Blast-related injury and loss of consciousness is common in military TBI. Structural MR imaging demonstrates a high incidence of white matter T2-weighted hyperintense areas and pituitary abnormalities, with a low incidence of microhemorrhage in the chronic phase.

Traumatic brain injury (TBI) is a common combat injury, often through explosive blast, and produces heterogeneous brain changes due to various mechanisms of injury. It is unclear whether the vulnerability of white matter differs between blast and impact injury, and the consequences of microstructural changes on neuropsychological function are poorly understood in military TBI patients. Diffusion tensor imaging (DTI) techniques were used to assess the neurocircuitry in 37 U.S. service members (29 mild, 7 moderate, 1 severe; 17 blast and 20 nonblast), who sustained a TBI while deployed, compared to 14 nondeployed, military controls. High-dimensional deformable registration of MRI diffusion tensor data was followed by fiber tracking and tract-specific analysis along with region-of-interest analysis. DTI results were examined in relation to post-concussion and post-traumatic stress disorder (PTSD) symptoms. The most prominent white matter microstructural injury for both blast and nonblast patients was in the frontal fibers within the fronto-striatal (corona radiata, internal capsule) and fronto-limbic circuits (fornix, cingulum), the fronto-parieto-occipital association fibers, in brainstem fibers, and in callosal fibers. Subcortical superior-inferiorly oriented tracts were more vulnerable to blast injury than nonblast injury, while direct impact force had more detrimental effects on anterior-posteriorly oriented tracts, which tended to cause heterogeneous left and right hemispheric asymmetries of white matter connectivity. The tractography using diffusion anisotropy deficits revealed the cortico-striatal-thalamic-cerebellar-cortical (CSTCC) networks, where increased post-concussion and PTSD symptoms were associated with low fractional anisotropy in the major nodes of compromised CSTCC neurocircuitry, and the consequences on cognitive function were explored as well.

A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.

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We identified significant differences between answering and thinking aloud within the motor cortex, prefrontal cortex, cerebellum, and basal ganglia. These differences were by degree (more focal activation in these areas with thinking aloud as opposed to answering). Prefrontal cortex and cerebellum activity was attributable to working memory. Basal ganglia activity was attributed to the reward of answering a question. The identified neuroimaging differences between answering and thinking aloud were expected based on existing theory and research in other fields. These findings add evidence to the notion that the think-aloud protocol is a reasonable measure of thinking.