The symptoms of hyperactivity-impulsivity and inattention displayed by children with ADHD put them at risk of experiencing peer victimization. Hippocampal maturation, may reduce a child’s vulnerability to the experience of peer victimization, as it has been associated with decreased ADHD symptomatology. Working memory is an important executive function in the formation and maintenance of social relationships, which is often impaired in ADHD. We aimed to evaluate the relationship between problem behaviours, peer victimization, hippocampal morphology, and working memory in children with and without ADHD. 218 typically-developing participants (50.5% male) and 232 participants diagnosed with ADHD (77.6% male) were recruited. The ADHD group was subdivided into inattentive (ADHD-I) or combined (ADHD-C) types. The Child Behavior Checklist measured problem behaviours and peer victimization. Children underwent Magnetic Resonance Imaging (MRI). Hippocampal subfield volumes were obtained using FreeSurfer. The Wechsler Intelligence Scale for Children-fifth edition measured working memory (WM). The ADHD-C group displayed significantly higher levels of problem behaviours and peer victimization (all, p < 0.001), compared to the other groups. Left Cornu Ammonis 3 (CA3) volume was a positive predictor of peer victimization (all, p < 0.013). Left CA3 volume was a positive predictor of WM and left Cornu Ammonis 4 (CA4) volume negatively predicted WM (all, p < 0.025). A cluster analysis revealed that children displaying symptoms of hyperactivity-impulsivity are the most at risk for peer victimization. Interventions focusing on minimizing peer victimization may aid in mitigating adverse downstream effects, and assist in promoting brain health and cognitive function.

Fetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI, funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workflow. Open-access fetal fMRI data with manual brain masks from 159 fetuses (1103 total volumes) were used for training and testing the U-net model. We also tested generalizability of the model using 82 locally acquired functional scans from 19 fetuses, which included over 2300 manually segmented volumes. Dice metrics were used to compare performance of funcmasker-flex to the ground truth manually segmented volumes, and segmentations were consistently robust (all Dice metrics ≥0.74). The tool is freely available and can be applied to any BIDS dataset containing fetal bold sequences. Funcmasker-flex reduces the need for manual segmentation, even when applied to novel fetal functional datasets, resulting in significant time-cost savings for performing fetal fMRI analysis.

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The default mode network is essential for higher-order cognitive processes and is composed of an extensive network of functional and structural connections. Early in fetal life, the default mode network shows strong connectivity with other functional networks; however, the association with structural development is not well understood. In this study, resting-state functional magnetic resonance imaging and anatomical images were acquired in 30 pregnant women with singleton pregnancies. Participants completed 1 or 2 MR imaging sessions, on average 3 weeks apart (43 data sets), between 28- and 39-weeks postconceptional ages. Subcortical volumes were automatically segmented. Activation time courses from resting-state functional magnetic resonance imaging were extracted from the default mode network, medial temporal lobe network, and thalamocortical network. Generalized estimating equations were used to examine the association between functional connectivity strength between default mode network–medial temporal lobe, default mode network–thalamocortical network, and subcortical volumes, respectively. Increased functional connectivity strength in the default mode network–medial temporal lobe network was associated with smaller right hippocampal, left thalamic, and right caudate nucleus volumes, but larger volumes of the left caudate. Increased functional connectivity strength in the default mode network–thalamocortical network was associated with smaller left thalamic volumes. The strong associations seen among the default mode network functional connectivity networks and regionally specific subcortical volume development indicate the emergence of short-range connectivity in the third trimester.

Autism spectrum disorder (ASD) is clinically characterized by social and communication difficulties as well as repetitive behaviors. Many children with ASD also suffer from anxiety, which has been associated with alterations in amygdala structure. In this work, the association between amygdala subnuclei volumes and anxiety was assessed in a cohort of 234 participants (mean age = 11.0 years, SD = 3.9, 95 children with ASD, 139 children were non-autistic). Children underwent magnetic resonance imaging. Amygdala subnuclei volumes were extracted automatically. Anxiety was assessed using the Screen for Child Anxiety Related Disorders, the Child Behavior Checklist, and the Strength and Difficulties Questionnaire. Children with ASD had higher anxiety scores relative to non-autistic children on all anxiety measures (all, p < 0.05). Anxiety levels were significantly predicted in children with ASD by right basal (right: B = 0.235, p = 0.002) and paralaminar (PL) (B = −0.99, p = 0.009) volumes. Basal nuclei receive multisensory information from cortical and subcortical areas and have extensive projections within the limbic system while the PL nuclei are involved in emotional processing. Alterations in basal and PL nuclei in children with ASD and the association with anxiety may reflect morphological changes related to in the neurocircuitry of anxiety in ASD. Lay abstract Autism spectrum disorder (ASD) is clinically characterized by social communication difficulties as well as restricted and repetitive patterns of behavior. In addition, children with ASD are more likely to experience anxiety compared with their peers who do not have ASD. Recent studies suggest that atypical amygdala structure, a brain region involved in emotions, may be related to anxiety in children with ASD. However, the amygdala is a complex structure composed of heterogeneous subnuclei, and few studies to date have focused on how amygdala subnuclei relate to in anxiety in this population. The current sample consisted of 95 children with ASD and 139 non-autistic children, who underwent magnetic resonance imaging (MRI) and assessments for anxiety. The amygdala volumes were automatically segmented. Results indicated that children with ASD had elevated anxiety scores relative to peers without ASD. Larger basal volumes predicted greater anxiety in children with ASD, and this association was not seen in non-autistic children. Findings converge with previous literature suggesting ASD children suffer from higher levels of anxiety than non-autistic children, which may have important implications in treatment and interventions. Our results suggest that volumetric estimation of amygdala’s subregions in MRI may reveal specific anxiety-related associations in children with ASD.