Explore the vast range of titles available.

Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test–retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. We constructed undirected networks based on the Anatomic-Automatic-Labeling (AAL) atlas template and calculated several commonly used measures from the field of graph theory, focusing on the influence of different strategies for confound correction. For each subject, method and session we computed the following graph metrics: clustering coefficient, characteristic path length, local and global efficiency, assortativity, modularity, hierarchy and the small-worldness scalar. Reliability of each graph metric was assessed using the intraclass correlation coefficient (ICC). Overall ICCs ranged from low to high (0 to 0.763) depending on the method and metric. Methodologically, the use of a broader frequency band (0.008–0.15Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics. In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest. ► Test–retest reliability of graph metrics derived from resting-state fMRI. ► Different preprocessing and confound correction methods are examined. ► Moderate overall reliability, but differed between methods. ► Using a broad filter frequency range (0.008–0.15Hz) yielded best results.

Psychopathy is a severe personality disorder marked by a wide range of emotional deficits, including a lack of empathy, emotion dysregulation, and alexithymia. Previous research has largely examined these emotional impairments in isolation, ignoring their influence on each other. Thus, we examined the concurrent interrelationship between emotional impairments in psychopathy, with a particular focus on the mediating role of alexithymia. Using path analyses with cross-sectional data from a community sample ( N = 315) and a forensic sample ( N = 50), our results yielded a statistically significant mediating effect of alexithymia on the relationship between psychopathy and empathy (community and forensic) and between psychopathy and emotion dysregulation (community). Moreover, replacing psychopathy with its three dimensions (i.e., meanness, disinhibition, and boldness) in the community sample revealed that boldness may function as an adaptive trait, with lower levels of alexithymia counteracting deficits in empathy and emotion dysregulation. Overall, our findings indicate that psychopathic individuals’ limited understanding of their own emotions contributes to their lack of empathy and emotion dysregulation. This underscores the potential benefits of improving emotional awareness in the treatment of individuals with psychopathy.

Schizophrenia is a devastating, highly heritable brain disorder of unknown etiology. Recently, the first common genetic variant associated on a genome-wide level with schizophrenia and possibly bipolar disorder was discovered in ZNF804A (rs1344706). We show, by using an imaging genetics approach, that healthy carriers of rs1344706 risk genotypes exhibit no changes in regional activity but pronounced gene dosage-dependent alterations in functional coupling (correlated activity) of dorsolateral prefrontal cortex (DLPFC) across hemispheres and with hippocampus, mirroring findings in patients, and abnormal coupling of amygdala. Our findings establish disturbed connectivity as a neurogenetic risk mechanism for psychosis supported by genome-wide association, show that rs1344706 or variation in linkage disequilibrium is functional in human brain, and validate the intermediate phenotype strategy in psychiatry.

Schizophrenia is associated with significant impairments in social cognition. These impairments have been shown to go along with altered activation of the posterior superior temporal sulcus (pSTS). However, studies that investigate connectivity of pSTS during social cognition in schizophrenia are sparse. Twenty-two patients with schizophrenia and 22 matched healthy controls completed a social-cognitive task for functional magnetic resonance imaging that allows the investigation of affective Theory of Mind (ToM), emotion recognition and the processing of neutral facial expressions. Moreover, a resting-state measurement was taken. Patients with schizophrenia performed worse in the social-cognitive task (main effect of group). In addition, a group by social-cognitive processing interaction was revealed for activity, as well as for connectivity during the social-cognitive task, i.e., patients with schizophrenia showed hyperactivity of right pSTS during neutral face processing, but hypoactivity during emotion recognition and affective ToM. In addition, hypoconnectivity between right and left pSTS was revealed for affective ToM, but not for neutral face processing or emotion recognition. No group differences in connectivity from right to left pSTS occurred during resting state. This pattern of aberrant activity and connectivity of the right pSTS during social cognition might form the basis of false-positive perceptions of emotions and intentions and could contribute to the emergence and sustainment of delusions.

Dynamic causal modeling (DCM) is an analysis technique that has been successfully used to infer about directed connectivity between brain regions based on imaging data such as functional magnetic resonance imaging (fMRI). Most variants of DCM for fMRI rely on a simple bilinear differential equation for neural activation, making it difficult to interpret the results in terms of local neural dynamics. In this work, we introduce a modification to DCM for fMRI by replacing the bilinear equation with a non-linear Wilson-Cowan based equation and use Bayesian Model Comparison (BMC) to show that this modification improves the model evidences. Improved model evidence of the non-linear model is shown for our empirical data (imitation of facial expressions) and validated by synthetic data as well as an empirical test dataset (attention to visual motion) used in previous foundational papers. For our empirical data, we conduct the analysis for a group of 42 healthy participants who performed an imitation task, activating regions putatively containing the human mirror neuron system (MNS). In this regard, we build 540 models as one family for comparing the standard bilinear with the modified Wilson-Cowan models on the family-level. Using this modification, we can interpret the sigmoid transfer function as an averaged f-I curve of many neurons in a single region with a sigmoidal format. In this way, we can make a direct inference from the macroscopic model to detailed microscopic models. The new DCM variant shows superior model evidence on all tested data sets.

Aberrant salience may explain hasty decision making and psychotic symptoms in schizophrenia. In healthy individuals, final decisions in probabilistic reasoning tasks are related to Nucleus accumbens (Nacc) activation. However, research investigating the Nacc in social decision making is missing. Our study aimed at investigating the role of the Nacc for social decision making and its link to (aberrant) salience attribution. 47 healthy individuals completed a novel social jumping-to-conclusion (JTC) fMRI-paradigm, showing morphed faces simultaneously expressing fear and happiness. Participants decided on the ‘current’ emotion after each picture, and on the ‘general’ emotion of series of faces. Nacc activation was stronger during final decisions than in previous trials without a decision, particularly in fear rather than happiness series. A JTC-bias was associated with higher Nacc activation for last fearful, but not last happy faces. Apparently, mechanisms underlying probabilistic reasoning are also relevant for social decision making. The pattern of Nacc activation suggests salience, not reward, drives the final decision. Based on these findings, we hypothesize that aberrant salience might also explain social-cognitive deficits in schizophrenia.

Patients with schizophrenia display metacognitive impairments, such as hasty decision-making during probabilistic reasoning — the “jumping to conclusion” bias (JTC). Our recent fMRI study revealed reduced activations in the right ventral striatum (VS) and the ventral tegmental area (VTA) to be associated with decision-making in patients with schizophrenia. It is unclear whether these functional alterations occur in the at-risk mental state (ARMS). We administered the classical beads task and fMRI among ARMS patients and healthy controls matched for age, sex, education and premorbid verbal intelligence. None of the ARMS patients was treated with antipsychotics. Both tasks request probabilistic decisions after a variable amount of stimuli. We evaluated activation during decision-making under certainty versus uncertainty and the process of final decision-making. We included 24 AMRS patients and 24 controls in our study. Compared with controls, ARMS patients tended to draw fewer beads and showed significantly more JTC bias in the classical beads task, mirroring findings in patients with schizophrenia. During fMRI, ARMS patients did not demonstrate JTC bias on the behavioural level, but showed a significant hypoactivation in the right VS during the decision stage. Owing to the cross-sectional design of the study, results are constrained to a better insight into the neurobiology of risk constellations, but not pre-psychotic stages. Nine of the ARMS patients were treated with antidepressants and/or lorazepam. As in patients with schizophrenia, a striatal hypoactivation was found in ARMS patients. Confounding effects of antipsychotic medication can be excluded. Our findings indicate that error prediction signalling and reward anticipation may be linked to striatal dysfunction during prodromal stages and should be examined for their utility in predicting transition risk.

Patients with schizophrenia have an approximately 10-fold higher risk for obsessive–compulsive symptoms (OCS) than the general population. A large subgroup seems to experience OCS as a consequence of second-generation antipsychotic agents (SGA), such as clozapine. So far little is known about underlying neural mechanisms. To investigate the role of SGA treatment on neural processing related to OCS in patients with schizophrenia, we stratified patients according to their monotherapy into 2 groups (group I: clozapine or olanzapine; group II: amisulpride or aripiprazole). We used an fMRI approach, applying a go/no-go task assessing inhibitory control and an n-back task measuring working memory. We enrolled 21 patients in group I and 19 patients in group II. Groups did not differ regarding age, sex, education or severity of psychotic symptoms. Frequency and severity of OCS were significantly higher in group I and were associated with pronounced deficits in specific cognitive abilities. Whereas brain activation patterns did not differ during working memory, group I showed significantly increased activation in the orbitofrontal cortex (OFC) during response inhibition. Alterations in OFC activation were associated with the severity of obsessions and mediated the association between SGA treatment and co-occurring OCS on a trend level. The main limitation of this study is its cross-sectional design. To our knowledge, this is the first imaging study conducted to elucidate SGA effects on neural systems related to OCS. We propose that alterations in brain functioning reflect a pathogenic mechanism in the development of SGA-induced OCS in patients with schizophrenia. Longitudinal studies and randomized interventions are needed to prove the suggested causal interrelations.

An attentional bias to health-threat stimuli is assumed to represent the primary pathogenetic factor for the development and maintenance of pathological health anxiety (PHA; formerly termed “hypochondriasis”). However, little is known about the neural basis of this attentional bias in individuals with PHA. A group of patients with PHA, a group of depressed patients and a healthy control group completed an emotional Stroop task with health-threat (body symptom and illness) words and neutral control words while undergoing functional MRI. We included 33 patients with PHA, 28 depressed patients and 31 controls in our analyses. As reflected in reaction times, patients with PHA showed a significantly stronger attentional bias to health-threat words than both control groups. In addition, patients with PHA showed increased amygdala and rostral anterior cingulate cortex activation for body symptom, but not for illness words. Moreover, only in patients with PHA amygdala activation in response to symptom words was positively associated with higher arousal and more negative valence ratings of the body symptom word material. A control group of patients with an anxiety disorder but without PHA would have helped to define the specificity of the results for PHA. The attentional bias observed in patients with PHA is associated with hyperactivation in response to body symptom words in brain regions that are crucial for an arousal-related fear response (e.g., the amygdala) and for resolving emotional interference (e.g., the rostral anterior cingulate cortex). The findings have important implications for the nosological classification of PHA and suggest the application of innovative exposure-based interventions for the treatment of PHA.

Much research has focused on executive function (EF) impairments in psychopathy, a severe personality disorder characterized by a lack of empathy, antisocial behavior, and a disregard for social norms and moral values. However, it is still unclear to what extent EF deficits are present across psychopathy factors and, more importantly, which EF domains are impaired. The current meta-analysis answers these questions by synthesizing the results of 50 studies involving 5,694 participants from 12 different countries. Using multilevel random-effects models, we pooled effect sizes (Cohen's d ) for five different EF domains: overall EF, inhibition, planning, shifting, and working memory. Moreover, differences between psychopathy factors were evaluated. Our analyses revealed small deficits in overall EF, inhibition, and planning performance. However, a closer inspection of psychopathy factors indicated that EF deficits were specific to lifestyle/antisocial traits, such as disinhibition. Conversely, interpersonal/affective traits, such as boldness, showed no deficits and in some cases even improved EF performance. These findings suggest that EF deficits are not a key feature of psychopathy per se, but rather are related to antisociality and disinhibitory traits. Potential brain correlates of these findings as well as implications for future research and treatment are discussed.