The Role of Socio-Affective and Socio-Cognitive Mechanisms in the Processing of Witnessed Traumatic Events

Experiencing traumatic events has a high lifetime prevalence ranging between 60.7 and 76.2% across different countries (1). Exposure to traumatic events is associated with a higher risk for various mental disorders such as posttraumatic stress disorder (2, 3), which are related to high individual and societal costs (4). The development of interventions to prevent adverse mental health consequences following traumatic event exposure is therefore of vital importance. This, however, requires detailed knowledge about the underlying biological and psychological mechanisms involved in the association between traumatic events and psychopathology. Various risk factors at different levels have already been described in the last decades (5). Biological risk factors include genetic and epigenetic variations (6), alterations in the function of the hypothalamic pituitary adrenal (HPA) axis (7, 8) and the autonomic nervous system (9) as well as changes in brain structure and functioning (10). Psychological risk factors include impairments in cognitive abilities (11) and specific personality traits such as high trait anxiety (12) and maladaptive emotion regulation (13). Social risk factors include impaired interpersonal relations and stigmatization (14, 15). Further, clinical risk factors such as mental health history as well as previous traumatic experiences may also increase the risk for psychopathology after trauma exposure (16). Most of these factors are supposed to be associated with risk of psychopathology independent of the type of traumatic event. However, it is likely that specific traumatic events are associated with different constellations of risk factors, which has so far received little attention in the existing literature. Importantly, traumatic events explicitly include not only events that are personally experienced but also events that are witnessed by an observer (17). This includes witnessing someone being seriously hurt, seeing atrocities or witnessing dead bodies. Witnessed traumatic events are among the most frequent traumatic experiences (1). They are also of high current relevance in the contexts of natural disasters, terrorist attacks and military crises (16, 18, 19). The fact that individuals can develop psychopathological reactions to events that are actually experienced by others raises the question how the suffering of others is being processed. Based on theoretical models and findings from social cognition and neuroscience research, we propose that socio-affective and socio-cognitive mechanisms are involved in the processing and pathological consequences of witnessing traumatic events and could contribute to a better understanding of adverse reactions to this type of traumatic events

A coordinate-based meta-analysis of white matter alterations in patients with alcohol use disorder

Introduction: Besides the commonly described grey matter (GM) deficits, there is growing evidence of significant white matter (WM) alterations in patients with alcohol use disorder (AUD). WM changes can be assessed using volumetric and diffusive magnetic resonance imaging methods, such as voxel-based morphometry (VBM) and diffusion tensor imaging (DTI). The aim of the present meta-analysis is to investigate the spatial convergence of the reported findings on WM alterations in AUD. Methods: Systematic literature search on PubMed and further databases revealed 18 studies eligible for inclusion, entailing a total of 462 AUD patients and 416 healthy controls (up to January 18, 2021). All studies that had used either VBM or DTI whole-brain analyzing methods and reported results as peak-coordinates in standard reference space were considered for inclusion. We excluded studies using approaches nonconcordant with recent guidelines for neuroimaging meta-analyses and studies investigating patient groups with Korsakoff syndrome or other comorbid substance use disorders (except tobacco). Results: Anatomical Likelihood Estimation (ALE) revealed four significant clusters of convergent macro- and microstructural WM alterations in AUD patients that were assigned to the genu and body of the corpus callosum, anterior and posterior cingulum, fornix, and the right posterior limb of the internal capsule. Discussion: The changes in WM could to some extent explain the deteriorations in motor, cognitive, affective, and perceptual functions seen in AUD. Future studies are needed to clarify how WM alterations vary over the course of the disorder and to what extent they are reversible with prolonged abstinence

Emotion regulation and psychopathology: investigating differential associations between emotion regulation skills and psychological symptoms using a network approach

Objectives Emotion regulation plays an important role in the development and maintenance of psychopathology. However, the question whether specific ER skills are related to specific psychological symptoms has rarely been studied, but has important implications for targeted interventions. This analysis aims to explore potential differential associations between various ER skills and psychological symptoms using a network analysis approach. Methods Routine data from a transdiagnostic clinical sample of 716 patients (460 females, 256 males) from an outpatient clinic for psychotherapy were analysed. Nine ER skills were assessed with the Emotion Regulation Skills Questionnaire, and nine symptom dimension scores were obtained using the Brief Symptom Inventory. A regularised partial correlation network models including ER skills and individual symptom domains were calculated. Bridge expected influence was calculated to estimate the strength of association of each ER skill with psychological symptoms. Results Only the following ER skills were most strongly related to psychological symptoms (bridge expected influence): Tolerance, Confrontation, and Modification. All other ER skills were indirectly connected to symptom severity through these four skills. The strongest direct edges between ER skills and symptoms were Modification - Depression, Confrontation - Obsession-Compulsion, and Tolerance - Interpersonal Sensitivity, which were significantly stronger than the vast majority of other associations between ER skills and psychological symptoms. Conclusions These exploratory findings provide valuable targets for future studies to investigate specific associations between ER skills and psychological symptoms which could help to improve outcome monitoring and efficacy of interventions targeting ER

How specific is specific phobia? Different neural response patterns in two subtypes of specific phobia

Specific phobia of the animal subtype has been employed as a model disorder exploring the neurocircuitry of anxiety disorders, but evidence is lacking whether the detected neural response pattern accounts for all animal subtypes, nor across other phobia subtypes. The present study aimed at directly comparing two subtypes of specific phobia: snake phobia (SP) representing the animal, and dental phobia (DP) representing the blood-injection-injury subtype. Using functional magnetic resonance imaging (fMRI), brain activation and skin conductance was measured during phobogenic video stimulation in 12 DP, 12 SP, and 17 healthy controls. For SP, the previously described activation of fear circuitry structures encompassing the insula, anterior cingulate cortex and thalamus could be replicated and was furthermore associated with autonomic arousal. In contrast, DP showed circumscribed activation of the prefrontal and orbitofrontal cortex (PFC/OFC) when directly compared to SP, being dissociated from autonomic arousal. Results provide preliminary evidence for the idea that snake and dental phobia are characterized by distinct underlying neural systems during sustained emotional processing with evaluation processes in DP being controlled by orbitofrontal areas, whereas phobogenic reactions in SP are primarily guided by limbic and paralimbic structures. Findings support the current diagnostic classification conventions, separating distinct subtypes in DSM-IV-TR. They highlight that caution might be warranted though for generalizing findings derived from animal phobia to other phobic and anxiety disorders. If replicated, results could contribute to a better understanding of underlying neurobiological mechanisms of specific phobia and their respective classification

Peak voxel and sub regions from the conjunction analysis of the task induced deactivation (TID) during run 1 and relative sAA increase immediately prior to scanning.

<p>Peakvoxel from the conjunction analysis are based on a voxelwise p<0.005, uncorrected and a minimum cluster size of k = 30. MTG: middle temporal gyrus; STG: superior temporal gyrus; SFG: superior frontal gyrus; MFG: medial frontal gyrus.</p

Salivary alpha-amylase (sAA) profile over the six sampling points.

<p>Error bars indicate SEM. T0  =  training phase; Prep.  =  MRI preparation (subjects were placed on the MRI table, get goggles, headphones, headcoil, ect.); R1  =  Run 1; Struct.  =  high resolution structural scan; R2  =  Run 2. **p<0.01.</p

Peak voxel and sub regions from the conjunction analysis of task induced activation during run 1 and relative sAA increase immediately prior to scanning.

<p>Peakvoxel from the conjunction analysis are based on a voxelwise p<0.005, uncorrected and a minimum cluster size of k = 30. SMA: supplementary motor area.</p

Schematic view of the target detection task.

<p>The example illustrates the brightening of the inner circle (cue) indicating a short cue target interval (CTI). After the cue stimulus a CTI of either 600 ms (expected) or 1400 ms (unexpected) followed, than the target appeared (large cross). Long CTIs’ were cued by brightening of the outer circle.</p

Scatter plots and coefficients of determination R² of salivary alpha-amylase (sAA), brain activation/deactivation and behavioral data.

<p>a) Associations between reaction times (RT)/correct responses during run 1 and percentage sAA increase immediately prior to scanning. b) Associations between reaction times (RT)/correct responses and extracted mean beta values. Task induced activation: supplementary motor area (SMA), lentiform nucleus and declive. Task induced deactivation: angular gyrus.</p

Peak voxel and sub regions from the task induced activation and deactivation.

<p>Peakvoxel based on a voxelwise T≥10 for activation and T≥4 for TID with a minimum cluster size of k = 10. SMA: supplementary motor area; MOG: middle occipital gyrus, MTG: middle temporal gyrus, MFG: medial frontal gyrus, IPL: inferior parietal lobule, IFG: inferior frontal gyrus, SFG: superior frontal gyrus, SPL: superior parietal lobule.</p