Dissecting task-based fMRI activity using normative modelling: an application to the Emotional Face Matching Task

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. Taken together, we demonstrate that normative modelling of fMRI task-activation can be used to illustrate the influence of different task choices and map replicable individual differences, and we encourage its application to other neuroimaging tasks in future studies

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

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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

Movement, mood and cognition: Preliminary insights into the therapeutic effects of electroconvulsive therapy for depression through a resting-state connectivity analysis.

Electroconvulsive therapy (ECT) is a highly effective treatment for depression but how it achieves its clinical effects remains unclear. We set out to study the brain's response to ECT from a large-scale brain-network perspective. Using a voxelwise analysis, we looked at resting-state functional connectivity before and after a course of ECT at the whole-brain and the between- and within-network levels in 17 patients with a depressive episode. Using a group-independent component analysis approach, we focused on four networks known to be affected in depression: the salience network (SN), the default mode network (DMN), the cognitive executive network (CEN), and a subcortical network (SCN). Our clinical measures included mood, cognition, and psychomotor symptoms. We found ECT to have increased the connectivity of the left CEN with the left angular gyrus and left middle frontal gyrus as well as its within-network connectivity. Both the right CEN and the SCN showed increased connectivity with the precuneus and the anterior DMN with the left amygdala. Finally, improvement of psychomotor retardation was positively correlated with an increase of within-posterior DMN connectivity. The limitations of our study include its small sample size and the lack of a control dataset to confirm our findings. Our voxelwise data demonstrate that ECT induces a significant increase of connectivity across the whole brain and at the within-network level. Furthermore, we provide the first evidence on the association between an increase of within-posterior DMN connectivity and an improvement of psychomotor retardation, a core symptom of depression

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

BackgroundIt 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). ObjectiveThe 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. MethodsThis 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. ResultsWe 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. ConclusionsThe 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

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