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.

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.

Attention allocation to negatively-valenced stimuli in PTSD is associated with reward-related neural pathways.

BACKGROUND: In a recent eye-tracking study we found a differential dwell time pattern for negatively-valenced and neutral faces among patients with posttraumatic stress disorder (PTSD), trauma-exposed healthy control (TEHCs), and healthy control (HC) participants. Here, we explored whether these group differences relate to resting-state functional connectivity (rsFC) patterns of brain areas previously linked to both attention processes and PTSD. These encompass the amygdala, dorsal anterior cingulate cortex (dACC), dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (vlPFC), and nucleus accumbens (NAcc). METHODS: Ten minutes magnetic resonance imaging rsFC scans were recorded in 17 PTSD patients, 21 TEHCs, and 16 HCs. Participants then completed a free-viewing eye-tracking task assessing attention allocation outside the scanner. Dwell time on negatively-valenced stimuli (DT%) were assessed relative to functional connectivity in the aforementioned seed regions of interest (amygdala, dACC, dlPFC, vlPFC, and NAcc) to whole-brain voxel-wise rsFC. RESULTS: As previously reported, group differences occurred in attention allocation to negative-valence stimuli, with longer dwell time on negatively valence stimuli in the PTSD and TEHC groups than the HC group. Higher DT% correlated with weaker NAcc-orbitofrontal cortex (OFC) connectivity in patients with PTSD. Conversely, a positive association emerged in the HC group between DT% and NAcc-OFC connectivity. CONCLUSIONS: While exploratory in nature, present findings may suggest that reward-related brain areas are involved in disengaging attention from negative-valenced stimuli, and possibly in regulating ensuing negative emotions.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites.

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 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 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 was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Elucidating behavioral and functional connectivity markers of aberrant threat discrimination in PTSD.

BACKGROUND: Patients with posttraumatic stress disorder (PTSD) tend to overgeneralize threat to safe stimuli, potentially reflecting aberrant stimuli discrimination. Yet, it is not clear whether threat overgeneralization reflects general discrimination deficits, or rather a specific bias related to aversive stimuli. Here we tested this question and characterized the neural correlates of threat discrimination. METHODS: One-hundred and eight participants (33 PTSD; 43 trauma-exposed controls; 32 healthy controls) completed an emotionally neutral complex shape discrimination task involving identifying in 42 similar pairs the previously observed shape; and an emotionally aversive discrimination task, involving providing risk ratings for an aversive conditioned stimulus (CS+), and for several stimuli gradually differing in size from the original CS+. Resting state functional connectivity (rsFC) was collected before completing the tasks. RESULTS: No group differences emerged on the emotionally neutral task. Conversely, on the emotionally aversive task, individuals with PTSD had steeper linear risk rating slopes as the stimuli more resembled the conditioned stimulus. Finally, lower rsFC of amygdala-default mode network (DMN) and DMN-salience network (SN) were associated with steeper risk slopes, while for hippocampus-SN, lower rsFC was found only among participants with PTSD. CONCLUSIONS: Individuals with PTSD show deficits in discrimination only when presented with aversive stimuli. Dysregulated discrimination pattern may relate to a lack of input from regulatory brain areas (e.g., DMN/hippocampus) to threat-related brain areas (e.g., SN/amygdala).

Structural brain features signaling trauma, PTSD, or resilience? A systematic exploration.

BACKGROUND: Studies have searched for neurobiological markers of trauma exposure, posttraumatic stress disorder (PTSD) diagnosis, and resilience to trauma to identify therapeutic targets for PTSD. Despite some promising results, findings are inconsistent. AIMS: The present study adopted a data-driven approach to systematically explore whether structural brain markers of trauma, PTSD, or resilience emerge when all are explored. MATERIALS & METHODS: Differences between clusters in the proportion of PTSD, healthy controls (HC), and trauma-exposed healthy controls (TEHC) served to indicate the presence of PTSD, trauma, and resilience markers, respectively. A total of 129 individuals, including 46 with PTSD, 49 TEHCs, and 34 HCs not exposed to trauma were scanned. Volumes, cortical thickness, and surface areas of interest were obtained from T1 structural MRI and used to identify data-driven clusters. RESULTS: Two clusters were identified, differing in the proportion of TEHCs but not of PTSDs or HCs. The cluster with the higher proportion of TEHCs, referred to as the resilience cluster, was characterized by higher volume in brain regions implicated in trauma exposure, especially the thalamus and rostral middle frontal gyrus. Cross-validation established the robustness and consistency of the identified clusters. DISCUSSION & CONCLUSION: Findings support the existence of structural brain markers of resilience.

Neural changes following equine-assisted therapy for posttraumatic stress disorder: A longitudinal multimodal imaging study.

BACKGROUND: While effective treatments for posttraumatic stress disorder (PTSD) exist, many individuals, including military personnel and veterans fail to respond to them. Equine-assisted therapy (EAT), a novel PTSD treatment, may complement existing PTSD interventions. This study employs longitudinal neuro-imaging, including structural magnetic resonance imaging (sMRI), resting state-fMRI (rs-fMRI), and diffusion tensor imaging (DTI), to determine mechanisms and predictors of EAT outcomes for PTSD. METHOD: Nineteen veterans with PTSD completed eight weekly group sessions of EAT undergoing multimodal MRI assessments before and after treatment. Clinical assessments were conducted at baseline, post-treatment and at 3-month follow-up. RESULTS: At post-treatment patients showed a significant increase in caudate functional connectivity (FC) and reduction in the gray matter density of the thalamus and the caudate. The increase of caudate FC was positively associated with clinical improvement seen immediately at post-treatment and at 3-month follow-up. In addition, higher baseline caudate FC was associated with greater PTSD symptom reduction post-treatment. CONCLUSIONS: This exploratory study is the first to demonstrate that EAT can affect functional and structural changes in the brains of patients with PTSD. The findings suggest that EAT may target reward circuitry responsiveness and produce a caudate pruning effect from pre- to post-treatment.

Attention allocation in posttraumatic stress disorder: an eye-tracking study.

BACKGROUND: Eye-tracking-based attentional research implicates sustained attention to threat in posttraumatic stress disorder (PTSD). However, most of this research employed small stimuli set-sizes, small samples that did not include both trauma-exposed healthy participants and non-trauma-exposed participants, and generally failed to report the reliability of used tasks and attention indices. Here, using an established eye-tracking paradigm, we explore attention processes to different negatively-valenced cues in PTSD while addressing these limitations. METHODS: PTSD patients (n = 37), trauma-exposed healthy controls (TEHC; n = 34), and healthy controls (HC; n = 30) freely viewed three blocks of 30 different matrices of faces, each presented for 6 s. Each block consisted of matrices depicting eight negatively-valenced faces (anger, fear, or sadness) and eight neutral faces. Gaze patterns on negative and neural areas of interest were compared. Internal consistency and test-retest reliability were evaluated for the entire sample and within groups. RESULTS: The two trauma-exposed groups dwelled longer on negatively-valenced faces over neutral faces, while HC participants showed the opposite pattern. This attentional bias was more prominent in the PTSD than the TEHC group. Similar results emerged for first-fixation dwell time, but with no differences between the two trauma-exposed groups. No group differences emerged for first-fixation latency or location. Internal consistency and 1-week test-retest reliability were adequate, across and within groups. CONCLUSIONS: Sustained attention on negatively-valenced stimuli emerges as a potential target for therapeutic intervention in PTSD designed to divert attention away from negatively-valenced stimuli and toward neutral ones.

Linked networks for learning and expressing location-specific threat.

Learning locations of danger within our environment is a vital adaptive ability whose neural bases are only partially understood. We examined fMRI brain activity while participants navigated a virtual environment in which flowers appeared and were "picked." Picking flowers in the danger zone (one-half of the environment) predicted an electric shock to the wrist (or "bee sting"); flowers in the safe zone never predicted shock; and household objects served as controls for neutral spatial memory. Participants demonstrated learning with shock expectancy ratings and skin conductance increases for flowers in the danger zone. Patterns of brain activity shifted between overlapping networks during different task stages. Learning about environmental threats, during flower approach in either zone, engaged the anterior hippocampus, amygdala, and ventromedial prefrontal cortex (vmPFC), with vmPFC-hippocampal functional connectivity increasing with experience. Threat appraisal, during approach in the danger zone, engaged the insula and dorsal anterior cingulate (dACC), with insula-hippocampal functional connectivity. During imminent threat, after picking a flower, this pattern was supplemented by activity in periaqueductal gray (PAG), insula-dACC coupling, and posterior hippocampal activity that increased with experience. We interpret these patterns in terms of multiple representations of spatial context (anterior hippocampus); specific locations (posterior hippocampus); stimuli (amygdala); value (vmPFC); threat, both visceral (insula) and cognitive (dACC); and defensive behaviors (PAG), interacting in different combinations to perform the functions required at each task stage. Our findings illuminate how we learn about location-specific threats and suggest how they might break down into overgeneralization or hypervigilance in anxiety disorders.

On the validity of the centrality hypothesis in cross-sectional between-subject networks of psychopathology.

BACKGROUND: In the network approach to psychopathology, psychiatric disorders are considered networks of causally active symptoms (nodes), with node centrality hypothesized to reflect symptoms' causal influence within a network. Accordingly, centrality measures have been used in numerous network-based cross-sectional studies to identify specific treatment targets, based on the assumption that deactivating highly central nodes would proliferate to other nodes in the network, thereby collapsing the network structure and alleviating the overall psychopathology (i.e., the centrality hypothesis). METHODS: Here, we summarize three types of evidence pertaining to the centrality hypothesis in psychopathology. First, we discuss the validity of the theoretical assumptions underlying the centrality hypothesis in psychopathology. We then summarize the methodological aspects of extant studies using centrality measures as predictors of symptom change following treatment, while delineating their main findings and several of their limitations. Finally, using a specific dataset of 710 treatment-seeking patients with posttraumatic stress disorder (PTSD) as an example, we empirically examine node centrality as a predictor of therapeutic change, replicating the approach taken by previous studies, while addressing some of their limitations. Specifically, we investigated whether three pre-treatment centrality indices (strength, predictability, and expected influence) were significantly correlated with the strength of the association between a symptom's change and the change in the severity of all other symptoms in the network from pre- to post-treatment (Δnode-Δnetwork association). Using similar analyses, we also examine the predictive validity of two simple non-causal node properties (mean symptom severity and infrequency of symptom endorsement). RESULTS: Of the three centrality measures, only expected influence successfully predicted how strongly changes in nodes/symptoms were associated with change in the remainder of the nodes/symptoms. Importantly, when excluding the amnesia node, a well-documented outlier in the phenomenology of PTSD, none of the tested centrality measures predicted symptom change. Conversely, both mean symptom severity and infrequency of symptom endorsement, two standard non-network-derived indices, were found to be more predictive than expected influence and remained significantly predictive also after excluding amnesia from the network analyses. CONCLUSIONS: The centrality hypothesis in its current form is ill-defined, showing no consistent supporting evidence in the context of cross-sectional, between-subject networks.

Neural signatures of conditioning, extinction learning, and extinction recall in posttraumatic stress disorder: a meta-analysis of functional magnetic resonance imaging studies.

BACKGROUND: Establishing neurobiological markers of posttraumatic stress disorder (PTSD) is essential to aid in diagnosis and treatment development. Fear processing deficits are central to PTSD, and their neural signatures may be used as such markers. METHODS: Here, we conducted a meta-analysis of seven Pavlovian fear conditioning fMRI studies comparing 156 patients with PTSD and 148 trauma-exposed healthy controls (TEHC) using seed-based d-mapping, to contrast neural correlates of experimental phases, namely conditioning, extinction learning, and extinction recall. RESULTS: Patients with PTSD, as compared to TEHCs, exhibited increased activation in the anterior hippocampus (extending to the amygdala) and medial prefrontal cortex during conditioning; in the anterior hippocampus-amygdala regions during extinction learning; and in the anterior hippocampus-amygdala and medial prefrontal areas during extinction recall. Yet, patients with PTSD have shown an overall decreased activation in the thalamus during all phases in this meta-analysis. CONCLUSION: Findings from this metanalysis suggest that PTSD is characterized by increased activation in areas related to salience and threat, and lower activation in the thalamus, a key relay hub between subcortical areas. If replicated, these fear network alterations may serve as objective diagnostic markers for PTSD, and potential targets for novel treatment development, including pharmacological and brain stimulation interventions. Future longitudinal studies are needed to examine whether these observed network alteration in PTSD are the cause or the consequence of PTSD.

Symptom structure of PTSD and co-morbid depressive symptoms - a network analysis of combat veteran patients.

BACKGROUND: Despite extensive research, symptom structure of posttraumatic stress disorder (PTSD) is highly debated. The network approach to psychopathology offers a novel method for understanding and conceptualizing PTSD. However, extant studies have mainly used small samples and self-report measures among sub-clinical populations, while also overlooking co-morbid depressive symptoms. METHODS: PTSD symptom network topology was estimated in a sample of 1489 treatment-seeking veteran patients based on a clinician-rated PTSD measure. Next, clinician-rated depressive symptoms were incorporated into the network to assess their influence on PTSD network structure. The PTSD-symptom network was then contrasted with the network of 306 trauma-exposed (TE) treatment-seeking patients not meeting full criteria for PTSD to assess corresponding network differences. Finally, a directed acyclic graph (DAG) was computed to estimate potential directionality among symptoms, including depressive symptoms and daily functioning. RESULTS: The PTSD symptom network evidenced robust reliability. Flashbacks and getting emotionally upset by trauma reminders emerged as the most central nodes in the PTSD network, regardless of the inclusion of depressive symptoms. Distinct clustering emerged for PTSD and depressive symptoms within the comorbidity network. DAG analysis suggested a key triggering role for re-experiencing symptoms. Network topology in the PTSD sample was significantly distinct from that of the TE sample. CONCLUSIONS: Flashbacks and psychological reactions to trauma reminders, along with their strong connections to other re-experiencing symptoms, have a pivotal role in the clinical presentation of combat-related PTSD among veterans. Depressive and posttraumatic symptoms constitute two separate diagnostic entities, but with meaningful between-disorder connections, suggesting two mutually-influential systems.

Anterior hippocampal volume predicts affect-focused psychotherapy outcome.

BACKGROUND: The hippocampus plays an important role in psychopathology and treatment outcome. While posterior hippocampus (PH) may be crucial for the learning process that exposure-based treatments require, affect-focused treatments might preferentially engage anterior hippocampus (AH). Previous studies have distinguished the different functions of these hippocampal sub-regions in memory, learning, and emotional processes, but not in treatment outcome. Examining two independent clinical trials, we hypothesized that anterior hippocampal volume would predict outcome of affect-focused treatment outcome [Interpersonal Psychotherapy (IPT); Panic-Focused Psychodynamic Psychotherapy (PFPP)], whereas posterior hippocampal volume would predict exposure-based treatment outcome [Prolonged Exposure (PE); Cognitive Behavioral Therapy (CBT); Applied Relaxation Training (ART)]. METHODS: Thirty-five patients with posttraumatic stress disorder (PTSD) and 24 with panic disorder (PD) underwent structural magnetic resonance imaging (MRI) before randomization to affect-focused (IPT for PTSD; PFPP for PD) or exposure-based treatments (PE for PTSD; CBT or ART for PD). AH and PH volume were regressed with clinical outcome changes. RESULTS: Baseline whole hippocampal volume did not predict post-treatment clinical severity scores in any treatment. For affect-focused treatments, but not exposure-based treatments, anterior hippocampal volume predicted clinical improvement. Smaller AH correlated with greater affect-focused treatment improvement. Posterior hippocampal volume did not predict treatment outcome. CONCLUSIONS: This is the first study to explore associations between hippocampal volume sub-regions and treatment outcome in PTSD and PD. Convergent results suggest that affect-focused treatment may influence the clinical outcome through the 'limbic' AH, whereas exposure-based treatments do not. These preliminary, theory-congruent, therapeutic findings require replication in a larger clinical trial.

Attention to threat in posttraumatic stress disorder as indexed by eye-tracking indices: a systematic review.

BACKGROUND: Cognitive models of posttraumatic stress disorder (PTSD) implicate threat-related attentional biases in the etiology and phenomenology of the disorder. However, extant attentional research using reaction time (RT)-based paradigms and measures has yielded mixed results. Eye-tracking methodology has emerged in recent years to overcome several inherent drawbacks of RT-based tasks, striving to better delineate attentional processes. METHODS: A systematic review of experimental studies examining threat-related attention biases in PTSD, using eye-tracking methodology and group-comparison designs, was conducted conforming to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Studies were selected following a systematic search for publications between 1980 and December 2017 in PsycINFO, MEDLINE and the National Center for PTSD Research's Published International Literature on Traumatic Stress (PILOTS) database. Additional records were identified by employing the Similar Articles feature in PubMed, and the Cited Reference Search in ISI Web of Science. Reference sections of review articles, book chapters and studies selected for inclusion were searched for further studies. Ongoing studies were also sought through Clinicaltrials.gov. RESULTS: A total of 11 studies (n = 456 participants in total) were included in the final review. Results indicated little support for enhanced threat detection, hypervigilance and attentional avoidance. However, consistent evidence emerged for sustained attention on threat (i.e. attention maintenance) in PTSD. CONCLUSIONS: This review is the first to systematically evaluate extant findings in PTSD emanating from eye-tracking studies employing group-comparison designs. Results suggest that sustained attention on threat might serve as a potential target for therapeutic intervention.

Bias-contingent attention bias modification and attention control training in treatment of PTSD: a randomized control trial.

BACKGROUND: Randomized control trials (RCTs) comparing attention control training (ACT) and attention bias modification (ABM) in posttraumatic stress disorder (PTSD) have shown mixed results. The current RCT extends the extant literature by comparing the efficacy of ACT and a novel bias-contingent-ABM (BC-ABM), in which direction of training is contingent upon the direction of pre-treatment attention bias (AB), in a sample of civilian patients with PTSD. METHODS: Fifty treatment-seeking civilian patients with PTSD were randomly assigned to either ACT or BC-ABM. Clinician and self-report measures of PTSD and depression, as well as AB and attention bias variability (ABV), were acquired pre- and post-treatment. RESULTS: ACT yielded greater reductions in PTSD and depressive symptoms on both clinician-rated and self-reported measures compared with BC-ABM. The BC-ABM condition successfully shifted ABs in the intended training direction. In the ACT group, there was no significant change in ABV or AB from pre- to post-treatment. CONCLUSIONS: The current RCT extends previous results in being the first to apply ABM that is contingent upon AB at pre-treatment. This personalized BC-ABM approach is associated with significant reductions in symptoms. However, ACT produces even greater reductions, thereby emerging as a promising treatment for PTSD.

Exposure-based therapy changes amygdala and hippocampus resting-state functional connectivity in patients with posttraumatic stress disorder.

BACKGROUND: Recent research suggests that posttraumatic stress disorder (PTSD) is associated with altered amygdala and hippocampal resting-state functional connectivity (rsFC). However, less research has examined whether Prolonged Exposure (PE), a first line exposure-based treatment for PTSD, has the potential to alter resting state neural networks. METHODS: A total of 24 patients with PTSD and 26 matched trauma-exposed healthy controls (TEHCs) underwent resting-state functional magnetic resonance imaging (fMRI) at baseline. PTSD patients were scanned a second time after completing 10-session PE in which patients narrated a detailed trauma account (imaginal exposure) and confronted trauma reminders (in vivo exposure) to extinguish trauma-related fear responses. TEHC were scanned again following a 10-week waiting period. Seed regions of interest (ROIs) included centromedial amygdala (CMA), basolateral amygdala (BLA), and the hippocampus. RESULTS: Post- versus pretreatment comparisons indicated increased rsFC of the BLA and CMA with the orbitofrontal cortex (OFC), and hippocampus-medial prefrontal cortex (mPFC) among patients with PTSD, but not among TEHC participants. CONCLUSIONS: Enhanced amygdala and hippocampus rsFC with prefrontal cortical regions following PE could underlie improved capacity for inhibition and re-evaluation of threat, and heightened memory encoding and retrieval ability, respectively. These findings encourage further investigation of this circuitry as a therapeutic target in PTSD.

Sex Differences in Trauma-Related Psychopathology: a Critical Review of Neuroimaging Literature (2014-2017).

PURPOSE OF REVIEW: Sex differences in the epidemiology and clinical presentation of trauma-related psychopathology have long been documented. Multiple underlying mechanisms have been examined, both psychosocial and biological. Among the most promising biological mechanisms are neural substrates of trauma-related psychopathology that have been uncovered in recent years. RECENT FINDINGS: Neuroimaging studies of sex-related heterogeneity published over the past 3 years (2014-2017) demonstrate an interaction between sex and type, timing, and load of trauma exposure. These studies suggest that, for males, early trauma exposure may involve a loss of gray matter in the limbic system, including the prefrontal cortex (PFC), amygdala, and hippocampus, and an over-activity and increased connectivity of salience hubs, and particularly dorsal anterior cingulate cortex (dACC). For females, however, early trauma exposure may involve overactive and possibly an enlarged amygdala, as well as decreased connectivity of salience hubs such as the dACC. Underlying mechanisms may include interaction with several endocrine systems and result in differential neural response to naturally occurring and added endocrine ligands, as well as sex-specific genetic and epigenetic risk and resilience factors. This complex interaction between multiple biological systems may be associated with sex-specific behavioral patterns, in turn associated with trauma-related psychopathology. While substantial number of published studies present preliminary evidence for neural mechanisms of sex-specific posttraumatic responses, there is a paucity of research directly designed to examine sex as a biological factor in trauma-related psychopathology. Specific foci for future studies aiming to bridge current gaps in the literature are discussed.

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.