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Developmental imaging studies show that cortical grey matter decreases in volume during childhood and adolescence. However, considerably less research has addressed the development of subcortical regions (caudate, putamen, pallidum, accumbens, thalamus, amygdala, hippocampus and the cerebellar cortex), in particular not in longitudinal designs. We used the automatic labeling procedure in FreeSurfer to estimate the developmental trajectories of the volume of these subcortical structures in 147 participants (age 7.0–24.3years old, 94 males; 53 females) of whom 53 participants were scanned twice or more. A total of 223 magnetic resonance imaging (MRI) scans (acquired at 1.5-T) were analyzed. Substantial diversity in the developmental trajectories was observed between the different subcortical gray matter structures: the volume of caudate, putamen and nucleus accumbens decreased with age, whereas the volume of hippocampus, amygdala, pallidum and cerebellum showed an inverted U-shaped developmental trajectory. The thalamus showed an initial small increase in volume followed by a slight decrease. All structures had a larger volume in males than females over the whole age range, except for the cerebellum that had a sexually dimorphic developmental trajectory. Thus, subcortical structures appear to not yet be fully developed in childhood, similar to the cerebral cortex, and continue to show maturational changes into adolescence. In addition, there is substantial heterogeneity between the developmental trajectories of these structures. •Development of subcortical structures was examined in 150 typically developing children.•Similar to the cerebral cortex, subcortical structures are not yet fully developed in childhood.•There was substantial heterogeneity in developmental trajectories of subcortical structures.•All structures were larger in males than females over the whole age range.•The cerebellum was the only structure to show a sexually dimorphic trajectory.

Response inhibition involves proactive and reactive modes. Proactive inhibition is goal-directed, triggered by warning cues, and serves to restrain actions. Reactive inhibition is stimulus-driven, triggered by salient stop-signals, and used to stop actions completely. Functional MRI studies have identified brain regions that activate during proactive and reactive inhibition. It remains unclear how these brain regions operate in functional networks, and whether proactive and reactive inhibition depend on common networks, unique networks, or a combination. To address this we analyzed a large fMRI dataset (N=65) of a stop-signal task designed to measure proactive and reactive inhibition, using independent component analysis (ICA). We found 1) three frontal networks that were associated with both proactive and reactive inhibition, 2) one network in the superior parietal lobe, which also included dorsal premotor cortex and left putamen, that was specifically associated with proactive inhibition, and 3) two right-lateralized frontal and fronto-parietal networks, including the right inferior frontal gyrus and temporoparietal junction as well as a bilateral fronto-temporal network that were uniquely associated with reactive inhibition. Overlap between networks was observed in dorsolateral prefrontal and parietal cortices. Taken together, we offer a new perspective on the neural underpinnings of inhibitory control, by showing that proactive inhibition and reactive inhibition are supported by a group of common and unique networks that appear to integrate and interact in frontoparietal areas. [Display omitted] •Proactive and reactive inhibitory controls are supported by multiple networks.•We found proactive (P), reactive (R), and proactive/reactive (PR) networks.•P and P/R networks are bilaterally organized; R network is right-dominant.•These networks may integrate and interact in dorsolateral frontoparietal areas.

This paper discusses how converging methods may form a powerful tool in unraveling the neurobiology of attention-deficit/hyperactivity disorder (ADHD). Integrating findings from multiple disciplines can inform us on how different neurobiological and cognitive mechanisms tie together in both typical and atypical development. Examples are discussed of this approach: combining family and genetic approaches with anatomical neuroimaging illustrates how mapping familial effects can bring us closer to understanding the neurobiology of ADHD. Functional neuroimaging has convincingly linked cognitive problems in this disorder with frontostriatal functioning, but also shows that other systems may be involved in some of the symptoms of ADHD. Combining these findings has suggested new avenues for investigation, such as the role of frontocerebellar networks. Furthermore, findings may have practical applications: this paper discusses an example of how converging evidence of striatal dysregulation in ADHD suggests possible directions for treatment that are now being explored in functional imaging studies.

Most studies aiming to predict transition to psychosis for individuals at ultra-high risk (UHR) have focused on either neurocognitive or clinical variables and have made little effort to combine the two. Furthermore, most have focused on a dichotomous measure of transition to psychosis rather than a continuous measure of functional outcome. We aimed to investigate the relative value of neurocognitive and clinical variables for predicting both transition to psychosis and functional outcome. Forty-three UHR individuals and 47 controls completed an extensive clinical and neurocognitive assessment at baseline and participated in long-term follow-up approximately six years later. UHR adolescents who had converted to psychosis (UHR-P; n = 10) were compared to individuals who had not (UHR-NP; n = 33) and controls on clinical and neurocognitive variables. Regression analyses were performed to determine which baseline measures best predicted transition to psychosis and long-term functional outcome for UHR individuals. Low IQ was the single neurocognitive parameter that discriminated UHR-P individuals from UHR-NP individuals and controls. The severity of attenuated positive symptoms was the only significant predictor of a transition to psychosis and disorganized symptoms were highly predictive of functional outcome. Clinical measures are currently the most important vulnerability markers for long-term outcome in adolescents at imminent risk of psychosis.

Recent neurobiological models of ADHD suggest that deficits in different neurobiological pathways may independently lead to symptoms of this disorder. At least three independent pathways may be involved: a dorsal frontostriatal pathway involved in cognitive control, a ventral frontostriatal pathway involved in reward processing and a frontocerebellar pathway related to temporal processing. Importantly, we and others have suggested that disruptions in these three pathways should lead to separable deficits at the cognitive level. Furthermore, if these truly represent separate biological pathways to ADHD, these cognitive deficits should segregate between individuals with ADHD. The present study tests these hypotheses in a sample of children, adolescents and young adults with ADHD and controls. 149 Subjects participated in a short computerized battery assessing cognitive control, timing and reward sensitivity. We used Principal Component Analysis to find independent components underlying the variance in the data. The segregation of deficits between individuals was tested using Loglinear Analysis. We found four components, three of which were predicted by the model: Cognitive control, reward sensitivity and timing. Furthermore, 80% of subjects with ADHD that had a deficit were deficient on only one component. Loglinear Analysis statistically confirmed the independent segregation of deficits between individuals. We therefore conclude that cognitive control, timing and reward sensitivity were separable at a cognitive level and that deficits on these components segregated between individuals with ADHD. These results support a neurobiological framework of separate biological pathways to ADHD with separable cognitive deficits.

Background Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data. Methods We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7–18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P  < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research. Results Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples—EU-AIMS LEAP. Limitations Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability. Conclusions Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

Autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD) are neurodevelopmental disorders with considerable overlap in terms of their defining symptoms of compulsivity/repetitive behaviour. Little is known about the extent to which ASD and OCD have common versus distinct neural correlates of compulsivity. Previous research points to potentially common dysfunction in frontostriatal connectivity, but direct comparisons in one study are lacking. Here, we assessed frontostriatal resting-state functional connectivity in youth with ASD or OCD, and healthy controls. In addition, we applied a cross-disorder approach to examine whether repetitive behaviour across ASD and OCD has common neural substrates. A sample of 78 children and adolescents aged 8-16 years was used (ASD n = 24; OCD n = 25; healthy controls n = 29), originating from the multicentre study COMPULS. We tested whether diagnostic group, repetitive behaviour (measured with the Repetitive Behavior Scale-Revised) or their interaction was associated with resting-state functional connectivity of striatal seed regions. No diagnosis-specific differences were detected. The cross-disorder analysis, on the other hand, showed that increased functional connectivity between the left nucleus accumbens (NAcc) and a cluster in the right premotor cortex/middle frontal gyrus was related to more severe symptoms of repetitive behaviour. We demonstrate the fruitfulness of applying a cross-disorder approach to investigate the neural underpinnings of compulsivity/repetitive behaviour, by revealing a shared alteration in functional connectivity in ASD and OCD. We argue that this alteration might reflect aberrant reward or motivational processing of the NAcc with excessive connectivity to the premotor cortex implementing learned action patterns.

Background Psychiatric classifications are understood in many different ways. For children with ADHD and their parents, psychoeducation is an important source of information for shaping their understanding. Moreover, psychoeducation is often taken by children and parents to represent how their story is understood by the therapist. As a result, the way psychoeducation is formulated may affect the therapeutic alliance, one of the most robust mediators of treatment outcome. In addition, psychoeducation may indirectly influence the way we understand psychological differences as a society. Methods To better understand how the classification ADHD is given meaning through psychoeducation, we analyzed 41 written psychoeducational materials from four different countries; the USA, UK, Netherlands and Hungary. Results We identified five patterns of how the materials construct the discourse on ADHD. Notably, tension between biomedical and psychosocial perspectives resulted in conflict within a single thematic stance on ADHD as opposed to a conflict between parties with a different vision on ADHD. There were only few differences between countries in the way they constructed the discourse in the materials. Conclusions These conflicts cause confusion, misrepresentation and decontextualization of ADHD. Ultimately, for those diagnosed with ADHD and their parents, conflicting information in psychoeducation materials may hamper their ability to understand themselves in the context of their difficulties.

Background Low recruitment in clinical trials is a common and costly problem which undermines medical research. This study aimed to investigate the challenges faced in recruiting children and adolescents with obsessive-compulsive disorder and autism spectrum disorder for a randomized, double-blind, placebo-controlled clinical trial and to analyze reasons for non-participation. The trial was part of the EU FP7 project TACTICS (Translational Adolescent and Childhood Therapeutic Interventions in Compulsive Syndromes). Methods Demographic data on pre-screening patients were collected systematically, including documented reasons for non-participation. Findings were grouped according to content, and descriptive statistical analyses of the data were performed. Results In total, n  = 173 patients were pre-screened for potential participation in the clinical trial. Of these, only five (2.9%) were eventually enrolled. The main reasons for non-inclusion were as follows: failure to meet all inclusion criteria/meeting one or more of the exclusion criteria ( n  = 73; 42.2%), no interest in the trial or trials in general ( n  = 40; 23.1%), and not wanting changes to current therapy/medication ( n  = 14; 8.1%). Conclusions The findings from this study add valuable information to the existing knowledge on reasons for low clinical trial recruitment rates in pediatric psychiatric populations. Low enrollment and high exclusion rates raise the question of whether such selective study populations are representative of clinical patient cohorts. Consequently, the generalizability of the results of such trials may be limited. The present findings will be useful in the development of improved recruitment strategies and may guide future research in establishing the measurement of representativeness to ensure enhanced external validity in psychopharmacological clinical trials in pediatric populations. Trial registration EudraCT 2014-003080-38 . Registered on 14 July 2014.

Background Voxel-based morphometry (VBM) studies in autism spectrum disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case–control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms. Methods We studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project. All participants’ VBM maps were decomposed into spatially independent components using independent component analysis. A generalized linear model (GLM) was used to examine case–control differences. Next, canonical correlation analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms. Results GLM analyses showed significant case–control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals. Limitations Only 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures. Conclusions Covaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior, whereas others may underpin sensory processing and integration, and motor behavior.