Research indicates that Veterans with a history of traumatic brain injury (TBI) are at increased risk for dementia. Although the precise mechanisms underlying this relationship are poorly understood, remote TBI may exacerbate normal age-related changes to cerebral white matter (WM) and result in cognitive decline. However, Veterans commonly experience a constellation of mental (e.g., post-traumatic stress disorder [PTSD] and depression) and vascular (e.g., diabetes, hypertension, obesity) health conditions that have also been implicated in pathologic cerebral WM and cognitive aging trajectories. Therefore, the present study sought to (1) clarify the effects of remote TBI within the context of PTSD, depression, and vascular risk on WM micro- and macrostructure, and (2) explore if WM integrity is associated with cognition in a sample of Vietnam-Era Veterans.

The sample consisted of 195 male Veterans ages 60-80 (mean age=69.3) enrolled in the Department of Defense-Alzheimer’s Disease Neuroimaging Initiative (DoD-ADNI) study. 102 Veterans met criteria for TBI by sustaining a head-injury that resulted in a loss of consciousness, alteration of consciousness, or post-traumatic amnesia. Current and/or lifetime PTSD was designated by scores >30 on the Clinician-Administered PTSD Scale. The Geriatric Depression Scale was used as a continuous measure of depression. A vascular risk score (0-3) was calculated based on diabetes, hypertension, and obesity (BMI >30 kg/m2). An executive functioning composite was created by averaging sample-specific z-scores for Trail Making Tests (A and B), with higher scores indicating worse performance. Voxelwise analysis of WM microstructure (fractional anisotropy [FA]) was conducted with Tract-Based Spatial Statistics (TBSS), using non-parametric permutation testing with threshold-free cluster enhancement. SPM’s Lesion Segmentation Tool was used to investigate WM macrostructure (WM hyperintensity [WMH] volume). Lesion probability maps were masked to restrict WMH volume calculations to WM. Robust regression using M-estimation and predictive R2 calculated using 10-fold cross-validation examined WMH volume, predictor, and cognitive associations. Age was a covariate in all WM analyses, and education was a covariate in all cognitive analyses.

TBSS analysis revealed widespread, significant negative relationships between vascular risk and FA across numerous WM tracts (p’s<0.05). These associations remained significant after adjusting for TBI history, PTSD, and depression. TBSS identified significant positive relationships between executive functioning performance and FA across similar brain regions (p’s<0.05). Robust regressions revealed that vascular risk significantly predicted WMH volume (p=0.006; ß=0.161; R2=0.093), whereas TBI history, PTSD, and depression did not (p’s=0.107-0.166; ß's=-0.089-0.101). WMH volume significantly predicted executive functioning (p=0.002; ß=0.216; R2=0.105), whereas TBI history, PTSD, depression, and vascular risk did not (p’s=0.123-0.888; ß's=-0.012-0.125).

Our results suggest that vascular health, relative to remote TBI, PTSD, and depression, may be more robustly associated with cerebral WM micro- and macrostructure in older Veterans. Furthermore, poorer WM integrity is associated with poorer cognitive performance. These findings underscore the importance of vascular health interventions in preventing negative brain and cognitive aging outcomes in Veterans, independent of TBI history. Future studies might leverage other neuroimaging modalities (e.g., functional MRI) to further investigate the effects of vascular health on aging in Veterans with a history of TBI.

Memory impairment is a common comorbidity in individuals with temporal lobe epilepsy (TLE). Further, in medication-resistant epilepsy the frontline option, neurosurgical epileptogenic zone destruction, places memory at significant risk. Research has highlighted that TLE causes whole-brain network efficiency disruption, but it is not established how this may explain pre- and post-surgical cognition. Here we examine whether white matter structural network organization predicts pre-operative memory function and/or risk for post-operative memory decline.

Patients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-operative sample included 51 individuals with left TLE (L-TLE), 52 with right TLE (R-TLE), and 57 healthy controls who underwent T1- and diffusion-weighted MRI (dMRI), and neuropsychological tests of verbal and visual memory. Forty-four patients (n=21 L-TLE) subsequently underwent temporal lobe surgery (36 anterior temporal lobectomy; 7 stereotactic laser amygdalohippocampectomy; 1 amygdalohippocampectomy) and completed post-operative memory testing. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory, focusing on network integration (path length) and specialization (transitivity). In the preoperative dataset, first we compared TLE versus controls with analysis of covariance (ANCOVAs) controlling for age. Next, linear regressions examined the association between memory scores and network efficiency between L-TLE, R-TLE and controls. In the post-operative sample, bivariate correlations examined the association between pre- to post-operative memory change and 1) global network efficiency and 2) asymmetry of mesial temporal efficiency (i.e., local efficiency of the hippocampal, parahippocampal, and entorhinal nodes). Finally, efficiency metrics were entered into stepwise regressions along with established predictors of memory decline.

Compared to controls, TLE showed longer path length (p < .05; ηp2 = .03) and lower transitivity (p = .01; ηp2 = .04). Pre-operatively, better verbal learning and memory were associated with both shorter path length (β = -0.23 to -0.32; psadjusted < .05) and increased transitivity (β = 0.20 to 0.31; psadjusted < .05). These associations were greater in L-TLE than R-TLE (i.e., a significant interaction; β = -0.29 to 0.25; psadjusted <.05). Post-operatively, global metrics predicted decline on list learning for LTLEs (rs = -.57 to .58; ps < .01), and were marginal on list recall (rs = -.42 to .40; ps < .10). Leftward asymmetry of mesial temporal local efficiency predicted greater decline across most verbal memory measures for L-TLE (rs -.47 to -59; psadjusted <.05), but not R-TLE. Asymmetry of mesial network efficiency uniquely explained at least 20 to 43% of the variance in list learning, recall, and story learning for L-TLE, outperforming hippocampal asymmetry and preoperative score (psadjusted <.05).

Our findings suggest that global white matter network abnormalities contribute to verbal memory impairment pre-operatively and vulnerability to decline post-operatively in L-TLE. Asymmetry of a predefined mesial temporal sub-network may help predict post-operative memory function following left temporal lobe surgery, such that greater efficiency in the to-beresected mesial temporal network may be an important risk factor for decline. Our findings extend the importance of network approaches in TLE to include the relationships between neurobiological networks and memory function.

Machine learning studies of PTSD show promise for identifying neurobiological signatures of this disorder, but studies to date have largely excluded Black American women, who experience disproportionately greater trauma and have relatively higher rates of PTSD. PTSD is characterized by four symptom clusters: trauma reexperiencing, trauma avoidance, hyperarousal, and anhedonia. A prior machine learning study reported successful PTSD symptom cluster severity prediction using functional MRI data but did not examine white matter predictors. White matter microstructural integrity has been related to PTSD presence and symptoms, and unexplored metrics such as estimates of tract shape may provide unique predictive utility. Therefore, this study examines the relationship between white matter tract shape and PTSD symptom cluster severity amongst trauma-exposed Black American women using multiple machine learning models.

Participants included 45 Black American women with PTSD (Mage=40.4(12.9)) and 89 trauma-exposed controls (Mage=39.8(11.6)). Shape and diffusion metrics for the cingulum, corpus callosum, fornix, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus were calculated using deterministic tractography. Current symptom severity was calculated using the PTSD Symptom Scales. Input features included tract metrics, questionnaire responses, and age. The following regression models were generated: least absolute shrinkage and selection operator (LASSO), ridge, elastic net, and gaussian process (GPR). Additionally, two forms of latent-scale GPR, one without (lsGPR) and with (sp-lsGPR) node selection via spike and slab priors, were calculated. The performance of regression models was estimated using mean square error (MSE) and R2.

sp-lsGPR performed at or above other models across all symptom clusters. LASSO models were comparable to sp-lsGPR for avoidance and hyperarousal clusters. Ridge regression and GPR had the weakest performance across clusters. Scores for sp-lsGPR by cluster are as follows: reexperiencing Mmse =0.70(0.17), Mr2=0.56(0.13); avoidance Mmse =0.75(0.17), Mr2= 0.51(0.13); hyperarousal Mmse =0.57(0.18), Mr2=0.66(0.12); anhedonia Mmse =0.74(0.27), Mr2=0.57(0.13). The top three ranked posterior inclusion probabilities for white matter tracts across sp-lsGPR models include four sections of the cingulum, three sections of the corpus callosum, the right fornix, the left inferior longitudinal fasciculus, the first segment of the right superior longitudinal fasciculus, and the right uncincate fasciculus. The greatest posterior inclusion probability value for the sp-lsGPR models was the left frontal parahippocampal cingulum for the hyperarousal cluster.

Results support the combined predictive utility of white matter metrics for brain imaging regression models of PTSD. Results also support the use of sp-lsGPR models, which are designed to balance interpretable linear models and highly-flexible non-linear models. The sp-lsGPR model performance was similar across clusters but was relatively better for the hyperarousal cluster. This finding contrasts with prior machine learning work using functional data which was unable to predict hyperarousal scores above chance (MR2=0.06). These diverging findings highlight the importance of examining both functional and structural data in PTSD populations. Differing findings may also be related to sample characteristics as the prior study was conducted in China. Black American women and Chinese individuals have unique lived experiences that may differentially impact brain structure and function. Future work should continue to include diverse research samples to account for such experiences.

The increasing complexity of social stress may be especially threatening to mental health during childhood and adolescence. One's skills in effectively coping with this stress may contribute to symptoms of pediatric anxiety and depression, a growing, significant, and pervasive public health concern. In addition to strategic skills, individual differences in coping may reflect differences in brain structure, including the white matter pathways that integrate frontal lobe networks with those involved in social functioning. Identifying the neurological substrates underlying anxiety and depression is an important way to delineate mechanisms underlying development of these disorders. Deterministic automated-fiber quantification (AFQ) is a technique that removes potential error from manual tracking of white matter, segregating tracts into distinct nodes—diminishing the effect of crossing fibers—and quantifying the number of fibers in a tract, allowing for assessment of connectivity across regions. Collectively, this investigation aims to quantify the interplay between anxiety, depression, coping with social stress, and white matter microstructure in children and adolescents.

Ninety-two healthy children and adolescents (8-17 years old; n=53 female, Mage=12.96; n=39 male, Mage=12.31) and a parent rated symptoms of anxiety and depression using the Behavior Assessment System for Children (BASC-III). Coping and stress reactivity were assessed using the Responses to Stress Questionnaire, Social Stress version. Children and adolescents also completed 64-direction DTI in a Siemens 3T Prisma scanner. White matter microstructure was quantified using AFQ; Fractional anisotropy (FA) values were extracted for 18 tracts, comprised of 100 nodes each.

Mean levels of parent- and self-reported anxiety and depression fell within the normative range, and children reported mild- to moderate social stress. Higher levels of social stress were associated with increased parent reported anxiety (r=.294, p=.002) and parent- and self-reported depression (r=.481, p<.001; r=.211, p=.034, respectively). Anxiety and depression were not significantly related to white matter microstructure; however, several specific links with coping were noted. Use of secondary control coping (e.g., cognitive restructuring) was associated with higher FA of the bilateral inferior fronto-occipital fasciculi (left IFOF r=.228, p=.027; right IFOF r=.299, p=.003) and left inferior longitudinal fasciculus (r=.269, p=.009); use of primary control coping (e.g., problem solving) was associated with higher FA of the bilateral uncinate fasciculi (left UF r=.216, p=.036; right UF r=.207, p=.045). Furthermore, use of primary and secondary control coping were associated with fewer symptoms of anxiety and depression, whereas greater use of disengagement coping (e.g., wishful thinking) was associated with more depressive symptoms.

These findings highlight links among white matter microstructure in tracts integrating frontal with temporal and occipital regions, and adoption of adaptive (i.e., primary and secondary control) coping responses. This may suggest that strong connections between brain regions supports more of a modulatory than a neglecting coping strategy. Finding also replicate extant literature on the ties between coping style and psychosocial distress. Given that coping responses are amenable to intervention, capitalizing on these brain-behavior links during ongoing neuromaturation is worthy of future research, with a goal of reducing symptoms of anxiety and depression via the brain's support of adaptive coping.

Non-Hispanic Black older adults experience a disproportionate burden of Alzheimer’s Disease and related dementias (ADRD) risk compared to non-Hispanic White older adults. It is necessary to identify mechanisms that may be contributing to inequities in cognitive aging. Psychosocial stressors that disproportionately affect Black adults (e.g., discrimination) have the potential to impact brain health through stress pathways. The brain’s white matter, which appears to be particularly important for ADRD risk among Black older adults, may be uniquely vulnerable to stress-related physiological dysfunction. To further understand whether and how discrimination can affect ADRD risk, this study aimed to examine associations between multiple forms of racial discrimination and white matter integrity, operationalized through diffusion tensor imaging.

Cross-sectional data were obtained from 190 non-Hispanic Black residents aged 65+ without dementia in northern Manhattan. Racial discrimination was self-reported using the Everyday Discrimination and Major Experiences of Lifetime Discrimination scales. Example items from the Everyday Discrimination Scale include: “You are treated with less respect than other people”; “You are called names or insulted.” Example items from the Major Experiences of Lifetime Discrimination Scale include: “At any time in your life, have you ever been unfairly fired from a job?”; “Have you ever been unfairly denied a bank loan?” Racial discrimination was operationalized as experiences attributed to “race” or “skin color.” White matter integrity was assessed using fractional anisotropy (FA) via diffusion tensor imaging. Multivariable regression models evaluated the unique effects of everyday and major experiences of lifetime racial discrimination on mean FA in the whole brain and specific regions. Initial models controlled for age, sex/gender, intracranial volume, and white matter hyperintensities. Subsequent models additionally controlled for socioeconomic and health factors to consider potential confounders or mediators of the relationship between discrimination and white matter integrity.

Major experiences of lifetime discrimination were negatively associated with mean FA within the left cingulum cingulate gyrus and the right inferior fronto-occipital fasciculus. These associations persisted when controlling for additional covariates (i.e., education, depression, and cardiovascular diseases). In contrast, major experiences of lifetime discrimination were positively associated with mean FA within the right superior longitudinal fasciculus (temporal part). This association was attenuated when controlling for additional covariates. Everyday racial discrimination was not associated with mean FA in any regions.

These results extend prior work linking racial discrimination to brain health and provide evidence for both risk and resilience among Black older adults. Major experiences of lifetime racial discrimination, a proxy for institutional racism, may have a stronger effect on white matter integrity than everyday racial discrimination, a proxy for interpersonal racism. Educational opportunities and cardiovascular risk factors may represent mediators between racial discrimination and white matter integrity. White matter integrity within specific brain regions may be a mechanism through which racially patterned social stressors contribute to racial disparities in ADRD. Future research should characterize within-group heterogeneity in order to identify factors that promote resilience among Black older adults.

Blast-related traumatic brain injury (bTBI) is one of the most common injuries among Veterans who have served in recent wars in Iraq and Afghanistan. Despite representing a distinct mechanism of injury, long-term clinical and functional outcomes of bTBI are generally comparable with non-blast-related traumatic brain injury (TBI). However, controversy remains over whether bTBI etiology differentially impacts emotional regulation and neurocognition - particularly with respect to post-traumatic stress disorder (PTSD) and verbal and visual memory. Through diffusion tensor imaging (DTI), the present study investigates the microstructural pathophysiology of bTBI, compared to non-blast TBI, in neural pathways involved in emotional regulation and cognitive control.

Participants included 36 Veterans (25% female; age M = 36.33, SD = 10.11; years of education M = 15.67, SD = 2.34). Axial diffusivity (AD) in networks of emotional and cognitive control was acquired using magnetic resonance imaging (MRI) with a DTI protocol. Analyses of variance (ANOVA) were used to compare Veterans with self-reported bTBI (n = 23) to those with non-blast-related TBI (n = 13).

In the left hemisphere, Veterans with bTBI exhibited significantly smaller AD in axonal projections from the caudate nucleus (CN) to the orbitofrontal cortex (OFC), as well as in projections from the putamen to the OFC (p < 0.05). In the right hemisphere, Veterans with bTBI also exhibited significantly smaller AD in networks connecting the hippocampus to the amygdala (p < 0.05).

Compared to Veterans with non-blast-related TBI, Veterans with bTBI exhibited decreased AD in neural pathways from the CN to the OFC, the putamen to the OFC, and the hippocampus to the amygdala - indicative of increased axonal injury in these areas. Our results suggest that, on a microstructural level, emotional and cognitive networks are susceptible to longitudinal blast-related white matter damage. This is consistent with the literature in post-concussion syndrome (PCS) and provides a potential mechanism underlying results previously reported from this sample, describing subjective cognitive complaints in the absence of objective clinical deficits. As such, therapies that target networks of emotional and cognitive control may be particularly beneficial for Veterans with bTBI.