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1. Parent attitudes towards predictive testing for autism in the first year of life

Author

Aurora M. Washington, Amanda H. Mercer, Catherine A. Burrows, Stephen R. Dager, Jed T. Elison, Annette M. Estes, Rebecca Grzadzinski, Chimei Lee, Joseph Piven, John R. Pruett, Mark D. Shen, Benjamin Wilfond, Jason Wolff, Lonnie Zwaigenbaum, and Katherine E. MacDuffie

Subjects
Autism, Biomarkers, Prediction, Stakeholder engagement, Bioethics, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Background Emerging biomarker technologies (e.g., MRI, EEG, digital phenotyping, eye-tracking) have potential to move the identification of autism into the first year of life. We investigated the perspectives of parents about the anticipated utility and impact of predicting later autism diagnosis from a biomarker-based test in infancy. Methods Parents of infants were interviewed to ascertain receptiveness and perspectives on early (6-12 months) prediction of autism using emerging biomarker technologies. One group had experience parenting an older autistic child (n=30), and the other had no prior autism parenting experience (n=25). Parent responses were analyzed using inductive qualitative coding methods. Results Almost all parents in both groups were interested in predictive testing for autism, with some stating they would seek testing only if concerned about their infant’s development. The primary anticipated advantage of testing was to enable access to earlier intervention. Parents also described the anticipated emotions they would feel in response to test results, actions they might take upon learning their infant was likely to develop autism, attitudes towards predicting a child’s future support needs, and the potential impacts of inaccurate prediction. Conclusion In qualitative interviews, parents of infants with and without prior autism experience shared their anticipated motivations and concerns about predictive testing for autism in the first year of life. The primary reported motivators for testing—to have more time to prepare and intervene early—could be constrained by familial resources and service availability. Implications for ethical communication of results, equitable early intervention, and future research are discussed.

Published
2024
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2. Neurobehavioral outcomes of neonatal asymptomatic congenital cytomegalovirus infection at 12-months

Author

Sally M. Stoyell, Jed T. Elison, Emily Graupmann, Neely C. Miller, Jessica Emerick, Elizabeth Ramey, Kristen Sandness, Mark R. Schleiss, and Erin A. Osterholm

Subjects
Congenital CMV infection, Intellectual disability, TORCH infections, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Background Congenital cytomegalovirus (cCMV) is the most common congenital viral infection in the United States. Symptomatic infections can cause severe hearing loss and neurological disability, although ~ 90% of cCMV infections are asymptomatic at birth. Despite its prevalence, the long-term neurobehavioral risks of asymptomatic cCMV infections are not fully understood. The objective of this work was to evaluate for potential long-term neurobehavioral sequelae in infants with asymptomatic cCMV. Methods Infants with cCMV were identified from a universal newborn cCMV screening study in a metropolitan area in the midwestern United States. Asymptomatic infants with cCMV were enrolled in a longitudinal neurodevelopmental study (N = 29). Age- and sex-matched healthy control infants (N = 193) were identified from the Baby Connectome Project (BCP), a longitudinal study of brain and behavioral development. The BCP sample supplemented an additional group of healthy control infants (N = 30), recruited from the same participant registry as the BCP specifically for comparison with infants with asymptomatic cCMV. Neurobehavioral assessments and parent questionnaires, including the Mullen Scales of Early Learning, the Repetitive Behavior Scales for Early Childhood (RBS-EC), and the Infant Toddler Social Emotional Assessment (ITSEA) were administered at 12 months of age. Neurobehavioral scores were compared between infants with asymptomatic cCMV and all identified healthy control infants. Results Infants with asymptomatic cCMV performed equivalently compared to healthy control infants on the neurobehavioral measures tested at 12 months of age. Conclusions These results indicate that at 12 months of age, infants with asymptomatic cCMV are not statistically different from controls in a number of neurobehavioral domains. Although follow-up is ongoing, these observations provide reassurance about neurobehavioral outcomes for infants with asymptomatic cCMV and inform the ongoing discussion around universal screening. Additional follow-up will be necessary to understand the longer-term outcomes of these children.

Published
2024
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3. Metagenomic assessment of the bacterial breastfeeding microbiome in mature milk across lactation

Author

Kelly Ingram, Collin Gregg, Allison Tegge, Jed T. Elison, Weili Lin, and Brittany R. Howell

Subjects
human milk, microbiome, breastfeeding, metagenomic, longitudial analysis, Pediatrics, RJ1-570
Abstract

IntroductionResearch has illustrated the presence of a diverse range of microbiota in human milk. The composition of the milk microbiome varies across different stages of lactation, emphasizing the need to consider the lactation stage when studying its composition. Additionally, the transfer of both milk and skin microbiota during breastfeeding is crucial for understanding their collective impact on infant health and development. Further exploration of the complete breastfeeding microbiome is necessary to unravel the role these organisms play in infant development. We aim to longitudinally assess the bacterial breastfeeding microbiome across stages of lactation. This includes all the bacteria that infants are exposed to during breastfeeding, such as bacteria found within human milk and any bacteria found on the breast and nipple.MethodsForty-six human milk samples were collected from 15 women at 1, 4, 7, and 10 months postpartum. Metagenomic analysis of the bacterial microbiome for these samples was performed by CosmosID (Rockville, MD) via deep sequencing.ResultsStaphylococcus epidermidis and Propionibacteriaceae species are the most abundant bacterial species from these samples. Samples collected at 10 months showed higher abundances of Proteobacteria, Streptococcaceae, Lactobacillales, Streptococcus, and Neisseria mucosa compared to other timepoints. Alpha diversity varied greatly between participants but did not change significantly over time.DiscussionAs the bacterial breastfeeding microbiome continues to be studied, bacterial contributions could be used to predict and reduce health risks, optimize infant outcomes, and design effective management strategies, such as altering the maternal flora, to mitigate adverse health concerns.

Published
2024
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4. Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample

Author

Trevor K.M. Day, Robert Hermosillo, Gregory Conan, Anita Randolph, Anders Perrone, Eric Earl, Nora Byington, Timothy J. Hendrickson, Jed T. Elison, Damien A. Fair, and Eric Feczko

Subjects
FMRI, RsfMRI, Hemispheric specialization, Cortical specialization, Neurophysiology and neuropsychology, QP351-495
Abstract

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term “Wernicke’s area” near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Published
2024
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6. Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Author

Matthew W. Mosconi, Cassandra J. Stevens, Kathryn E. Unruh, Robin Shafer, and Jed T. Elison

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of “endophenotype trait domains” (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Published
2023
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7. Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples

Author

Catherine A. Burrows, Carolyn Lasch, Julia Gross, Jessica B. Girault, Joshua Rutsohn, Jason J. Wolff, Meghan R. Swanson, Chimei M. Lee, Stephen R. Dager, Emil Cornea, Rebecca Stephens, Martin Styner, Tanya St. John, Juhi Pandey, Meera Deva, Kelly N. Botteron, Annette M. Estes, Heather C. Hazlett, John R. Pruett, Jr., Robert T. Schultz, Lonnie Zwaigenbaum, John H. Gilmore, Mark D. Shen, Joseph Piven, and Jed T. Elison

Subjects
Autism spectrum disorder (ASD), Anxiety, Amygdala, Reproducibility, Magnetic resonance imaging (MRI), Neurophysiology and neuropsychology, QP351-495
Abstract

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6–12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups.

Published
2024
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8. Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life

Author

Weixiong Jiang, Zhen Zhou, Guoshi Li, Weiyan Yin, Zhengwang Wu, Li Wang, Maryam Ghanbari, Gang Li, Pew-Thian Yap, Brittany R. Howell, Martin A. Styner, Essa Yacoub, Heather Hazlett, John H. Gilmore, J. Keith Smith, Kamil Ugurbil, Jed T. Elison, Han Zhang, Dinggang Shen, and Weili Lin

Subjects
Longitudinal, Development, Brain network, Graph theory, RsfMRI, Cognitive ability, Neurophysiology and neuropsychology, QP351-495
Abstract

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P

Published
2023
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9. Interactions between Bifidobacterium and Bacteroides and human milk oligosaccharides and their associations with infant cognition

Author

Seoyoon Cho, Tinu M. Samuel, Tengfei Li, Brittany R. Howell, Kristine Baluyot, Heather C. Hazlett, Jed T. Elison, Hongtu Zhu, Jonas Hauser, Norbert Sprenger, and Weili Lin

Subjects
human milk, infant gut microbiota, early cognitive development, Mullen Scales of Early Learning, human milk oligosaccharides, random linear mixed effects model, Nutrition. Foods and food supply, TX341-641
Abstract

While ample research on independent associations between infant cognition and gut microbiota composition and human milk (HM) oligosaccharides (HMOs) has been reported, studies on how the interactions between gut microbiota and HMOs may yield associations with cognitive development in infancy are lacking. We aimed to determine how HMOs and species of Bacteroides and Bifidobacterium genera interact with each other and their associations with cognitive development in typically developing infants. A total of 105 mother-infant dyads were included in this study. The enrolled infants [2.9–12 months old (8.09 ± 2.48)] were at least predominantly breastfed at 4 months old. A total of 170 HM samples from the mothers and fecal samples of the children were collected longitudinally. Using the Mullen Scales of Early Learning to assess cognition and the scores as the outcomes, linear mixed effects models including both the levels of eight HMOs and relative abundance of Bacteroides and Bifidobacterium species as main associations and their interactions were employed with adjusting covariates; infant sex, delivery mode, maternal education, site, and batch effects of HMOs. Additionally, regression models stratifying infants based on the A-tetrasaccharide (A-tetra) status of the HM they received were also employed to determine if the associations depend on the A-tetra status. With Bacteroides species, we observed significant associations with motor functions, while Bif. catenulatum showed a negative association with visual reception in the detectable A-tetra group both as main effect (value of p = 0.012) and in interaction with LNFP-I (value of p = 0.007). Additionally, 3-FL showed a positive association with gross motor (p = 0.027) and visual reception (p = 0.041). Furthermore, significant associations were observed with the interaction terms mainly in the undetectable A-tetra group. Specifically, we observed negative associations for Bifidobacterium species and LNT [breve (p = 0.011) and longum (p = 0.022)], and positive associations for expressive language with 3′-SL and Bif. bifidum (p = 0.01), 6′-SL and B. fragilis (p = 0.019), and LNFP-I and Bif. kashiwanohense (p = 0.048), respectively. Our findings suggest that gut microbiota and HMOs are both independently and interactively associated with early cognitive development. In particular, the diverse interactions between HMOs and Bacteroides and Bifidobacterium species reveal different candidate pathways through which HMOs, Bifidobacterium and Bacteroides species potentially interact to impact cognitive development in infancy.

Published
2023
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10. Creating a sustainable action-oriented engagement infrastructure—a UMN-MIDB perspective

Author

Anita C. Randolph, Alex Henry, Amy Hewitt, Angie P. Mejia, Raj Sethuraju, Meriah DeJoseph, Melissa Koenig, Jed T. Elison, and Damien A. Fair

Subjects
community engagement, diversity, infrastructure building, diversifying STEAM, neuroscience, inequities in education, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Following the murder of George Floyd on May 25, 2020, Minneapolis represented the epicenter of protests that would reverberate internationally and re-instantiate a reckoning of the systemic and institutional racism that plagues American society. Also in the summer of 2020, and after several years of planning, the University of Minnesota (UMN) launched the Masonic Institute for the Developing Brain (MIDB), an interdisciplinary clinical and community research enterprise designed to create knowledge and engage all members of our community. In what follows, we describe the mission of the MIDB Community Engagement and Education (CEEd) Core and adjacent efforts within the UMN neuroscience and psychology community. Inherent to these efforts is the explicit attempt to de-center the dominant academic voice and affirm knowledge creation is augmented by diverse voices within and outside of traditional academic institutions. We describe several initiatives, including the Neuroscience Opportunities for Discovery and Equity (NODE) network, the NextGen Psych Scholars Program (NPSP), the Young Scientist Program, among others as exemplars of our approach. Developing and fortifying sustainable pathways for authentic community-academic partnerships are of central importance to enhance mutually beneficial scientific discovery. We posit that traditional academic approaches to community engagement to benefit the institution are severely constrained and perpetuate inherently exploitative power dynamics between academic institutions and communities.

Published
2022
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11. Joint analyses of human milk fatty acids, phospholipids, and choline in association with cognition and temperament traits during the first 6 months of life

Author

Tengfei Li, Tinu M. Samuel, Ziliang Zhu, Brittany Howell, Seoyoon Cho, Kristine Baluyot, Heather Hazlett, Jed T. Elison, Di Wu, Jonas Hauser, Norbert Sprenger, Hongtu Zhu, and Weili Lin

Subjects
human milk, cognition and temperament, Mullen Scales of Early Learning, IBQ, receptive language, surgency, Nutrition. Foods and food supply, TX341-641
Abstract

Early dietary exposure via human milk nutrients offers a window of opportunity to support cognitive and temperament development. While several studies have focused on associations of few pre-selected human milk nutrients with cognition and temperament, it is highly plausible that human milk nutrients synergistically and jointly support cognitive and behavioral development in early life. We aimed to discern the combined associations of three major classes of human milk nutrients with cognition and temperament during the first 6 months of life when human milk is the primary source of an infant’s nutrition and explore whether there were persistent effects up to 18 months old. The Mullen Scales of Early Learning and Infant Behavior Questionnaires—Revised were used to assess cognition and temperament, respectively, of 54 exclusively/predominantly breastfed infants in the first 6 months of life, whose follow-ups were conducted at 6–9, 9–12, and 12–18 months old. Human milk samples were obtained from the mothers of the participants at less than 6 months of age and analyzed for fatty acids [total monounsaturated fatty acids, polyunsaturated fatty acid, total saturated fatty acid (TSFA), arachidonic acid (ARA), docosahexaenoic acid (DHA), ARA/DHA, omega-6/omega-3 polyunsaturated fatty acids ratio (n-6/n-3)], phospholipids [phosphatidylcholine, phosphatidylethanolamine (PE), phosphatidylinositol (PI), sphingomyelin], and choline [free choline, phosphocholine (PCho), glycerophosphocholine]. Feature selection was performed to select nutrients associated with cognition and temperament. The combined effects of selected nutrients were analyzed using multiple regression. A positive association between the arachidonic acid (ARA) and surgency was observed (p = 0.024). A significant effect of DHA, n-6/n-3, PE, and TSFA concentrations on receptive language (R2 = 0.39, p = 0.025) and the elevated ARA, PCho, and PI with increased surgency (R2 = 0.43, p = 0.003) was identified, suggesting that DHA and ARA may have distinct roles for temperament and language functions. Furthermore, the exploratory association analyses suggest that the effects of human milk nutrients on R.L. and surgency may persist beyond the first 6 months of life, particularly surgency at 12–18 months (p = 0.002). Our study highlighted that various human milk nutrients work together to support the development of cognition and temperament traits during early infancy.

Published
2022
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12. Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds

Author

Omid Kardan, Sydney Kaplan, Muriah D. Wheelock, Eric Feczko, Trevor K.M. Day, Óscar Miranda-Domínguez, Dominique Meyer, Adam T. Eggebrecht, Lucille A. Moore, Sooyeon Sung, Taylor A. Chamberlain, Eric Earl, Kathy Snider, Alice Graham, Marc G. Berman, Kamil Uğurbil, Essa Yacoub, Jed T. Elison, Christopher D. Smyser, Damien A. Fair, and Monica D. Rosenberg

Subjects
Functional connectivity, FMRI, Reliability, Development, Machine learning, Age prediction, Neurophysiology and neuropsychology, QP351-495
Abstract

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler’s connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants’ age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network—i.e. within-network connections—predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Published
2022
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13. Real-time motion monitoring improves functional MRI data quality in infants

Author

Carolina Badke D’Andrea, Jeanette K. Kenley, David F. Montez, Amy E. Mirro, Ryland L. Miller, Eric A. Earl, Jonathan M. Koller, Sooyeon Sung, Essa Yacoub, Jed T. Elison, Damien A. Fair, Nico U.F. Dosenbach, Cynthia E. Rogers, Christopher D. Smyser, and Deanna J. Greene

Subjects
Functional MRI, Head motion, Infant brain, Neurodevelopment, Neuroimaging, Neurophysiology and neuropsychology, QP351-495
Abstract

Imaging the infant brain with MRI has improved our understanding of early neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are typically scanned while asleep, they commonly exhibit motion during scanning causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Here, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2 mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

Published
2022
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14. Synthesizing pseudo-T2w images to recapture missing data in neonatal neuroimaging with applications in rs-fMRI

Author

Sydney Kaplan, Anders Perrone, Dimitrios Alexopoulos, Jeanette K. Kenley, Deanna M. Barch, Claudia Buss, Jed T. Elison, Alice M. Graham, Jeffrey J. Neil, Thomas G. O'Connor, Jerod M. Rasmussen, Monica D. Rosenberg, Cynthia E. Rogers, Aristeidis Sotiras, Damien A. Fair, and Christopher D. Smyser

Subjects
Structural MRI, Synthetic medical images, Deep learning, Multi-atlas fusion, Neuroimaging, Neonate, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

Published
2022
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15. Longitudinal change in restricted and repetitive behaviors from 8-36 months

Author

Robin Sifre, Daniel Berry, Jason J. Wolff, and Jed T. Elison

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Background Restricted and repetitive behaviors (RRBs) are core features of autism spectrum disorder (ASD) and one of the earliest behavioral signs of ASD. However, RRBs are also present in typically developing (TD) infants, toddlers, and preschool-aged children. Past work suggests that examining change in these behaviors over time is essential to distinguish between normative manifestations of these behaviors and behaviors that denote risk for a neurodevelopmental disorder. One challenge in examining changes in these behaviors over time is that most measures of RRBs have not established longitudinal measurement invariance. The aims of this study were to (1) establish measurement invariance in the Repetitive Behavior Scales for Early Childhood (RBS-EC), a parent-report questionnaire of RRBs, and (2) model developmental change in RRBs from 8 to 36 months. Methods We collected RBS-EC responses from parents of TD infants (n = 180) from 8 to 36 months (n = 606 responses, with participants contributing an average of 3-time points). We leverage a novel methodological approach to measurement invariance testing (Bauer, Psychological Models, 22(3), 507–526, 2017), moderated nonlinear factor analysis (MNLFA), to determine whether the RBS-EC was invariant across age and sex. We then generated adjusted factor score estimates for each subscale of the RBS-EC (repetitive motor, self-directed, and higher-order behaviors), and used linear mixed effects models to estimate between- and within-person changes in the RBS-EC over time. Results The RBS-EC showed some non-invariance as a function of age. We were able to adjust for this non-invariance in order to more accurately model changes in the RBS-EC over time. Repetitive motor and self-directed behaviors showed a linear decline from 8 to 36 months, while higher-order behaviors showed a quadratic trajectory such that they began to decline later in development at around 18 months. Using adjusted factor scores as opposed to unadjusted raw mean scores provided a number of benefits, including increased within-person variability and precision. Conclusions The RBS-EC is sensitive enough to measure the presence of RRBs in a TD sample, as well as their decline with age. Using factor score estimates of each subscale adjusted for non-invariance allowed us to more precisely estimate change in these behaviors over time.

Published
2021
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16. Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations

Author

Sydney Kaplan, Dominique Meyer, Oscar Miranda-Dominguez, Anders Perrone, Eric Earl, Dimitrios Alexopoulos, Deanna M. Barch, Trevor K.M. Day, Joseph Dust, Adam T. Eggebrecht, Eric Feczko, Omid Kardan, Jeanette K. Kenley, Cynthia E. Rogers, Muriah D. Wheelock, Essa Yacoub, Monica Rosenberg, Jed T. Elison, Damien A. Fair, and Christopher D. Smyser

Subjects
Resting-state fMRI, Respiratory filtering, Neurodevelopment, Neuroimaging, infant, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., “scrubbing”) and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8–24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.

Published
2022
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17. Emerging ethical issues raised by highly portable MRI research in remote and resource-limited international settings

Author

Francis X. Shen, Susan M. Wolf, Supriya Bhavnani, Sean Deoni, Jed T. Elison, Damien Fair, Michael Garwood, Michael S. Gee, Sairam Geethanath, Kendrick Kay, Kelvin O. Lim, Georgia Lockwood Estrin, Monica Luciana, David Peloquin, Karen Rommelfanger, Nicoline Schiess, Khan Siddiqui, Efraín Torres, and J. Thomas Vaughan

Subjects
Portable MRI, Neuroimaging, Neuroethics, Low- and middle-income countries (LMICs), International research, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Smaller, more affordable, and more portable MRI brain scanners offer exciting opportunities to address unmet research needs and long-standing health inequities in remote and resource-limited international settings. Field-based neuroimaging research in low- and middle-income countries (LMICs) can improve local capacity to conduct both structural and functional neuroscience studies, expand knowledge of brain injury and neuropsychiatric and neurodevelopmental disorders, and ultimately improve the timeliness and quality of clinical diagnosis and treatment around the globe. Facilitating MRI research in remote settings can also diversify reference databases in neuroscience, improve understanding of brain development and degeneration across the lifespan in diverse populations, and help to create reliable measurements of infant and child development. These deeper understandings can lead to new strategies for collaborating with communities to mitigate and hopefully overcome challenges that negatively impact brain development and quality of life. Despite the potential importance of research using highly portable MRI in remote and resource-limited settings, there is little analysis of the attendant ethical, legal, and social issues (ELSI). To begin addressing this gap, this paper presents findings from the first phase of an envisioned multi-staged and iterative approach for creating ethical and legal guidance in a complex global landscape. Section 1 provides a brief introduction to the emerging technology for field-based MRI research. Section 2 presents our methodology for generating plausible use cases for MRI research in remote and resource-limited settings and identifying associated ELSI issues. Section 3 analyzes core ELSI issues in designing and conducting field-based MRI research in remote, resource-limited settings and offers recommendations. We argue that a guiding principle for field-based MRI research in these contexts should be including local communities and research participants throughout the research process in order to create sustained local value. Section 4 presents a recommended path for the next phase of work that could further adapt these use cases, address ethical and legal issues, and co-develop guidance in partnership with local communities.

Published
2021
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18. Measurement of Cognition for the National Children's Study

Author

Philip David Zelazo, Stella F. Lourenco, Michael C. Frank, Jed T. Elison, Robert K. Heaton, Henry M. Wellman, Jerry Slotkin, Maria Kharitonova, and J. Steven Reznick

Subjects
cognition, measurement, longitudinal, environment, tablet-based, Pediatrics, RJ1-570
Abstract

The National Children's Study Cognitive Health Domain Team developed detailed plans for assessing cognition longitudinally from infancy to early adulthood. These plans identify high-priority aspects of cognition that can be measured efficiently and effectively, and we believe they can serve as a model for future large-scale longitudinal research. For infancy and toddlerhood, we proposed several paradigms that collectively allowed us to assess six broad cognitive constructs: (1) executive function skills, (2) episodic memory, (3) language, (4) processing speed, (5) spatial and numerical processing, and (6) social cognition. In some cases, different trial sequences within a paradigm allow for the simultaneous assessment of multiple cognitive skills (e.g., executive function skills and processing speed). We define each construct, summarize its significance for understanding developmental outcomes, discuss the feasibility of its assessment throughout development, and present our plan for measuring specific skills at different ages. Given the need for well-validated, direct behavioral measures of cognition that can be used in large-scale longitudinal studies, especially from birth to age 3 years, we also initiated three projects focused on the development of new measures.

Published
2021
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19. Sex differences associated with corpus callosum development in human infants: A longitudinal multimodal imaging study

Author

Astrid Schmied, Takahiro Soda, Guido Gerig, Martin Styner, Meghan R. Swanson, Jed T. Elison, Mark D. Shen, Robert C. McKinstry, John R. Pruett, Jr., Kelly N. Botteron, Annette M. Estes, Stephen R. Dager, Heather C. Hazlett, Robert T. Schultz, Joseph Piven, and Jason J. Wolff

Subjects
Corpus callosum, Sexual dimorphism, Development, Brain imaging, Infants, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The corpus callosum (CC) is the largest connective pathway in the human brain, linking cerebral hemispheres. There is longstanding debate in the scientific literature whether sex differences are evident in this structure, with many studies indicating the structure is larger in females. However, there are few data pertaining to this issue in infancy, during which time the most rapid developmental changes to the CC occur. In this study, we examined longitudinal brain imaging data collected from 104 infants at ages 6, 12, and 24 months. We identified sex differences in brain-size adjusted CC area and thickness characterized by a steeper rate of growth in males versus females from ages 6–24 months. In contrast to studies of older children and adults, CC size was larger for male compared to female infants. Based on diffusion tensor imaging data, we found that CC thickness is significantly associated with underlying microstructural organization. However, we observed no sex differences in the association between microstructure and thickness, suggesting that the role of factors such as axon density and/or myelination in determining CC size is generally equivalent between sexes. Finally, we found that CC length was negatively associated with nonverbal ability among females.

Published
2020
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20. Cost-Effectiveness of MRI-Based Identification of Presymptomatic Autism in a High-Risk Population

Author

Ian O. Williamson, Jed T. Elison, Jason J. Wolff, and Carlisle Ford Runge

Subjects
autism spectrum disorder, magnetic resonance imaging, cost-effectiveness, screening, early intensive behavioral intervention, Psychiatry, RC435-571
Abstract

Biological siblings of children with autism spectrum disorder (ASD) have increased risk of receiving an ASD diagnosis. In the U.S., most children with ASD are diagnosed after the optimal age to initiate early intervention which can reduce symptom severity and improve outcomes. Recent evidence suggests magnetic resonance imaging (MRI) in the first year of life can predict later diagnostic status in high-risk siblings. We investigated whether MRI-based screening is a cost-effective method for assigning early intervention. A hybrid decision tree/Markov model was used to evaluate two MRI-based screening strategies at 6 and 12 months of age. Primary outcomes were costs in U.S. dollars and quality-adjusted life years (QALYs). Results were reported as incremental cost-effectiveness ratios (ICERs). Costs were estimated from societal, health care, and educational perspectives. One-way and probabilistic sensitivity analyses were performed. From a societal perspective, the ICER for MRI-based screening at 6 months was $49,000 per QALY when compared to the status quo, implying that such screening is cost-effective at willingness-to-pay (WTP) thresholds of $50,000–$100,000 per QALY. From the health care and educational perspectives, the ICERs were larger at $99,000 and $76,000 per QALY, respectively. Sensitivity analysis identified that the parameters most influential in affecting cost-effectiveness were the prevalence of ASD and/or co-occurring intellectual disability. MRI specificity also has significant impacts which add to the uncertainty of the results. Future work is needed to determine the sensitivity and, in particular, the specificity of MRI with more certainty. Notably, the cost of the MRI-based screening had the least impact.

Published
2020
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21. Social brain circuitry and social cognition in infants born preterm

Author

Angela Fenoglio, Michael K. Georgieff, and Jed T. Elison

Subjects
Prematurity, Social cognition, Social brain, Neurodevelopment, Neuroplasticity, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Preterm birth is associated with an increased risk of adverse neurologic, psychiatric, and cognitive outcomes. The brain circuits involved in processing social information are critical to all of these domains, but little work has been done to examine whether and how these circuits may be especially sensitive to prematurity. This paper contains a brief summary of some of the cognitive, psychiatric, and social outcomes associated with prematurity, followed by a description of findings from the modest body of research into social-cognitive development in infants and children born preterm. Next, findings from studies of structural and functional brain development in infants born preterm are reviewed, with an eye toward the distinctive role of the brain circuits implicated in social functioning. The goal of this review is to investigate the extent to which the putative “social brain” may have particular developmental susceptibilities to the insults associated with preterm birth, and the role of early social-cognitive development in later neurodevelopmental outcomes. Much work has been done to characterize neurobehavioral outcomes in the preterm population, but future research must incorporate both brain and behavioral measures to identify early biomarkers linked to later emerging social-cognitive clinical impairment in order to guide effective, targeted intervention.

Published
2017
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22. An Examination of Recording Accuracy and Precision From Eye Tracking Data From Toddlerhood to Adulthood

Author

Kirsten A. Dalrymple, Marie D. Manner, Katherine A. Harmelink, Elayne P. Teska, and Jed T. Elison

Subjects
eye tracking, calibration, development, methods, quality assessment, toddlers, Psychology, BF1-990
Abstract

The quantitative assessment of eye tracking data quality is critical for ensuring accuracy and precision of gaze position measurements. However, researchers often report the eye tracker’s optimal manufacturer’s specifications rather than empirical data about the accuracy and precision of the eye tracking data being presented. Indeed, a recent report indicates that less than half of eye tracking researchers surveyed take the eye tracker’s accuracy into account when determining areas of interest for analysis, an oversight that could impact the validity of reported results and conclusions. Accordingly, we designed a calibration verification protocol to augment independent quality assessment of eye tracking data and examined whether accuracy and precision varied between three age groups of participants. We also examined the degree to which our externally quantified quality assurance metrics aligned with those reported by the manufacturer. We collected data in standard laboratory conditions to demonstrate our method, to illustrate how data quality can vary with participant age, and to give a simple example of the degree to which data quality can differ from manufacturer reported values. In the sample data we collected, accuracy for adults was within the range advertised by the manufacturer, but for school-aged children, accuracy and precision measures were outside this range. Data from toddlers were less accurate and less precise than data from adults. Based on an a priori inclusion criterion, we determined that we could exclude approximately 20% of toddler participants for poor calibration quality quantified using our calibration assessment protocol. We recommend implementing and reporting quality assessment protocols for any eye tracking tasks with participants of any age or developmental ability. We conclude with general observations about our data, recommendations for what factors to consider when establishing data inclusion criteria, and suggestions for stimulus design that can help accommodate variability in calibration. The methods outlined here may be particularly useful for developmental psychologists who use eye tracking as a tool, but who are not experts in eye tracking per se. The calibration verification stimuli and data processing scripts that we developed, along with step-by-step instructions, are freely available for other researchers.

Published
2018
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23. Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

Author

John R. Pruett, Jr., Sridhar Kandala, Sarah Hoertel, Abraham Z. Snyder, Jed T. Elison, Tomoyuki Nishino, Eric Feczko, Nico U.F. Dosenbach, Binyam Nardos, Jonathan D. Power, Babatunde Adeyemo, Kelly N. Botteron, Robert C. McKinstry, Alan C. Evans, Heather C. Hazlett, Stephen R. Dager, Sarah Paterson, Robert T. Schultz, D. Louis Collins, Vladimir S. Fonov, Martin Styner, Guido Gerig, Samir Das, Penelope Kostopoulos, John N. Constantino, Annette M. Estes, Steven E. Petersen, Bradley L. Schlaggar, and Joseph Piven

Subjects
Functional connectivity magnetic resonance imaging (fcMRI), Infant, Development, Multivariate pattern analysis (MVPA), Support vector machine (SVM), Functional brain networks, Neurophysiology and neuropsychology, QP351-495
Abstract

Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI) data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs) classified 6 versus 12 month-old infants (128 datasets) above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

Published
2015
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30. The Art, Science, and Secrets of Scanning Young Children

Author

Marisa N. Spann, Jessica L. Wisnowski, Christopher D. Smyser, Brittany Howell, Douglas C. Dean, Banu Ahtam, Wei Gao, Hao Huang, Mary Beth Nebel, Elizabeth S. Norton, Minhui Ouyang, Vidya Rajagopalan, Tracy Riggins, Zeynep M. Saygin, Lisa Scott, Moriah E. Thomason, Lauren S. Wakschlag, Sahar Ahmad, Ezra Aydin, A. James Barkovich, Evelyn Berger-Jenkins, Johanna Brick, Lindsay C. Bowman, M. Catalina Camacho, Claudia Lugo-Candelas, Rhodri Cusack, Jessica DuBois, Alexander J. Dufford, Jed T. Elison, Cameron T. Ellis, Silvina L. Ferradal, Courtney Filippi, Aiden Leigh Ford, Mahshid Fouladivanda, Nadine Gaab, Dawn Gano, Melanie Ganz-Benjaminsen, Simona Ghetti, Orit Ariel Glenn, Maria Jose Castro Gomez, Alice Graham, Cassandra L. Hendrix, Cristin M. Holland, Kathryn Humphreys, Marta Korom, Heather L. Kosakowski, Gang Li, Angela Gigliotti Manessis, Saara Nolvi, Roberta Pineda, Angeliki Pollatou, Caroline Rae, Jerod M. Rasmussen, Dustin Scheinost, Sara Shultz, Cristina Simon-Martinez, Kathrine Skak Madsen, Sooyeon Sung, Chad M. Sylvester, Ted K. Turesky, Kelly A. Vaughn, Lauren Wagner, Li Wang, Fleur L. Warton, Sylia Wilson, Pia Wintermark, Ye Wu, Pew-Thian Yap, Tristan S. Yates, Elizabeth Yen, Xi Yu, Hongtu Zhu, and Lilla Zöllei

Subjects
Article, Biological Psychiatry
Published
2023

31. A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood

Author

Catherine A. Burrows, Rebecca L. Grzadzinski, Kevin Donovan, Isabella C. Stallworthy, Joshua Rutsohn, Tanya St. John, Natasha Marrus, Julia Parish-Morris, Leigh MacIntyre, Jacqueline Hampton, Juhi Pandey, Mark D. Shen, Kelly N. Botteron, Annette M. Estes, Stephen R. Dager, Heather C. Hazlett, John R. Pruett, Robert T. Schultz, Lonnie Zwaigenbaum, Kinh N. Truong, Joseph Piven, and Jed T. Elison

Subjects
Male, Sex Characteristics, Autism Spectrum Disorder, Child, Preschool, Siblings, Humans, Infant, Female, Prospective Studies, Sex Ratio, Child, Biological Psychiatry
Abstract

Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD.We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nWe identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group.This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence.

Published
2022

32. Infant Visual Brain Development and Inherited Genetic Liability in Autism

Author

Jessica B, Girault, Kevin, Donovan, Zoë, Hawks, Muhamed, Talovic, Elizabeth, Forsen, Jed T, Elison, Mark D, Shen, Meghan R, Swanson, Jason J, Wolff, Sun Hyung, Kim, Tomoyuki, Nishino, Savannah, Davis, Abraham Z, Snyder, Kelly N, Botteron, Annette M, Estes, Stephen R, Dager, Heather C, Hazlett, Guido, Gerig, Robert, McKinstry, Juhi, Pandey, Robert T, Schultz, Tanya, St John, Lonnie, Zwaigenbaum, Alexandre, Todorov, Young, Truong, Martin, Styner, John R, Pruett, John N, Constantino, and Joseph, Piven

Subjects
Psychiatry and Mental health, Autism Spectrum Disorder, Siblings, Brain, Humans, Prospective Studies, Autistic Disorder, Magnetic Resonance Imaging
Abstract

Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings.In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months.Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy.The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD.

Published
2023

33. Subcortical Brain Development in Autism and Fragile X Syndrome: Evidence for Dynamic, Age- and Disorder-Specific Trajectories in Infancy

Author

Mark D, Shen, Meghan R, Swanson, Jason J, Wolff, Jed T, Elison, Jessica B, Girault, Sun Hyung, Kim, Rachel G, Smith, Michael M, Graves, Leigh Anne H, Weisenfeld, Lisa, Flake, Leigh, MacIntyre, Julia L, Gross, Catherine A, Burrows, Vladimir S, Fonov, D Louis, Collins, Alan C, Evans, Guido, Gerig, Robert C, McKinstry, Juhi, Pandey, Tanya, St John, Lonnie, Zwaigenbaum, Annette M, Estes, Stephen R, Dager, Robert T, Schultz, Martin A, Styner, Kelly N, Botteron, Heather C, Hazlett, and Joseph, Piven

Subjects
Adult, Adolescent, Autism Spectrum Disorder, Brain, Infant, Amygdala, Magnetic Resonance Imaging, Article, Young Adult, Psychiatry and Mental health, Child, Preschool, Fragile X Syndrome, Humans, Autistic Disorder, Child
Abstract

OBJECTIVE: Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown. METHODS: Longitudinal MRIs were acquired at 6–24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans). RESULTS: Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen’s d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors. CONCLUSIONS: This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome–related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis.

Published
2022

34. BIBSNet: A Deep Learning Baby Image Brain Segmentation Network for MRI Scans

Author

Timothy J. Hendrickson, Paul Reiners, Lucille A. Moore, Anders J. Perrone, Dimitrios Alexopoulos, Erik G. Lee, Martin Styner, Omid Kardan, Taylor A. Chamberlain, Anurima Mummaneni, Henrique A. Caldas, Brad Bower, Sally Stoyell, Tabitha Martin, Sooyeon Sung, Ermias Fair, Jonathan Uriarte-Lopez, Amanda R. Rueter, Essa Yacoub, Monica D. Rosenberg, Christopher D. Smyser, Jed T. Elison, Alice Graham, Damien A. Fair, and Eric Feczko

Subjects
Article
Abstract

ObjectivesBrain segmentation of infant magnetic resonance (MR) images is vitally important in studying developmental mental health and disease. The infant brain undergoes many changes throughout the first years of postnatal life, making tissue segmentation difficult for most existing algorithms. Here, we introduce a deep neural network BIBSNet (Baby andInfantBrainSegmentation NeuralNetwork), an open-source, community-driven model that relies on data augmentation and a large sample size of manually annotated images to facilitate the production of robust and generalizable brain segmentations.Experimental DesignIncluded in model training and testing were MR brain images on 84 participants with an age range of 0-8 months (median postmenstrual ages of 13.57 months). Using manually annotated real and synthetic segmentation images, the model was trained using a 10-fold cross-validation procedure. Testing occurred on MRI data processed with the DCAN labs infant-ABCD-BIDS processing pipeline using segmentations produced from gold standard manual annotation, joint-label fusion (JLF), and BIBSNet to assess model performance.Principal ObservationsUsing group analyses, results suggest that cortical metrics produced using BIBSNet segmentations outperforms JLF segmentations. Additionally, when analyzing individual differences, BIBSNet segmentations perform even better.ConclusionsBIBSNet segmentation shows marked improvement over JLF segmentations across all age groups analyzed. The BIBSNet model is 600x faster compared to JLF and can be easily included in other processing pipelines.

Published
2023

35. A cybernetic theory of autism: Autism as a consequence of low trait plasticity

Author

Matthew A. Rogers, Jed T. Elison, Scott D. Blain, and Colin G. DeYoung

Subjects
Social Psychology
Abstract

According to Cybernetic Big Five Theory (CB5T), personality traits reflect variation in the parameters of evolved cybernetic mechanisms, and extreme manifestations of these traits correspond to a risk for psychopathology because they threaten the organism's ability to pursue its goals effectively. Our theory of autism as a consequence of low Plasticity extends CB5T to provide a cybernetic account of the origin of autistic traits. The theory argues that, because all psychological competencies are initially developed through exploration, typical development requires sensitivity to the incentive reward value of the unknown (i.e., the unpredicted). According to CB5T, motivation to explore the unknown is the core function underlying the metatrait Plasticity, the shared variance of Extraversion and Openness/Intellect. This theory makes predictions regarding the downstream developmental consequences of early low Plasticity, and each prediction maps well onto autistic symptomatology. This approach may help to explain the heterogeneity of autism, as there are many ways that rigidity can reinforce itself to create a developmental trap influencing the development of competencies. We end by presenting preliminary meta-analytic and new data showing a strong negative relation between Plasticity and autistic symptomatology.

Published
2023

36. Social motivation in infancy is associated with familial recurrence of ASD

Author

Natasha Marrus, Kelly N. Botteron, Zoë Hawks, John R. Pruett, Jed T. Elison, Joshua J. Jackson, Lori Markson, Adam T. Eggebrecht, Catherine A. Burrows, Lonnie Zwaigenbaum, Stephen R. Dager, Annette M. Estes, Heather Cody Hazlett, Robert T. Schultz, Joseph Piven, and John N. Constantino

Subjects
Psychiatry and Mental health, Developmental and Educational Psychology
Abstract

Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation’s course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation’s importance to risk assessment and clarification of the ontogeny of ASD.

Published
2022

37. Responding to joint attention as a developmental catalyst: Longitudinal associations with language and social responsiveness

Author

Carolyn Lasch, Stephanie M. Carlson, and Jed T. Elison

Subjects
Pediatrics, Perinatology and Child Health, Developmental and Educational Psychology
Abstract

Joint attention (JA), infants' ability to engage in triadic attention with another person and a separate object or event, emerges in infancy. Responding to joint attention (RJA) develops earlier than initiating joint attention (IJA) and may benefit from a reconceptualization from a competence to a skill that varies in performance. Investigating associations between RJA performance and important skills of toddlerhood such as language, social responsiveness, and executive function (EF) in typically developing samples can better elucidate how RJA may serve as a developmental precursor to later dimensional skills, with implications for both typical and atypical development. Here, 210 (82% White) infants completed the Dimensional Joint Attention Assessment (DJAA), a naturalistic play-based assessment of RJA, at 8-15 months. At 16-38 months social responsiveness, verbal ability, and EF were assessed. Multilevel models showed that DJAA scores were associated with later verbal abilities and parent-reported social responsiveness. Exploratory analyses showed trend-level associations between RJA and EF. Results establish the content validity of the DJAA as a measure of RJA, and longitudinal associations with later verbal ability and social responsiveness. Future work should examine EF emergence and consolidation, and RJA and later EF associations.

Published
2022

38. Towards a Data-Driven Approach to Screen for Autism Risk at 12 Months of Age

Author

Jed T. Elison, Shoba Sreenath Meera, Linda R. Watson, Annette Estes, Jason J. Wolff, Truong Kinh, Heather C. Hazlett, Kelly N. Botteron, Catherine A. Burrows, Stephen R. Dager, Grace T. Baranek, Joseph Piven, Mark D. Shen, Tanya St John, Robert T. Schultz, Kevin Donovan, Juhi Pandey, Meghan R. Swanson, and Lonnie Zwaigenbaum

Subjects
Pediatrics, medicine.medical_specialty, education.field_of_study, Autism Spectrum Disorder, business.industry, 05 social sciences, Population, Infant, Familial risk, medicine.disease, Article, Psychiatry and Mental health, Autism spectrum disorder, Child, Preschool, mental disorders, Developmental and Educational Psychology, medicine, Humans, Diagnostic assessment, Autism, 0501 psychology and cognitive sciences, Autistic Disorder, education, business, 050104 developmental & child psychology
Abstract

Objective This study aimed to develop a classifier for infants at 12 months of age based on a parent-report measure (the First Year Inventory 2.0 [FYI]), for the following reasons: (1) to classify infants at elevated risk, above and beyond that attributable to familial risk status for ASD; and (2) to serve as a starting point to refine an approach for risk estimation in population samples. Method A total of 54 high−familial risk (HR) infants later diagnosed with ASD (HR-ASD), 183 HR infants not diagnosed with ASD at 24 months of age (HR-Neg), and 72 low-risk controls participated in the study. All infants contributed FYI data at 12 months of age and had a diagnostic assessment for ASD at age 24 months. A data-driven, cross-validated analytic approach was used to develop a classifier to determine screening accuracy (eg, sensitivity) of the FYI to classify HR-ASD and HR-Neg. Results The newly developed FYI classifier had an estimated sensitivity of 0.71 (95% CI: 0.50, 0.91) and specificity of 0.72 (95% CI: 0.49, 0.91). Conclusion This classifier demonstrates the potential to improve current screening for ASD risk at 12 months of age in infants already at elevated familial risk for ASD, increasing opportunities for detection of autism risk in infancy. Findings from this study highlight the utility of combining parent-report measures with machine learning approaches.

Published
2021

39. Frontiers in Nutrition

Author

Tengfei Li, Tinu M. Samuel, Ziliang Zhu, Brittany Howell, Seoyoon Cho, Kristine Baluyot, Heather Hazlett, Jed T. Elison, Di Wu, Jonas Hauser, Norbert Sprenger, Hongtu Zhu, and Weili Lin

Subjects
DHA, Nutrition and Dietetics, ARA, cognition and temperament, Mullen Scales of Early Learning, Endocrinology, Diabetes and Metabolism, human milk, receptive language, IBQ, surgency, Food Science
Abstract

Early dietary exposure via human milk nutrients offers a window of opportunity to support cognitive and temperament development. While several studies have focused on associations of few pre-selected human milk nutrients with cognition and temperament, it is highly plausible that human milk nutrients synergistically and jointly support cognitive and behavioral development in early life. We aimed to discern the combined associations of three major classes of human milk nutrients with cognition and temperament during the first 6 months of life when human milk is the primary source of an infant’s nutrition and explore whether there were persistent effects up to 18 months old. The Mullen Scales of Early Learning and Infant Behavior Questionnaires—Revised were used to assess cognition and temperament, respectively, of 54 exclusively/predominantly breastfed infants in the first 6 months of life, whose follow-ups were conducted at 6–9, 9–12, and 12–18 months old. Human milk samples were obtained from the mothers of the participants at less than 6 months of age and analyzed for fatty acids [total monounsaturated fatty acids, polyunsaturated fatty acid, total saturated fatty acid (TSFA), arachidonic acid (ARA), docosahexaenoic acid (DHA), ARA/DHA, omega-6/omega-3 polyunsaturated fatty acids ratio (n-6/n-3)], phospholipids [phosphatidylcholine, phosphatidylethanolamine (PE), phosphatidylinositol (PI), sphingomyelin], and choline [free choline, phosphocholine (PCho), glycerophosphocholine]. Feature selection was performed to select nutrients associated with cognition and temperament. The combined effects of selected nutrients were analyzed using multiple regression. A positive association between the arachidonic acid (ARA) and surgency was observed (p = 0.024). A significant effect of DHA, n-6/n-3, PE, and TSFA concentrations on receptive language (R2 = 0.39, p = 0.025) and the elevated ARA, PCho, and PI with increased surgency (R2 = 0.43, p = 0.003) was identified, suggesting that DHA and ARA may have distinct roles for temperament and language functions. Furthermore, the exploratory association analyses suggest that the effects of human milk nutrients on R.L. and surgency may persist beyond the first 6 months of life, particularly surgency at 12–18 months (p = 0.002). Our study highlighted that various human milk nutrients work together to support the development of cognition and temperament traits during early infancy.

Published
2022

40. Quantifying latent social motivation and its associations with joint attention and language in infants at high and low likelihood for autism spectrum disorder

Author

Isabella C, Stallworthy, Daniel, Berry, Savannah, Davis, Jason J, Wolff, Catherine A, Burrows, Meghan R, Swanson, Rebecca L, Grzadzinski, Kelly, Botteron, Stephen R, Dager, Annette M, Estes, Robert T, Schultz, Joseph, Piven, Jed T, Elison, John R, Pruett, and Natasha, Marrus

Subjects
Cognitive Neuroscience, Developmental and Educational Psychology
Abstract

Social motivation-the psychobiological predisposition for social orienting, seeking social contact, and maintaining social interaction-manifests in early infancy and is hypothesized to be foundational for social communication development in typical and atypical populations. However, the lack of infant social-motivation measures has hindered delineation of associations between infant social motivation, other early-arising social abilities such as joint attention, and language outcomes. To investigate how infant social motivation contributes to joint attention and language, this study utilizes a mixed longitudinal sample of 741 infants at high (HL = 515) and low (LL = 226) likelihood for ASD. Using moderated nonlinear factor analysis (MNLFA), we incorporated items from parent-report measures to establish a novel latent factor model of infant social motivation that exhibits measurement invariance by age, sex, and familial ASD likelihood. We then examined developmental associations between 6- and 12-month social motivation, joint attention at 12-15 months, and language at 24 months of age. On average, greater social-motivation growth from 6-12 months was associated with greater initiating joint attention (IJA) and trend-level increases in sophistication of responding to joint attention (RJA). IJA and RJA were both positively associated with 24-month language abilities. There were no additional associations between social motivation and future language in our path model. These findings substantiate a novel, theoretically driven approach to modeling social motivation and suggest a developmental cascade through which social motivation impacts other foundational skills. These findings have implications for the timing and nature of intervention targets to support social communication development in infancy. HIGHLIGHTS: We describe a novel, theoretically based model of infant social motivation wherein multiple parent-reported indicators contribute to a unitary latent social-motivation factor. Analyses revealed social-motivation factor scores exhibited measurement invariance for a longitudinal sample of infants at high and low familial ASD likelihood. Social-motivation growth from ages 6-12 months is associated with better 12-15-month joint attention abilities, which in turn are associated with greater 24-month language skills. Findings inform timing and targets of potential interventions to support healthy social communication in the first year of life.

Published
2022

41. A broadened estimate of syntactic and lexical ability from the MB-CDI

Author

Trevor K.M. Day and Jed T. Elison

Subjects
Linguistics and Language, media_common.quotation_subject, Experimental and Cognitive Psychology, computer.software_genre, Language Development, Vocabulary, 01 natural sciences, Language and Linguistics, 010104 statistics & probability, 0504 sociology, Factor (programming language), Developmental and Educational Psychology, Humans, Natural (music), Language Development Disorders, 0101 mathematics, Function (engineering), General Psychology, Language, computer.programming_language, media_common, Language Tests, Parsing, Gestures, business.industry, 05 social sciences, 050401 social sciences methods, Language acquisition, Comprehension, Language development, Artificial intelligence, Psychology, business, computer, Natural language processing, Gesture
Abstract

A critical question in the study of language development is to understand lexical and syntactic acquisition, which play different roles in speech to the extent it would be natural to surmise they are acquired differently. As measured through the comprehension and production of closed-class words, syntactic ability emerges at roughly the 400-word mark. However, a significant proportion of the developmental work uses a coarse combination of function and content words on the MacArthur-Bates Communicative Development Inventory (MB-CDI). Using the MB-CDI Wordbank database, we implemented a factor analytic approach to distinguish between lexical and syntactic development from the Words and Sentences (WS) form that involves both function words and the explicit categorizations. Although the Words and Gestures (WG) form did not share the factor structure, common WG/WS elements recapitulate the expected age-related changes. This parsing of the MB-CDI may prove simple, yet fruitful in subsequent investigation.

Published
2021

42. Diagnostic shifts in autism spectrum disorder can be linked to the fuzzy nature of the diagnostic boundary: a data‐driven approach

Author

Robert T. Schultz, Jed T. Elison, Jennifer E Maldarelli, Shoba Sreenath Meera, Robert C. McKinstry, John R. Pruett, Lonnie Zwaigenbaum, Ragini Verma, Annette Estes, Tanya St John, Birkan Tunç, Juhi Pandey, Joseph Piven, Stephen R. Dager, Jessica B. Girault, Kelly N. Botteron, and Heather C. Hazlett

Subjects
medicine.medical_specialty, Autism Spectrum Disorder, Boundary (topology), Audiology, behavioral disciplines and activities, Article, Cohort Studies, Adaptive skills, 03 medical and health sciences, 0302 clinical medicine, mental disorders, Developmental and Educational Psychology, medicine, Humans, 0501 psychology and cognitive sciences, Older sibling, Medical diagnosis, Siblings, 05 social sciences, medicine.disease, Individual level, Psychiatry and Mental health, Early Diagnosis, Phenotype, Autism spectrum disorder, Child, Preschool, Pediatrics, Perinatology and Child Health, Cohort, Psychology, 030217 neurology & neurosurgery, 050104 developmental & child psychology
Abstract

Background Diagnostic shifts at early ages may provide invaluable insights into the nature of separation between autism spectrum disorder (ASD) and typical development. Recent conceptualizations of ASD suggest the condition is only fuzzily separated from non-ASD, with intermediate cases between the two. These intermediate cases may shift along a transition region over time, leading to apparent instability of diagnosis. Methods We used a cohort of children with high ASD risk, by virtue of having an older sibling with ASD, assessed at 24 months (N = 212) and 36 months (N = 191). We applied machine learning to empirically characterize the classification boundary between ASD and non-ASD, using variables quantifying developmental and adaptive skills. We computed the distance of children to the classification boundary. Results Children who switched diagnostic labels from 24 to 36 months, in both directions, (dynamic group) had intermediate phenotypic profiles. They were closer to the classification boundary compared to children who had stable diagnoses, both at 24 months (Cohen's d = .52) and at 36 months (d = .75). The magnitude of change in distance between the two time points was similar for the dynamic and stable groups (Cohen's d = .06), and diagnostic shifts were not associated with a large change. At the individual level, a few children in the dynamic group showed substantial change. Conclusions Our results suggested that a diagnostic shift was largely due to a slight movement within a transition region between ASD and non-ASD. This fact highlights the need for more vigilant surveillance and intervention strategies. Young children with intermediate phenotypes may have an increased susceptibility to gain or lose their diagnosis at later ages, calling attention to the inherently dynamic nature of early ASD diagnoses.

Published
2021

43. Comparison of U.S. and Tajik infants' time in containment devices

Author

Lana B. Karasik, Yana A. Kuchirko, Rano M. Dodojonova, and Jed T. Elison

Subjects
Developmental and Educational Psychology, Article
Abstract

How infants are held or contained throughout the day shape infants' experiences, particularly around movement and exploration. In Tajikistan, caregivers use "gahvora" cradles, which severely restrict the body and limbs. The present study explored the variability and use of containment devices in U.S. and Tajik infants. Using time diaries, we compared 12-month-olds in the U.S. and Tajikistan on the types of containments used and time spent in them throughout the day. During the day, Tajik infants accumulated more time in gahvoras than infants in the U.S. spent in cribs, primarily used for sleep, suggesting gahvoras served other functions. Given the availability of other devices, U.S. infants' time was distributed in short yet frequent bouts across devices. Accumulated time in these containments matched accumulated time Tajik infants spent in gahvoras. Tajik infants accumulated more unrestricted time on the ground, which was distributed in prolonged bouts, than U.S. infants. Findings highlight differences in infants' everyday experiences during the developmental period when motor skills emerge. By embracing commonalities and exploring differences between cultures, this study offers insights into differences in infants' everyday experiences and opportunities for movement.

Published
2022

44. Examining the factor structure and discriminative utility of the Infant Behavior Questionnaire-Revised in infant siblings of autistic children

Author

Sooyeon, Sung, Angela, Fenoglio, Jason J, Wolff, Robert T, Schultz, Kelly N, Botteron, Stephen R, Dager, Annette M, Estes, Heather C, Hazlett, Lonnie, Zwaigenbaum, Joseph, Piven, Jed T, Elison, and H, Gu

Subjects
Autism Spectrum Disorder, Siblings, Surveys and Questionnaires, Infant Behavior, Humans, Infant, Female, Autistic Disorder, Child
Abstract

Using the Infant Behavior Questionnaire-Revised in a longitudinal sample of infant siblings of autistic children (HR; n = 427, 171 female, 83.4% White) and a comparison group of low-risk controls (LR, n = 200, 86 female, 81.5% White), collected between 2007 and 2017, this study identified an invariant factor structure of temperament traits across groups at 6 and 12 months. Second, after partitioning the groups by familial risk and diagnostic outcome at 24 months, results reveal an endophenotypic pattern of Positive Emotionality at both 6 and 12 months, (HR-autism spectrum disorder [ASD] HR-no-ASD LR). Third, increased 'Duration of Orienting' at 12 months was associated with lower scores on the 24-month developmental outcomes in HR infants. These findings may augment efforts for early identification of ASD.

Published
2022

45. Jointly analyzing the association of human milk nutrients with cognition and temperament traits during the first 6 months of life

Author

Tengfei Li, Tinu M. Samuel, Ziliang Zhu, Brittany Howell, Seoyoon Cho, Kristine Baluyot, Heather Hazlett, Jed T. Elison, Di Wu, Jonas Hauser, Norbert Sprenger, Hongtu Zhu, and Weili Lin

Abstract

Early dietary exposure via human milk (HM) components offers a window of opportunity to support cognitive and temperamental development. While several studies have focused on associations of few pre-selected HM components with cognition and temperament, it is highly plausible that HM components synergistically and jointly support cognitive and behavioral development in early life. We aimed to discern the combined associations of a wide array of HM nutrients with cognition and temperament during the first six months of life and explore if there were persistent effects up to 18 months old, when HM is the primary source of an infant’s nutrition. The Mullen Scales of Early Learning and Infant Behavior Questionnaires-Revised were used to assess cognition and temperament, respectively, of fifty-four exclusively/predominantly breastfed infants in the first 6 months of life, whose follow-ups were conducted at 6-9, 9-12 and 12-18 months old. HM samples were obtained from the mothers of the participants at less than 6 months of life and analyzed for fatty acids (total monounsaturated fatty acids, polyunsaturated fatty acid, total saturated fatty acid (TSFA), arachidonic acid (ARA), docosahexaenoic acid (DHA), ARA/DHA, omega-6/omega-3 polyunsaturated fatty acids ratio (n-6/n-3)), phospholipids (phosphatidylcholine, phosphatidylethanolamine (PE), phosphatidylinositol (PI), sphingomyelin) and choline (free choline, phosphocholine (PCho), glycerophosphocholine). Feature selection was performed to select nutrients associated with cognition and temperament, respectively. The combined effects of selected nutrients were analyzed using multiple regression. A positive association between the arachidonic acid (ARA) and surgency was observed (p = 0.024). Significant effect of DHA, n-6/n-3, PE and TSFA concentrations on receptive language (R2 = 0.39, p = 0.025), and the elevated ARA, PCho, and PI with increased surgency (R2 = 0.43, p = 0.003) was identified, suggesting that DHA and ARA may have distinct roles for temperament and language functions. Furthermore, the exploratory association analyses suggest that the effects of HM nutrients on R.L. and surgency may persist beyond the first 6 months of life, particularly surgency at 12-18 months (p = 0.002). Our studies highlighted that various HM nutrients work together to support the development of cognition and temperament traits during early infancy.

Published
2022

46. Brain charts for the human lifespan

Author

Armin Raznahan, Eric Courchesne, Andrea Parolin Jackowski, Kamen A. Tsvetanov, Cameron T. Ellis, R.C. Gur, Bin Bae J, Park Mtm, Pedro A. Valdes-Sosa, Simon N. Vandekar, Jacob W. Vogel, Juan Zhou, Machteld Marcelis, Kiho Im, Patricia Ellen Grant, Minhui Ouyang, Blesa Cabez M, Michael V. Lombardo, Sarah E. Morgan, James P. Boardman, Adamson C, Calhoun Vd, Delarue M, James H. Cole, Pichet Binette A, Roberto Toro, David H. Rowitch, Nynke A. Groenewold, Kevin M. Anderson, David T.W. Jones, Michael Schöll, Wang Ys, Aiden Corvin, R.E. Gur, Damien A. Fair, Gareth Ball, Herma Lina Schaare, Andrew Zalesky, Evdokia Anagnostou, Michael J. Meaney, Taki Y, Gareth J. Sullivan, Warrier, Petra E. Vértes, Chixiang Chen, Lisa T. Eyler, Wei Liao, Tomáš Paus, Jeremy A. Elman, Phillip McGuire, Hisham Ziauddeen, William S. Kremen, Etienne Vachon-Presseau, E.T. Bullmore, Christophe Tzourio, White, Hammill Cf, Mothersill D, Richard N. Henson, Jiang Qiu, Duncan E. Astle, Fabrice Crivello, Paul C. Fletcher, Chertavian C, Kim K, Jennifer Crosbie, Russell Schachar, Gabriel A. Devenyi, Manfred G. Kitzbichler, Tianye Jia, Trey Hedden, Sang Jae Lee, Ross D. Markello, Silke Kern, Ian M. Goodyer, Keith A. Johnson, Frauke Beyer, Bernard Mazoyer, A. Heinz, Sylvane Desrivières, Rosenberg, Gary Donohoe, Ong Mq, Alexander D. Edwards, Dan J. Stein, Nenad Medic, Zuo Xn, Travis T. Mallard, Peter Fonagy, Lindsay W. Victoria, Ingmar Skoog, Avram J. Holmes, Jason P. Lerch, Jed T. Elison, Jianfu Li, John H. Gilmore, Rosemary Holt, Caitlin K. Rollins, Carol E. Franz, Pedro Mario Pan, Saashi A Bedford, Yang N, Jonathan C Ipser, Richard A. I. Bethlehem, Tuulari Jj, Stolicyn A, Hua Huang, Bratislav Misic, Conor Liston, Ayub M, Lisa Ronan, Yeo Bt, Sophie Adler, Charles J. Lynch, Faith M. Gunning, Konrad Wagstyl, M. Mallar Chakravarty, John Suckling, Theodore D. Satterthwaite, Bharath Holla, Yap Seng Chong, Jinglei Lv, Jakob Seidlitz, Niall J Bourke, Xinlei Qian, Simon Baron-Cohen, Cynthia M. Ortinau, Deirel Paz Linares, Thyreau B, René S. Kahn, Aaron P. Schultz, Vanessa Cropley, Eric Westman, Mitchell Valdés-Sosa, Rik Ossenkoppele, André Zugman, Hasse Karlsson, Sylvia Villeneuve, Katja Heuer, Di Biase Ma, Margaret L. Westwater, Sofie L. Valk, David J. Sharp, Brigitte Landeau, Matthew Borzage, Kirsten A. Donald, Timothy Rittman, Richard Beare, Giovanni Abrahão Salum, Gunter Schumann, Ryuta Kawashima, Romero-Garcia R, John Blangero, Yun Hj, Russel T. Shinohara, Nicolas Crossley, Simon K. Warfield, Karen Pierce, George S. Alexopoulos, Katharine Dunlop, David C. Glahn, Francois Lalonde, Anqi Qiu, Lana Vasung, Gaël Chételat, Lídice Galán-García, Clifford R. Jack, Reisa A. Sperling, Anna Zettergren, Elizabeth Kelley, Arno Villringer, Andrea Mechelli, Benegal, Aaron Alexander-Bloch, Nicholas B. Turk-Browne, van Amelsvoort T, John D. Lewis, Heather C. Whalley, A. V. Witte, Zdenka Pausova, Joel T. Nigg, Heather J. Zar, Raymond J. Dolan, Christopher D. Smyser, Jay N. Giedd, Lena Palaniyappan, Ali Gholipour, Areces-Gonzalez A, Peter B. Jones, Jacqueline Hoare, Oskar Hansson, Linnea Karlsson, C Pantelis, Paly L, Bonnie Auyeung, Jorge Bosch-Bayard, Bethlehem, Richard [0000-0002-0714-0685], White, Simon [0000-0001-8642-7037], Astle, Duncan [0000-0002-7042-5392], Baron-Cohen, Simon [0000-0001-9217-2544], Henson, Rik [0000-0002-0712-2639], Jones, Peter [0000-0002-0387-880X], Kitzbichler, Manfred [0000-0002-4494-0753], Rittman, Timothy [0000-0003-1063-6937], Rowitch, David [0000-0002-0079-0060], Tsvetanov, Kamen A. [0000-0002-3178-6363], Westwater-Wozniak, Margaret [0000-0002-2918-0979], Ziauddeen, Hisham [0000-0003-4044-1719], Apollo - University of Cambridge Repository, British Academy, Autism Research Trust, National Institute of Mental Health (US), UK Research and Innovation, Medical Research Council (UK), National Institute for Health and Care Research (US), Wellcome Trust, University of Cambridge, Cambridge Biomedical Research Centre, University of Cambridge [UK] (CAM), University of Pennsylvania, Yale University [New Haven], Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Child and Adolescent Psychiatry Department [AP- HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de Neuroscience - Department of Neuroscience, Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Neurology, Amsterdam Neuroscience - Neurodegeneration, 3R-BRAIN, AIBL, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Repository Without Borders Investigators, CALM Team, Cam-CAN, CCNP, COBRE, cVEDA, ENIGMA Developmental Brain Age Working Group, Developing Human Connectome Project, FinnBrain, Harvard Aging Brain Study, IMAGEN, KNE96, The Mayo Clinic Study of Aging, NSPN, POND, The PREVENT-AD Research Group, VETSA, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Auyeung, B.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Baron-Cohen, S.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bedford, S. A.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Holt, R.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Lombardo, M. V.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Seidlitz, J.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Vogel, J. W.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. E.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. C.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Jackowski, A. P.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Chertavian, C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. E.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [White, S. R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Goodyer, I. M.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Henson, R. N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Jones, P. B.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Medic, N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Morgan, S. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Romero-Garcia, R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ronan, L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Suckling, J.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Vertes, P. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Warrier, V.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Westwater, M. L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ziauddeen, H.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Bullmore, E. T.] Univ Cambridge, Dept Psychiat, Cambridge, England, [White, S. R.] Univ Cambridge, MRC Biostat Unit, Cambridge, England, [Vogel, J. W.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Anderson, K. M.] Yale Univ, Dept Psychol, New Haven, CT USA, [Ellis, C. T.] Yale Univ, Dept Psychol, New Haven, CT USA, [Turk-Browne, N. B.] Yale Univ, Dept Psychol, New Haven, CT USA, [Adamson, C.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Ball, G.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Beare, R.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Jackowski, A. P.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Adamson, C.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Beare, R.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Adler, S.] UCL Great Ormond St Inst Child Hlth, London, England, [Alexopoulos, G. S.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Anagnostou, E.] Univ Toronto, Dept Pediat, Toronto, ON, Canada, [Anagnostou, E.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Pierce, K.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Areces-Gonzalez, A.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Paz-Linares, D.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Areces-Gonzalez, A.] Univ Pinar del Rio Hermanos Saiz Montes de Oca, Pinar Del Rio, Cuba, [Astle, D. E.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Henson, R. N.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Whalley, H. C.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Auyeung, B.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Pausova, Z.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Ayub, M.] Queens Univ, Dept Psychiat, Ctr Neurosci Studies, Kingston, ON, Canada, [Ayub, M.] UCL, Mental Hlth Neurosci Res Dept, Div Psychiat, London, England, [Bae, J.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Ball, G.] Univ Melbourne, Dept Paediat, Melbourne, Vic, Australia, [Baron-Cohen, S.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge Lifetime Asperger Syndrome Serv CLASS, Cambridge, England, [Benegal, V.] Natl Inst Mental Hlth & Neurosci NIMHANS, Ctr Addict Med, Bengaluru, India, [Beyer, F.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Villringer, A.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Witte, A. V.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Blangero, J.] Univ Texas Rio Grande Valley, South Texas Diabet & Obes Inst, Dept Human Genet, Edinburg, TX USA, [Blesa Cabez, M.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Boardman, J. P.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Sullivan, G.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Borzage, M.] Univ Southern Calif, Childrens Hosp Los Angeles, Keck Sch Med, Fetal & Neonatal Inst,Div Neonatol,Dept Pediat, Los Angeles, CA 90007 USA, [Bosch-Bayard, J. F.] Montreal Neurol Inst, Ludmer Ctr Neuroinformat & Mental Hlth, McGill Ctr Integrat Neurosci, Montreal, PQ, Canada, [Bosch-Bayard, J. F.] McGill Univ, Montreal, PQ, Canada, [Chakravarty, M. M.] McGill Univ, Montreal, PQ, Canada, [Bourke, N.] Imperial Coll London, Dept Brain Sci, London, England, [Sharp, D.] Imperial Coll London, Dept Brain Sci, London, England, [Alexander-Bloch, A. F.] Imperial Coll London, Dept Brain Sci, London, England, [Bourke, N.] Dementia Res Inst, Care Res & Technol Ctr, London, England, [Calhoun, V. D.] Georgia State Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia Inst Technol, Atlanta, GA 30303 USA, [Calhoun, V. D.] Emory Univ, Atlanta, GA 30322 USA, [Chakravarty, M. M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Comp Brain Anat CoBrA Lab, Montreal, PQ, Canada, [Chen, C.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Shinohara, R. T.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Chetelat, G.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Delarue, M.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Landeau, B.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Paly, L.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Chong, Y. S.] Agcy Sci Technol & Res, Singapore Inst Clin Sci, Singapore, Singapore, [Chong, Y. S.] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Obstet & Gynaecol, Singapore, Singapore, [Cole, J. H.] UCL, Ctr Med Image Comp CMIC, London, England, [Cole, J. H.] UCL, Dementia Res Ctr DRC, London, England, [Corvin, A.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Costantino, M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Verdun, PQ, Canada, [Costantino, M.] McGill Univ, Undergrad Program Neurosci, Montreal, PQ, Canada, [Courchesne, E.] Univ Calif San Diego, Dept Neurosci, San Diego, CA 92103 USA, [Courchesne, E.] Univ Calif San Diego, Autism Ctr Excellence, San Diego, CA 92103 USA, [Crivello, F.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Mazoyer, B.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Cropley, V. L.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Di Biase, M. A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Lv, J.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Zalesky, A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Hammill, C. F.] Hosp Sick Children, Toronto, ON, Canada, [Schachar, R. J.] Hosp Sick Children, Toronto, ON, Canada, [Crossley, N.] Pontificia Univ Catolica Chile, Sch Med, Dept Psychiat, Santiago, Chile, [Crossley, N.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [McGuire, P.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [Crossley, N.] Inst Milenio Intelligent Healthcare Engn, Santiago, Chile, [Delorme, R.] Robert Debre Univ Hosp, AP HP, Child & Adolescent Psychiat Dept, Paris, France, [Delorme, R.] Inst Pasteur, Human Genet & Cognit Funct, Paris, France, [Desrivieres, S.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Social Genet & Dev Psychiat Ctr, London, England, [Devenyi, G. A.] Douglas Mental Hlth Univ Inst, McGill Dept Psychiat, Cerebral Imaging Ctr, Montreal, PQ, Canada, [Devenyi, G. A.] McGill Univ, Dept Psychiat, Montreal, PQ, Canada, [Di Biase, M. A.] Harvard Med Sch, Brigham & Womens Hosp, Dept Psychiat, Boston, MA 02115 USA, [Dolan, R.] UCL, Max Planck UCL Ctr Computat Psychiat & Ageing Res, London, England, [Dolan, R.] Wellcome Ctr Human Neuroimaging, London, England, [Wagstyl, K.] Wellcome Ctr Human Neuroimaging, London, England, [Donald, K. A.] Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Div Dev Paediat, Cape Town, South Africa, [Donald, K. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Groenewold, N. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Donohoe, G.] Natl Univ Ireland Galway, Sch Psychol, Ctr Neuroimaging Cognit & Genom NICOG, Galway, Ireland, [Dunlop, K.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Lynch, C.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Edwards, A. D.] Kings Coll London, Ctr Dev Brain, London, England, [Edwards, A. D.] Evelina London Childrens Hosp, London, England, [Edwards, A. D.] MRC Ctr Neurodev Disorders, London, England, [Elison, J. T.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Fair, D. A.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Feczko, E.] Univ Minnesota, Mason Inst Dev Brain, Dept Pediat, Inst Child Dev, Minneapolis, MN USA, [Ellis, C. T.] Haskins Labs Inc, New Haven, CT USA, [Elman, J. A.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Franz, C. E.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Kremen, W. S.] Univ Calif San Diego, Dept Psychiat, Ctr Behav Genet Aging, La Jolla, CA 92093 USA, [Eyler, L.] VA San Diego Healthcare, Desert Pacific Mental Illness Res Educ & Clin Ctr, San Diego, CA USA, [Eyler, L.] Univ Calif San Diego, Dept Psychiat, Los Angeles, CA USA, [Fletcher, P. C.] Univ Cambridge, Dept Psychiat, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Wellcome Trust MRC Inst Metab Sci, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Jones, P. B.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Suckling, J.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Ziauddeen, H.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Fonagy, P.] UCL, Dept Clin Educ & Hlth Psychol, London, England, [Fonagy, P.] Anna Freud Natl Ctr Children & Families, London, England, [Galan-Garcia, L.] Cuban Ctr Neurosci, Havana, Cuba, [Valdes-Sosa, M. J.] Cuban Ctr Neurosci, Havana, Cuba, [Gholipour, A.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Warfield, S. K.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Giedd, J.] Univ Calif San Diego, Dept Child & Adolescent Psychiat, San Diego, CA 92103 USA, [Giedd, J.] Univ Calif San Diego, Dept Psychiat, San Diego, CA 92103 USA, [Gilmore, J. H.] Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27515 USA, [Glahn, D. C.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Im, K.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Mathias, S. R.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Rodrigue, A.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Glahn, D. C.] Harvard Med Sch, Boston, MA 02115 USA, [Im, K.] Harvard Med Sch, Boston, MA 02115 USA, [Johnson, K. A.] Harvard Med Sch, Boston, MA 02115 USA, [Mathias, S. R.] Harvard Med Sch, Boston, MA 02115 USA, [Rodrigue, A.] Harvard Med Sch, Boston, MA 02115 USA, [Schultz, A. P.] Harvard Med Sch, Boston, MA 02115 USA, [Sperling, R. A.] Harvard Med Sch, Boston, MA 02115 USA, [Grant, P. E.] Harvard Med Sch, Fetal Neonatal Neuroimaging & Dev Sci Ctr, Boston Childrens Hosp, Div Newborn Med & Neuroradiol, Boston, MA 02115 USA, [Groenewold, N. A.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Zar, H. J.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Gunning, F. M.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Victoria, L. W.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Hammill, C. F.] Mouse Imaging Ctr, Toronto, ON, Canada, [Hansson, O.] Lund Univ, Dept Clin Sci Malmo, Clin Memory Res Unit, Malmo, Sweden, [Hansson, O.] Skane Univ Hosp, Memory Clin, Malmo, Sweden, [Hedden, T.] Icahn Sch Med Mt Sinai, Dept Neurol, New York, NY 10029 USA, [Hedden, T.] Harvard Med Sch, Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Boston, MA 02115 USA, [Heinz, A.] Charite Univ Med Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Free Univ Berlin, Charite Campus Mitte, Berlin, Germany, [Heinz, A.] Humboldt Univ, Dept Psychiat & Psychotherapy, Charite Campus Mitte, Berlin, Germany, [Heuer, K.] Max Planck Inst Human Cognit & Brain Sci, Dept Neuropsychol, Leipzig, Germany, [Heuer, K.] Univ Paris, Paris, France, [Toro, R.] Univ Paris, Paris, France, [Hoare, J.] Univ Cape Town, Dept Psychiat, Cape Town, South Africa, [Holla, B.] NIMHANS, Dept Integrat Med, Bengaluru, India, [Holla, B.] NIMHANS, Dept Psychiat, Accelerator Program Discovery Brain Disorders Usi, Bengaluru, India, [Holmes, A. J.] Yale Univ, Dept Psychol, New Haven, CT USA, [Villeneuve, S.] Yale Univ, Dept Psychol, New Haven, CT USA, [Holmes, A. J.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Villeneuve, S.] Yale Univ, Dept Psychiat, New Haven, CT 06520 USA, [Huang, H.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Ouyang, M.] Childrens Hosp Philadelphia, Radiol Res, Philadelphia, PA 19104 USA, [Huang, H.] Univ Penn, Dept Radiol, Perelman Sch Med, Philadelphia, PA 19104 USA, [Ipser, J.] Univ Cape Town, Dept Psychiat & Mental Hlth, Clin Neurosci Inst, Cape Town, South Africa, [Jack, C. R., Jr.] Mayo Clin, Dept Radiol, Rochester, MN USA, [Jones, D. T.] Mayo Clin, Dept Radiol, Rochester, MN USA, Univ Fed Sao Paulo, Dept Psychiat, Sao Paulo, Brazil, [Jackowski, A. P.] Natl Inst Dev Psychiat, Beijing, Peoples R China, [Jia, T.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China, [Jia, T.] Fudan Univ, Minist Educ, Key Lab Computat Neurosci & Brain Inspired Intell, Shanghai, Peoples R China, [Jia, T.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Ctr Populat Neurosci & Precis Med PONS, SGDP Ctr, London, England, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Sperling, R. A.] Massachusetts Gen Hosp, Dept Neurol, Harvard Aging Brain Study, Boston, MA 02114 USA, [Johnson, K. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Sperling, R. A.] Brigham & Womens Hosp, Dept Neurol, Ctr Alzheimer Res & Treatment, 75 Francis St, Boston, MA 02115 USA, [Johnson, K. A.] Massachusetts Gen Hosp, Dept Radiol, Boston, MA USA, [Jones, D. T.] Mayo Clin, Dept Neurol, Rochester, MN USA, [3R-BRAIN] Mayo Clin, Dept Neurol, Rochester, MN USA, [Kahn, R. S.] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA, [Karlsson, H.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, L.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Dept Psychiat, Dept Clin Med, Turku, Finland, [Karlsson, H.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, L.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Tuulari, J. J.] Univ Turku, FinnBrain Birth Cohort Study, Turku Brain & Mind Ctr, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Turku, Finland, [Tuulari, J. J.] Turku Univ Hosp, Turku, Finland, [Karlsson, H.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, L.] Turku Univ Hosp, Ctr Populat Hlth Res, Turku, Finland, [Karlsson, H.] Univ Turku, Turku, Finland, [Karlsson, L.] Univ Turku, Turku, Finland, [Kawashima, R.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Taki, Y.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Thyreau, B.] Tohoku Univ, Inst Dev Aging & Canc, Aoba Ku, Sendai, Miyagi, Japan, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychol, Kingston, ON, Canada, [Kelley, E. A.] Queens Univ, Ctr Neurosci Studies, Dept Psychiat, Kingston, ON, Canada, [Kern, S.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Skoog, I.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Zettergren, A.] Univ Gothenburg, Neuropsychiat Epidemiol Unit, Dept Psychiat & Neurochem,Sahlgrenska Acad, Ctr Ageing & Hlth AGECAP,Inst Neurosci & Physiol, Gothenburg, Sweden, [Kern, S.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Skoog, I.] Sahlgrens Univ Hosp, Psychiat Cognit & Old Age Psychiat Clin, Reg Vastra Gotaland, Gothenburg, Sweden, [Kim, K. W.] Seoul Natl Univ, Dept Brain & Cognit Sci, Coll Nat Sci, Seoul, South Korea, [Kim, K. W.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Kim, K. W.] Seoul Natl Univ, Dept Psychiat, Coll Med, Seoul, South Korea, [Kim, K. W.] SNU MRC, Inst Human Behav Med, Seoul, South Korea, [Lalonde, F.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Raznahan, A.] NIMH, Sect Dev Neurogenom, Human Genet Branch, Bethesda, MD 20892 USA, [Lee, S.] Seoul Natl Univ, Coll Nat Sci, Dept Brain & Cognit Sci, Seoul, South Korea, [Lerch, J.] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada, [Lerch, J.] Univ Oxford, Nuffield Dept Clin Neurosci, FMRIB, Wellcome Ctr Integrat Neuroimaging, Oxford, England, [Lewis, J. D.] McGill Univ, Montreal Neurol Inst, Montreal, PQ, Canada, [Li, J.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liao, W.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Valdes-Sosa, P. A.] Univ Elect Sci & Technol China, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Liston, C.] Weill Cornell Med, Dept Psychiat, New York, NY USA, [Liston, C.] Weill Cornell Med, Brain & Mind Res Inst, New York, NY USA, [Lombardo, M. V.] Ist Italiano Tecnol, Ctr Neurosci & Cognit Syst UniTn, Lab Autism & Neurodev Disorders, Rovereto, Italy, [Lv, J.] Univ Sydney, Sch Biomed Engn, Sydney, NSW, Australia, [Lv, J.] Univ Sydney, Brain & Mind Ctr, Sydney, NSW, Australia, [Mallard, T. T.] Univ Texas Austin, Dept Psychol, Austin, TX 78712 USA, [Marcelis, M.] Maastricht Univ, Sch Mental Hlth & Neurosci, Dept Psychiat & Neuropsychol, EURON,Med Ctr, Maastricht, Netherlands, [Marcelis, M.] Inst Mental Hlth Care Eindhoven GGzE, Eindhoven, Netherlands, [Markello, R. D.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Misic, B.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Vasung, L.] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ, Canada, [Mazoyer, B.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Douglas Mental Hlth Univ Inst, Ludmer Ctr Neuroinformat & Mental Hlth, Montreal, PQ, Canada, [Meaney, M. J.] Singapore Inst Clin Sci, Singapore, Singapore, [Mechelli, A.] Bordeaux Univ Hosp, Bordeaux, France, [Morgan, S. E.] Univ Cambridge, Dept Comp Sci & Technol, Cambridge, England, [Morgan, S. E.] Alan Turing Inst, London, England, [Vertes, P. E.] Alan Turing Inst, London, England, [Mothersill, D.] Natl Coll Ireland, Sch Business, Dept Psychol, Dublin, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Sch Psychol, Galway, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Ctr Neuroimaging & Cognit Genom, Galway, Ireland, [Mothersill, D.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Nigg, J.] Oregon Hlth & Sci Univ, Dept Psychiat, Sch Med, Portland, OR 97201 USA, [Ong, M. Q. W.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Qian, X.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Ortinau, C.] Washington Univ, Dept Pediat, St Louis, MO 63130 USA, [Ossenkoppele, R.] Vrije Univ Amsterdam, Alzheimer Ctr Amsterdam, Amsterdam UMC, Dept Neurol,Amsterdam Neurosci, Amsterdam, Netherlands, [Ossenkoppele, R.] Lund Univ, Clin Memory Res Unit, Lund, Sweden, [Palaniyappan, L.] Univ Western Ontario, Robarts Res Inst, London, ON, Canada, [Palaniyappan, L.] Univ Western Ontario, Brain & Mind Inst, London, ON, Canada, [Pan, P. M.] Fed Univ Sao Poalo UNIFESP, Dept Psychiat, Sao Poalo, Brazil, [Pan, P. M.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Zugman, A.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Pantelis, C.] Univ Melbourne, Dept Psychiat, Melbourne Neuropsychiat Ctr, Carlton, Vic, Australia, [Pantelis, C.] Melbourne Hlth, Carlton, Vic, Australia, [Pantelis, C.] Univ Melbourne, Melbourne Sch Engn, Parkville, Vic, Australia, [Pantelis, C.] Florey Inst Neurosci & Mental Hlth, Parkville, Vic, Australia, [Park, M. M.] Western Univ, Schulich Sch Med & Dent, Dept Psychiat, London, ON, Canada, [Rollins, C. K.] Univ Montreal, Dept Psychiat, Fac Med, Montreal, PQ, Canada, [Rollins, C. K.] Univ Montreal, CHU St Justine, Montreal, PQ, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychiat, Toronto, ON, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Physiol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Nutr Sci, Toronto, ON, Canada, [Paz-Linares, D.] Cuban Neurosci Ctr, Havana, Cuba, [Pichet Binette, A.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Villeneuve, S.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Pichet Binette, A.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Villeneuve, S.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Qiu, J.] Southwest Univ, Sch Psychol, Chongqing, Peoples R China, [Qiu, A.] Natl Univ Singapore, N1 Inst Hlth, Dept Biomed Engn, Singapore, Singapore, [Rittman, T.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Tsvetanov, K. A.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Rollins, C. K.] Harvard Med Sch, Dept Neurol, Boston, MA 02115 USA, [Rollins, C. K.] Boston Childrens Hosp, Dept Neurol, Boston, MA USA, [Romero-Garcia, R.] Univ Seville, Dpto Fisiol Med & Biofis, Inst Biomed Sevilla IBiS HUVR CSIC, Seville, Spain, [Rosenberg, M. D.] Univ Chicago, Dept Psychol, 5848 S Univ Ave, Chicago, IL 60637 USA, [Rosenberg, M. D.] Univ Chicago, Inst Neurosci, Chicago, IL USA, [Rowitch, D. H.] Univ Cambridge, Dept Paediat, Cambridge, England, [Rowitch, D. H.] Univ Cambridge, Wellcome MRC Cambridge Stem Cell Inst, Cambridge, England, [Salum, G. A.] Univ Fed Rio Grande Sul UFRGS, Hosp Clin Porto Alegre, Dept Psychiat, Porto Alegre, RS, Brazil, [Salum, G. A.] Natl Inst Dev Psychiat INPD, Sao Paulo, Brazil, [Schaare, H. L.] Max Planck Inst Human Cognit & Brain Sci, Otto Hahn Grp Cognit Neurogenet, Leipzig, Germany, [Schaare, H. L.] Res Ctr Juelich, Inst Neurosci & Med INM 7 Brain & Behav, Julich, Germany, [Schultz, A. P.] Massachusetts Gen Hosp, Dept Radiol, Athinoula Martinos Ctr Biomed Imaging, Charlestown, MA USA, [Schumann, G.] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Ctr Populat Neurosci & Stratified Med PONS, Shanghai, Peoples R China, [Schumann, G.] Charite Campus Mitte, Dept Psychiat & Psychotherapy, Charite Mental Hlth, PONS Ctr, Berlin, Germany, [Scholl, M.] Univ Gothenburg, Wallenberg Ctr Mol & Translat Med, Gothenburg, Sweden, [Scholl, M.] Univ Gothenburg, Dept Psychiat & Neurochem, Gothenburg, Sweden, [Scholl, M.] UCL, Queens Sq Inst Neurol, Dementia Res Ctr, London, England, [Sharp, D.] UK Dementia Res Inst, Care Res & Technol Ctr, London, England, [Shinohara, R. T.] Univ Penn, Perelman Sch Med, Dept Radiol, Ctr Biomed Image Comp & Analyt, Philadelphia, PA 19104 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Neurol, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Pediat, St Louis, MO 63110 USA, [Smyser, C. D.] Washington Univ, Sch Med, Dept Radiol, St Louis, MO 63110 USA, [Stein, D. J.] Univ Cape Town, Dept Psychiat, SA MRC Unit Risk & Resilience Mental Disorders, Cape Town, South Africa, [Stein, D. J.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Stolicyn, A.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Whalley, H. C.] Univ Edinburgh, Ctr Clin Brain Sci, Div Psychiat, Edinburgh, Midlothian, Scotland, [Toro, R.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Inst Pasteur, Dept Neurosci, Paris, France, [Traut, N.] Univ Paris 05, Ctr Res & Interdisciplinar CRI, Paris, France, [Tsvetanov, K. A.] Univ Cambridge, Dept Psychol, Cambridge, England, [Turk-Browne, N. B.] Yale Univ, Wu Tsai Inst, New Haven, CT USA, [Tuulari, J. J.] Univ Turku, Dept Clin Med, Turku, Finland, [Tuulari, J. J.] Univ Turku, Turku Coll Sci Med & Technol, Turku, Finland, [Tzourio, C.] Univ Bordeaux, Bordeaux Populat Hlth Res Ctr, CHU Bordeaux, U1219,INSERM, Bordeaux, France, [Vachon-Presseau, E.] McGill Univ, Fac Dent Med & Oral Hlth Sci, Montreal, PQ, Canada, [Valdes-Sosa, P. A.] McGill Univ, Alan Edwards Ctr Res Pain AECRP, Montreal, PQ, Canada, [Valk, S. L.] Forschungszentrum Julich, Inst Neurosci & Med 7, Julich, Germany, [Valk, S. L.] Max Planck Inst Human Cognit & Brain Sci, Leipzig, Germany, [van Amelsvoort, T.] Maastricht Univ, Dept Psychiat & Neurosychol, Maastricht, Netherlands, [Vandekar, S. N.] Vanderbilt Univ, Dept Biostat, 221 Kirkland Hall, Nashville, TN 37235 USA, [Villeneuve, S.] Vanderbilt Univ, Med Ctr, Dept Biostat, Nashville, TN USA, [Villringer, A.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Witte, A. V.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Zuo, X. N.] Univ Leipzig, Clin Cognit Neurol, Med Ctr, Leipzig, Germany, [Wang, Y. S.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yeo, B.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Wang, Y. S.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Wang, Y. S.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Yang, N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Zuo, X. N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Wang, Y. S.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Yang, N.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Westman, E.] Karolinska Inst, Ctr Alzheimer Res, Dept Neurobiol Care Sci & Soc, Div Clin Geriatr, Stockholm, Sweden, [Witte, A. V.] Univ Leipzig, CRC 1052 Obes Mech, Fac Med, Leipzig, Germany, [Zhou, J. H.] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat MR Res, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, N1 Inst Hlth, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Inst Digital Med, Singapore, Singapore, [Yun, H.] Natl Univ Singapore, Integrat Sci & Engn Programme ISEP, Singapore, Singapore, [Zar, H. J.] Univ Melbourne, Dept Biomed Engn, Melbourne, Vic, Australia, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat Magnet Resonance Res, Singapore, Singapore, [Ziauddeen, H.] Univ Cambridge, Wellcome Trust MRC Inst Metab Sci, Cambridge, England, [Zugman, A.] NIMH, NIH, Bethesda, MD 20892 USA, [Zugman, A.] Escola Paulista Med, Dept Psychiat, Sao Paulo, Brazil, [Zuo, X. N.] Nanning Normal Univ, Sch Educ Sci, Key Lab Brain & Educ, Nanning, Peoples R China, British Academy Postdoctoral fellowship, NIMH, UKRI Medical Research Council, NIHR Cambridge Biomedical Research Centre, NIHR Senior Investigator award, MRC research infrastructure award, Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Ontario Brain Institute

Subjects
631/378/2649, OpenPain Project, KNE96, Growth, Psychiatric-disorders, DISEASE, 3R-BRAIN, Brain charts, MRI Brain, OASIS-3, Disease, CCNP, 631/378/2571, UMN BCP, Multidisciplinary, medicine.diagnostic_test, PSYCHIATRIC-DISORDERS, article, Brain, Human brain, ASSOCIATION, Magnetic Resonance Imaging, Harvard Aging Brain Study, The Mayo Clinic Study of Aging, NSPN, medicine.anatomical_structure, GROWTH, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ddc:500, BURDEN, WHITE-MATTER, FinnBrain, Harvard Aging Brain Study, Organization, Mri, MRI, medicine.medical_specialty, Concurrent validity, MODELS, Cam-CAN, Longevity, CALM Team, POND, Neuroimaging, Burden, ORGANIZATION, AIBL, The PREVENT-AD Research Group, VETSA, Cortical thickness, Association, Physical medicine and rehabilitation, FinnBrain, IMAGEN, KNE96, White-matter, medicine, Humans, ASRB, 631/378/1689, COBRE, business.industry, 631/378/2611, Brain morphometry, Neurosciences, Alzheimer’s Disease Repository Without Borders Investigators, Magnetic resonance imaging, Alzheimer’s Disease Neuroimaging Initiative, Anthropometry, Body Height, Brain growth, Birth, 59/57, Normative, IMAGEN, ENIGMA Developmental Brain Age working group, NSPN, business, CCNP, 3R-BRAIN, CORTICAL THICKNESS, Developing Human Connectome Project, ENIGMA Developmental Brain Age working group, The PREVENT-AD Research Group, VETSA, Bullmore, E.T
Abstract

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes., R.A.I.B. was supported by a British Academy Postdoctoral fellowship and by the Autism Research Trust. J. Seidlitz was supported by NIMH T32MH019112-29 and K08MH120564. S.R.W. was funded by UKRI Medical Research Council MC_UU_00002/2 and was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network. A.F.A.-B. was supported by NIMH K08MH120564. Data were curated and analysed using a computational facility funded by an MRC research infrastructure award (MR/M009041/1) to the School of Clinical Medicine, University of Cambridge and supported by the mental health theme of the NIHR Cambridge Biomedical Research Centre.

Published
2022

47. Genetic architecture of reciprocal social behavior in toddlers: Implications for heterogeneity in the early origins of autism spectrum disorder

Author

Theodore Jacob, Jed T. Elison, Jon Randolph Haber, Natasha Marrus, Yi Zhang, Anne L. Glowinski, John N. Constantino, Brooke Harris-Olenak, Drew Bolster, Arpana Agrawal, Julia D. Grant, Jordan Albright, and Andrew C. Heath

Subjects
Autism Spectrum Disorder, Video Recording, Child Behavior, Infant, Heritability, medicine.disease, Article, Genetic architecture, Developmental psychology, Psychiatry and Mental health, Cognition, Autism spectrum disorder, Child, Preschool, Genetic structure, Developmental and Educational Psychology, medicine, Humans, Autism, Social competence, Autistic Disorder, Toddler, Social Behavior, Psychology, Reciprocal
Abstract

Impairment in reciprocal social behavior (RSB), an essential component of early social competence, clinically defines autism spectrum disorder (ASD). However, the behavioral and genetic architecture of RSB in toddlerhood, when ASD first emerges, has not been fully characterized. We analyzed data from a quantitative video-referenced rating of RSB (vrRSB) in two toddler samples: a community-based volunteer research registry (n = 1,563) and an ethnically diverse, longitudinal twin sample ascertained from two state birth registries (n = 714). Variation in RSB was continuously distributed, temporally stable, significantly associated with ASD risk at age 18 months, and only modestly explained by sociodemographic and medical factors (r2 = 9.4%). Five latent RSB factors were identified and corresponded to aspects of social communication or restricted repetitive behaviors, the two core ASD symptom domains. Quantitative genetic analyses indicated substantial heritability for all factors at age 24 months (h2 ≥ .61). Genetic influences strongly overlapped across all factors, with a social motivation factor showing evidence of newly-emerging genetic influences between the ages of 18 and 24 months. RSB constitutes a heritable, trait-like competency whose factorial and genetic structure is generalized across diverse populations, demonstrating its role as an early, enduring dimension of inherited variation in human social behavior. Substantially overlapping RSB domains, measurable when core ASD features arise and consolidate, may serve as markers of specific pathways to autism and anchors to inform determinants of autism's heterogeneity.

Published
2020

48. Sex differences in age of diagnosis of autism spectrum disorder: preliminary evidence from Uganda

Author

Jed T. Elison, Catherine Abbo, Michele E. Villalobos, Collin Ogara, and Emmanuel Bonney

Subjects
Male, Pediatrics, medicine.medical_specialty, genetic structures, Autism Spectrum Disorder, Black People, Context (language use), behavioral disciplines and activities, Article, Epilepsy, Chart review, mental disorders, medicine, Humans, Uganda, Medical diagnosis, Child, Genetics (clinical), Retrospective Studies, Sex Characteristics, business.industry, General Neuroscience, Significant difference, medicine.disease, Mental health, Autism spectrum disorder, Child, Preschool, Autism, Female, Neurology (clinical), business
Abstract

This study was performed to determine (a) the age at which ASD is first diagnosed in Ugandan children receiving mental health services; (b) whether age at diagnosis varies by sex and clinical presentation and (c) the average age of ASD diagnosis in children manifesting comorbid conditions. A retrospective chart review was performed and demographic as well as clinical data were collected from children with ASD diagnoses who attended two mental health clinics in Uganda between 2014 and 2019. Descriptive statistics such as percentages, means and standard deviations were used to summarize the data. Independent t-test was also performed to determine differences in the mean age of diagnosis between males and females. Two hundred and thirty-seven (156 males, 81 females) children with ASD were identified. The average age of ASD diagnosis was (6.9±4.0 years). A statistically significant difference in age of ASD diagnosis was found between males and females [t= −2.106, p=0.036], such that on average females received a diagnosis at least one year later than males. Of the 237 participants, 53.6% were identified with ASD only, 16.0% had ASD and ADHD, 10.5% were diagnosed with ASD and epilepsy and 7.2% had a diagnosis of complex ASD. The results confirm delays in access to ASD diagnosis and suggest that females are more likely to receive a diagnosis of ASD later than males within the Ugandan context. ASD awareness should be intensified to improve public or professional knowledge about ASD in Uganda. Finally, effective strategies should be developed to improve early identification.

Published
2021

49. Real-time motion monitoring improves functional MRI data quality in infants

Author

Carolina Badke D'Andrea, Jeanette K. Kenley, Eric Earl, David F. Montez, Christopher D. Smyser, Ryland L. Miller, Essa Yacoub, Jonathan M. Koller, Nico U.F. Dosenbach, Amy E. Mirro, Cynthia E. Rogers, Deanna J. Greene, Sooyeon Sung, Damien A. Fair, and Jed T. Elison

Subjects
Neuroimaging, Computer science, Data quality, Data loss, Mri scan, Motion (physics), Biomedical engineering, Motion monitoring
Abstract

Imaging the infant brain with MRI has improved our understanding of early stages of neurodevelopment. However, head motion during MRI acquisition is detrimental to both functional and structural MRI scan quality. Though infants are commonly scanned while asleep, they commonly exhibit motion during scanning, causing data loss. Our group has shown that providing MRI technicians with real-time motion estimates via Framewise Integrated Real-Time MRI Monitoring (FIRMM) software helps obtain high-quality, low motion fMRI data. By estimating head motion in real time and displaying motion metrics to the MR technician during an fMRI scan, FIRMM can improve scanning efficiency. Hence, we compared average framewise displacement (FD), a proxy for head motion, and the amount of usable fMRI data (FD ≤ 0.2mm) in infants scanned with (n = 407) and without FIRMM (n = 295). Using a mixed-effects model, we found that the addition of FIRMM to current state-of-the-art infant scanning protocols significantly increased the amount of usable fMRI data acquired per infant, demonstrating its value for research and clinical infant neuroimaging.

Published
2021

50. Pre-symptomatic intervention for autism spectrum disorder (ASD): defining a research agenda

Author

Michael J. Guralnick, Jed T. Elison, Kevin G. Bath, Joseph Piven, Dima Amso, Gedeon O. Deák, Rebecca Landa, Leonard J Abbeduto, Linda R. Watson, Rebecca Grzadzinski, Lonnie Zwaigenbaum, Annette Estes, Jason J. Wolff, and Jessica Brian

Subjects
medicine.medical_specialty, Neurology, Autism Spectrum Disorder, Intellectual and Developmental Disabilities (IDD), Autism, Cognitive Neuroscience, MEDLINE, Neurosciences. Biological psychiatry. Neuropsychiatry, Review, behavioral disciplines and activities, Pathology and Forensic Medicine, Empirical research, Behavior Therapy, Clinical Research, Multidisciplinary approach, Intervention (counseling), Behavioral and Social Science, mental disorders, medicine, Humans, Psychology, Social Behavior, Pediatric, Prevention, Neurosciences, Neuropsychology, Infant, medicine.disease, Brain Disorders, Mental Health, Conceptual framework, Autism spectrum disorder, Pediatrics, Perinatology and Child Health, Neurology (clinical), RC321-571, Clinical psychology
Abstract

Autism spectrum disorder (ASD) impacts an individual’s ability to socialize, communicate, and interact with, and adapt to, the environment. Over the last two decades, research has focused on early identification of ASD with significant progress being made in understanding the early behavioral and biological markers that precede a diagnosis, providing a catalyst for pre-symptomatic identification and intervention. Evidence from preclinical trials suggest that intervention prior to the onset of ASD symptoms may yield more improved developmental outcomes, and clinical studies suggest that the earlier intervention is administered, the better the outcomes. This article brings together a multidisciplinary group of experts to develop a conceptual framework for behavioral intervention, during the pre-symptomatic period prior to the consolidation of symptoms into diagnosis, in infants at very-high-likelihood for developing ASD (VHL-ASD). The overarching goals of this paper are to promote the development of new intervention approaches, empirical research, and policy efforts aimed at VHL-ASD infants during the pre-symptomatic period (i.e., prior to the consolidation of the defining features of ASD).

Published
2021

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