Three approaches to investigating functional compromise to the default mode network after traumatic axonal injury.
ABSTRACT The default mode network (DMN) is a reliably elicited functional neural network with potential clinical implications. Its discriminant and prognostic utility following traumatic axonal injury (TAI) have not been previously investigated. The present study used three approaches to analyze DMN functional connectedness, including a whole-brain analysis [A1], network-specific analysis [A2], and between-node (edge) analysis [A3]. The purpose was to identify the utility of each method in distinguishing between healthy and brain-injured individuals, and determine whether observed differences have clinical significance. Resting-state fMRI was acquired from 25 patients with TAI and 17 healthy controls. Patients were scanned 6-11 months post-injury, and functional and neurocognitive outcomes were assessed the same day. Using all three approaches, TAI subjects revealed significantly weaker functional connectivity (FC) than controls, and binary logistic regressions demonstrated all three approaches have discriminant value. Clinical outcomes were not correlated with FC using any approach. Results suggest that compromise to the functional connectedness of the DMN after TAI can be identified using resting-state FC; however, the degree of functional compromise to this network, as measured in this study, may not have clinical implications in chronic TAI.
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ABSTRACT: Reviewed herein are contemporary neuroimaging methods that detect abnormalities associated with mild traumatic brain injury (mTBI). Despite advances in demonstrating underlying neuropathology in a subset of individuals who sustain mTBI, considerable disagreement persists in neuropsychology about mTBI outcome and metrics for evaluation. This review outlines a thesis for the select use of sensitive neuroimaging methods as potential biomarkers of brain injury recognizing that the majority of individuals who sustain an mTBI recover without neuroimaging signs or neuropsychological sequelae detected with methods currently applied. Magnetic resonance imaging (MRI) provides several measures that could serve as mTBI biomarkers including the detection of hemosiderin and white matter abnormalities, assessment of white matter integrity derived from diffusion tensor imaging (DTI), and quantitative measures that directly assess neuroanatomy. Improved prediction of neuropsychological outcomes in mTBI may be achieved with the use of targeted neuroimaging markers.Neuropsychology Review 08/2013; · 5.40 Impact Factor
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ABSTRACT: Blast-related traumatic brain injury (TBI) has been one of the "signature injuries" of the wars in Iraq and Afghanistan. However, neuroimaging studies in concussive 'mild' blast-related TBI have been challenging due to the absence of abnormalities in computed tomography or conventional magnetic resonance imaging (MRI) and the heterogeneity of the blast-related injury mechanisms. The goal of this study was to address these challenges utilizing single-subject, module-based graph theoretic analysis of resting-state functional MRI (fMRI) data. We acquired 20minutes of resting-state fMRI in 63 U.S. military personnel clinically diagnosed with concussive blast-related TBI and 21 U.S. military controls who had blast exposures but no diagnosis of TBI. All subjects underwent an initial scan within 90days post-injury and 65 subjects underwent a follow-up scan 6 to 12months later. A second independent cohort of 40 U.S. military personnel with concussive blast-related TBI patients served as a validation dataset. The second independent cohort underwent an initial scan within 30days post-injury. 75% of scans were of good quality, with exclusions primarily due to excessive subject motion. Network analysis of the subset of these subjects in the first cohort with good quality scans revealed spatially localized reductions in participation coefficient, a measure of between-module connectivity, in the TBI patients relative to the controls at the time of the initial scan. These group differences were less prominent on the follow-up scans. The 15 brain areas with the most prominent reductions in participation coefficient were next used as regions of interest (ROIs) for single-subject analyses. In the first TBI cohort, more subjects than would be expected by chance (27/47 versus 2/47 expected, p<0.0001) had 3 or more brain regions with abnormally low between-module connectivity relative to the controls on the initial scans. On the follow-up scans, more subjects than expected by chance (5/37, p=0.044) but fewer subjects than on the initial scans had 3 or more brain regions with abnormally low between-module connectivity. Analysis of the second TBI cohort validation dataset with no free parameters provided a partial replication; again more subjects than expected by chance (8/31, p=0.006) had 3 or more brain regions with abnormally low between-module connectivity on the initial scans, but the numbers were not significant (2/27, p=0.276) on the follow-up scans. A single-subject, multivariate analysis by probabilistic principal component analysis of the between-module connectivity in the 15 identified ROIs, showed that 31/47 subjects in the first TBI cohort were found to be abnormal relative to the controls on the initial scans. In the second TBI cohort, 9/31 patients were found to be abnormal in identical multivariate analysis with no free parameters. Again, there were not substantial differences on the follow-up scans. Taken together, these results indicate that single-subject, module-based graph theoretic analysis of resting-state fMRI provides potentially useful information for concussive blast-related TBI if high quality scans can be obtained. The underlying biological mechanisms and consequences of disrupted between-module connectivity are unknown, thus further studies are required.NeuroImage 08/2013; 84. · 6.13 Impact Factor
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ABSTRACT: While traumatic brain injury (TBI) results in widespread disruption of neural networks, changes in regional resting-state functional connectivity patterns after insult remain unclear. Specifically, little is known about the chronology of emergent connectivity alterations and whether they persist after a critical recovery window. We used resting-state fMRI and seed-voxel correlational analyses in both cross-sectional and longitudinal designs to probe intrinsic connectivity patterns involving the posterior cingulate cortex (PCC) and hippocampi, regions shown to be important in the default mode network (DMN) and vulnerable to neuropathology. A total of 22 participants in the chronic stage of moderate-severe TBI and 18 healthy controls were included for cross-sectional study. Longitudinal analyses included 13 individuals in the TBI group for whom data approximately three months after injury (subacute) were available. Overall, results indicated dissociable connectivity trajectories of the PCC and hippocampi during recovery from TBI, with PCC alterations characterized by early hypersynchrony with the anterior DMN that is gradually reduced, and hippocampal changes marked by increasing synchrony with proximal cortex and subcortex. The PCC also showed increasing antiphase synchrony with posterior attentional regions, and the hippocampi showed decreasing antiphase synchrony with frontal attentional regions. Antiphase synchrony of the hippocampus and dorsolateral prefrontal cortex at the subacute stage of TBI was positively associated with attentional performance on neuropsychological tests at both the subacute and chronic stages. Our findings highlight the heterogeneity of regional-whole brain connectivity changes after TBI, and suggest that residual connectivity alterations exist in the clinically stable phase of TBI. Parallels between the chronicity of the observed effects and findings in neurodegenerative disease are discussed in the context of potential long-term outcomes of TBI.Journal of Neurotrauma 06/2014; · 3.97 Impact Factor