Abstract
(1) Background: Mild traumatic brain injury produces significant changes in neurotransmission including brain oscillations. We investigated potential quantitative electroencephalography biomarkers in 57 patients with post-concussive syndrome and chronic pain following motor vehicle collision, and 54 healthy nearly age- and sex-matched controls. (2) Methods: Electroencephalography processing was completed in MATLAB, statistical modeling in SPSS, and machine learning modeling in Rapid Miner. Group differences were calculated using current-source density estimation, yielding whole-brain topographical distributions of absolute power, relative power and phase-locking functional connectivity. Groups were compared using independent sample Mann–Whitney U tests. Effect sizes and Pearson correlations were also computed. Machine learning analysis leveraged a post hoc supervised learning support vector non-probabilistic binary linear kernel classification to generate predictive models from the derived EEG signatures. (3) Results: Patients displayed significantly elevated and slowed power compared to controls: delta (p = 0.000000, r = 0.6) and theta power (p < 0.0001, r = 0.4), and relative delta power (p < 0.00001) and decreased relative alpha power (p < 0.001). Absolute delta and theta power together yielded the strongest machine learning classification accuracy (87.6%). Changes in absolute power were moderately correlated with duration and persistence of symptoms in the slow wave frequency spectrum (<15 Hz). (4) Conclusions: Distributed increases in slow wave oscillatory power are concurrent with post-concussive syndrome and chronic pain.
Highlights
Traumatic brain injury (TBI) is a common and important cause of morbidity
Changes in absolute power were moderately correlated with duration and persistence of symptoms in the slow wave frequency spectrum (
While most people recover after TBI, it is estimated that about 5.3 million Americans and over 500 thousand Canadians are living with TBIrelated disabilities, including many that persist after Mild TBI (mTBI)— known as Post-Concussive Syndrome (PCS) [5]
Summary
Reports indicate over 2.4 million annual United States emergency department visits for TBI in 2013 and 100 thousand in Canada; with slips and falls, followed by motor vehicle accidents (MVA) being the leading causes [1,2,3]. The global estimate of TBI is reported to be between 64 million and 74 million annually [4]. While most people recover after TBI, it is estimated that about 5.3 million Americans and over 500 thousand Canadians are living with TBIrelated disabilities, including many that persist after mTBI— known as Post-Concussive Syndrome (PCS) [5]. Chronic pain (CP) is an even more prevalent and debilitating condition with a global estimate of up to 20% of adults suffering worldwide, including approximately 25 million Americans and 6 million Canadians [6,7,8]. Recent neuroimaging studies have attempted to uncover the pathophysiology of these conditions independently [11,12,13,14,15,16,17,18,19], but neuroimaging studies in PCS + CP following mTBI are scarce [20,21]
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