Search

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = −0.111 to −0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site- specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,343 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,067 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM were more sensitive to the detection of significant case-control differences in regional cortical thickness (X2(3) = 34.339, p < 0.001), and case-control differences in age-related cortical thinning (X2(3) = 15.128, p = 0.002). Specifically, ComBat-GAM led to larger effect size estimates of cortical thickness reductions (corrected p-values < 0.001), smaller age-appropriate declines (corrected p-values < 0.001), and lower female to male contrast (corrected p-values < 0.001) in cases compared to controls relative to other harmonization methods. Harmonization with ComBat-GAM also led to greater estimates of age-related declines in cortical thickness (corrected p-values < 0.001) in both cases and controls compared to other harmonization methods. Our results support the use of ComBat-GAM for harmonizing cortical thickness data aggregated from multiple sites and scanners to minimize confounds and increase statistical power.

Posttraumatic stress disorder (PTSD) is a complex psychiatric condition that has generated much attention in the neuroimaging literature. A neurocircuitry model supporting fronto-limbic dysfunction as a major player in facilitating clinical symptoms of PTSD is well-characterized; however, recent literature suggests that network-based approaches may provide additional insight into neural dysfunction in PTSD. Our analysis uses resting-state neuroimaging scans of 1063 adults from the PGC-ENIGMA PTSD Consortium to investigate a network-based model of functional connectivity in PTSD. With a novel, resolution limit-free community detection approach, 16 communities corresponding to functionally meaningful networks were detected with high quality. After group-level community detection, participants were classified into three groups (PTSD, n=418, trauma-exposed controls without PTSD, n=434, and non-trauma exposed healthy controls, n=211). Individual network connectivity metrics were calculated, including whole-brain, default mode network, and central executive network participation coefficient and connectivity strength. Linear mixed effects models revealed group differences in the whole-brain, default mode, and central executive network participation coefficient and connectivity strength such that individuals with PTSD demonstrated overall greater values. We also described sex differences such that males demonstrate greater whole-brain participation coefficient vs. females and females demonstrate greater default mode network connectivity strength vs. males. Our results suggest that PTSD in adults is associated with reduced specialization and enhanced inter-module communication throughout the brain network, which may contribute to inefficient information processing and poor emotional regulation. This study presents a novel use of resolution limit-free community detection in a large PTSD sample, revealing robust differences in resting-state network topology.

IntroductionCortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subjects’ data from 29 cohorts in five countries (n=3439).MethodsUsing Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN.ResultsNotable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus.ConclusionUnlike previous studies with smaller sample sizes (≤318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into a node’s relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

Traumatic brain injury (TBI) disrupts brain communication and increases risk for post-traumatic stress disorder (PTSD). However, mechanisms by which TBI-related disruption of brain communication confers PTSD risk have not been successfully elucidated in humans. This may be in part because functional MRI (fMRI), the most common technique for measuring functional brain communication, is unreliable for characterizing individual patients. However, this unreliability can be overcome with sufficient within-individual data. Here, we examined whether relationships could be observed among TBI, structural and functional brain connectivity, and PTSD severity by collecting ∼3.5 hours of resting-state fMRI and diffusion tensor imaging (DTI) data in each of 26 United States military veterans. We observed that a TBI history was associated with decreased whole-brain resting-state functional connectivity (RSFC), while the number of lifetime TBIs was associated with reduced whole-brain fractional anisotropy (FA). Both RSFC and FA explained independent variance in PTSD severity, with RSFC mediating the TBI-PTSD relationship. Finally, we showed that large amounts of per-individual data produced highly reliable RSFC measures, and that relationships among TBI, RSFC/FA, and PTSD could not be observed with typical data quantities. These results demonstrate links among TBI, brain connectivity, and PTSD severity, and illustrate the need for precise characterization of individual patients using high-data fMRI scanning.

Energy storage using batteries is accepted as one of the most important and efficient ways of stabilising electricity networks and there are a variety of different battery chemistries that may be used. Lead batteries are very well established both for automotive and industrial applications and have been successfully applied for utility energy storage but there are a range of competing technologies including Li-ion, sodium-sulfur and flow batteries that are used for energy storage. The technology for lead batteries and how they can be better adapted for energy storage applications is described. Lead batteries are capable of long cycle and calendar lives and have been developed in recent years to have much longer cycle lives compared to 20 years ago in conditions where the battery is not routinely returned to a fully charged condition. Li-ion batteries have advantages in terms of energy density and specific energy but this is less important for static installations. The other technical features of Li-ion and other types of battery are discussed in relation to lead batteries. A selection of larger lead battery energy storage installations are analysed and lessons learned identified. Lead is the most efficiently recycled commodity metal and lead batteries are the only battery energy storage system that is almost completely recycled, with over 99% of lead batteries being collected and recycled in Europe and USA. The sustainability of lead batteries is compared with other chemistries.

Traumatic brain injuries (TBIs) induce persistent behavioral and cognitive deficits via diffuse axonal injury. Axonal injuries are often examined in vivo using diffusion MRI, which identifies damaged and demyelinated regions in deep white matter. However, TBI patients can exhibit impairment in the absence of diffusion-measured abnormalities, suggesting that axonal injury and demyelination may occur outside the deep white matter. Importantly, myelinated axons are also present within the cortex. Cortical myelination cannot be measured using diffusion imaging, but can be mapped in-vivo using the T1-w/T2-w ratio method. Here, we conducted the first work examining effects of TBI on intracortical myelin in living humans by applying myelin mapping to 46 US Military Veterans with a history of TBI. We observed that myelin maps could be created in TBI patients that matched known distributions of cortical myelin. After controlling for age and presence of blast injury, the number of lifetime TBIs was associated with reductions in the T1-w/T2-w ratio across the cortex, most significantly in a highly-myelinated lateral occipital region corresponding with the human MT+ complex. Further, the T1-w/T2-w ratio in this MT+ region predicted resting-state functional connectivity of that region. By contrast, a history of blast TBI did not affect the T1-w/T2-w ratio in either a diffuse or focal pattern. These findings suggest that intracortical myelin, as measured using the T1-w/T2-w ratio, may be a TBI biomarker that is anatomically complementary to diffusion MRI. Thus, myelin mapping could potentially be combined with diffusion imaging to improve MRI-based diagnostic tools for TBI.

Traumatic brain injuries (TBIs) induce persistent behavioral and cognitive deficits via diffuse axonal injury. Such axonal injuries are often examined in vivo using diffusion MRI, which identifies demyelinated regions in deep white matter. However, TBI patients can exhibit impairment in the absence of diffusion-measured abnormalities, suggesting that axonal injury and demyelination may occur outside the deep white matter. Importantly, myelinated axons are also present within the cortex. Cortical myelination cannot be measured using diffusion imaging, but can be assessed using the T1/T2 ratio myelin mapping method. Here, we conducted the first work examining effects of TBI on intracortical myelin in living humans by applying the myelin mapping technique to 26 US Military Veterans with varying histories of TBI severity. We observed that myelin maps could be created in individual TBI patients that were similar to known distributions of cortical myelin. Critically, after controlling for participant age, a history of more severe TBI was associated with progressively reduced intracortical myelin in a broad, diffuse pattern across the cortex. Such significant but diffuse reductions in myelin were observed in high-myelin but not low-myelin regions. By contrast, the presence of blast TBI did not affect intracortical myelin above and beyond TBI severity in either a diffuse or focal pattern. These findings suggest that intracortical myelin may be a biomarker of TBI that is anatomically complimentary to diffusion MRI measures of deep white matter. Thus, myelin mapping could potentially be combined with diffusion imaging measures to improve MRI-based diagnostic tools for TBI.