The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development

&NA; The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain‐behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high‐resolution structural MRI (T1‐and T2‐weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0–5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well‐established behavioral assessments during this time period will yield an invaluable resource for the scientific community. HighlightsComplete description of the UNC/UMN Baby Connectome Project (BCP) protocol.The importanc'e of dense longitudinal sampling.Protocol optimization and preliminary results of optimized imaging protocol.BCP study data as a unique resource for the scientific community.

[1]  Stefan Skare,et al.  How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.

[2]  S. Bradley-Johnson.  Mullen Scales of Early Learning , 1997 .

[3]  Stamatios N. Sotiropoulos,et al.  Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images , 2016, NeuroImage.

[4]  J. Allsop,et al.  Thalamocortical Connectivity Predicts Cognition in Children Born Preterm , 2015, Cerebral cortex.

[5]  Richard Rowe,et al.  Validity of the Strengths and Difficulties Questionnaire in Preschool-Aged Children , 2015, Pediatrics.

[6]  J. Shimony,et al.  Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. , 2001, Radiology.

[7]  Yong He,et al.  Development of human brain structural networks through infancy and childhood. , 2015, Cerebral cortex.

[8]  Domenic V. Cicchetti,et al.  Vineland Adaptive Behavior Scales, Second Edition , 2012 .

[9]  Holly Dirks,et al.  Pediatric neuroimaging using magnetic resonance imaging during non-sedated sleep , 2013, Pediatric Radiology.

[10]  Andrew C. Heath,et al.  Rapid video-referenced ratings of reciprocal social behavior in toddlers: a twin study. , 2015, Journal of child psychology and psychiatry, and allied disciplines.

[11]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[12]  Elizabeth Bates,et al.  MacArthur-Bates Communicative Development Inventories, Second Edition , 2012 .

[13]  Christopher H. Chatham,et al.  Adaptive behavior in autism: Minimal clinically important differences on the Vineland‐II , 2018, Autism research : official journal of the International Society for Autism Research.

[14]  Guido Gerig,et al.  Joint Attention and Brain Functional Connectivity in Infants and Toddlers , 2017, Cerebral cortex.

[15]  Abraham Z. Snyder,et al.  Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp , 2013, NeuroImage.

[16]  P. Gluckman,et al.  Prenatal maternal depression alters amygdala functional connectivity in 6-month-old infants , 2015, Translational Psychiatry.

[17]  M. Tomasello,et al.  Social cognition, joint attention, and communicative competence from 9 to 15 months of age. , 1998, Monographs of the Society for Research in Child Development.

[18]  Christine M. Freitag,et al.  Validity of the social responsiveness scale to differentiate between autism spectrum disorders and disruptive behaviour disorders , 2014, European Child & Adolescent Psychiatry.

[19]  M. Tomasello,et al.  Understanding and sharing intentions: The origins of cultural cognition , 2005, Behavioral and Brain Sciences.

[20]  Sean C. L. Deoni,et al.  Quantifying cortical development in typically developing toddlers and young children, 1–6 years of age , 2017, NeuroImage.

[21]  P. Hüppi,et al.  Cortical Development in the Fetus and the Newborn: Advanced MR Techniques , 2011, Topics in magnetic resonance imaging : TMRI.

[22]  Dinggang Shen,et al.  Consistent Spatial-Temporal Longitudinal Atlas Construction for Developing Infant Brains , 2016, IEEE Transactions on Medical Imaging.

[23]  P. Mundy,et al.  CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE Attention, Joint Attention, and Social Cognition , 2022 .

[24]  Dinggang Shen,et al.  Correction for Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects, by Wei Gao, Hongtu Zhu, Kelly S. Giovanello, J. Keith , 2009 .

[25]  Carlo Pierpaoli,et al.  T2 relaxometry of normal pediatric brain development , 2009, Journal of magnetic resonance imaging : JMRI.

[26]  Daniel C. Alexander,et al.  NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.

[27]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[28]  Terrie E Inder,et al.  Neurobehavior at term and white and gray matter abnormalities in very preterm infants. , 2009, The Journal of pediatrics.

[29]  K. Miller.  Executive functions. , 2005, Pediatric annals.

[30]  J. Gilmore,et al.  Dynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood. , 2015, Cerebral cortex.

[31]  D. Louis Collins,et al.  Unbiased average age-appropriate atlases for pediatric studies , 2011, NeuroImage.

[32]  Stamatios N. Sotiropoulos,et al.  An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.

[33]  D. Mathalon,et al.  A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. , 1994, Archives of neurology.

[34]  J. Steven Reznick,et al.  The Onset of Working Memory in Infants , 2004 .

[35]  A. Dale,et al.  Structural growth trajectories and rates of change in the first 3 months of infant brain development. , 2014, JAMA neurology.

[36]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[37]  J. Singer,et al.  The design and analysis of longitudinal studies of development and psychopathology in context: Statistical models and methodological recommendations , 1998, Development and Psychopathology.

[38]  J. Reznick,et al.  Development of visuospatial short-term memory in the second half of the 1st year. , 2004, Developmental psychology.

[39]  F A Jolesz,et al.  Optimized single-slab three-dimensional spin-echo MR imaging of the brain. , 2000, Radiology.

[40]  Dinggang Shen,et al.  Spatial Transformation of DWI Data Using Non-Negative Sparse Representation , 2012, IEEE Transactions on Medical Imaging.

[41]  Hiroyuki Kidokoro,et al.  Brain Injury and Altered Brain Growth in Preterm Infants: Predictors and Prognosis , 2014, Pediatrics.

[42]  Timothy Edward John Behrens,et al.  Task-free MRI predicts individual differences in brain activity during task performance , 2016, Science.

[43]  Steen Moeller,et al.  Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project , 2013, NeuroImage.

[44]  Stanislas Dehaene,et al.  A Neural Marker of Perceptual Consciousness in Infants , 2013, Science.

[45]  Thomas F. Nugent,et al.  Dynamic mapping of human cortical development during childhood through early adulthood. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[46]  M. Rothbart,et al.  Studying infant temperament via the Revised Infant Behavior Questionnaire , 2003 .

[47]  L. Moses,et al.  The Children's Social Understanding Scale: construction and validation of a parent-report measure for assessing individual differences in children's theories of mind. , 2014, Developmental psychology.

[48]  Shuiwang Ji,et al.  Deep convolutional neural networks for multi-modality isointense infant brain image segmentation , 2015, NeuroImage.

[49]  Guido Gerig,et al.  Increased Extra-axial Cerebrospinal Fluid in High-Risk Infants Who Later Develop Autism , 2017, Biological Psychiatry.

[50]  J. Constantino,et al.  Validation of a Brief Quantitative Measure of Autistic Traits: Comparison of the Social Responsiveness Scale with the Autism Diagnostic Interview-Revised , 2003, Journal of autism and developmental disorders.

[51]  J. Sijbers,et al.  More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging , 2011, Magnetic resonance in medicine.

[52]  G. Dehaene-Lambertz,et al.  The Infancy of the Human Brain , 2015, Neuron.

[53]  Guido Gerig,et al.  Splenium development and early spoken language in human infants. , 2017, Developmental science.

[54]  Tomoki Arichi,et al.  Specialization and integration of functional thalamocortical connectivity in the human infant , 2015, Proceedings of the National Academy of Sciences.

[55]  A. Snyder,et al.  Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. , 1998, Radiology.

[56]  K. Abel,et al.  Psychometrics and validation of a brief rating measure of parent-infant interaction , 2017 .

[57]  H. Kraemer,et al.  How can we learn about developmental processes from cross-sectional studies, or can we? , 2000, The American journal of psychiatry.

[58]  Rebecca C. Knickmeyer,et al.  A Structural MRI Study of Human Brain Development from Birth to 2 Years , 2008, The Journal of Neuroscience.

[59]  Yong He,et al.  Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain , 2016, Cerebral cortex.

[60]  Abraham Z. Snyder,et al.  Real-time motion analytics during brain MRI improve data quality and reduce costs , 2017, NeuroImage.

[61]  Beate Sodian,et al.  Infants' joint attention skills predict toddlers' emerging mental state language. , 2011, Developmental psychology.

[62]  Martin Styner,et al.  Associations between white matter microstructure and infants' working memory , 2013, NeuroImage.

[63]  Guido Gerig,et al.  Walking, Gross Motor Development, and Brain Functional Connectivity in Infants and Toddlers , 2017, Cerebral cortex.

[64]  M. Rothbart,et al.  Measurement of fine-grained aspects of toddler temperament: the early childhood behavior questionnaire. , 2006, Infant behavior & development.

[65]  M. Styner,et al.  Longitudinal development of cortical and subcortical gray matter from birth to 2 years. , 2012, Cerebral cortex.

[66]  Alan C. Evans,et al.  The NIH MRI study of normal brain development , 2006, NeuroImage.

[67]  E. Bates,et al.  The Emergence of Symbols: Cognition and Communication in Infancy , 2014 .

[68]  Wei Gao,et al.  Functional Network Development During the First Year: Relative Sequence and Socioeconomic Correlations. , 2015, Cerebral cortex.

[69]  P. Matthews,et al.  Multimodal population brain imaging in the UK Biobank prospective epidemiological study , 2016, Nature Neuroscience.

[70]  Steen Moeller,et al.  The Human Connectome Project's neuroimaging approach , 2016, Nature Neuroscience.

[71]  Louis J. Moses,et al.  The Children's Social Understanding Scale , 2015 .

[72]  John H. Gilmore,et al.  3 Tesla magnetic resonance imaging of the brain in newborns , 2004, Psychiatry Research: Neuroimaging.

[73]  Tyrone D. Cannon,et al.  Reciprocal social behavior in youths with psychotic illness and those at clinical high risk , 2013, Development and Psychopathology.

[74]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[75]  G. Dawson,et al.  The Vineland Adaptive Behavior Scales: Supplementary Norms for Individuals with Autism , 1998, Journal of autism and developmental disorders.

[76]  A. Snyder,et al.  Longitudinal analysis of neural network development in preterm infants. , 2010, Cerebral cortex.

[77]  Guido Gerig,et al.  Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data , 2015, Developmental Cognitive Neuroscience.

[78]  Damien A. Fair,et al.  Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature , 2017, NeuroImage.

[79]  John H. Gilmore,et al.  Correction: Family Poverty Affects the Rate of Human Infant Brain Growth , 2015, PloS one.

[80]  Vince D. Calhoun,et al.  Functional connectivity in the developing brain: A longitudinal study from 4 to 9months of age , 2014, NeuroImage.

[81]  Brenna Hassinger-Das,et al.  Domain-general mediators of the relation between kindergarten number sense and first-grade mathematics achievement. , 2014, Journal of experimental child psychology.

[82]  J. Gilmore,et al.  Infant Brain Atlases from Neonates to 1- and 2-Year-Olds , 2011, PloS one.

[83]  Brian B. Avants,et al.  N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.

[84]  Guido Gerig,et al.  Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism , 2017, Molecular Autism.

[85]  M. Sera,et al.  Executive function and magnitude skills in preschool children. , 2016, Journal of experimental child psychology.

[86]  Walter Schneider,et al.  High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications. , 2012, Neurosurgery.

[87]  Dinggang Shen,et al.  Multi-Tissue Decomposition of Diffusion MRI Signals via $\ell _{0}$ Sparse-Group Estimation , 2016, IEEE Transactions on Image Processing.

[88]  C. Lebel,et al.  Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood , 2011, The Journal of Neuroscience.

[89]  Roger Bakeman,et al.  Toddlers' joint engagement experience facilitates preschoolers' acquisition of theory of mind. , 2008, Developmental science.

[90]  Martin Styner,et al.  Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline , 2014, Front. Neuroinform..

[91]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[92]  Brain Development Cooperative Group,et al.  The NIH MRI study of normal brain development (Objective-2): Newborns, infants, toddlers, and preschoolers , 2007, NeuroImage.

[93]  Yong He,et al.  Developmental Connectomics from Infancy through Early Childhood , 2017, Trends in Neurosciences.

[94]  J. Constantino,et al.  Autistic Traits in the General Population , 2003 .

[95]  Catherine Schaefer,et al.  Executive Function in Preschool Children: Test–Retest Reliability , 2011, Journal of cognition and development : official journal of the Cognitive Development Society.

[96]  D. Norman,et al.  Normal maturation of the neonatal and infant brain: MR imaging at 1.5 T. , 1988, Radiology.

[97]  Dinggang Shen,et al.  SPHERE: SPherical Harmonic Elastic REgistration of HARDI data , 2011, NeuroImage.

[98]  Alan C. Evans,et al.  Early brain development in infants at high risk for autism spectrum disorder , 2017, Nature.

[99]  R. Kikinis,et al.  Quantitative magnetic resonance imaging of brain development in premature and mature newborns , 1998, Annals of neurology.

[100]  M. Gunnar,et al.  Beyond stimulus deprivation: iron deficiency and cognitive deficits in postinstitutionalized children. , 2014, Child development.

[101]  Thomas H. Ollendick,et al.  COMPARING PERSONAL TRAJECTORIES AND DRAWING CAUSAL INFERENCES FROM LONGITUDINAL DATA , 2008 .

[102]  J. Mazziotta,et al.  Positron emission tomography study of human brain functional development , 1987, Annals of neurology.

[103]  J. Constantino,et al.  Quantitative assessment of autistic symptomatology in preschoolers , 2006, Autism : the international journal of research and practice.

[104]  Joseph V. Hajnal,et al.  Development of cortical microstructure in the preterm human brain , 2013, Proceedings of the National Academy of Sciences.

[105]  Timothy O. Laumann,et al.  Methods to detect, characterize, and remove motion artifact in resting state fMRI , 2014, NeuroImage.

[106]  Abraham Z. Snyder,et al.  Corrigendum to “Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion” [NeuroImage 59 (3) (2012) 2142–2154] , 2012, NeuroImage.

[107]  J. Piven,et al.  Magnetic resonance imaging and head circumference study of brain size in autism: birth through age 2 years. , 2005, Archives of general psychiatry.

[108]  P. Kuhl,et al.  Foreign-language experience in infancy: Effects of short-term exposure and social interaction on phonetic learning , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[109]  Guido Gerig,et al.  Frontolimbic neural circuitry at 6 months predicts individual differences in joint attention at 9 months. , 2013, Developmental science.

[110]  Bertrand Thirion,et al.  Exploring the Early Organization and Maturation of Linguistic Pathways in the Human Infant Brain. , 2016, Cerebral cortex.

[111]  J. Bruner,et al.  The capacity for joint visual attention in the infant , 1975, Nature.

[112]  Hong Wang,et al.  Abnormal Cerebral Structure Is Present at Term in Premature Infants , 2005, Pediatrics.

[113]  Alan C. Evans,et al.  Intellectual ability and cortical development in children and adolescents , 2006, Nature.

[114]  Martin Styner,et al.  DTIPrep: quality control of diffusion-weighted images , 2014, Front. Neuroinform..

[115]  Stephen R. Dager,et al.  Journal of Neuroscience Methods Computational Neuroscience Adaptive Prior Probability and Spatial Temporal Intensity Change Estimation for Segmentation of the One-year-old Human Brain the Results of Igm-em Show Good Performance in Temporal and Prefrontal Lobe Areas , 2022 .

[116]  Todd D. Little,et al.  The Infant–Toddler Social and Emotional Assessment (ITSEA): Factor Structure, Reliability, and Validity , 2003, Journal of abnormal child psychology.

[117]  O. Pascalis,et al.  Is Face Processing Species-Specific During the First Year of Life? , 2002, Science.

[118]  J. Townsend,et al.  Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers. , 2000, Radiology.

[119]  Alan C. Evans,et al.  Brain development during childhood and adolescence: a longitudinal MRI study , 1999, Nature Neuroscience.

[120]  Virginia A. Marchman,et al.  MacArthur-Bates Communicative Development Inventories , 2006 .

[121]  M. Phelps,et al.  Maturational changes in cerebral function in infants determined by 18FDG positron emission tomography. , 1986, Science.

[122]  Guido Gerig,et al.  Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age , 2017, Science Translational Medicine.

[123]  Birgit A. Fink,et al.  Executive functioning deficits in preschool children with Fetal Alcohol Spectrum Disorders , 2015, Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence.

[124]  John H. Gilmore,et al.  Functional Connectivity of the Infant Human Brain , 2016, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[125]  Yaozong Gao,et al.  LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images , 2015, NeuroImage.

[126]  Martin Styner,et al.  Implications of newborn amygdala connectivity for fear and cognitive development at 6-months-of-age , 2015, Developmental Cognitive Neuroscience.

[127]  R. Kahn,et al.  The Neonatal Connectome During Preterm Brain Development , 2014, Cerebral cortex.

[128]  J K Smith,et al.  Functional Connectivity MR Imaging Reveals Cortical Functional Connectivity in the Developing Brain , 2008, American Journal of Neuroradiology.

[129]  François Lazeyras,et al.  Magnetic Resonance in Preterm and Term Newborns: 1H-Spectroscopy in Developing Human Brain , 1991, Pediatric Research.

[130]  Thomas E. Nichols,et al.  Best practices in data analysis and sharing in neuroimaging using MRI , 2017, Nature Neuroscience.

[131]  Wei Gao,et al.  Longitudinal Study of the Emerging Functional Connectivity Asymmetry of Primary Language Regions during Infancy , 2016, The Journal of Neuroscience.

[132]  Michael W. Spratling,et al.  Gamma oscillations and object processing in the infant brain. , 2000, Science.

[133]  Guido Gerig,et al.  The Emergence of Network Inefficiencies in Infants With Autism Spectrum Disorder , 2017, Biological Psychiatry.

[134]  Rachel J. Steiner,et al.  Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y , 2016, Proceedings of the National Academy of Sciences.

[135]  Yaozong Gao,et al.  LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images , 2014, NeuroImage.