Autistic and non-autistic individuals show the same amygdala activity during emotional face processing.

BACKGROUND: Autistic and non-autistic individuals often differ in how they perceive and show emotions, especially in their ability and inclination to infer other people's feelings from subtle cues like facial expressions. Prominent theories of autism have suggested that these differences stem from alterations in amygdala functioning and that amygdala hypoactivation causes problems with emotion recognition. Thus far, however, empirical investigations of this hypothesis have yielded mixed results and largely relied on relatively small samples. METHODS: In a sample of 72 autistic and 79 non-autistic participants, we conducted a study in which we used the Hariri paradigm to test whether amygdala activation during emotional face processing is altered in autism spectrum disorder, and whether common mental disorders like depression, ADHD or anxiety disorders influence any potential alterations in activation patterns. RESULTS: We found no evidence for differences in amygdala activation, neither when comparing autistic and non-autistic participants, nor when taking into account mental disorders or the overall level of functional impairment. LIMITATIONS: Because we used one basic emotion processing task in a Dutch sample, results might not generalise to other tasks and other populations. CONCLUSIONS: Our results challenge the view that autistic and non-autistic processing of emotional faces in the amygdala is vastly different and call for a more nuanced view of differences between non-autistic and autistic emotion processing.

Preliminary evidence for changes in frontoparietal network connectivity in the early abstinence period in alcohol use disorder: a longitudinal resting-state functional magnetic resonance imaging study.

The early abstinence period is a crucial phase in alcohol use disorder (AUD) in which patients have to find a new equilibrium and may start recovery, or conversely, relapse. However, the changes in brain functions during this key period are still largely unknown. We set out to study longitudinal changes in large-scale brain networks during the early abstinence period using resting-state scans. We scanned AUD patients twice in a well-controlled inpatient setting, with the first scan taking place shortly after admission and the second scan 4 weeks (±9 days) later near the end of the treatment period. We studied 37 AUD patients (22 males) and 27 healthy controls (16 males). We focused on three networks that are affected in AUD and underly core symptom dimensions in this disorder: the frontoparietal networks (left and right FPN) and default mode network (DMN). Both the whole brain and within network connectivity of these networks were studied using dual regression. Finally, we explored correlations between these brain networks and various neuropsychological and behavioral measures. In contrast to the controls (Z = -1.081, p = 0.280), the AUD patients showed a decrease in within left FPN connectivity (Z = -2.029, p = 0.042). However, these results did not survive a strict Bonferroni correction. The decrease in left FPN connectivity during the early abstinence period in AUD may reflect an initially upregulated FPN, which recovers to a lower resting-state connectivity level during subsequent weeks of abstinence. The AUD patients showed a trend for a positive association between the change in left FPN connectivity and trait anxiety (rs = 0.303, p = 0.068), and a trend for a negative association between the change in left FPN connectivity and delay discounting (rs = -0.283, p = 0.089) (uncorrected for multiple comparisons). This suggests that the FPN might be involved in top-down control of impulsivity and anxiety, which are important risk factors for relapse. Although there were no statistically significant results (after multiple comparison correction), our preliminary findings encourage further research into the dynamic neuroadaptations during the clinically crucial early abstinence period and could inform future study designs.

Brain structure and function link to variation in biobehavioral dimensions across the psychopathological continuum.

In line with the Research Domain Criteria (RDoC) , we set out to investigate the brain basis of psychopathology within a transdiagnostic, dimensional framework. We performed an integrative structural-functional linked independent component analysis to study the relationship between brain measures and a broad set of biobehavioral measures in a sample (n = 295) with both mentally healthy participants and patients with diverse non-psychotic psychiatric disorders (i.e. mood, anxiety, addiction, and neurodevelopmental disorders). To get a more complete understanding of the underlying brain mechanisms, we used gray and white matter measures for brain structure and both resting-state and stress scans for brain function. The results emphasize the importance of the executive control network (ECN) during the functional scans for the understanding of transdiagnostic symptom dimensions. The connectivity between the ECN and the frontoparietal network in the aftermath of stress was correlated with symptom dimensions across both the cognitive and negative valence domains, and also with various other health-related biological and behavioral measures. Finally, we identified a multimodal component that was specifically associated with the diagnosis of autism spectrum disorder (ASD). The involvement of the default mode network, precentral gyrus, and thalamus across the different modalities of this component may reflect the broad functional domains that may be affected in ASD, like theory of mind, motor problems, and sensitivity to sensory stimuli, respectively. Taken together, the findings from our extensive, exploratory analyses emphasize the importance of a dimensional and more integrative approach for getting a better understanding of the brain basis of psychopathology.

The impact of schizophrenia spectrum disorder, bipolar disorder and borderline personality disorder on radiotherapy treatment and overall survival in cancer patients: A matched pair analysis.

Introduction: The effect of a psychiatric disorder (PD) on the choice of radiotherapy regimens and subsequent cancer control outcomes is largely unknown. In this study, we evaluated differences in radiotherapy regimens and overall survival (OS) between cancer patients with a PD in comparison with a control population of patients without a PD. Methods: Referred patients with a PD (i.e. schizophrenia spectrum disorder, bipolar disorder or borderline personality disorder) were included through a text-based search of the electronic patient database of all the patients that received radiotherapy between 2015 and 2019 at a single centre. Each patient was matched to a patient without a PD. Matching was based on cancer type, staging, performance score (WHO/KPS), non-radiotherapeutic cancer treatment, gender and age. Outcomes were the amount of fractions received, total dose, and OS. Results: 88 patients with PD were identified; 44 patients with schizophrenia spectrum disorder, 34 with bipolar disorder, and 10 with borderline personality disorder. Matched patients without a PD showed similar baseline characteristics. No statistically significant difference was observed regarding the number of fractions with a median of 16 (interquartile range [IQR] 3-23) versus 16 (IQR 3-25), respectively (p = 0.47). Additionally, no difference in total dose was found. Kaplan-Meier curves showed a statistically significant difference in OS between the patients with a PD versus those without a PD, with 3-year OS rates of 47 % versus 61 %, respectively (hazard ratio 1.57, 95 % confidence interval 1.05-2.35, p = 0.03). No clear differences in causes of death were observed. Conclusion: Cancer patients referred for radiotherapy with schizophrenia spectrum disorder, bipolar disorder or borderline personality disorder receive similar radiotherapy schedules for a variety of tumour types but attain worse survival.

Unpacking the functional heterogeneity of the Emotional Face Matching Task: a normative modelling approach.

Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N=7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals' transdiagnostic functioning.

Striatal connectopic maps link to functional domains across psychiatric disorders.

Transdiagnostic approaches to psychiatry have significant potential in overcoming the limitations of conventional diagnostic paradigms. However, while frameworks such as the Research Domain Criteria have garnered significant enthusiasm among researchers and clinicians from a theoretical angle, examples of how such an approach might translate in practice to understand the biological mechanisms underlying complex patterns of behaviors in realistic and heterogeneous populations have been sparse. In a richly phenotyped clinical sample (n = 186) specifically designed to capture the complex nature of heterogeneity and comorbidity within- and between stress- and neurodevelopmental disorders, we use exploratory factor analysis on a wide range of clinical questionnaires to identify four stable functional domains that transcend diagnosis and relate to negative valence, cognition, social functioning and inhibition/arousal before replicating them in an independent dataset (n = 188). We then use connectopic mapping to map inter-individual variation in fine-grained topographical organization of functional connectivity in the striatum-a central hub in motor, cognitive, affective and reward-related brain circuits-and use multivariate machine learning (canonical correlation analysis) to show that these individualized topographic representations predict transdiagnostic functional domains out of sample (r = 0.20, p = 0.026). We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.

Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum.

Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.

Amygdala sensitivity for negative information as a neural marker for negative memory bias across psychiatric diagnoses.

Self-referent negative memory bias is a known risk factor for depression, but recent evidence suggests its function as a transdiagnostic cognitive depressotypic marker. The amygdala's sensitivity for negative information is considered a neurobiological depressotypic marker. However, their relationship remains unknown. We transdiagnostically investigated the association between the amygdala's sensitivity, self-referent negative memory bias and its two components: negative endorsement bias and negative recall bias. Patients (n= 125) with (multimorbid) stress-related and neurodevelopmental psychiatric disorders and healthy controls (n= 78) performed an fMRI task to assess the amygdala's sensitivity for negative information and a task outside the scanner for the biases. Linear regression models assessed their associations. The left amygdala's sensitivity for negative information was significantly positively associated with negative recall bias in patients, but not controls. There were no significant associations with self-referent negative memory bias or negative endorsement bias or between the two depressotypic markers. Thus, the left amygdala's sensitivity for negative information may be considered a neural marker of negative memory bias across psychiatric diagnoses. Further research on the interactons with known determinants such as genetic predisposition is required to fully understand the relationship between the amygdala's sensitivity for negative information and these biases.

Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders (MIND-SET): Protocol for a Cross-sectional Comorbidity Study From a Research Domain Criteria Perspective.

BACKGROUND: It is widely acknowledged that comorbidity between psychiatric disorders is common. Shared and diverse underpinnings of psychiatric disorders cannot be systematically understood based on symptom-based categories of mental disorders, which map poorly onto pathophysiological mechanisms. In the Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders (MIND-SET) study, we make use of current concepts of comorbidity that transcend the current diagnostic categories. We test this approach to psychiatric problems in patients with frequently occurring psychiatric disorders and their comorbidities (excluding psychosis). OBJECTIVE: The main aim of the MIND-SET project is to determine the shared and specific mechanisms of neurodevelopmental and stress-related psychiatric disorders at different observational levels. METHODS: This is an observational cross-sectional study. Data from different observational levels as defined in the Research Domain Criteria (genetics, physiology, neuropsychology, system-level neuroimaging, behavior, self-report, and experimental neurocognitive paradigms) are collected over four time points. Included are adult (aged ≥18 years), nonpsychotic, psychiatric patients with a clinical diagnosis of a stress-related disorder (mood disorder, anxiety disorder, or substance use disorder) or a neurodevelopmental disorder (autism spectrum disorder or attention-deficit/hyperactivity disorder). Individuals with no current or past psychiatric diagnosis are included as neurotypical controls. Data collection started in June 2016 with the aim to include a total of 650 patients and 150 neurotypical controls by 2021. The data collection procedure includes online questionnaires and three subsequent sessions with (1) standardized clinical examination, physical examination, and blood sampling; (2) psychological constructs, neuropsychological tests, and biological marker sampling; and (3) neuroimaging measures. RESULTS: We aim to include a total of 650 patients and 150 neurotypical control participants in the time period between 2016 and 2022. In October 2021, we are at 95% of our target. CONCLUSIONS: The MIND-SET study enables us to investigate the mechanistic underpinnings of nonpsychotic psychiatric disorders transdiagnostically. We will identify both shared and disorder-specific markers at different observational levels that can be used as targets for future diagnostic and treatment approaches.

Exploring the Relationship Between Movement Disorders and Physical Activity in Patients With Schizophrenia: An Actigraphy Study.

Low physical activity (PA) and sedentary behavior (SB) are major contributors to mental health burden and increased somatic comorbidity and mortality in people with schizophrenia and related psychoses. Movement disorders are highly prevalent in schizophrenia populations and are related to impaired functioning and poor clinical outcome. However, the relationship between movement disorders and PA and SB has remained largely unexplored. Therefore, we aimed to examine the relationship between movement disorders (akathisia, dyskinesia, dystonia, and parkinsonism) and PA and SB in 216 patients with schizophrenia and related psychoses. Actigraphy, the St. Hans Rating Scale for extrapyramidal syndromes, and psychopathological ratings (PANSS-r) were applied. Data were analyzed using multiple linear regression, adjusting for sex, age, negative symptoms, and defined daily dose of prescribed antipsychotics. Parkinsonism was significantly associated with decreased PA (ß = -0.21, P < .01) and increased SB (ß = 0.26, P < .001). For dystonia, only the relationship with SB was significant (ß = 0.15, P < .05). Akathisia was associated with more PA (ß = 0.14, P < .05) and less SB (ß = -0.15, P < .05). For dyskinesia, the relationships were non-significant. In a prediction model, akathisia, dystonia, parkinsonism and age significantly predicted PA (F(5,209) = 16.6, P < .001, R2Adjusted = 0.27) and SB (F(4,210) = 13.4, P < .001, R2Adjusted = 0.19). These findings suggest that movement disorders, in particular parkinsonism, are associated with reduced PA and increased SB in patients with psychotic disorders. Future studies should take movement disorders into account when examining PA and SB, to establish the clinical value of movement disorders in activating people with psychotic disorders to improve their mental and somatic health.