Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology.

BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Population modelling, often referred to as normative modelling, provides a unified framework for studying age-specific and sex-specific divergences in brain development. METHODS: Here we used population modelling and a large, multi-site neuroimaging dataset (N = 4255 after quality control) to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD). RESULTS: We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume, that was localised to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness, but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only. CONCLUSIONS: These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

The development of aperiodic and periodic resting-state power between early childhood and adulthood: New insights from optically pumped magnetometers.

Neurophysiological signals, comprised of both periodic (e.g., oscillatory) and aperiodic (e.g., non-oscillatory) activity, undergo complex developmental changes between childhood and adulthood. With much of the existing literature primarily focused on the periodic features of brain function, our understanding of aperiodic signals is still in its infancy. Here, we are the first to examine age-related changes in periodic (peak frequency and power) and aperiodic (slope and offset) activity using optically pumped magnetometers (OPMs), a new, wearable magnetoencephalography (MEG) technology that is particularly well-suited for studying development. We examined age-related changes in these spectral features in a sample (N=65) of toddlers (1-3 years), children (4-5 years), young adults (20-26 years), and adults (27-38 years). Consistent with the extant literature, we found significant age-related decreases in the aperiodic slope and offset, and changes in peak frequency and power that were frequency-specific; we are the first to show that the effect sizes of these changes also varied across brain regions. This work not only adds to the growing body of work highlighting the advantages of using OPMs, especially for studying development, but also contributes novel information regarding the variation of neurophysiological changes with age across the brain.

Early nutritional influences on brain regions related to processing speed in children born preterm: A secondary analysis of a randomized trial.

BACKGROUND: Processing speed is a foundational skill supporting intelligence and executive function, areas often delayed in preterm-born children. The impact of early-life nutrition on gray matter facilitating processing speed for this vulnerable population is unknown. METHODS: Magnetic resonance imaging and the Wechsler Preschool and Primary Scale of Intelligence-IV Processing Speed Index were acquired in forty 5-year-old children born preterm with very low birth weight. Macronutrient (grams per kilogram per day) and mother's milk (percentage of feeds) intakes were prospectively collected in the first postnatal month and associations between early-life nutrition and the primary outcome of brain regions supporting processing speed were investigated. RESULTS: Children had a mean (SD) gestational age of 27.8 (1.8) weeks and 45% were male. Macronutrient intakes were unrelated, but mother's milk was positively related, to greater volumes in brain regions, including total cortical gray matter, cingulate gyri, and occipital gyri. CONCLUSION: First postnatal month macronutrient intakes showed no association, but mother's milk was positively associated, with volumetric measures of total and regional cortical gray matter related to processing speed in preterm-born children. This exploratory analysis suggests early-life mother's milk supports processing speed by impacting structural underpinnings. Further research is needed on this potential strategy to improve preterm outcomes.

Paediatric Magnetoencephalography and its Role in Neurodevelopmental Disorders.

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that assesses neurophysiology, through detection of the magnetic fields generated by neural currents. In this way, it is sensitive to brain activity, both in individual regions and brain-wide networks. Conventional MEG systems employ an array of sensors that must be cryogenically cooled to low temperature, in a rigid one-size-fits-all helmet. Systems are typically designed to fit adults and are therefore challenging to use for paediatric measurements. Despite this, MEG has been employed successfully in research to investigate neurodevelopmental disorders, and clinically for presurgical planning for paediatric epilepsy. Here, we review the applications of MEG in children, specifically focussing on autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). Our review demonstrates the significance of MEG in furthering our understanding of these neurodevelopmental disorders, whilst also highlighting the limitations of current instrumentation. We also consider the future of paediatric MEG, with a focus on newly developed instrumentation based on optically pumped magnetometers (OPM-MEG). We provide a brief overview of the development of OPM-MEG systems, and how this new technology might enable investigation of brain function in very young children and infants.

Tracking the neurodevelopmental trajectory of beta band oscillations with optically pumped magnetometer-based magnetoencephalography.

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - optically pumped magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Early-life nutrition is associated with processing speed at age 5 in children born preterm with very low birth weight.

OBJECTIVE: Processing speed is suboptimal among preterm-born children which is of concern as it is a foundational skill supporting higher-level cognitive functions. The study objective was to evaluate associations between early-life nutrition and processing speed in childhood. METHODS: Macronutrient and human milk (mother's own, donor) intakes from 137 children born preterm with very low birth weight enrolled in a nutrition feeding trial were included. Processing speed was evaluated at age 5 using the Wechsler Preschool and Primary Scale of Intelligence-fourth edition Processing Speed Index. Associations between early-life nutrition and processing speed were explored through linear regression. RESULTS: Children had a mean (standard deviation [SD]) birth gestational age of 28.1 (2.5) weeks, weight of 1036 (260) g and 52% were male. The mean (SD) assessment age was 5.7 (0.2) years. Sex-dependent relationships were identified between first postnatal month protein, lipid and energy intakes and processing speed at 5 years. For females, lower protein (per 0.1 g/kg/d: -0.88, 95% confidence interval [CI]: -1.53, -0.23; p = 0.01) and energy (per 10 kcal/kg/d: -2.38, 95% CI: -4.70, -0.05; p = 0.03) intakes were related to higher processing speed scores. Mother's milk provision was positively associated (per 10% increase: 0.80, 95% CI: 0.22, 1.37; p = 0.01) and donor milk was negatively associated (per 10% increase: -1.15, 95% CI: -2.22, -0.08; p = 0.04) with processing speed scores; no sex differences were observed. CONCLUSIONS: First postnatal month nutrition was related to processing speed at age 5 in children born preterm with very low birth weight. Early-life nutrition that supports processing speed may be leveraged to improve later cognitive outcomes for this vulnerable population.

Behaviour-correlated profiles of cerebellar-cerebral functional connectivity observed in independent neurodevelopmental disorder cohorts.

The cerebellum, through its connectivity with the cerebral cortex, plays an integral role in regulating cognitive and affective processes, and its dysregulation can result in neurodevelopmental disorder (NDD)-related behavioural deficits. Identifying cerebellar-cerebral functional connectivity (FC) profiles in children with NDDs can provide insight into common connectivity profiles and their correlation to NDD-related behaviours. 479 participants from the Province of Ontario Neurodevelopmental Disorders (POND) network (typically developing = 93, Autism Spectrum Disorder = 172, Attention Deficit/Hyperactivity Disorder = 161, Obsessive-Compulsive Disorder = 53, mean age = 12.2) underwent resting-state functional magnetic resonance imaging and behaviour testing (Social Communication Questionnaire, Toronto Obsessive-Compulsive Scale, and Child Behaviour Checklist - Attentional Problems Subscale). FC components maximally correlated to behaviour were identified using canonical correlation analysis. Results were then validated by repeating the investigation in 556 participants from an independent NDD cohort provided from a separate consortium (Healthy Brain Network (HBN)). Replication of canonical components was quantified by correlating the feature vectors between the two cohorts. The two cerebellar-cerebral FC components that replicated to the greatest extent were correlated to, respectively, obsessive-compulsive behaviour (behaviour feature vectors, rPOND-HBN = -0.97; FC feature vectors, rPOND-HBN = -0.68) and social communication deficit contrasted against attention deficit behaviour (behaviour feature vectors, rPOND-HBN = -0.99; FC feature vectors, rPOND-HBN = -0.78). The statistically stable (|z| > 1.96) features of the FC feature vectors, measured via bootstrap re-sampling, predominantly comprised of correlations between cerebellar attentional and control network regions and cerebral attentional, default mode, and control network regions. In both cohorts, spectral clustering on FC loading values resulted in subject clusters mixed across diagnostic categories, but no cluster was significantly enriched for any given diagnosis as measured via chi-squared test (p > 0.05). Overall, two behaviour-correlated components of cerebellar-cerebral functional connectivity were observed in two independent cohorts. This suggests the existence of generalizable cerebellar network differences that span across NDD diagnostic boundaries.

Gender diversity is correlated with dimensional neurodivergent traits but not categorical neurodevelopmental diagnoses in children.

BACKGROUND: Gender clinic and single-item questionnaire-based data report increased co-occurrence of gender diversity and neurodevelopmental conditions. The nuances of these associations are under-studied. We used a transdiagnostic approach, combining categorical and dimensional characterization of neurodiversity, to further the understanding of its associations with gender diversity in identity and expression in children. METHODS: Data from 291 children (Autism N = 104, ADHD N = 104, Autism + ADHD N = 17, neurotypical N = 66) aged 4-12 years enrolled in the Province of Ontario Neurodevelopmental Network were analyzed. Gender diversity was measured multi-dimensionally using a well-validated parent-report instrument, the Gender Identity Questionnaire for Children (GIQC). We used gamma regression models to determine the significant correlates of gender diversity among age, puberty, sex-assigned-at-birth, categorical neurodevelopmental diagnoses, and dimensional neurodivergent traits (using the Social Communication Questionnaire and the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scales). Internalizing and externalizing problems were included as covariates. RESULTS: Neither a categorical diagnosis of autism nor ADHD significantly correlated with current GIQC-derived scores. Instead, higher early-childhood dimensional autistic social-communication traits correlated with higher current overall gender incongruence (as defined by GIQC-14 score). This correlation was potentially moderated by sex-assigned-at-birth: greater early-childhood autistic social-communication traits were associated with higher current overall gender incongruence in assigned-males-at-birth, but not assigned-females-at-birth. For fine-grained gender diversity domains, greater autistic restricted-repetitive behavior traits were associated with greater diversity in gender identity across sexes-assigned-at-birth; greater autistic social-communication traits were associated with lower stereotypical male expression across sexes-assigned-at-birth. CONCLUSIONS: Dimensional autistic traits, rather than ADHD traits or categorical neurodevelopmental diagnoses, were associated with gender diversity domains across neurodivergent and neurotypical children. The association between early-childhood autistic social-communication traits and overall current gender diversity was most evident in assigned-males-at-birth. Nuanced interrelationships between neurodivergence and gender diversity should be better understood to clarify developmental links and to offer tailored support for neurodivergent and gender-diverse populations.

Medical student non-modifiable risk factors and USMLE Step 1 exam score.

For diversity to exist in the medical graduate workforce, students from all backgrounds should have equitable opportunities of employment. Specialties have utilized a minimal threshold for USMLE Step 1 score when screening applicants for residency interviews. The OHSU SOM class of 2021 completed a 14-question voluntary survey on their Step 1 score and the following non-modifiable risk factors: Adverse Childhood Experience score (ACEs), sex, gender, Underrepresented in Medicine status (URiM), family income during adolescence, highest degree held by a guardian, discrimination experience during medical school, federal/state assistance use, and rural versus urban primary home. Descriptive statistics and unadjusted risk ratios were applied to study the relation between Step 1 score and non-modifiable risk factors as well as certain non-modifiable risk factors and ACEs ≥ 3. The mean Step 1 score was 230 (213, 247). Of the students, 28.2% identified ACEs ≥ 3, 13.6% were considered URiM, and 65.4% were female. URiM were 2.34 (1.30, 4.23),females were 2.77 (1.06-7.29), and those who experienced discrimination in medical school were 4.25 (1.85, 9.77) times more likely to have ACEs ≥ 3. Students who had ACEs ≥ 3 were 3.58 (1.75, 7.29) times less likely to meet a minimal threshold for residency interviews of 220. These are the first results to demonstrate a relationship between Step 1 score and ACEs. Those who identified as URiM, females, and those who experienced discrimination in medical school were at a higher risk of ACEs of ≥ 3. Step 1 transitioned to pass/fail in January 2022. However, the first application cycle that residencies will see pass/fail scoring is 2023-2024, and fellowships will continue to see scored Step 1 until, at the earliest, the 2026-2027 application cycle. These data contribute to a foundation of research that could apply to Step 2CK testing scores, and help to inform decisions about the diversity and equity of the residency interview process.

Using optically pumped magnetometers to replicate task-related responses in next generation magnetoencephalography.

Optically pumped magnetometers (OPMs) offer a new wearable means to measure magnetoencephalography (MEG) signals, with many advantages compared to conventional systems. However, OPMs are an emerging technology, thus characterizing and replicating MEG recordings is essential. Using OPM-MEG and SQUID-MEG, this study investigated evoked responses, oscillatory power, and functional connectivity during emotion processing in 20 adults, to establish replicability across the two technologies. Five participants with dental fixtures were included to assess the validity of OPM-MEG recordings in those with irremovable metal. Replicable task-related evoked responses were observed in both modalities. Similar patterns of oscillatory power to faces were observed in both systems. Increased connectivity was found in SQUID-versus OPM-MEG in an occipital and parietal anchored network. Notably, high quality OPM-MEG data were retained in participants with metallic fixtures, from whom no useable data were collected using conventional MEG.

The neurodevelopmental trajectory of beta band oscillations: an OPM-MEG study.

Neural oscillations mediate the coordination of activity within and between brain networks, supporting cognition and behaviour. How these processes develop throughout childhood is not only an important neuroscientific question but could also shed light on the mechanisms underlying neurological and psychiatric disorders. However, measuring the neurodevelopmental trajectory of oscillations has been hampered by confounds from instrumentation. In this paper, we investigate the suitability of a disruptive new imaging platform - Optically Pumped Magnetometer-based magnetoencephalography (OPM-MEG) - to study oscillations during brain development. We show how a unique 192-channel OPM-MEG device, which is adaptable to head size and robust to participant movement, can be used to collect high-fidelity electrophysiological data in individuals aged between 2 and 34 years. Data were collected during a somatosensory task, and we measured both stimulus-induced modulation of beta oscillations in sensory cortex, and whole-brain connectivity, showing that both modulate significantly with age. Moreover, we show that pan-spectral bursts of electrophysiological activity drive task-induced beta modulation, and that their probability of occurrence and spectral content change with age. Our results offer new insights into the developmental trajectory of beta oscillations and provide clear evidence that OPM-MEG is an ideal platform for studying electrophysiology in neurodevelopment.

Dorsal Striatal Functional Connectivity and Repetitive Behavior Dimensions in Children and Youths With Neurodevelopmental Disorders.

BACKGROUND: Impairing repetitive behaviors are one of the core diagnostic symptoms in autism spectrum disorder and obsessive-compulsive disorder, but they also manifest in attention-deficit/hyperactivity disorder. Although the dorsal striatal circuit has been implicated in repetitive behaviors, extensive heterogeneity in and cross-diagnostic manifestations of these behaviors have suggested phenotypic and likely neurobiological heterogeneity across neurodevelopmental disorders (NDDs). METHODS: Intrinsic dorsal striatal functional connectivity was examined in 3 NDDs (autism spectrum disorder, obsessive-compulsive disorder, and attention-deficit/hyperactivity disorder) and typically developing control participants in a large single-cohort sample (N = 412). To learn how diagnostic labels and overlapping behaviors manifest in dorsal striatal functional connectivity measured with functional magnetic resonance imaging, the main and interaction effects of diagnosis and behavior were examined in 8 models (2 seed functional connectivity [caudate and putamen] × 4 sub-behavioral domains [sameness/ritualistic, self-injury, stereotypy, and compulsions]). RESULTS: The obsessive-compulsive disorder group demonstrated distinctive patterns in visual and visuomotor coordination regions compared with the other diagnostic groups. Lower-order repetitive behaviors (self-injury and stereotypy) manifesting across all participants were implicated in regions involved in motor and cognitive control, although the findings did not survive effects of multiple comparisons, suggesting heterogeneity in these behavioral domains. An interaction between self-injurious behavior and an attention-deficit/hyperactivity disorder diagnosis were observed on caudate-cerebellum functional connectivity. CONCLUSIONS: These findings confirmed high heterogeneity and overlapping behavioral manifestations in NDDs and their complex underlying neural mechanisms. A call for diagnosis-free symptom measures that can capture not only observable symptoms and severity across NDDs but also the underlying functions and motivations of such behaviors across diagnoses is needed.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology.

Background: Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development. Methods: Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD). Results: We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only. Conclusions: These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Characterizing Subcortical Structural Heterogeneity in Autism.

Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large (n=3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth). We investigated three potentially important sources of neuroanatomical heterogeneity: sex, age, and intelligence quotient (IQ), using a meta-analytic technique after strict quality control to minimize non-biological sources of variation. We observed no volumetric differences in the thalamus, globus pallidus, or striatum in autism. Rather, we identified a variety of localized shape differences in all three structures. Including age, but not sex or IQ, in the statistical model improved the fit for both the pallidum and striatum, but not for the thalamus. Age-centered shape analysis indicated a variety of age-dependent regional differences. Overall, our findings help confirm that the neurodevelopment of the striatum, globus pallidus and thalamus are atypical in autism, in a subtle location-dependent manner that is not reflected in overall structure volumes, and that is highly non-uniform across the lifespan.

The development of functional connectivity within the dorsal striatum from early childhood to adulthood.

Dorsal striatum, principally comprising of caudate and putamen, is well-known to support motor function but also various higher-order cognitive functions. This is enabled by developing short- and long-range connections to distributed cortical regions throughout the life span, but few studies have examined developmental changes from young children to adults in the same cohort. Here we investigated the development of dorsal-striatal network in a large (n = 476), single-site sample of healthy subjects 3-42 years of age in three groups (children, adolescence, adults). The results showed that the connectivity within the striatum and to sensorimotor regions was established at an early stage of life and remained strong in adolescence, supporting that sensory-seeking behaviours and habit formation are important learning mechanisms during the developmental periods. This connectivity diminished with age, as many behaviours become more efficient and automated. Adolescence demonstrated a remarkable transition phase where the connectivity to dorsolateral prefrontal cortex emerged but connectivity to the dorsomedial prefrontal and posterior brain, which belong to the ventral attentional and default mode networks, was only seen in adults. This prolonged maturation in between-network integration may explain the behavioural characteristics of adolescents in that they exhibit elaborated cognitive performance but also demonstrate high risk-taking behaviours.

Richer than we thought: neurophysiological methods reveal rich-club network development is frequency- and sex-dependent.

A set of highly connected brain regions called the "rich-club" are vital in integrating information across the functional connectome. Although the literature has identified some changes in rich-club organization with age, little is known about potential sex-specific developmental trajectories, and neurophysiologically relevant frequency-dependent changes have not been established. Here we examine the frequency- and sex-dependent development of rich-club organization using magnetoencephalography in a large normative sample (N = 383) over a wide age span (4-39 years). We report strong divergence between males and females across alpha, beta, and gamma frequencies. While males show increased or no change in rich-club organization with age, females show a consistent, non-linear trajectory that increases through childhood, shifting direction in early adolescence. Using neurophysiological modalities for capturing complex inter-relations between oscillatory dynamics, age, and sex, we establish diverging, sex-specific developmental trajectories of the brain's core functional organization, critically important to our understanding of brain health and disease.

Atypical oscillatory dynamics during emotional face processing in paediatric obsessive-compulsive disorder with MEG.

Children and youth with obsessive-compulsive disorder (OCD) demonstrate difficulties with social, emotional and cognitive functions in addition to the core diagnosis of obsessions and compulsions. This is the first magnetoencephalography (MEG) study to examine whole-brain neurophysiological functional connectivity of emotional face processing networks in paediatric OCD. Seventy-two participants (OCD: n = 36; age 8-17 yrs; typically developing controls: n = 36, age 8-17 yrs) completed an implicit emotional face processing task in the MEG. Functional connectivity networks in canonical frequency bands were compared between groups, and within OCD and control groups between emotions (angry vs. happy). Between groups, participants with OCD showed increased functional connectivity in the gamma band to angry faces, suggesting atypical perception of angry faces in OCD. Within groups, the OCD group showed greater engagement of the beta band, suggesting the over-use of top-down processing when perceiving happy versus angry emotions, while controls engaged in bottom-up gamma processing, also greater to happy faces. Over-activation of top-down processing has been linked to difficulties modifying one's cognitive set. Findings establish altered patterns of neurophysiological connectivity in children with OCD, and are striking in their oscillatory specificity. Our results contribute to a greater understanding of the neurobiology of the disorder, and are foundational for the possibility of alternative targets for intervention.

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data.

Importance: Neurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings. Objective: To identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets. Design, Setting, and Participants: This case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study. Main Outcomes and Measures: The analyses consisted of a data-driven clustering procedure on measures derived from each participant's resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested. Results: Overall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set. Conclusions and Relevance: The findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.

Functional connectivity changes during working memory in autism spectrum disorder: A two-year longitudinal MEG study.

Working memory impairments have been reported in adults with autism spectrum disorder (ASD) and associated with functional outcomes and social difficulties. However, little is known about the developmental trajectory of working memory in youth with ASD. The current magnetoencephalography (MEG) study is the first to examine the longitudinal development over two years of working memory networks in youth with ASD. We analysed MEG data from 32 children and adolescents with and without ASD (64 datasets; 7-14 years), all tested twice at a two-year interval, during a visual n-back task, with two loads (1- and 2-back). We performed a whole-brain functional connectivity analysis to examine the networks during the successful recognition of visual stimuli. We demonstrate that youth with ASD show decreased connectivity in the theta frequency (4-7 Hz) in the higher memory load (2-back) condition compared to typically developing (TD) controls. This hypo-connected theta network was anchored in primary visual areas with connections to frontal, parietal and limbic regions. These network differences were found despite similar task performance between ASD and TD groups. Within the TD group, we found an increase in alpha (8-14 Hz) connectivity at Time 2 compared to Time 1 in both the 1- and 2-back conditions. These findings demonstrate the continued development of working memory mechanisms over middle childhood, which were not apparent in youth with ASD. Together, our findings support a network-based approach to understanding atypical neural functioning in ASD and the developmental trajectories of working memory processes over middle childhood.

Cerebellar gamma-aminobutyric acid: Investigation of group effects in neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD) are thought to arise in part from the disruption in the excitatory/inhibitory balance of gamma-aminobutyric acid (GABA) and glutamate in the brain. Recent evidence has shown the involvement of the cerebellum in cognition and affect regulation, and cerebellar atypical function or damage is reported frequently in NDDs. Magnetic resonance spectroscopy studies have reported decreases in GABA in cortical brain areas in the NDDs, however, GABA levels in the cerebellum have not been examined. To determine possible group effects, we used a MEGA-PRESS acquisition to investigate GABA+ levels in a cerebellar voxel in 343 individuals (aged 2.5-22 years) with ASD, ADHD, OCD and controls. Using a mixed effects model, we found no significant differences between groups in GABA+ concentration. Our findings suggest that cerebellar GABA+ levels do not differentiate NDD groups.