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.

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.

Electroconvulsive therapy is associated with increased immunoreactivity of neuroplasticity markers in the hippocampus of depressed patients.

Electroconvulsive therapy (ECT) is an effective therapy for depression, but its cellular effects on the human brain remain elusive. In rodents, electroconvulsive shocks increase proliferation and the expression of plasticity markers in the hippocampal dentate gyrus (DG), suggesting increased neurogenesis. Furthermore, MRI studies in depressed patients have demonstrated increases in DG volume after ECT, that were notably paralleled by a decrease in depressive mood scores. Whether ECT also triggers cellular plasticity, inflammation or possibly injury in the human hippocampus, was unknown. We here performed a first explorative, anatomical study on the human post-mortem hippocampus of a unique, well-documented cohort of bipolar or unipolar depressed patients, who had received ECT in the 5 years prior to their death. They were compared to age-matched patients with a depressive disorder who had not received ECT and to matched healthy controls. Upon histopathological examination, no indications were observed for major hippocampal cell loss, overt cytoarchitectural changes or classic neuropathology in these 3 groups, nor were obvious differences present in inflammatory markers for astrocytes or microglia. Whereas the numbers of proliferating cells expressing Ki-67 was not different, we found a significantly higher percentage of cells positive for Doublecortin, a marker commonly used for young neurons and cellular plasticity, in the subgranular zone and CA4 / hilus of the hippocampus of ECT patients. Also, the percentage of positive Stathmin 1 cells was significantly higher in the subgranular zone of ECT patients, indicating neuroplasticity. These first post-mortem observations suggest that ECT has no damaging effects but may rather have induced neuroplasticity in the DG of depressed patients.

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy.

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. OBJECTIVE: We investigated whether there are consistent changes in effective resting-state connectivity. METHODS: This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. RESULTS: Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. CONCLUSIONS: A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis.

INTRODUCTION: For major depression, a one-size-fits-all treatment does not exist. Patients enter a 'trial-and-change' algorithm in which effective therapies are subsequently applied. Unfortunately, an empirically based order of treatments has not yet been determined. There is a magnitude of different treatment strategies while clinical trials only compare a small number of these. Network meta-analyses (NMA) might offer a solution, but so far have been limited in scope and did not account for possible differences in population characteristics that arise with increasing levels of treatment-resistance, potentially violating the transitivity assumption. We; therefore, present a protocol for a systematic review and NMA aiming at summarising and ranking treatments for treatment-resistant depression (TRD) while covering a broad range of therapeutic options and accounting for possible differences in population characteristics at increasing levels of treatment-resistance. METHODS AND ANALYSIS: Randomised controlled trials will be included that compared next-step pharmacological, neuromodulation or psychological treatments for treatment-resistant depression (TRD; ie, failure to respond to ≥1 adequate antidepressant drug trial(s) in the current episode) to each other or to a control condition. Primary outcomes will be the proportion of patients who responded to (efficacy) and dropped out of (acceptability) the allocated treatment. A random effects NMA will be conducted, synthesising the evidence for each outcome and determining the differential efficacy of treatments. Heterogeneity in treatment nodes will be reduced by considering alternative geometries of the network structure and by conducting a meta-regression examining different levels of TRD. Local and global methods will be applied to evaluate consistency. The Cochrane Risk of Bias 2 tool, Confidence in Network Meta-Analysis and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework will be used to assess risk of bias and certainty. ETHICS AND DISSEMINATION: This review does not require ethical approval.

Depressive Symptoms Account for Loss of Positive Attention Bias in ADHD Patients: An Eye-Tracking Study.

OBJECTIVES: Depression and ADHD often co-occur and are both characterized by altered attentional processing. Differences and overlap in the profile of attention to emotional information may help explain the co-occurence. We examined negative attention bias in ADHD as neurocognitive marker for comorbid depression. METHODS: Patients with depression (n = 63), ADHD (n = 43), ADHD and depression (n = 25), and non-psychiatric controls (n = 68) were compared on attention allocation toward emotional faces. The following eye-tracking indices were used: gaze duration, number of revisits, and location and duration of first fixation. RESULTS: Controls revisited the happy faces more than the other facial expressions. Both the depression and the comorbid group showed significantly less revisits of the happy faces compared to the ADHD and the control group. Interestingly, after controlling for depressive symptoms, the groups no longer differed on the number of revisits. CONCLUSION: ADHD patients show a relative positive attention bias, while negative attention bias in ADHD likely indicates (sub)clinical comorbid depression.

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.

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.

Structural changes induced by electroconvulsive therapy are associated with clinical outcome.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective treatment option for major depressive disorder, so understanding whether its clinical effect relates to structural brain changes is vital for current and future antidepressant research. OBJECTIVE: To determine whether clinical response to ECT is related to structural volumetric changes in the brain as measured by structural magnetic resonance imaging (MRI) and, if so, which regions are related to this clinical effect. We also determine whether a similar model can be used to identify regions associated with electrode placement (unilateral versus bilateral ECT). METHODS: Longitudinal MRI and clinical data (Hamilton Depression Rating Scale) was collected from 10 sites as part of the Global ECT-MRI research collaboration (GEMRIC). From 192 subjects, relative changes in 80 (sub)cortical areas were used as potential features for classifying treatment response. We used recursive feature elimination to extract relevant features, which were subsequently used to train a linear classifier. As a validation, the same was done for electrode placement. We report accuracy as well as the structural coefficients of regions included in the discriminative spatial patterns obtained. RESULTS: A pattern of structural changes in cortical midline, striatal and lateral prefrontal areas discriminates responders from non-responders (75% accuracy, p < 0.001) while left-sided mediotemporal changes discriminate unilateral from bilateral electrode placement (81% accuracy, p < 0.001). CONCLUSIONS: The identification of a multivariate discriminative pattern shows that structural change is relevant for clinical response to ECT, but this pattern does not include mediotemporal regions that have been the focus of electroconvulsive therapy research so far.

Default mode network coherence in treatment-resistant major depressive disorder during electroconvulsive therapy.

BACKGROUND: Functional connectivity in the "default mode network" (DMN) is changed in depression, and evidence suggests depression also affects the DMN's spatial topography and might cause a dissociation between its anterior and posterior regions. As antidepressive treatment affects anterior and posterior regions of the network differently, how depression and treatment change DMN-organization is crucial for understanding their mechanisms. We present a novel way of assessing the coherence of a network's regions to the network as a whole, and apply this to investigate treatment-resistant depression and the effects of electroconvulsive therapy (ECT). METHODS: Resting-state functional MRI was collected from 16 patients with treatment-resistant depression before and after ECT and 16 healthy controls matched for age and sex. For each subject, the mean time series of the DMN was used as a regressor for each voxel within the DMN, creating a map of "network coherence" (NC). The obtained maps were compared across groups using permutation testing. RESULTS: NC was significantly decreased in depressed subjects in the precuneus and the angular gyrus. With ECT the NC normalized in responders (n=8), but not in non-responders (n=8). CONCLUSIONS: We present a novel method of investigating within-network coherence and apply this to show that in depression, a large area of the DMN shows a decrease in coherence to the network as a whole. Although tentative due to the small sample size, we find that this effect is not present after ECT in those improving clinically, but persists in patients not responding to ECT.