Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study

The default-mode network (DMN) is a set of functionally connected regions that play crucial roles in internal cognitive processing. Previous resting-state fMRI studies have demonstrated that the intrinsic functional organization of the DMN undergoes remarkable reconfigurations during childhood and adolescence. However, these studies have mainly focused on cross-sectional designs with small sample sizes, limiting the consistency and interpretations of the findings. Here, we used a large sample of longitudinal resting-state fMRI data comprising 305 typically developing children (6-12 years of age at baseline, 491 scans in total) and graph theoretical approaches to delineate the developmental trajectories of the functional architecture of the DMN. For each child, the DMN was constructed according to a prior parcellation with 32 brain nodes. We showed that the overall connectivity increased in strength from childhood to adolescence and became spatially similar to that in the young adult group (N=61, 18-28 years of age). These increases were primarily located in the midline structures. Global and local network efficiency in the DMN also increased with age, indicating an enhanced capability in parallel information communication within the brain system. Based on the divergent developmental rates of nodal centrality, we identified three subclusters within the DMN, with the fastest rates in the cluster mainly comprising the anterior medial prefrontal cortex and posterior cingulate cortex. Together, our findings highlight the developmental patterns of the functional architecture in the DMN from childhood to adolescence, which has implications for the understanding of network mechanisms underlying the cognitive development of individuals.

[1]  P. Skudlarski,et al.  Brain Connectivity Related to Working Memory Performance , 2006, The Journal of Neuroscience.

[2]  G. Chételat,et al.  Age effect on the default mode network, inner thoughts, and cognitive abilities , 2013, Neurobiology of Aging.

[3]  C. Kelly,et al.  Differential Development of Human Brain White Matter Tracts , 2011, PloS one.

[4]  K. Kaski,et al.  Intensity and coherence of motifs in weighted complex networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Jeffrey D. Rudie,et al.  Development of the Default Mode and Central Executive Networks across early adolescence: A longitudinal study , 2014, Developmental Cognitive Neuroscience.

[6]  Alan C. Evans,et al.  Unbiased age-specific structural brain atlases for Chinese pediatric population , 2019, NeuroImage.

[7]  Alan C. Evans,et al.  Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. , 2009, Cerebral cortex.

[8]  M. Raichle The brain's default mode network. , 2015, Annual review of neuroscience.

[9]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[10]  Arthur F. Kramer,et al.  Behavioural Brain Research Age-related Differences in Cortical Recruitment and Suppression: Implications for Cognitive Performance , 2022 .

[11]  Mark A. Elliott,et al.  Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth , 2012, NeuroImage.

[12]  S. Carey,et al.  The development of intent-based moral judgment , 2013, Cognition.

[13]  A longitudinal study of the health status of a community of religious sisters: addressing the advantages, challenges, and limitations. , 2015, Research in gerontological nursing.

[14]  Wen-Ming Luh,et al.  Multi-echo fMRI replication sample of autobiographical memory, prospection and theory of mind reasoning tasks , 2016, Scientific Data.

[15]  Linear mixed model better than repeated measures analysis , 2019, European journal of ophthalmology.

[16]  Jonas Persson,et al.  Longitudinal assessment of default-mode brain function in aging , 2014, Neurobiology of Aging.

[17]  Yong He,et al.  GRETNA: a graph theoretical network analysis toolbox for imaging connectomics , 2015, Front. Hum. Neurosci..

[18]  Iroise Dumontheil,et al.  Online usage of theory of mind continues to develop in late adolescence. , 2010, Developmental science.

[19]  S. Petersen,et al.  Concepts and principles in the analysis of brain networks , 2011, Annals of the New York Academy of Sciences.

[20]  M. Hodes,et al.  A review of adolescent autobiographical memory and the implications for assessment of unaccompanied minors’ refugee determinations , 2018, Clinical child psychology and psychiatry.

[21]  G. Varoquaux,et al.  Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants , 2018, Proceedings of the National Academy of Sciences.

[22]  Jonathan D Clayden,et al.  Normative development of white matter tracts: similarities and differences in relation to age, gender, and intelligence. , 2012, Cerebral cortex.

[23]  A. Bhana Middle childhood and pre-adolescence , 2010 .

[24]  Angela D. Evans,et al.  The role of theory of mind and social skills in predicting children's cheating. , 2019, Journal of experimental child psychology.

[25]  R. Wood,et al.  Adolescents and androgens, receptors and rewards , 2008, Hormones and Behavior.

[26]  R. Nathan Spreng,et al.  Patterns of Brain Activity Supporting Autobiographical Memory, Prospection, and Theory of Mind, and Their Relationship to the Default Mode Network , 2010, Journal of Cognitive Neuroscience.

[27]  Jonathan D. Power,et al.  Functional Brain Networks Develop from a “Local to Distributed” Organization , 2009, PLoS Comput. Biol..

[28]  S. Petersen,et al.  The maturing architecture of the brain's default network , 2008, Proceedings of the National Academy of Sciences.

[29]  E. Leibenluft,et al.  The social re-orientation of adolescence: a neuroscience perspective on the process and its relation to psychopathology , 2005, Psychological Medicine.

[30]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

[31]  Yufeng Zang,et al.  DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging , 2016, Neuroinformatics.

[32]  Alan C. Evans,et al.  Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence , 2013, PloS one.

[33]  R. Buckner,et al.  The brain’s default network: updated anatomy, physiology and evolving insights , 2019, Nature Reviews Neuroscience.

[34]  Christos Davatzikos,et al.  Individual Variation in Functional Topography of Association Networks in Youth , 2020, Neuron.

[35]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[36]  M. Corbetta,et al.  Common Blood Flow Changes across Visual Tasks: II. Decreases in Cerebral Cortex , 1997, Journal of Cognitive Neuroscience.

[37]  G. Shulman,et al.  Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[38]  Yufeng Zang,et al.  Functional brain hubs and their test–retest reliability: A multiband resting-state functional MRI study , 2013, NeuroImage.

[39]  M. Greicius,et al.  Resting-state functional connectivity reflects structural connectivity in the default mode network. , 2009, Cerebral cortex.

[40]  Timothy D. Wilson,et al.  Prospection: Experiencing the Future , 2007, Science.

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

[42]  Yong He,et al.  Intrinsic Brain Hub Connectivity Underlies Individual Differences in Spatial Working Memory , 2016, Cerebral cortex.

[43]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[44]  Simon B. Eickhoff,et al.  An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data , 2013, NeuroImage.

[45]  Rebecca Saxe,et al.  Contributions of episodic retrieval and mentalizing to autobiographical thought: Evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses , 2014, NeuroImage.

[46]  Rodrigo M. Braga,et al.  Parallel Interdigitated Distributed Networks within the Individual Estimated by Intrinsic Functional Connectivity , 2017, Neuron.

[47]  K. Davis,et al.  Cognitive and default‐mode resting state networks: Do male and female brains “rest” differently? , 2010, Human brain mapping.

[48]  Frederik Barkhof,et al.  Resting‐state networks in awake five‐ to eight‐year old children , 2012, Human brain mapping.

[49]  P. Tu,et al.  Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis , 2013, Neurobiology of Aging.

[50]  Evan M. Gordon,et al.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain , 2015, Neuron.

[51]  Yong He,et al.  Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain , 2013, Proceedings of the National Academy of Sciences.

[52]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[53]  Yong He,et al.  BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics , 2013, PloS one.

[54]  K. Hwang,et al.  The development of hub architecture in the human functional brain network. , 2013, Cerebral cortex.

[55]  J. Callicott,et al.  Age-related alterations in default mode network: Impact on working memory performance , 2010, Neurobiology of Aging.

[56]  Rory T. Devine,et al.  Silent films and strange stories: theory of mind, gender, and social experiences in middle childhood. , 2013, Child development.

[57]  A. Newman,et al.  An Overview of the Design, Implementation, and Analyses of Longitudinal Studies on Aging , 2010, Journal of the American Geriatrics Society.

[58]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[59]  R. Nathan Spreng,et al.  The Common Neural Basis of Autobiographical Memory, Prospection, Navigation, Theory of Mind, and the Default Mode: A Quantitative Meta-analysis , 2009, Journal of Cognitive Neuroscience.

[60]  J. Whitwell,et al.  Alzheimer's disease neuroimaging , 2018, Current opinion in neurology.

[61]  B. J. Casey,et al.  Structural and functional brain development and its relation to cognitive development , 2000, Biological Psychology.

[62]  Lauren E. Mak,et al.  The Default Mode Network in Healthy Individuals: A Systematic Review and Meta-Analysis , 2017, Brain Connect..

[63]  Yong He,et al.  Individual differences and time-varying features of modular brain architecture , 2017, NeuroImage.

[64]  P. Rochat The self as phenotype , 2011, Consciousness and Cognition.

[65]  Angela D. Friederici,et al.  The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5 , 2015, Brain Imaging and Behavior.

[66]  Edward T. Bullmore,et al.  Efficiency and Cost of Economical Brain Functional Networks , 2007, PLoS Comput. Biol..

[67]  Malika Charrad,et al.  NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set , 2014 .

[68]  L. Rohde,et al.  Default Mode Network Maturation and Environmental Adversities During Childhood , 2018, Chronic stress.

[69]  P. McGuire,et al.  Age effects on the default mode and control networks in typically developing children. , 2014, Journal of psychiatric research.

[70]  Karl J. Friston,et al.  Movement‐Related effects in fMRI time‐series , 1996, Magnetic resonance in medicine.

[71]  S. Blakemore,et al.  The role of puberty in the developing adolescent brain , 2010, Human brain mapping.

[72]  S. Blakemore The social brain in adolescence , 2008, Nature Reviews Neuroscience.

[73]  Randy L. Buckner,et al.  Parallel distributed networks resolved at high resolution reveal close juxtaposition of distinct regions , 2018, bioRxiv.

[74]  Mert R. Sabuncu,et al.  Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models , 2013, NeuroImage.

[75]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[76]  Michael D. Greicius,et al.  Development of functional and structural connectivity within the default mode network in young children , 2010, NeuroImage.

[77]  L. Westlye,et al.  Brain maturation in adolescence and young adulthood: regional age-related changes in cortical thickness and white matter volume and microstructure. , 2010, Cerebral cortex.

[78]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[79]  R. Buckner,et al.  Functional-Anatomic Fractionation of the Brain's Default Network , 2010, Neuron.

[80]  R. Cameron Craddock,et al.  A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics , 2013, NeuroImage.

[81]  H. Akaike A new look at the statistical model identification , 1974 .