ArticleNeuroImage. Clinical2015
Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury.
Article in NeuroImage. Clinical, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 81 citations in OpenAlex.
- Correlating Magnetoencephalography, Diffusion Kurtosis Imaging, Biomechanics, and Neuropsychology in American Youth Football.Journal of neurotrauma · 2025Article
- The Use of Magnetoencephalography in the Diagnosis and Monitoring of Mild Traumatic Brain Injuries and Post-Concussion Syndrome.Brain sciences · 2025Review
- A Comparative Neuroimaging Review of Repetitive Head Impacts and Mild Traumatic Brain Injury from Pediatrics to Professionals.Neurotrauma reports · 2025Review
- Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group.Journal of Huntington's disease · 2024Review
- Using normative modeling and machine learning for detecting mild traumatic brain injury from magnetoencephalography data.PLoS computational biology · 2023Article
- Assessing Pediatric Mild Traumatic Brain Injury and Its Recovery Using Resting-State Magnetoencephalography Source Magnitude Imaging and Machine Learning.Journal of neurotrauma · 2023Article
- Network inference from short, noisy, low time-resolution, partial measurements: Application toProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Assessing the Repeatability of Multi-Frequency Multi-Layer Brain Network Topologies Across Alternative Researcher's Choice Paths.Neuroinformatics · 2023Article
- Dynamic Reconfiguration of Dominant Intrinsic Coupling Modes in Elderly at Prodromal Alzheimer's Disease Risk.Advances in experimental medicine and biology · 2023Article
- Dyconnmap: Dynamic connectome mapping-A neuroimaging python module.Human brain mapping · 2021Article
- Alterations in the Magnetoencephalography Default Mode Effective Connectivity following Concussion.AJNR. American journal of neuroradiology · 2021Article
- Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury.Human brain mapping · 2021Article
- Elevated and Slowed EEG Oscillations in Patients with Post-Concussive Syndrome and Chronic Pain Following a Motor Vehicle Collision.Brain sciences · 2021Article
- Magnetoencephalography in the Detection and Characterization of Brain Abnormalities Associated with Traumatic Brain Injury: A Comprehensive Review.Medical sciences (Basel, Switzerland) · 2021Review
- Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents.Brain communications · 2021Article
- A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.Frontiers in neurology · 2020Article
- Typical and Aberrant Functional Brain Flexibility: Lifespan Development and Aberrant Organization in Traumatic Brain Injury and Dyslexia.Brain sciences · 2019Article
- Statistical Significance Assessment of Phase Synchrony in the Presence of Background Couplings: An ECoG Study.Brain topography · 2019Article
- Modeling the Switching Behavior of Functional Connectivity Microstates (FCμstates) as a Novel Biomarker for Mild Cognitive Impairment.Frontiers in neuroscience · 2019Article
- Current trends in biomarker discovery and analysis tools for traumatic brain injury.Journal of biological engineering · 2019Review
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.