Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

Abstract

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI.

Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

“…We considered macroscopic neural circuits based on MEG (magnetoencephalographic) synchrony as one fingerprint source. Indeed, MEG has been used to understand human neurophysiology, including a wide range of neurodegenerative and neuropsychological disorders, such as mTBI, Alzheimer's disease, depression and bipolar disorder [9][10][11] . Neural oscillations recovered using MEG are known to be dysfunctional in PTSD and correlate with primary symptoms and secondary complaints in the disorder [12][13][14][15]22 .…”

“…A mechanism that mediates communication and information processing within and between brain circuits is neural oscillations and synchrony 7 . Magnetoencephalography (MEG) can image these phenomena non-invasively, and has been used as an effective research tool for exploring the neural activity associated with various neurodegenerative and neuropsychological disorders, including depression, bipolar disorder, mild traumatic brain injury (mTBI) and Alzheimer's disease [8][9][10][11] as well as PTSD-related functional circuitry [12][13][14][15] . At the group level, neural synchrony can stratify those with PTSD from a heavily traumatised, but otherwise matched, control group 15 , with hippocampal synchrony directly related to symptom severity across individuals 14 .…”

Applications of Resting State Functional MR Imaging to Traumatic Brain Injury

“…Vakorin et al 53 investigated the type of alterations that occur in resting state oscillatory network phase synchrony in adults with mTBI and whether machine learning can accurately detect mTBI in individual subjects. rs-MEG was recorded and structural MRI was aquired from 20 patients with mTBI and 21 age, gender and handedness matched healthy controls.…”

Magnetoencephalography With Optically Pumped4He Magnetometers at Ambient Temperature

“…Novel potential clinical indications of MEG are also progressively emerging from clinical research, based on the investigation of resting state functional connectivity. In particular, MEG appears very promising for the management and diagnosis of dementia (mild cognitive impairment and Alzheimer's disease) [12]- [15], Parkinson's disease [16]- [18], traumatic brain injury [19]- [21] and multiple sclerosis [22]- [24].…”