ArticleJournal of neurology & neuromedicine2020
Assessing Recovery from Mild Traumatic Brain Injury (Mtbi) using Magnetoencephalography (MEG): An Application of the Synchronous Neural Interactions (SNI) Test.
Article in Journal of neurology & neuromedicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The Use of Magnetoencephalography in the Diagnosis and Monitoring of Mild Traumatic Brain Injuries and Post-Concussion Syndrome.Brain sciences · 2025Review
- Using normative modeling and machine learning for detecting mild traumatic brain injury from magnetoencephalography data.PLoS computational biology · 2023Article
- Dependence of cognitive ability on synchronous neural interactions determined by magnetoencephalography.Journal of neurophysiology · 2023Article
- Classification of posttraumatic stress disorder and related outcomes in women veterans using magnetoencephalography.Experimental brain research · 2022Article
- LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors.
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Abstract
Mild traumatic brain injury (mTBI) affects 22% of U.S. service members returning from Afghanistan and Iraq. Its diagnosis is challenging due to the heterogeneous structural and functional alterations inflicted by diverse injury mechanisms. mTBI is diagnosed mainly based on history (trauma) and clinical evaluation, since conventional neuroimaging methods, such as magnetic resonance imaging (MRI) and computerized tomography (CT) of the brain, typically do not reveal clear abnormalities. Similarly, the assessment of recovery following mTBI relies exclusively on clinical evaluation, based on several criteria. With respect to brain function, we hypothesized that mTBI reflects disturbed dynamic interactions among neuronal populations, a disturbance not detectable by the aforementioned techniques. In a quest for an objective tool to detect the presence of mTBI and assess recovery from it, here we used magnetoencephalography (MEG), a modality highly suited to assess the dynamic functional status of the brain. Specifically, we used the Synchronous Neural Interactions (SNI) test to evaluate functional brain status of 257 healthy ("control") veterans, 19 veterans with a clinical diagnosis of active mTBI ("a-mTBI"), and 18 veterans who suffered from mTBI and, at the time of testing, were deemed to have recovered from it ("r-mTBI"). A stepwise linear discriminant analysis (LDA) yielded 37 SNI predictors that classified 100% correctly of all 257 control and 19 a-mTBI brains. We then used these predictors to classify the 18 r-mTBI brains to control or a-mTBI groups: 9 brains (50%) were classified as control, whereas the other 10 (50%) were classified as a-mTBI. These findings (a) document the power of SNI MEG to correctly detect a-mTBI, and (b) raise concerns regarding the validity of clinical assessment tools to pronounce recovery from mTBI. On the positive side, our results provide an objective brain-based continuum along which the status of a mTBI brain can be assessed. This measure, together with clinical evaluation, should appreciably reduce the uncertainty and considerably improve the quantification of recovery from mTBI, guiding further treatment.
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