ArticleNeuroImage. Clinical2019
Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.
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 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.
- Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI.NeuroImage. Clinical · 2023Pooled it
- A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy.Brain imaging and behavior · 2022Pooled it
- Age-dependent effects of oxytocin in brain regions enriched with oxytocin receptors.Psychoneuroendocrinology · 2024Trial
- Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- The co-activation patterns of multiple brain regions in Juvenile Myoclonic Epilepsy.Cognitive neurodynamics · 2024Review
- CHANGES IN FUNCTIONAL CONNECTIVITY FOLLOWING INTENSIVE ATTENTION TRAINING IN PATIENTS WITH TRAUMATIC BRAIN INJURY. A PILOT STUDY.Journal of rehabilitation medicine. Clinical communications · 2024Article
- Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy.Korean journal of radiology · 2022Article
- Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy.Human brain mapping · 2022Article
- Dataset of whole-brain resting-state fMRI of 227 young and elderly adults acquired at 3T.Data in brief · 2021Article
- No Alteration Between Intrinsic Connectivity Networks by a Pilot Study on Localized Exposure to the Fourth-Generation Wireless Communication Signals.Frontiers in public health · 2021Article
- Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators.Contrast media & molecular imaging · 2021Article
- Dynamics and Concordance Abnormalities Among Indices of Intrinsic Brain Activity in Individuals With Subjective Cognitive Decline: A Temporal Dynamics Resting-State Functional Magnetic Resonance Imaging Analysis.Frontiers in aging neuroscience · 2020Article
- Altered dynamic effective connectivity of the default mode network in newly diagnosed drug-naïve juvenile myoclonic epilepsy.NeuroImage. Clinical · 2020Article
- Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis.Frontiers in neuroscience · 2019Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeCharacterize the static and dynamic functional connectivity for subjects with juvenile myoclonic epilepsy (JME) using a quantitative data-driven analysis approach.
methodsWhole-brain resting-state functional MRI data were acquired on a 3 T whole-body clinical MRI scanner from 18 subjects clinically diagnosed with JME and 25 healthy control subjects. 2-min sliding-window approach was incorporated in the quantitative data-driven data analysis framework to assess both the dynamic and static functional connectivity in the resting brains. Two-sample t-tests were performed voxel-wise to detect the differences in functional connectivity metrics based on connectivity strength and density.
resultsThe static functional connectivity metrics based on quantitative data-driven analysis of the entire 10-min acquisition window of resting-state functional MRI data revealed significantly enhanced functional connectivity in JME patients in bilateral dorsolateral prefrontal cortex, dorsal striatum, precentral and middle temporal gyri. The dynamic functional connectivity metrics derived by incorporating a 2-min sliding window into quantitative data-driven analysis demonstrated significant hyper dynamic functional connectivity in the dorsolateral prefrontal cortex, middle temporal gyrus and dorsal striatum. Connectivity strength metrics (both static and dynamic) can detect more extensive functional connectivity abnormalities in the resting-state functional networks (RFNs) and depict also larger overlap between static and dynamic functional connectivity results.
conclusionIncorporating a 2-min sliding window into quantitative data-driven analysis of resting-state functional MRI data can reveal additional information on the temporally fluctuating RFNs of the human brain, which indicate that RFNs involving dorsolateral prefrontal cortex have temporal varying hyper dynamic characteristics in JME patients. Assessing dynamic along with static functional connectivity may provide further insights into the abnormal function connectivity underlying the pathological brain functioning in JME.
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