained 19 DOC patients (12 with unresponsive wakefulness syndrome and 7 in a minimally conscious state, diagnosed with the Coma Recovery Scale-Revised [CRS-R]) for the dFC analysis. We used the sliding windows approach to construct dFC matrices. Then these matrices were clustered into distinct states using the k-means clustering algorithm. We found that the DOC patients showed decreased dFC in the sensory and somatomotor networks compared with the healthy controls. There were also significant differences in temporal properties, the mean dwell time (MDT) and the number of transitions (NT), between the DOC patients and the healthy controls. In addition, we also used a hidden Markov model (HMM) to test the robustness of the results. With the connectome-based predictive modeling (CPM) approach, we found that the properties of abnormal dynamic network can be used to predict the CRS-R scores of the patients after severe brain injury. These findings may contribute to a better understanding of the abnormal brain networks in DOC patients.
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