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 Magnetoencephalography (MEG)A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain., a modality highly suited to assess the dynamic functional status of the brain. Specifically, we used the SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. 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 SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. 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 SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. MEGMagnetoencephalography (MEG)A noninvasive technique that detects magnetic fields above the surface of the head produced by postsynaptic potentials in the brain. 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.