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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.

We suggest that individuals with obsessive-compulsive disorder (OCD) experience difficulty accessing their internal states, including their feelings, emotions, preferences, and motivations. Instead, they rely on proxies to inform them of these states—that is, discernible substitutes in the form of fixed rules and rituals, observable behavior, and indexes. The Seeking Proxies for Internal States (SPIS) model of OCD proposes that compulsions, obsessions, indecision, and doubt result from seeking and using such proxies. The SPIS model not only accounts for these OCD symptoms but also sheds new light on normal processes of action control, metacognition, decision-making, and introspection.

Patients with anorexia nervosa (AN) display elevated anxiety and attention biases (ABs) in threat processing. Attention bias modification treatment (ABMT) is considered promising for anxiety disorders, but its potential for AN is limited. In this study, 154 young women hospitalised because of AN were assigned to ED-related and anxiety-related threat stimuli, or to a non-ABMT intervention control condition in a randomized control trial. Hundred-and-ten patients completed the study. ABMT was an add-on to the regular inpatient treatment. Research participants completed two pretreatment training sessions and eight biweekly sessions of ABMT. AB, ED-related symptoms, depression, anxiety and stress were assessed before and after ABMT in the research groups, and, similarly, 5 weeks apart, in the controls. We found that despite the different patterns of change in AB between the three groups following ABMT, the reduction in AB, or the between-group differences in AB-reduction, were not significant. While the severity of ED-symptoms, depression, anxiety and stress was reduced following ABMT, or control condition, in all groups, there were no between-group differences in these changes. Changes in AB were not correlated with baseline and pre-post-treatment changes in ED-related and comorbid symptomatology. Methodological and inpatient treatment-related considerations may explain our negative ABMT-related results.

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.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.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.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).

Eye-tracking-based attention research has shown attentional biases toward dysphoric and away from positive stimuli in depression. However, most research used prototypical stimuli (co-presented contrasting emotional faces/pictures), less reflective of real-life situations. The current study addressed this limitation by examining participants' attentional allocation patterns while freely viewing a news website containing dysphoric and positive news articles.Participants with high levels of depression (HD; n = 30) and with minimal levels of depression (MD; n = 30) freely viewed a fictitious news website for 3.5 min, containing six articles (picture + text) with dysphoric content and six with positive content. Gaze patterns on corresponding areas of interest (AOIs) were compared. Following the task, participants rated each article's valence, authenticity, and interest.Compared to MD participants, HD participants spent more time dwelling on dysphoric articles and less time dwelling on positive articles. Within group analyses showed that while HD participants spent more time dwelling on dysphoric compared to positive articles, MD participants showed no preference, allocating their attention equally to both article types. Echoing within-group gaze patterns, HD participants rated the dysphoric articles as being more interesting than the positive articles, while MD participants rated both types of articles as being equally interesting.Attentional biases in depression were also evident when using a more ecologically valid task such as viewing a news website, manifesting as increase attention allocation to dysphoric over positive content. This attention pattern may be related to corresponding differences in the level of interest participants found in each article type.

Background Social anxiety disorder (SAD) is common, first-line treatments are often only partially effective, and reliable predictors of treatment response are lacking. Here, we assessed resting state functional connectivity (rsFC) at pre-treatment and during early treatment as a potential predictor of response to a novel attention bias modification procedure, gaze-contingent music reward therapy (GC-MRT). Methods Thirty-two adults with SAD were treated with GC-MRT. rsFC was assessed with multi-voxel pattern analysis of fMRI at pre-treatment and after 2–3 weeks. For comparison, 20 healthy control (HC) participants without treatment were assessed twice for rsFC over the same time period. All SAD participants underwent clinical evaluation at pre-treatment, early-treatment (week 2–3), and post-treatment. Results SAD and depressive symptoms improved significantly from pre-treatment to post-treatment. After 2–3 weeks of treatment, decreased connectivity between the executive control network (ECN) and salience network (SN), and increased connectivity within the ECN predicted improvement in SAD and depressive symptoms at week 8. Increased connectivity between the ECN and default mode network (DMN) predicted greater improvement in SAD but not depressive symptoms at week 8. Connectivity within the DMN decreased significantly after 2–3 weeks of treatment in the SAD group, while no changes were found in HC over the same time interval. Conclusion We identified early changes in rsFC during a course of GC-MRT for SAD that predicted symptom change. Connectivity changes within the ECN, ECN-DMN, and ECN-SN may be related to mechanisms underlying the clinical effects of GC-MRT and warrant further study in controlled trials.

Choices and response times in two-alternative decision-making tasks can be modeled by assuming that individuals steadily accrue evidence in favor of each alternative until a response boundary for one of them is crossed, at which point that alternative is chosen. Prior studies have reported that evidence accumulation during decision-making tasks takes longer in adults with psychopathology than in healthy controls, indicating that slow evidence accumulation may be transdiagnostic. However, few studies have examined perceptual decision making in anxiety disorders, where hypervigilance might enhance performance. Therefore, this study used the Hierarchical Drift Diffusion model to investigate evidence accumulation in adults with social anxiety disorder (SAD) and healthy controls as they performed a probabilistic reward task (PRT), in which social rewards were delivered for correct perceptual judgments. Adults with SAD completed the PRT before and after gaze-contingent music reward therapy (GCMRT), which trains attention allocation and has shown efficacy for SAD. Healthy controls also completed the PRT twice. Results revealed excellent performance in adults with SAD, especially after GCMRT: relative to controls, they showed faster evidence accumulation, better discriminability, and earned more rewards. These data highlight a positive effect of attention training on performance in anxious adults and show how a behavioral trait that is typically problematic-hypervigilance in SAD-can nevertheless confer advantages in certain contexts. The data also indicate that, in contrast to other forms of psychopathology, SAD is not characterized by slow evidence accumulation, at least in the context of the social PRT. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Seeking Proxies for Internal States (SPIS) model of obsessive-compulsive disorder (OCD) posits that OCD is associated with attenuated access to internal states. Here we explored the implications of this model in the realm of emotions. Participants with OCD, anxiety disorders, and nonclinical control participants completed the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), assessing two domains of emotional intelligence: Experiential emotional intelligence (EI), reflecting the ability to perceive and feel emotions accurately, and Strategic EI, reflecting the ability to understand and manage emotions correctly. As only Experiential EI requires accurate perception of one’s emotions for adequate performance, we predicted an interaction between group and EI area. Specifically, we predicted that compared to both anxiety disorders and healthy control participants, OCD participants would show a larger deficit in Experiential area of the MSCEIT relative to the Strategic area. Results were fully in line with this prediction. Moreover, supporting the specificity of the hypothesized deficit to OCD, participants with anxiety disorders did not differ from nonclinical control participants in their performance, and findings were not attributable to anxiety or depression levels. These results replicate and extend previous findings obtained with analogue samples and suggest that OCD is associated with attenuated access to emotional states, which may be partially compensated for by reliance on semantic knowledge of emotion.

BackgroundCurrent clinical assessments of Posttraumatic stress disorder (PTSD) rely solely on subjective symptoms and experiences reported by the patient, rather than objective biomarkers of the illness. Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. Here we aimed to classify individuals with PTSD versus controls using heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.MethodsWe analyzed brain MRI data from 3,527 structural-MRI; 2,502 resting state-fMRI; and 1,953 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls (TEHC and HC) 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.ResultsWe 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 across all three modalities (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.ConclusionOur findings highlight the promise offered by machine learning methods for the diagnosis of patients with PTSD. The utility of brain biomarkers across three MRI modalities and the contribution of DVAE models for improving generalizability offers new insights into neural mechanisms involved in PTSD.Significance⍰Classifying PTSD from trauma-unexposed healthy controls (HC) using three imaging modalities performed well (∼75% AUC), but performance suffered markedly when classifying PTSD from trauma-exposed healthy controls (TEHC) using three imaging modalities (∼60% AUC).⍰Using deep learning for feature reduction (denoising variational auto-encoder; DVAE) dramatically reduced the number of features with no concomitant performance degradation.⍰Utilizing denoising variational autoencoder (DVAE) models improves generalizability across heterogeneous multi-site data compared with the traditional machine learning frameworks

Recently, a novel approach to obsessive-compulsive disorder has emerged, implicating altered reward functioning in the disorder. Yet, no study to date has directly examined the attentional aspect of reward functioning in participants with obsessive-compulsive (OC) symptoms, with past research mostly relying on reaction-time-based tasks.A reward-based value-modulated attentional capture task was completed by a sample of nonclinical student participants-44 with high (HOC) and 48 with low (LOC) levels of OC symptoms. We measured the extent to which high and low reward-signaling distractors captured attention and impaired performance on the task, resulting in a lower possibility of obtaining a monetary reward. Attentional capture was indexed via fixation data, and further explored using saccade data.Both groups performed more poorly when a high-reward signaling distractor was present, compared to when a low-reward signaling distractor was present. Importantly, this difference was significantly greater in the HOC group, and was found to be driven by the specific effects of reward-signaling distractors. Similar results emerged when exploring saccade data, and remained significant after controlling for both addiction-related compulsivity and depressive symptoms.Current findings suggest that attentional reward-related functioning may be associated with OC symptoms. Different aspects of reward functioning, including attention, should be further explored and incorporated into future research and clinical endeavors.

BackgroundThe cerebellum critically contributes to higher-order cognitive and emotional functions such fear learning and memory. Prior research on cerebellar volume in PTSD is scant and has neglected neuroanatomical subdivisions of the cerebellum that differentially map on to motor, cognitive, and affective functions.MethodsWe quantified cerebellar lobule volumes using structural magnetic resonance imaging in 4,215 adults (PTSD n= 1640; Control n=2575) across 40 sites from the from the ENIGMA-PGC PTSD working group. Using a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation, we obtained 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 total and subregional volume in PTSD compared to healthy controls. The Benjamini-Hochberg procedure was used to control the false discovery rate (p-FDR< .05).ResultsPTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume. In addition, people with PTSD showed reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), but also the vermis (VI, VIII), flocculonodular lobe (lobule X), and cerebellar white matter (allp-FDR< 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status.ConclusionsThese findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in high-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.

Cognitive models of obsessive-compulsive disorder (OCD) implicate heightened attention allocation to stimuli related to one's obsessions in the disorder. Recently, to overcome several limitations of reaction time-based measures, eye-tracking methodology has been increasingly used in attentional research.A meta-analysis of studies examining attention allocation towards OCD-related vs. neutral stimuli, using eye-tracking methodology and a group-comparison design, was conducted conforming to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Separate meta-analyses were performed for attentional vigilance (both latency and location of first fixations) and maintenance (total dwell time and total fixation count, conjointly). Each meta-analysis was conducted twice - once including all studies (main analysis) and once only including studies using the free-viewing paradigm (secondary analysis).The systematic search yielded a total of nine studies. Of those, eight provided the needed data to be included in the meta-analysis. No evidence emerged for vigilance via latency to first fixation. Vigilance reflected via first fixation location emerged in the main analysis, but not in the secondary one. Evidence for attentional maintenance was found only when analyzing free-viewing studies exclusively (the secondary analysis).To increase the accuracy of the research question, correlational studies were excluded, resulting in a small number of available studies.OCD may be characterized by vigilance, but mainly in tasks entailing specific demands and/or goals. Conversely, attentional maintenance may be evident only when using tasks that pose no requirements or demands for participants.

People with obsessive-compulsive disorder (OCD) tend to distrust their memory, perception, and other cognitive functions, and many OCD symptoms can be traced to diminished confidence in one's cognitive processes. For example, poor confidence in recall accuracy can cause doubt about one's memory and motivate repeated checking. At the same time, people with OCD also display performance deficits in a variety of cognitive tasks, so their reduced confidence must be evaluated in relation to their actual performance. To that end, we conducted an exhaustive review and meta-analysis of studies in which OCD participants and non-clinical control participants performed cognitive tasks and reported their confidence in their performance. Our search resulted in 19 studies that met criteria for inclusion in the quantitative analysis, with all studies addressing either memory or perception. We found that both performance and reported confidence were lower in OCD than in control participants. Importantly, however, confidence was more impaired than performance in participants with OCD. These findings suggest that people with OCD are less confident in their memory and perception than they should be, indicating a genuineunder-confidencein this population. We discuss potential mechanisms that might account for this finding and suggest avenues for further research into under-confidence and related meta-cognitive characteristics of OCD.

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.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.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.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.Findings support the existence of structural brain markers of resilience.

Accurate assessment is crucial for determining appropriate therapeutic interventions for social anxiety and conducting sound clinical research. While self-report measures of social anxiety are widely used in both research and clinical settings, they have several drawbacks inherent to their textual nature. Here, we describe the development and initial validation of the Visual Social Anxiety Scale (VSAS), a novel picture-based self-report measure of social anxiety, based on the well-established widely-used Liebowitz Social Anxiety Scale (LSAS). Specifically, the 24 items of the LSAS were used as the basis for social situations to be included in the VSAS. First, pictures to serve as VSAS items were selected using a rigorous two-phase process (four pilot studies; n = 225). Next, reliability (internal consistency, test-retest) and validity (convergent, discriminant) were explored with new participants (n = 304) who completed the VSAS and a battery of additional self-report questionnaires, delivered in a random order. The VSAS was completed again a month later (n = 260/304). The VSAS showed high internal consistency and test-retest reliability, and good convergent and discriminant validities. VSAS correlations with convergent measures were significantly greater than its correlations with discriminant measures. Thus, the VSAS shows initial promise as a novel picture-based self-report measure of social anxiety.