Dataset Information

Disruption of caudate working memory activation in chronic blast-related traumatic brain injury.

ABSTRACT: Mild to moderate traumatic brain injury (TBI) due to blast exposure is frequently diagnosed in veterans returning from the wars in Iraq and Afghanistan. However, it is unclear whether neural damage resulting from blast TBI differs from that found in TBI due to blunt-force trauma (e.g., falls and motor vehicle crashes). Little is also known about the effects of blast TBI on neural networks, particularly over the long term. Because impairment in working memory has been linked to blunt-force TBI, the present functional magnetic resonance imaging (fMRI) study sought to investigate whether brain activation in response to a working memory task would discriminate blunt-force from blast TBI. Twenty-five veterans (mean age = 29.8 years, standard deviation = 6.01 years, 1 female) who incurred TBI due to blast an average of 4.2 years prior to enrollment and 25 civilians (mean age = 27.4 years, standard deviation = 6.68 years, 4 females) with TBI due to blunt-force trauma performed the Sternberg Item Recognition Task while undergoing fMRI. The task involved encoding 1, 3, or 5 items in working memory. A group of 25 veterans (mean age = 29.9 years, standard deviation = 5.53 years, 0 females) and a group of 25 civilians (mean age = 27.3 years, standard deviation = 5.81 years, 0 females) without history of TBI underwent identical imaging procedures and served as controls. Results indicated that the civilian TBI group and both control groups demonstrated a monotonic relationship between working memory set size and activation in the right caudate during encoding, whereas the blast TBI group did not (p < 0.05, corrected for multiple comparisons using False Discovery Rate). Blast TBI was also associated with worse performance on the Sternberg Item Recognition Task relative to the other groups, although no other group differences were found on neuropsychological measures of episodic memory, inhibition, and general processing speed. These results could not be attributed to caudate atrophy or the presence of PTSD symptoms. Our results point to a specific vulnerability of the caudate to blast injury. Changes in activation during the Sternberg Item Recognition Task, and potentially other tasks that recruit the caudate, may serve as biomarkers for blast TBI.

SUBMITTER: Newsome MR

PROVIDER: S-EPMC4477106 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Disruption of caudate working memory activation in chronic blast-related traumatic brain injury.

Newsome Mary R MR Durgerian Sally S Mourany Lyla L Scheibel Randall S RS Lowe Mark J MJ Beall Erik B EB Koenig Katherine A KA Parsons Michael M Troyanskaya Maya M Reece Christine C Wilde Elisabeth E Fischer Barbara L BL Jones Stephen E SE Agarwal Rajan R Levin Harvey S HS Rao Stephen M SM

NeuroImage. Clinical 20150508

Mild to moderate traumatic brain injury (TBI) due to blast exposure is frequently diagnosed in veterans returning from the wars in Iraq and Afghanistan. However, it is unclear whether neural damage resulting from blast TBI differs from that found in TBI due to blunt-force trauma (e.g., falls and motor vehicle crashes). Little is also known about the effects of blast TBI on neural networks, particularly over the long term. Because impairment in working memory has been linked to blunt-force TBI, t ...[more]

PMID: 26110112

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Project description:Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients.

Project description:It is well established that chronic cognitive problems after traumatic brain injury relate to diffuse axonal injury and the consequent widespread disruption of brain connectivity. However, the pattern of diffuse axonal injury varies between patients and they have a correspondingly heterogeneous profile of cognitive deficits. This heterogeneity is poorly understood, presenting a non-trivial challenge for prognostication and treatment. Prominent amongst cognitive problems are deficits in working memory and reasoning. Previous functional MRI in controls has associated these aspects of cognition with distinct, but partially overlapping, networks of brain regions. Based on this, a logical prediction is that differences in the integrity of the white matter tracts that connect these networks should predict variability in the type and severity of cognitive deficits after traumatic brain injury. We use diffusion-weighted imaging, cognitive testing and network analyses to test this prediction. We define functionally distinct subnetworks of the structural connectome by intersecting previously published functional MRI maps of the brain regions that are activated during our working memory and reasoning tasks, with a library of the white matter tracts that connect them. We examine how graph theoretic measures within these subnetworks relate to the performance of the same tasks in a cohort of 92 moderate-severe traumatic brain injury patients. Finally, we use machine learning to determine whether cognitive performance in patients can be predicted using graph theoretic measures from each subnetwork. Principal component analysis of behavioural scores confirm that reasoning and working memory form distinct components of cognitive ability, both of which are vulnerable to traumatic brain injury. Critically, impairments in these abilities after traumatic brain injury correlate in a dissociable manner with the information-processing architecture of the subnetworks that they are associated with. This dissociation is confirmed when examining degree centrality measures of the subnetworks using a canonical correlation analysis. Notably, the dissociation is prevalent across a number of node-centric measures and is asymmetrical: disruption to the working memory subnetwork relates to both working memory and reasoning performance whereas disruption to the reasoning subnetwork relates to reasoning performance selectively. Machine learning analysis further supports this finding by demonstrating that network measures predict cognitive performance in patients in the same asymmetrical manner. These results accord with hierarchical models of working memory, where reasoning is dependent on the ability to first hold task-relevant information in working memory. We propose that this finer grained information may be useful for future applications that attempt to predict long-term outcomes or develop tailored therapies.

Dataset Information

Disruption of caudate working memory activation in chronic blast-related traumatic brain injury.

Publications

Disruption of caudate working memory activation in chronic blast-related traumatic brain injury.

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