Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Effects of mTBI with loss of consciousness on neurobehavioral symptoms, depression, and insomnia in former collegiate and NFL football athletes.

OBJECTIVE: Considering that diagnostic decisions about mTBI are often predicated on clinical symptom criteria, it is imperative to determine which initial presentation features of mTBI have prognostic significance for identifying those at high risk for long-term functional impairment. SETTING: Zoom interview Participants: Male, former NCAA Division I, and professional-level National Football League (NFL) athletes (n = 177) between the ages of 27 and 85 (M = 54.1, SD = 14.7). DESIGN: Cross-sectional case-control. Main Measures: History of mild TBI, history of loss of consciousness (LOC), depression symptoms, insomnia, neurobehavioral symptoms. RESULTS: Number of mTBI exposures did not predict neurobehavioral symptoms (B = 0.21, SE = 0.18, p = 0.23), but number of mTBI + LOC events did (B = 2.27, SE = 0.64, p = <.001). Further analysis revealed that the number of mTBI + LOC events predicted neurobehavioral symptoms indirectly through both depression (B = 0.85, 95% CI = [0.27, 1.52) and insomnia (B = 0.81, 95% CI = [0.3, 1.4]). Further, the direct effect of mTBI + LOC events on neurobehavioral symptoms became non-significant when depression and insomnia were added to the model (B = 0.78, SE = 0.45, p = 0.08). CONCLUSIONS: Findings support LOC at time of injury as an important predictor of long-term outcomes. Additionally, results suggest depression and insomnia as potential mediators in the association between mTBI + LOC and neurobehavioral symptoms. These findings provide justification for early depression and insomnia symptom monitoring following mTBI + LOC.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Care Disruption During COVID-19: a National Survey of Hospital Leaders.

BACKGROUND: The COVID-19 pandemic caused massive disruption in usual care delivery patterns in hospitals across the USA, and highlighted long-standing inequities in health care delivery and outcomes. Its effect on hospital operations, and whether the magnitude of the effect differed for hospitals serving historically marginalized populations, is unknown. OBJECTIVE: To investigate the perspectives of hospital leaders on the effects of COVID-19 on their facilities' operations and patient outcomes. METHODS: A survey was administered via print and electronic means to hospital leaders at 588 randomly sampled acute-care hospitals participating in Medicare's Inpatient Prospective Payment System, fielded from November 2020 to June 2021. Summary statistics were tabulated, and responses were adjusted for sampling strategy and non-response. RESULTS: There were 203 responses to the survey (41.6%), with 20.7% of respondents representing safety-net hospitals and 19.7% representing high-minority hospitals. Over three-quarters of hospitals reported COVID testing shortages, about two-thirds reported staffing shortages, and 78.8% repurposed hospital spaces to intensive care units, with a slightly higher proportion of high-minority hospitals reporting these effects. About half of respondents felt that non-COVID inpatients received worsened quality or outcomes during peak COVID surges, and almost two-thirds reported worsened quality or outcomes for outpatient non-COVID patients as well, with few differences by hospital safety-net or minority status. Over 80% of hospitals participated in alternative payment models prior to COVID, and a third of these reported decreasing these efforts due to the pandemic, with no differences between safety-net and high-minority hospitals. CONCLUSIONS: COVID-19 significantly disrupted the operations of hospitals across the USA, with hospitals serving patients in poverty and racial and ethnic minorities reporting relatively similar care disruption as non-safety-net and lower-minority hospitals.

Attributional negativity bias and acute stress disorder symptoms mediate the association between trauma history and future posttraumatic stress disorder.

Individuals who have experienced more trauma throughout their life have a heightened risk of developing posttraumatic stress disorder (PTSD) following injury. Although trauma history cannot be retroactively modified, identifying the mechanism(s) by which preinjury life events influence future PTSD symptoms may help clinicians mitigate the detrimental effects of past adversity. The current study proposed attributional negativity bias, the tendency to perceive stimuli/events as negative, as a potential intermediary in PTSD development. We hypothesized an association between trauma history and PTSD symptom severity following a new index trauma via heightened negativity bias and acute stress disorder (ASD) symptoms. Recent trauma survivors (N =189, 55.5% women, 58.7% African American/Black) completed assessments of ASD, negativity bias, and lifetime trauma 2-weeks postinjury; PTSD symptoms were assessed 6 months later. A parallel mediation model was tested with bootstrapping (10,000 resamples). Both negativity bias, Path b1 : ß = -.24, t(187) = -2.88, p = .004, and ASD symptoms, Path b2 : ß = .30, t(187) = 3.71, p < .001, fully mediated the association between trauma history and 6-month PTSD symptoms, full model: F(6, 182) = 10.95, p < .001, R 2 = .27; Path c': ß = .04, t(187) = 0.54, p = .587. These results suggest that negativity bias may reflect an individual cognitive difference that can be further activated by acute trauma. Moreover, negativity bias may be an important, modifiable treatment target, and interventions addressing both acute symptoms and negativity bias in the early posttrauma period may weaken the link between trauma history and new-onset PTSD.

Neural substrates of human fear generalization: A 7T-fMRI investigation.

Fear generalization - the tendency to interpret ambiguous stimuli as threatening due to perceptual similarity to a learned threat - is an adaptive process. Overgeneralization, however, is maladaptive and has been implicated in a number of anxiety disorders. Neuroimaging research has indicated several regions sensitive to effects of generalization, including regions involved in fear excitation (e.g., amygdala, insula) and inhibition (e.g., ventromedial prefrontal cortex). Research has suggested several other small brain regions may play an important role in this process (e.g., hippocampal subfields, bed nucleus of the stria terminalis [BNST], habenula), but, to date, these regions have not been examined during fear generalization due to limited spatial resolution of standard human neuroimaging. To this end, we utilized the high spatial resolution of 7T fMRI to characterize the neural circuits involved in threat discrimination and generalization. Additionally, we examined potential modulating effects of trait anxiety and intolerance of uncertainty on neural activation during threat generalization. In a sample of 31 healthy undergraduate students, significant positive generalization effects (i.e., greater activation for stimuli with increasing perceptual similarity to a learned threat cue) were observed in the visual cortex, thalamus, habenula and BNST, while negative generalization effects were observed in the dentate gyrus, CA1, and CA3. Associations with individual differences were underpowered, though preliminary findings suggested greater generalization in the insula and primary somatosensory cortex may be correlated with self-reported anxiety. Overall, findings largely support previous neuroimaging work on fear generalization and provide additional insight into the contributions of several previously unexplored brain regions.

Agreement Between Self- and Informant-Reported Ratings of Personality Traits: The Moderating Effects of Major Depressive and/or Panic Disorder.

Several personality traits are risk factors for psychopathology. As symptoms of psychopathology may influence self-rated personality, informant reports of personality are also sometimes collected. However, little is known about self-informant agreement in individuals with anxiety and/or depression. We investigated whether self-informant agreement on positive and negative affectivity (PA and NA) and anxiety sensitivity differs for individuals with major depressive disorder (MDD) and/or panic disorder (PD; total n = 117). Informant- and self-reported PA was correlated among those with MDD, but not among those without MDD. Informant- and self-reported anxiety sensitivity was correlated among those with PD, but not among those without PD. Informant- and self-reported NA was correlated irrespective of diagnosis. Results indicate that the agreement of self- and informant-reported personality may vary as a function of depression and/or anxiety disorders.

Childhood Maltreatment and Amygdala-Mediated Anxiety and Posttraumatic Stress Following Adult Trauma.

Background: Childhood abuse (physical, emotional, and sexual) is associated with aberrant connectivity of the amygdala, a key threat-processing region. Heightened amygdala activity also predicts adult anxiety and posttraumatic stress disorder (PTSD) symptoms, as do experiences of childhood abuse. The current study explored whether amygdala resting-state functional connectivity may explain the relationship between childhood abuse and anxiety and PTSD symptoms following trauma exposure in adults. Methods: Two weeks posttrauma, adult trauma survivors (n = 152, mean age [SD] = 32.61 [10.35] years; women = 57.2%) completed the Childhood Trauma Questionnaire and underwent resting-state functional magnetic resonance imaging. PTSD and anxiety symptoms were assessed 6 months posttrauma. Seed-to-voxel analyses evaluated the association between childhood abuse and amygdala resting-state functional connectivity. A mediation model evaluated the potential mediating role of amygdala connectivity in the relationship between childhood abuse and posttrauma anxiety and PTSD. Results: Childhood abuse was associated with increased amygdala connectivity with the precuneus while covarying for age, gender, childhood neglect, and baseline PTSD symptoms. Amygdala-precuneus resting-state functional connectivity was a significant mediator of the effect of childhood abuse on anxiety symptoms 6 months posttrauma (B = 0.065; 95% CI, 0.013-0.130; SE = 0.030), but not PTSD. A secondary mediation analysis investigating depression as an outcome was not significant. Conclusions: Amygdala-precuneus connectivity may be an underlying neural mechanism by which childhood abuse increases risk for anxiety following adult trauma. Specifically, this heightened connectivity may reflect attentional vigilance for threat or a tendency toward negative self-referential thoughts. Findings suggest that childhood abuse may contribute to longstanding upregulation of attentional vigilance circuits, which makes one vulnerable to anxiety-related symptoms in adulthood.

Experiences of childhood abuse are related to long-term mental health outcomes, but the mechanisms of this relationship have been unclear. In this study of adult trauma survivors, Harb et al. found that experiences of childhood abuse are related to abnormal connectivity patterns of the amygdala, a key region for fear and threat processing, and precuneus. These connectivity patterns were identified as a mechanism through which experiences of child abuse are related to adult anxiety symptoms posttrauma. These findings advance our understanding of the specific downstream impacts of experiencing childhood abuse and can inform targeted assessment and intervention methods, especially in an adult trauma sample.

The Dichotomy of Threat and Deprivation as Subtypes of Childhood Maltreatment: Differential Functional Connectivity Patterns of Threat and Reward Circuits in an Adult Trauma Sample.

BACKGROUND: Childhood maltreatment is associated with reduced activation of the nucleus accumbens, a central region in the reward network, and overactivity in the amygdala, a key region in threat processing. However, the long-lasting impact of these associations in the context of later-life stress is not well understood. The current study explored the association between childhood threat and deprivation and functional connectivity of threat and reward regions in an adult trauma sample. METHODS: Trauma survivors (N = 169; mean age [SD] = 32.2 [10.3] years; female = 55.6%) were recruited from a level I trauma center. Two weeks after injury, participants completed the Childhood Trauma Questionnaire (measuring experiences of threat and deprivation) and underwent resting-state functional magnetic resonance imaging. Seed-to-voxel analyses evaluated the effect of childhood threat and deprivation on amygdala and nucleus accumbens resting-state connectivity. RESULTS: Higher levels of threat were associated with increased connectivity between the right nucleus accumbens with temporal fusiform gyrus/parahippocampal gyrus and the left amygdala and the precuneus (false discovery rate-corrected p < .05). After controlling for posttraumatic symptoms 2 weeks posttrauma and lifetime trauma exposure, only the nucleus accumbens findings survived. There were no significant relationships between experiences of childhood deprivation and amygdala or nucleus accumbens connectivity. CONCLUSIONS: Experiences of threat are associated with increased nucleus accumbens and amygdala connectivity, which may reflect a preparedness to detect salient and visual stimuli. This may also reflect a propensity toward dysregulated reward processing. Overall, these results suggest that childhood threat may be contributing to aberrant neural baseline reward and threat sensitivity later in life in an adult trauma sample.

Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium.

Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n= 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. A random forest classification model was built on a training set using cross-validation, and the averaged cross-validation model performance for classification was evaluated using the area under the curve. The model was tested using a fully independent portion of the data (test dataset), and the test area under the curve was evaluated. Results: rsFC signatures differentiated TE-only participants from PTSD and ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontoparietal network, differentiated TE-only participants from one group (PTSD or ITRED-only) but to a lesser extent from the other group. Conclusions: Neural network connectivity supports ITRED as a novel neurobiologically based approach to classifying posttrauma psychopathology.

Neural processes of emotional conflict detection and prediction of posttraumatic stress disorder symptom clusters in traumatic injury survivors.

OBJECTIVE: Given the prevalence and significant burden of posttraumatic stress disorder (PTSD), identifying early predictors of symptom development following trauma is critical. PTSD is a heterogeneous disorder comprised of distinct symptom clusters-reexperiencing, avoidance, negative mood, and hyperarousal-that contribute to the broad range of possible symptom profiles. Affective and attentional regulation processes, such as emotional conflict detection, are impaired in individuals with PTSD; however, the neural mechanisms underlying these alterations and their predictive utility for the development of PTSD symptoms remain unclear. METHOD: Traumatic injury survivors (N = 49) without traumatic brain injury were recruited from the emergency department of an urban, Level-1 trauma center. Within 1 month of trauma exposure, participants completed a well-characterized emotional conflict task during a functional magnetic resonance imaging scan. Participants returned 6-month later for a clinical assessment of PTSD symptoms. Using a region-of-interest mask derived from whole-brain voxelwise analyses during emotional conflict detection (vs. no emotional conflict detection) we examined whether differential neural activity predicted 6-month PTSD symptom cluster severity. RESULTS: Greater activation of the right middle frontal gyrus during emotional conflict detection prospectively predicted lower PTSD avoidance symptom severity 6 months later (above and beyond the effects of self-reported baseline PTSD and depressive symptoms, previous traumatic life events, racial discrimination, age, sex, and injury severity). CONCLUSIONS: Neural processes of emotion conflict detection measured in the early aftermath of a potentially traumatic event are useful as predictors for the development of PTSD symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture.

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.

Articulation of postsurgical patient discharges: coordinating care transitions from hospital to home.

BACKGROUND: Cardiac surgery patients are at high risk for readmissions after hospital discharge- few of these readmissions are preventable by mitigating barriers underlying discharge care transitions. An in-depth evaluation of the nuances underpinning the discharge process and the use of tools to support the process, along with insights on patient and clinician experiences, can inform the design of evidence-based strategies to reduce preventable readmissions. OBJECTIVE: The study objectives are 3-fold: elucidate perceived factors affecting the postsurgical discharge care transitions of cardiac surgery patients going home; highlight differences among clinician and patient perceptions of the postsurgical discharge experiences, and ascertain the impact of these transitions on patient recovery at home. METHODS: We conducted a prospective multi-stakeholder study using mixed methods, including general observations, patient shadowing, chart reviews, clinician interviews, and follow-up telephone patient and caregiver surveys/interviews. We followed thematic and content analyses. FINDINGS: Participants included 49 patients, 6 caregivers, and 27 clinicians. We identified interdependencies between the predischarge preparation, discharge education, and postdischarge follow-up care phases that must be coordinated for effective discharge care transitions. We identified several factors that could lead to fragmented discharges, including limited preoperative preparation, ill-defined discharge education, and postoperative plans. To address these, clinicians often performed behind-the-scenes work, including offering informal preoperative preparation, tailoring discharge education, and personalizing postdischarge follow-up plans. As a result, majority of patients reported high satisfaction with care transitions and their positive impact on their home recovery. DISCUSSION AND CONCLUSIONS: Articulation work by clinicians (ie, behind the scenes work) is critical for ensuring safety, care continuity, and overall patient experience during care transitions. We discuss key evidence-based considerations for re-engineering postsurgical discharge workflows and re-designing discharge interventions.

A 7-Tesla MRI study of the periaqueductal gray: resting state and task activation under threat.

The periaqueductal gray (PAG) is a region of the midbrain implicated in a variety of behaviors including defensive responses to threat. Despite the wealth of knowledge pertaining to the differential functional roles of the PAG columns in nonhuman and human research, the basic functional connectivity of the PAG at rest has not been well characterized. Therefore, the current study utilized 7-Tesla magnetic resonance imaging (MRI) to characterize PAG functional connectivity at rest and task activation under uncertain threat. A sample of 53 neurologically healthy undergraduate participants (Mage = 22.2, s.d.age = 3.62) underwent structural and resting state functional MRI scans. Supporting previous work, voxel-wise analyses showed that the PAG is functionally connected to emotion regulation and fear networks. The comparison of functional connectivity of PAG columns did not reveal any significant differences. Thirty-five participants from the same sample also completed an uncertain threat task with blocks of three conditions-no shock, predictable shock and unpredictable shock. There were no robust activity differences within the PAG columns or the whole PAG across conditions although there was differential activity at the voxel level in the PAG and in other regions theoretically relevant to uncertain threat. Results of this study elucidate PAG connectivity at rest and activation in response to uncertain threat.

Hippocampal Resting-State Functional Connectivity Forecasts Individual Posttraumatic Stress Disorder Symptoms: A Data-Driven Approach.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a debilitating disorder, and there is no current accurate prediction of who develops it after trauma. Neurobiologically, individuals with chronic PTSD exhibit aberrant resting-state functional connectivity (rsFC) between the hippocampus and other brain regions (e.g., amygdala, prefrontal cortex, posterior cingulate), and these aberrations correlate with severity of illness. Previous small-scale research (n < 25) has also shown that hippocampal rsFC measured acutely after trauma is predictive of future severity using a region-of-interest-based approach. While this is a promising biomarker, to date, no study has used a data-driven approach to test whole-brain hippocampal FC patterns in forecasting the development of PTSD symptoms. METHODS: A total of 98 adults at risk of PTSD were recruited from the emergency department after traumatic injury and completed resting-state functional magnetic resonance imaging (8 min) within 1 month; 6 months later, they completed the Clinician-Administered PTSD Scale for DSM-5 for assessment of PTSD symptom severity. Whole-brain rsFC values with bilateral hippocampi were extracted (using CONN) and used in a machine learning kernel ridge regression analysis (PRoNTo); a k-folds (k = 10) and 70/30 testing versus training split approach were used for cross-validation (1000 iterations to bootstrap confidence intervals for significance values). RESULTS: Acute hippocampal rsFC significantly predicted Clinician-Administered PTSD Scale for DSM-5 scores at 6 months (r = 0.30, p = .006; mean squared error = 120.58, p = .006; R2 = 0.09, p = .025). In post hoc analyses, hippocampal rsFC remained significant after controlling for demographics, PTSD symptoms at baseline, and depression, anxiety, and stress severity at 6 months (B = 0.59, SE = 0.20, p = .003). CONCLUSIONS: Findings suggest that functional connectivity of the hippocampus across the brain acutely after traumatic injury is associated with prospective PTSD symptom severity.

Racial Discrimination and Resting-State Functional Connectivity of Salience Network Nodes in Trauma-Exposed Black Adults in the United States.

Importance: For Black US residents, experiences of racial discrimination are still pervasive and frequent. Recent empirical work has amplified the lived experiences and narratives of Black people and further documented the detrimental effects of racial discrimination on both mental and physical health; however, there is still a need for further research to uncover the mechanisms connecting experiences of racial discrimination with adverse health outcomes. Objective: To examine neurobiological mechanisms that may offer novel insight into the association of racial discrimination with adverse health outcomes. Design, Setting, and Participants: This cross-sectional study included 102 Black adults who had recently experienced a traumatic injury. In the acute aftermath of the trauma, participants underwent a resting-state functional magnetic resonance imaging scan. Individuals were recruited from the emergency department at a Midwestern level 1 trauma center in the United States between March 2016 and July 2020. Data were analyzed from February to May 2021. Exposures: Self-reported lifetime exposure to racial discrimination, lifetime trauma exposure, annual household income, and current posttraumatic stress disorder (PTSD) symptoms were evaluated. Main Outcomes and Measures: Seed-to-voxel analyses were conducted to examine the association of racial discrimination with connectivity of salience network nodes (ie, amygdala and anterior insula). Results: A total of 102 individuals were included, with a mean (SD) age of 33 (10) years and 58 (57%) women. After adjusting for acute PTSD symptoms, annual household income, and lifetime trauma exposure, greater connectivity between the amygdala and thalamus was associated with greater exposure to discrimination (t(97) = 6.05; false discovery rate (FDR)-corrected P = .03). Similarly, racial discrimination was associated with greater connectivity between the insula and precuneus (t(97) = 4.32; FDR-corrected P = .02). Conclusions and Relevance: These results add to the mounting literature that racial discrimination is associated with neural correlates of vigilance and hyperarousal. The study findings extend this theory by showing that this association is apparent even when accounting for socioeconomic position, lifetime trauma, and symptoms of psychological distress related to an acute trauma.

Neighborhood Socioeconomic Disadvantage and the Neurobiology of Uncertainty in Traumatically Injured Adults.

BACKGROUND: Individuals residing in more socioeconomically disadvantaged neighborhoods experience greater uncertainty through insecurity of basic needs such as food, employment, and housing, compared with more advantaged neighborhoods. Although the neurobiology of uncertainty has been less frequently examined in relation to neighborhood disadvantage, there is evidence that neighborhood disadvantage is associated with widespread neural alterations. METHODS: Recently traumatically injured participants (n = 90) completed a picture anticipation task in the magnetic resonance imaging scanner, in which they viewed images presented in a temporally predictable or unpredictable manner. We investigated how neighborhood disadvantage (via area deprivation index [ADI]) was related to neural activation during anticipation and presentation of negative and neutral images after accounting for individual factors (i.e., age, gender, income, acute posttraumatic stress symptoms). RESULTS: There was a significant interaction during the anticipation period such that higher ADI rankings were related to greater activation of the right anterior cingulate cortex to predictable versus unpredictable neutral stimuli. Although no other robust interactions emerged related to ADI, we note several novel simple effects of ADI during anticipation and presentation periods in the hippocampus and prefrontal, cingulate, and occipital cortices. CONCLUSIONS: Together, these results may represent an adaptive response to predictable and/or negative stimuli, stemming from chronic exposure to socioeconomic-based uncertainties. Although effects were modest, future work should continue to examine pretrauma context on posttrauma outcomes. To better understand trauma outcomes, it is imperative that researchers consider the broader context in which trauma survivors reside.

Neighborhood Disadvantage Associated With Blunted Amygdala Reactivity to Predictable and Unpredictable Threat in a Community Sample of Youth.

BACKGROUND: Childhood socioeconomic disadvantage is a form of adversity associated with alterations in critical frontolimbic circuits involved in the pathophysiology of psychiatric disorders. Most work has focused on individual-level socioeconomic position, yet individuals living in deprived communities typically encounter additional environmental stressors that have unique effects on the brain and health outcomes. Notably, chronic and unpredictable stressors experienced in the everyday lives of youth living in disadvantaged neighborhoods may impact neural responsivity to uncertain threat. METHODS: A community sample of children (N = 254) ages 8 to 15 years (mean = 12.15) completed a picture anticipation task during a functional magnetic resonance imaging scan, during which neutral and negatively valenced photos were presented in a temporally predictable or unpredictable manner. Area Deprivation Index (ADI) scores were derived from participants' home addresses as an index of relative neighborhood disadvantage. Voxelwise analyses examined interactions of ADI, valence, and predictability on neural response to picture presentation. RESULTS: There was a significant ADI × valence interaction in the middle temporal gyrus, anterior cingulate cortex, hippocampus, and amygdala. Higher ADI was associated with less amygdala activation to negatively valenced images. ADI also interacted with predictability. Higher ADI was associated with greater activation of lingual and calcarine gyri for unpredictably presented stimuli. There was no three-way interaction of ADI, valence, and predictability. CONCLUSIONS: Neighborhood disadvantage may impact how the brain perceives and responds to potential threats. Future longitudinal work is critical for delineating how such effects may persist across the life span and how health outcomes may be modifiable with community-based interventions and policies.

Resting state functional connectivity in the default mode network: Relationships between cannabis use, gender, and cognition in adolescents and young adults.

INTRODUCTION: Cannabis is the most commonly used illicit substance in the United States, and nearly 1 in 4 young adults are current cannabis users. Chronic cannabis use is associated with changes in resting state functional connectivity (RSFC) in the default mode network (DMN) in adolescents and young adults; results are somewhat inconsistent across studies, potentially due to methodological differences. The aims of the present study were to examine potential differences in DMN RSFC between cannabis users and controls, and to examine, as an exploratory analysis, if gender moderated any findings. We further examined whether differences in RSFC related to differences in performance on selected neuropsychological measures. MATERIALS AND METHODS: Seventy-seven 16-26-year-old participants underwent an MRI scan (including resting state scan), neuropsychological battery, toxicology screening, and drug use interview. Differences in DMN connectivity were examined between groups (cannabis vs. control) and with an exploratory group by gender interaction, using a left posterior cingulate cortex (PCC) seed-based analysis conducted in AFNI. RESULTS: Cannabis users demonstrated weaker connectivity than controls between the left PCC and various DMN nodes, and the right Rolandic operculum/Heschl's gyrus. Cannabis users demonstrated stronger connectivity between the left PCC and the cerebellum and left supramarginal gyrus. The group by gender interaction was not significantly associated with connectivity differences. Stronger left PCC-cerebellum connectivity was associated with poorer performance on cognitive measures in cannabis users. In controls, intra-DMN connectivity was positively correlated with performance on a speeded selective/sustained attention measure. DISCUSSION: Consistent with our hypotheses and other studies, cannabis users demonstrated weaker connectivity between the left PCC and DMN nodes. Chronic THC exposure may alter GABA and glutamate concentrations, which may alter brain communication. Future studies should be conducted with a larger sample size and examine gender differences and the mechanism by which these differences may arise.