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Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Although the neural scaffolding for language is putatively present before birth, the maturation of functional connections among the key nodes of the language network, Broca's and Wernicke's areas, is less known. We leveraged longitudinal and cross-sectional data from three sites collected through six studies to track the development of functional circuits between Broca's and Wernicke's areas from 30 weeks of gestation through 30 months of age in 127 unique participants. Using resting-state fMRI data, functional connectivity was calculated as the correlation between fMRI time courses from pairs of regions, defined as Broca's and Wernicke's in both hemispheres. The primary analysis evaluated 23 individuals longitudinally imaged from 30 weeks postmenstrual age (fetal) through the first postnatal month (neonatal). A secondary analysis in 127 individuals extended these curves into older infants and toddlers. These data demonstrated significant growth of interhemispheric connections including left Broca's and its homolog and left Wernicke's and its homolog from 30 weeks of gestation through the first postnatal month. In contrast, intrahemispheric connections did not show significant increases across this period. These data represent an important baseline for language systems in the developing brain against which to compare those neurobehavioral disorders with the potential fetal onset of disease., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Autism spectrum disorder (ASD) is characterized by atypical connectivity lateralization of functional networks. However, previous studies have not directly investigated if differences in specialization between ASD and typically developing (TD) peers are present in infancy, leaving the timing of onset of these differences relatively unknown. We studied the hemispheric asymmetries of connectivity in children with ASD and infants later meeting the diagnostic criteria for ASD. Analyses were performed in 733 children with ASD and TD peers and in 71 infants at high risk (HR) or normal risk (NR) for ASD, with data collected at 1 month and 9 months of age. Comparing children with ASD (n = 301) to TDs (n = 432), four regions demonstrated group differences in connectivity: posterior cingulate cortex (PCC), posterior superior temporal gyrus, extrastriate cortex, and anterior prefrontal cortex. At 1 month, none of these regions exhibited group differences between ASD (n = 10), HR-nonASD (n = 15), or NR (n = 18) infants. However, by 9 months, the PCC and extrastriate exhibited atypical connectivity in ASD (n = 11) and HR-nonASD infants (n = 24) compared to NR infants (n = 22). Connectivity did not correlate with symptoms in either sample. Our results demonstrate that differences in network asymmetries associated with ASD risk are observable prior to the age of a reliable clinical diagnosis., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Background: Fetal exposure risk factors are associated with increased autism spectrum disorder (ASD) risk. New hypotheses regarding multigenerational risk for ASD have been proposed, but epidemiological evidence is largely lacking. We evaluated whether parental birth characteristics, including preterm birth and low birthweight, were associated with ASD risk in offspring., Methods: We conducted a nationwide register-based cohort study that included 230 174 mother-child and 157 926 father-child pairs in Denmark. Logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for offspring ASD according to parental preterm (<37 weeks) and low birthweight (<2500 g) status, with or without adjustment for certain grandmaternal sociodemographic factors. Mediation analyses were performed for selected parental and offspring health-related factors., Results: Offspring of mothers or fathers with adverse birth characteristics had about 31-43% higher risk for ASD (maternal preterm birth, OR = 1.31, 95% CI= 1.12, 1.55; maternal low birthweight, OR = 1.35, 95% CI: 1.17,1.57; paternal preterm birth, OR = 1.43, 95% CI = 1.18, 1.73; paternal low birthweight, OR = 1.38, 95% CI= 1.13, 1.70). Parents born very preterm (<32 weeks) marked a nearly 2-fold increase in ASD risk in their children. These associations were slightly attenuated upon adjustment for grandmaternal sociodemographic factors. Mediation analyses suggested that parental social-mental and offspring perinatal factors might explain a small magnitude of the total effect observed, especially for maternal birth characteristic associations., Conclusions: Offspring of parents born with adverse characteristics had an elevated risk for ASD. Transmission of ASD risk through maternal and paternal factors should be considered in future research on ASD aetiology., (© The Author(s) 2021; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)