Functional connectivity based brain signatures of behavioral regulation in children with ADHD, DCD, and ADHD-DCD.

Behavioral regulation problems have been associated with daily-life and mental health challenges in children with neurodevelopmental conditions such as attention-deficit/hyperactivity disorder (ADHD) and developmental coordination disorder (DCD). Here, we investigated transdiagnostic brain signatures associated with behavioral regulation. Resting-state fMRI data were collected from 115 children (31 typically developing (TD), 35 ADHD, 21 DCD, 28 ADHD-DCD) aged 7-17 years. Behavioral regulation was measured using the Behavior Rating Inventory of Executive Function and was found to differ between children with ADHD (i.e., children with ADHD and ADHD-DCD) and without ADHD (i.e., TD children and children with DCD). Functional connectivity (FC) maps were computed for 10 regions of interest and FC maps were tested for correlations with behavioral regulation scores. Across the entire sample, greater behavioral regulation problems were associated with stronger negative FC within prefrontal pathways and visual reward pathways, as well as with weaker positive FC in frontostriatal reward pathways. These findings significantly increase our knowledge on FC in children with and without ADHD and highlight the potential of FC as brain-based signatures of behavioral regulation across children with differing neurodevelopmental conditions.

Aberrant limbic brain structures in young individuals at risk for mental illness.

AIM: Alterations in limbic structures may be present before the onset of serious mental illness, but whether subfield-specific limbic brain changes parallel stages in clinical risk is unknown. To address this gap, we compared the hippocampus, amygdala, and thalamus subfield-specific volumes in adolescents at various stages of risk for mental illness. METHODS: MRI scans were obtained from 182 participants (aged 12-25 years) from the Canadian Psychiatric Risk and Outcome study. The sample comprised of four groups: asymptomatic youth at risk due to family history of mental illness (Stage 0, n = 32); youth with early symptoms of distress (Stage 1a, n = 41); youth with subthreshold psychotic symptoms (Stage 1b, n = 72); and healthy comparison participants with no family history of serious mental illness (n = 37). Analyses included between-group comparisons of brain measurements and correlational analyses that aimed to identify significant associations between neuroimaging and clinical measurements. A machine-learning technique examined the discriminative properties of the clinical staging model. RESULTS: Subfield-specific limbic volume deficits were detected at every stage of risk for mental illness. A machine-learning classifier identified volume deficits within the body of the hippocampus, left amygdala nuclei, and medial-lateral nuclei of the thalamus that were most informative in differentiating between risk stages. CONCLUSION: Aberrant subfield-specific changes within the limbic system may serve as biological evidence to support transdiagnostic clinical staging in mental illness. Differential patterns of volume deficits characterize those at risk for mental illness and may be indicative of a risk-stage progression.

Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants.

Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal volumes manually is a time-consuming procedure, however, creating a need for automated segmentation methods that are both fast and reliable over time. Segmentation algorithms that employ deep convolutional neural networks (CNN) have emerged as a promising solution for large longitudinal neuroimaging studies. However, for these novel algorithms to be useful in clinical studies, the accuracy and reproducibility should be established on independent datasets. Here, we evaluate the performance of a CNN-based hippocampal segmentation algorithm that was developed by Thyreau and colleagues - Hippodeep. We compared its segmentation outputs to manual segmentation and FreeSurfer 6.0 in a sample of 200 healthy participants scanned repeatedly at seven sites across Canada, as part of the Canadian Biomarker Integration Network in Depression consortium. The algorithm demonstrated high levels of stability and reproducibility of volumetric measures across all time points compared to the other two techniques. Although more rigorous testing in clinical populations is necessary, this approach holds promise as a viable option for tracking volumetric changes in longitudinal neuroimaging studies.

The Canadian Biomarker Integration Network in Depression (CAN-BIND): magnetic resonance imaging protocols

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging ­ alone or in combination with other variables ­ can predict the outcomes of various treatment modalities.

Efficacy of Adjunctive D-Cycloserine to Intermittent Theta-Burst Stimulation for Major Depressive Disorder: A Randomized Clinical Trial.

Importance: The antidepressant effects of transcranial magnetic stimulation protocols for major depressive disorder (MDD) are thought to depend on synaptic plasticity. The theta-burst stimulation (TBS) protocol synaptic plasticity is known to be N-methyl-D-aspartate (NMDA)-receptor dependent, yet it is unknown whether enhancing NMDA-receptor signaling improves treatment outcomes in MDD. Objective: To test whether low doses of the NMDA-receptor partial-agonist, D-cycloserine, would enhance intermittent TBS (iTBS) treatment outcomes in MDD. Design, Setting, and Participants: This was a single-site 4-week, double-blind, placebo-controlled, randomized clinical trial conducted from November 6, 2019, to December 24, 2020, including 50 participants with MDD. Participants were recruited via advertisements and referral. Inclusion criteria were as follows: age 18 to 65 years with a primary diagnosis of MDD, a major depressive episode with score of 18 or more on the 17-item Hamilton Depression Rating Scale, a Young Mania Rating Scale score of 8 or less, and normal blood work (including complete blood cell count, electrolytes, liver function tests, and creatinine level). Interventions: Participants were randomly assigned 1:1 to either iTBS plus placebo or iTBS plus D-cycloserine (100 mg) for the first 2 weeks followed by iTBS without an adjunct for weeks 3 and 4. Main Outcomes and Measures: The primary outcome was change in depressive symptoms as measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) at the conclusion of treatment. Secondary outcomes included clinical response, clinical remission, and Clinical Global Impression (CGI) scores. Results: A total of 50 participants (mean [SD] age, 40.8 [13.4] years; 31 female [62%]) were randomly assigned to treatment groups: iTBS plus placebo (mean [SD] baseline score, 30.3 [4.2]) and iTBS plus D-cycloserine (mean [SD] baseline score, 30.4 [4.5]). The iTBS plus D-cycloserine group had greater improvements in MADRS scores compared with the iTBS plus placebo group (mean difference, -6.15; 95% CI, -2.43 to -9.88; Hedges g = 0.99; 95% CI, 0.34-1.62). Rates of clinical response were higher in the iTBS plus D-cycloserine group than in the iTBS plus placebo group (73.9% vs 29.3%), as were rates of clinical remission (39.1% vs 4.2%). This was reflected in lower CGI-severity ratings and greater CGI-improvement ratings. No serious adverse events occurred. Conclusions and Relevance: Findings from this clinical trial indicate that adjunctive D-cycloserine may be a promising strategy for enhancing transcranial magnetic stimulation treatment outcomes in MDD using iTBS requiring further investigation. Trial Registration: ClinicalTrials.gov Identifier: NCT03937596.

Cerebello-limbic functional connectivity patterns in youth at clinical high risk for psychosis.

Youth at clinical high risk (CHR) for psychosis can present not only with characteristic attenuated psychotic symptoms but also may have other comorbid conditions, including anxiety and depression. These undifferentiated mood symptoms can overlap with the clinical presentation of youth with Distress syndromes. Increased resting-state functional connectivity within cerebello-thalamo-cortical (CTC) pathways has been proposed as a trait-specific biomarker for CHR. However, it is unclear whether this functional neural signature remains specific when compared to a different risk group: youth with Distress syndromes. The purpose of the present work was to describe CTC alterations that distinguish between CHR and Distressed individuals. Using machine learning algorithms, we analyzed CTC connectivity features of CHR (n = 51), Distressed (n = 41), and healthy control (n = 36) participants. We found four cerebellar (lobes VII and left Crus II anterior/posterior) and two basal ganglia (right putamen and right thalamus) nodes containing a set of specific connectivity features that distinguished between CHR, Distressed and healthy control groups. Hyperconnectivity between medial lobule VIIb, somatomotor network and middle temporal gyrus was associated with CHR status and more severe symptoms. Detailed atlas parcellation suggested that CHR individuals may have dysfunction mainly within the associative (cognitive) pathways, particularly, between those brain areas responsible for the multi-sensory signal integration.

Manipulating visual scanpaths during facial emotion perception modulates functional brain activation in schizophrenia patients and controls.

Individuals with schizophrenia exhibit deficits in facial emotion processing, which have been associated with abnormalities in visual gaze behavior and functional brain activation. However, the relationship between gaze behavior and brain activation in schizophrenia remains unexamined. Studies in healthy individuals and other clinical samples indicate a relationship between gaze behavior and functional activation in brain regions implicated in facial emotion processing deficits in schizophrenia (e.g., fusiform gyrus), prompting the question of whether a similar relationship exists in schizophrenia. This study examined whether manipulating visual scanpaths during facial emotion perception would modulate functional brain activation in a sample of 23 schizophrenia patients and 26 community controls. Participants underwent functional magnetic resonance imaging (MRI) while viewing pictures of emotional faces. During the typical viewing condition, a fixation cue directed participants' gaze primarily to the eyes and mouth, whereas during the atypical viewing condition gaze was directed to peripheral features. Both viewing conditions elicited a robust response throughout face-processing regions. Typical viewing led to greater activation in visual association cortex including the right inferior occipital gyrus/occipital face area, whereas atypical viewing elicited greater activation in primary visual cortex and regions involved in attentional control. There were no between-groups activation differences in response to faces or interaction between group and gaze manipulation. The results indicate that gaze behavior modulates functional activation in early face-processing regions in individuals with and without schizophrenia, suggesting that abnormal gaze behavior in schizophrenia may contribute to activation abnormalities during facial emotion perception. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Learning with individual-interest outcomes in Autism Spectrum Disorder.

Recent work has suggested atypical neural reward responses in individuals with Autism Spectrum Disorder (ASD), particularly for social reinforcers. Less is known about neural responses to restricted interests and few studies have investigated response to rewards in a learning context. We investigated neurophysiological differences in reinforcement learning between adolescents with ASD and typically developing (TD) adolescents (27 ASD, 31 TD). FMRI was acquired during a learning task in which participants chose one of two doors to reveal an image outcome. Doors differed in their probability of showing liked and not-liked images, which were individualized for each participant. Participants chose the door paired with liked images, but not the door paired with not-liked images, significantly above chance and choice allocation did not differ between groups. Interestingly, participants with ASD made choices less consistent with their initial door preferences. We found a neural prediction-error response at the time of outcome in the ventromedial prefrontal and posterior cingulate cortices that did not differ between groups. Together, behavioural and neural findings suggest that learning with individual interest outcomes is not different between individuals with and without ASD, adding to our understanding of motivational aspects of ASD.

White Matter Structural Connectivity Is Not Correlated to Cortical Resting-State Functional Connectivity over the Healthy Adult Lifespan.

Structural connectivity (SC) of white matter (WM) and functional connectivity (FC) of cortical regions undergo changes in normal aging. As WM tracts form the underlying anatomical architecture that connects regions within resting state networks (RSNs), it is intuitive to expect that SC and FC changes with age are correlated. Studies that investigated the relationship between SC and FC in normal aging are rare, and have mainly compared between groups of elderly and younger subjects. The objectives of this work were to investigate linear SC and FC changes across the healthy adult lifespan, and to define relationships between SC and FC measures within seven whole-brain large scale RSNs. Diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI) data were acquired from 177 healthy participants (male/female = 69/108; aged 18-87 years). Forty cortical regions across both hemispheres belonging to seven template-defined RSNs were considered. Mean diffusivity (MD), fractional anisotropy (FA), mean tract length, and number of streamlines derived from DTI data were used as SC measures, delineated using deterministic tractography, within each RSN. Pearson correlation coefficients of rs-fMRI-obtained BOLD signal time courses between cortical regions were used as FC measure. SC demonstrated significant age-related changes in all RSNs (decreased FA, mean tract length, number of streamlines; and increased MD), and significant FC decrease was observed in five out of seven networks. Among the networks that showed both significant age related changes in SC and FC, however, SC was not in general significantly correlated with FC, whether controlling for age or not. The lack of observed relationship between SC and FC suggests that measures derived from DTI data that are commonly used to infer the integrity of WM microstructure are not related to the corresponding changes in FC within RSNs. The possible temporal lag between SC and FC will need to be addressed in future longitudinal studies to better elucidate the links between SC and FC changes in normal aging.

Morphological Alterations in the Thalamus, Striatum, and Pallidum in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with cognitive, motor, and emotional symptoms. The thalamus and basal ganglia form circuits with the cortex supporting all three of these behavioral domains. Abnormalities in the structure of subcortical regions may suggest atypical development of these networks, with implications for understanding the neural basis of ASD symptoms. Findings from previous volumetric studies have been inconsistent. Here, using advanced surface-based methodology, we investigated localized differences in shape and surface area in the basal ganglia and thalamus in ASD, using T1-weighted anatomical images from the Autism Brain Imaging Data Exchange (373 male participants aged 7-35 years with ASD and 384 typically developing). We modeled effects of diagnosis, age, and their interaction on volume, shape, and surface area. In participants with ASD, we found expanded surface area in the right posterior thalamus corresponding to the pulvinar nucleus, and a more concave shape in the left mediodorsal nucleus. The shape of both caudal putamen and pallidum showed a relatively steeper increase in concavity with age in ASD. Within ASD participants, restricted, repetitive behaviors were positively associated with surface area in bilateral globus pallidus. We found no differences in overall volume, suggesting that surface-based approaches have greater sensitivity to detect localized differences in subcortical structure. This work adds to a growing body of literature implicating corticobasal ganglia-thalamic circuits in the pathophysiology of ASD. These circuits subserve a range of cognitive, emotional, and motor functions, and may have a broad role in the complex symptom profile in ASD.