Objectives Research suggests that the majority of mild traumatic brain injury (mTBI) patients exhibit both cognitive and emotional dysfunction within the first weeks of injury, followed by symptom resolution 3–6 months post-injury. The neuronal correlates of said dysfunction are difficult to detect with standard clinical neuroimaging, complicating differential diagnosis and early identification of patients who may not recover. The current study examined whether resting state functional magnetic resonance imaging (FMRI) provides objective markers of injury and predicts cognitive, emotional and somatic complaints in mTBI patients semi-acutely (< 3 weeks post-injury) and in late recovery (3–5 month) phases. Methods Twenty seven semi-acute mTBI patients and 26 gender, age and education matched controls were studied. Fifteen out of 27 patients returned for a follow-up visit 3–5 months post-injury. The main dependent variables were spontaneous fluctuations (temporal correlation) in the default-mode (DMN) and fronto-parietal task-related (TRN) networks as measured by FMRI. Results Significant differences in self-reported cognitive, emotional and somatic complaints were observed (all p < .05), despite normal clinical (T1 and T2) imaging and neuropsychological testing results. Mild TBI patients demonstrated decreased functional connectivity within the DMN and hyper-connectivity between the DMN and lateral prefrontal cortex. Measures of functional connectivity exhibited high levels of sensitivity and specificity for patient classification and predicted cognitive complaints in the semi-acute injury stage. However, no changes in functional connectivity were observed across a four month recovery period. Conclusions Abnormal connectivity between the DMN and frontal cortex may provide objective biomarkers of mTBI and underlie cognitive impairment.

Mild traumatic brain injury is the most prevalent neurological insult and frequently results in neurobehavioural sequelae. However, little is known about the pathophysiology underlying the injury and how these injuries change as a function of time. Although diffusion tensor imaging holds promise for in vivo characterization of white matter pathology, both the direction and magnitude of anisotropic water diffusion abnormalities in axonal tracts are actively debated. The current study therefore represents both an independent replication effort (n = 28) of our previous findings (n = 22) of increased fractional anisotropy during semi-acute injury, as well as a prospective study (n = 26) on the putative recovery of diffusion abnormalities. Moreover, new analytical strategies were applied to capture spatially heterogeneous white matter injuries, which minimize implicit assumptions of uniform injury across diverse clinical presentations. Results indicate that whereas a general pattern of high anisotropic diffusion/low radial diffusivity was present in various white matter tracts in both the replication and original cohorts, this pattern was only consistently observed in the genu of the corpus callosum across both samples. Evidence for a greater number of localized clusters with increased anisotropic diffusion was identified across both cohorts at trend levels, confirming heterogeneity in white matter injury. Pooled analyses (50 patients; 50 controls) suggested that measures of diffusion within the genu were predictive of patient classification, albeit at very modest levels (71% accuracy). Finally, we observed evidence of recovery in lesion load in returning patients across a 4-month interval, which was correlated with a reduction in self-reported post-concussive symptomatology. In summary, the corpus callosum may serve as a common point of injury in mild traumatic brain injury secondary to anatomical (high frequency of long unmyelinated fibres) and biomechanics factors. A spatially heterogeneous pattern of increased anisotropic diffusion exists in various other white matter tracts, and these white matter anomalies appear to diminish with recovery. This macroscopic pattern of diffusion abnormalities may be associated with cytotoxic oedema following mechanical forces, resulting in changes in ionic homeostasis, and alterations in the ratio of intracellular and extracellular water. Animal models more specific to the types of mild traumatic brain injury typically incurred by humans are needed to confirm the histological correlates of these macroscopic markers of white matter pathology.

Chronic cocaine use is associated with enhanced cue reactivity to drug stimuli. However, it may also alter functional connectivity (fcMRI) in regions involved in processing drug stimuli. Our aims were to evaluate the neural regions involved in subjective craving and how fcMRI may be altered in chronic cocaine users. Fourteen patients with a confirmed diagnosis of cocaine abuse or dependence (CCA) and 16 gender, age, and education-matched healthy controls (HC) completed a cue reactivity task and a resting state scan while undergoing functional magnetic resonance imaging. CCA showed increased activation compared to HC in left dorsolateral prefrontal and bilateral occipital cortex in response to cocaine cues but not to appetitive control stimuli. Moreover, CCA also showed increased activation within the orbital frontal cortex (OFC) for cocaine cues relative to the appetitive stimuli during a hierarchical regression analysis. A negative association between subjective craving and activity in medial posterior cingulate gyrus (PCC) was also observed for CCA. CCA exhibited increased resting state correlation (positive) between cue-processing seed regions (OFC and ventral striatum), and negative connectivity between cue-processing regions and PCC/precuneus. These alterations in fcMRI may partially explain the neural basis of increased drug cue salience in CCA.

Single-voxel proton magnetic resonance imaging (1H-MRS) and proton MR spectroscopic imaging (1H-MRSI) were used to compare brain metabolite levels in semi-acute mild traumatic brain injury (mTBI) patients (n = 10) and matched healthy controls (n = 9). The 1H-MRS voxel was positioned in the splenium, a region known to be susceptible to axonal injury in TBI, and a single 1H-MRSI slice was positioned above the lateral ventricles. To increase sensitivity to the glutamate (Glu) and the combined glutamate-glutamine (Glx) signal, an inter-pulse echo time shown to emphasize the major Glu signals was used along with an analysis method that reduces partial volume errors by using water as a concentration standard. Our preliminary findings indicate significantly lower levels of gray matter Glx and higher levels of white matter creatine-phosphocreatine (Cr) in mTBI subjects relative to healthy controls. Furthermore, Cr levels were predictive of executive function and emotional distress in the combined groups. These results suggest that perturbations in Cr, a critical component of the brain’s energy metabolism, and Glu, the brain’s major neurotransmitter, may occur following mTBI. Moreover, the different pattern of results for gray and white matter suggests tissue-specific metabolic responses to mTBI.

The relationship between head motion and diffusion values such as fractional anisotropy (FA) and mean diffusivity (MD) is currently not well understood. Simulation studies suggest that head motion may introduce either a positive or negative bias, but this has not been quantified in clinical studies. Moreover, alternative measures for removing bias as result of head motion, such as the removal of problematic gradients, has been suggested but not carefully evaluated. The current study examined the impact of head motion on FA and MD across three common pipelines (tract-based spatial statistics, voxelwise, and region of interest analyses) and determined the impact of removing diffusion weighted images. Our findings from a large cohort of healthy controls indicate that while head motion was associated with a positive bias for both FA and MD, the effect was greater for MD. The positive bias was observed across all three analysis pipelines and was present following established protocols for data processing, suggesting that current techniques (i.e., correction of both image and gradient table) for removing motion bias are likely insufficient. However, the removal of images with gross artifacts did not fundamentally change the relationship between motion and DTI scalar values. In addition, Monte Carlo simulations suggested that the random removal of images increases the bias and reduces the precision of both FA and MD. Finally, we provide an example of how head motion can be quantified across different neuropsychiatric populations, which should be implemented as part of any diffusion tensor imaging quality assurance protocol.