Explore the vast range of titles available.

Post-traumatic stress disorder (PTSD) is a prevalent, debilitating and sometimes deadly consequence of exposure to severe psychological trauma. Although effective treatments exist for some individuals, they are limited. New approaches to intervention, treatment and prevention are therefore much needed. In the past few years, the field has rapidly developed a greater understanding of the dysfunctional brain circuits underlying PTSD, a shift in understanding that has been made possible by technological revolutions that have allowed the observation and perturbation of the macrocircuits and microcircuits thought to underlie PTSD-related symptoms. These advances have allowed us to gain a more translational knowledge of PTSD, have provided further insights into the mechanisms of risk and resilience and offer promising avenues for therapeutic discovery.

Resilience in the face of major life stressors is changeable over time and with experience. Accordingly, differing sets of neurobiological factors may contribute to an adaptive stress response before, during, and after the stressor. Longitudinal studies are therefore particularly effective in answering questions about the determinants of resilience. Here we provide an overview of the rapidly-growing body of longitudinal neuroimaging research on stress resilience. Despite lingering gaps and limitations, these studies are beginning to reveal individual differences in neural circuit structure and function that appear protective against the emergence of future psychopathology following a major life stressor. Here we outline a neural circuit model of resilience to trauma. Specifically, pre-trauma biomarkers of resilience show that an ability to modulate activity within threat and salience networks predicts fewer stress-related symptoms. In contrast, early post-trauma biomarkers of subsequent resilience or recovery show a more complex pattern, spanning a number of major circuits including attention and cognitive control networks as well as primary sensory cortices. This novel synthesis suggests stress resilience may be scaffolded by stable individual differences in the processing of threat cues, and further buttressed by post-trauma adaptations to the stressor that encompass multiple mechanisms and circuits. More attention and resources supporting this work will inform the targets and timing of mechanistic resilience-boosting interventions.

Trauma-related pathological dissociation is characterized by disruptions in one’s sense of self, perceptual, and affective experience. Dissociation and its trauma-related antecedents disproportionately impact women. However, despite the gender-related prevalence and high individual and societal costs, dissociation remains widely underappreciated in clinical practice. Moreover, dissociation lacks a synthesized neurobiological model across its subtypes. Leveraging the Triple Network Model of psychopathology, we sought to parse heterogeneity in dissociative experience by examining functional connectivity of three core neurocognitive networks as related to: (1) the dimensional dissociation subtypes of depersonalization/derealization and partially-dissociated intrusions; and, (2) the diagnostic category of dissociative identity disorder (DID). Participants were 91 women with and without: a history of childhood trauma, current posttraumatic stress disorder (PTSD), and varied levels of dissociation. Participants provided clinical data about dissociation, PTSD symptoms, childhood maltreatment history, and completed a resting-state functional magnetic resonance imaging scan. We used a novel statistical approach to assess both overlapping and unique contributions of dissociation subtypes. Covarying for age, childhood maltreatment and PTSD severity, we found dissociation was linked to hyperconnectivity within central executive (CEN), default (DN), and salience networks (SN), and decreased connectivity of CEN and SN with other areas. Moreover, we isolated unique connectivity markers associated with depersonalization/derealization in CEN and DN, to partially-dissociated intrusions in CEN, and to DID in CEN. This suggests dissociation subtypes have robust functional connectivity signatures that may serve as targets for PTSD/DID treatment engagement. Our findings underscore dissociation assessment as crucial in clinical care, in particular, to reduce gender-related health disparities.

Sexual trauma (ST) occurs with alarming frequency in the United States in the form of both childhood sexual abuse (CSA) and adulthood sexual assault (ASA). It is well established that the effects of ST are pervasive and that ST can be a risk factor for the development of several psychiatric disorders. However, the potential for distinct psychological consequences or neural correlates between CSA and ASA has received little attention. Furthermore, despite the high prevalence of sexual revictimization, the combinatorial effects of CSA and ASA are understudied in comparison to each form of ST on its own. In the current review, we present results from both clinical psychology and neuroscience research on the impacts of CSA and ASA, describing major psychological, biopsychosocial, and neuroimaging findings for each form of ST. We further highlight limitations in the current state of the research and needed areas of future research to better understand the distinct, overlapping, and cumulative effects of ST in both childhood and adulthood. The present study summarizes the state of the literature on this critical form of trauma and provides recommendations for future clinical research practices to mitigate the deleterious outcomes of ST.

A brief mindfulness intervention diminished bias in favor of one’s in-group and against one’s out-group. In the linguistic intergroup bias (LIB), individuals expect in-group members to behave positively and out-group members to behave negatively. Consequently, individuals choose abstract language beset with character inferences to describe these expected behaviors, and in contrast, choose concrete, objective language to describe unexpected behaviors. Eighty-four participants received either mindful attention instructions (observe their thoughts as fleeting mental states) or immersion instructions (become absorbed in the vivid details of thoughts). After instruction, participants viewed visual depictions of an imagined in-group or out-group member’s positive or negative behavior, selecting the best linguistic description from a set of four descriptions that varied in abstractness. Immersion groups demonstrated a robust LIB. Mindful attention groups, however, exhibited a markedly tempered LIB, suggesting that even a brief mindfulness related instruction can implicitly reduce the propensity to perpetuate stereotypical thinking through language. These results contribute to understanding the mechanisms that facilitate unprejudiced thinking.

Background: Suicide is a leading cause of death, and rates of attempted suicide have increased during the COVID-19 pandemic. The under-diagnosed psychiatric phenotype of dissociation is associated with elevated suicidal self-injury; however, it has largely been left out of attempts to predict and prevent suicide. Objective: We designed an artificial intelligence approach to identify dissociative patients and predict prior suicide attempts in an unbiased, data-driven manner. Method: Participants were 30 controls and 93 treatment-seeking female patients with posttraumatic stress disorder (PTSD) and various levels of dissociation, including some with the PTSD dissociative subtype and some with dissociative identity disorder (DID). Results: Unsupervised learning models identified patients along a spectrum of dissociation. Moreover, supervised learning models accurately predicted prior suicide attempts with an F 1 score up to 0.83. DID had the highest risk of prior suicide attempts, and distinct subtypes of dissociation predicted suicide attempts in PTSD and DID. Conclusions: These findings expand our understanding of the dissociative phenotype and underscore the urgent need to assess for dissociation to identify individuals at high-risk of suicidal self-injury. Dissociation, feelings of detachment and disruption in one's sense of self and surroundings, is associated with an elevated risk of suicidal self-injury; however, it has largely been left out of attempts to predict and prevent suicide. Using machine learning techniques, we found dissociative identity disorder had the highest risk of prior suicide attempts, and distinct subtypes of dissociation predicted suicide attempts in posttraumatic stress disorder and dissociative identity disorder. These findings underscore the urgent need to assess for dissociation to identify individuals at high-risk of suicidal self-injury.

Neurobiological markers of future susceptibility to posttraumatic stress disorder (PTSD) may facilitate identification of vulnerable individuals in the early aftermath of trauma. Variability in resting-state networks (RSNs), patterns of intrinsic functional connectivity across the brain, has previously been linked to PTSD, and may thus be informative of PTSD susceptibility. The present data are part of an initial analysis from the AURORA study, a longitudinal, multisite study of adverse neuropsychiatric sequalae. Magnetic resonance imaging (MRI) data from 109 recently (i.e., ~2 weeks) traumatized individuals were collected and PTSD and depression symptoms were assessed at 3 months post trauma. We assessed commonly reported RSNs including the default mode network (DMN), central executive network (CEN), and salience network (SN). We also identified a proposed arousal network (AN) composed of a priori brain regions important for PTSD: the amygdala, hippocampus, mamillary bodies, midbrain, and pons. Primary analyses assessed whether variability in functional connectivity at the 2-week imaging timepoint predicted 3-month PTSD symptom severity. Left dorsolateral prefrontal cortex (DLPFC) to AN connectivity at 2 weeks post trauma was negatively related to 3-month PTSD symptoms. Further, right inferior temporal gyrus (ITG) to DMN connectivity was positively related to 3-month PTSD symptoms. Both DLPFC-AN and ITG-DMN connectivity also predicted depression symptoms at 3 months. Our results suggest that, following trauma exposure, acutely assessed variability in RSN connectivity was associated with PTSD symptom severity approximately two and a half months later. However, these patterns may reflect general susceptibility to posttraumatic dysfunction as the imaging patterns were not linked to specific disorder symptoms, at least in the subacute/early chronic phase. The present data suggest that assessment of RSNs in the early aftermath of trauma may be informative of susceptibility to posttraumatic dysfunction, with future work needed to understand neural markers of long-term (e.g., 12 months post trauma) dysfunction. Furthermore, these findings are consistent with neural models suggesting that decreased top-down cortico-limbic regulation and increased network-mediated fear generalization may contribute to ongoing dysfunction in the aftermath of trauma.

Adolescent psychiatric rehospitalizations are common, cause patients and their families severe psychological distress, and use tremendous healthcare resources. This study sought to identify predictors of rehospitalization in 783 adolescents in the 2 year period following psychiatric hospitalization at a major treatment facility in a large urban area. A current diagnosis of posttraumatic stress disorder, greater severity of lifetime suicidal ideation (SI) and stronger treatment alliance prior to hospitalization were associated with a greater likelihood of rehospitalization. Overall, severe lifetime SI was the strongest predictor of rehospitalization; although, within the first 4 months post-discharge, moderate lifetime SI was the strongest predictor. Future research should continue to identify additional factors that may influence rehospitalization, such as the intensity of post-discharge services.

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.