1
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Tripathy K, Fogarty M, Svoboda AM, Schroeder ML, Rafferty SM, Richter EJ, Tracy C, Mansfield PK, Booth M, Fishell AK, Sherafati A, Markow ZE, Wheelock MD, Arbeláez AM, Schlaggar BL, Smyser CD, Eggebrecht AT, Culver JP. Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography. Hum Brain Mapp 2024; 45:e26684. [PMID: 38703090 PMCID: PMC11069306 DOI: 10.1002/hbm.26684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 03/27/2024] [Accepted: 04/03/2024] [Indexed: 05/06/2024] Open
Abstract
Human studies of early brain development have been limited by extant neuroimaging methods. MRI scanners present logistical challenges for imaging young children, while alternative modalities like functional near-infrared spectroscopy have traditionally been limited by image quality due to sparse sampling. In addition, conventional tasks for brain mapping elicit low task engagement, high head motion, and considerable participant attrition in pediatric populations. As a result, typical and atypical developmental trajectories of processes such as language acquisition remain understudied during sensitive periods over the first years of life. We evaluate high-density diffuse optical tomography (HD-DOT) imaging combined with movie stimuli for high resolution optical neuroimaging in awake children ranging from 1 to 7 years of age. We built an HD-DOT system with design features geared towards enhancing both image quality and child comfort. Furthermore, we characterized a library of animated movie clips as a stimulus set for brain mapping and we optimized associated data analysis pipelines. Together, these tools could map cortical responses to movies and contained features such as speech in both adults and awake young children. This study lays the groundwork for future research to investigate response variability in larger pediatric samples and atypical trajectories of early brain development in clinical populations.
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Affiliation(s)
- Kalyan Tripathy
- Division of Biological and Biomedical SciencesWashington University in St. LouisSt. LouisMissouriUSA
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Western Psychiatric HospitalUniversity of Pittsburgh Medical CenterPittsburghPennsylvaniaUSA
| | - Morgan Fogarty
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Imaging Science ProgramWashington University in St. LouisSt. LouisMissouriUSA
| | - Alexandra M. Svoboda
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Mariel L. Schroeder
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Sean M. Rafferty
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Edward J. Richter
- Department of Electrical and Systems EngineeringWashington University in St. LouisSt. LouisMissouriUSA
| | - Christopher Tracy
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Patricia K. Mansfield
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Madison Booth
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Andrew K. Fishell
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Arefeh Sherafati
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of PhysicsWashington University in St. LouisSt. LouisMissouriUSA
| | - Zachary E. Markow
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of Biomedical EngineeringWashington University in St. LouisSt. LouisMissouriUSA
| | - Muriah D. Wheelock
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Ana María Arbeláez
- Department of PediatricsWashington University School of MedicineSt. LouisMissouriUSA
| | - Bradley L. Schlaggar
- Kennedy Krieger InstituteBaltimoreMarylandUSA
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- Department of PediatricsJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Christopher D. Smyser
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of PediatricsWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Adam T. Eggebrecht
- Division of Biological and Biomedical SciencesWashington University in St. LouisSt. LouisMissouriUSA
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Imaging Science ProgramWashington University in St. LouisSt. LouisMissouriUSA
- Department of Electrical and Systems EngineeringWashington University in St. LouisSt. LouisMissouriUSA
- Department of PhysicsWashington University in St. LouisSt. LouisMissouriUSA
- Department of Biomedical EngineeringWashington University in St. LouisSt. LouisMissouriUSA
| | - Joseph P. Culver
- Mallinckrodt Institute of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Imaging Science ProgramWashington University in St. LouisSt. LouisMissouriUSA
- Department of PhysicsWashington University in St. LouisSt. LouisMissouriUSA
- Department of Biomedical EngineeringWashington University in St. LouisSt. LouisMissouriUSA
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2
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Luo AC, Sydnor VJ, Pines A, Larsen B, Alexander-Bloch AF, Cieslak M, Covitz S, Chen AA, Esper NB, Feczko E, Franco AR, Gur RE, Gur RC, Houghton A, Hu F, Keller AS, Kiar G, Mehta K, Salum GA, Tapera T, Xu T, Zhao C, Salo T, Fair DA, Shinohara RT, Milham MP, Satterthwaite TD. Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy. Nat Commun 2024; 15:3511. [PMID: 38664387 PMCID: PMC11045762 DOI: 10.1038/s41467-024-47748-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024] Open
Abstract
Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.
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Affiliation(s)
- Audrey C Luo
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Andrew A Chen
- Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA
| | | | - Eric Feczko
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Alexandre R Franco
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, 10962, USA
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Fengling Hu
- Penn Statistics in Imaging and Visualization Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Gregory Kiar
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Kahini Mehta
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Giovanni A Salum
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Tinashe Tapera
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, 02115, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Taylor Salo
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, 55455, USA
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, 10022, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, 10962, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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3
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Hill AT, Bailey NW, Zomorrodi R, Hadas I, Kirkovski M, Das S, Lum JAG, Enticott PG. EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power. Hum Brain Mapp 2023; 44:6484-6498. [PMID: 37873867 PMCID: PMC10681660 DOI: 10.1002/hbm.26525] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/04/2023] [Accepted: 10/06/2023] [Indexed: 10/25/2023] Open
Abstract
Electroencephalographic (EEG) microstates can provide a unique window into the temporal dynamics of large-scale brain networks across brief (millisecond) timescales. Here, we analysed fundamental temporal features of microstates extracted from the broadband EEG signal in a large (N = 139) cohort of children spanning early-to-middle childhood (4-12 years of age). Linear regression models were used to examine if participants' age and biological sex could predict the temporal parameters GEV, duration, coverage, and occurrence, for five microstate classes (A-E) across both eyes-closed and eyes-open resting-state recordings. We further explored associations between these microstate parameters and posterior alpha power after removal of the 1/f-like aperiodic signal. The microstates obtained from our neurodevelopmental EEG recordings broadly replicated the four canonical microstate classes (A to D) frequently reported in adults, with the addition of the more recently established microstate class E. Biological sex served as a significant predictor in the regression models for four of the five microstate classes (A, C, D, and E). In addition, duration and occurrence for microstate E were both found to be positively associated with age for the eyes-open recordings, while the temporal parameters of microstates C and E both exhibited associations with alpha band spectral power. Together, these findings highlight the influence of age and sex on large-scale functional brain networks during early-to-middle childhood, extending understanding of neural dynamics across this important period for brain development.
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Affiliation(s)
- Aron T. Hill
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
| | - Neil W. Bailey
- Monarch Research InstituteMonarch Mental Health GroupSydneyAustralia
- School of Medicine and PsychologyThe Australian National UniversityCanberraAustralia
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental HealthUniversity of TorontoTorontoCanada
| | - Itay Hadas
- Department of Psychiatry, School of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Melissa Kirkovski
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Institute for Health and SportVictoria UniversityMelbourneAustralia
| | - Sushmit Das
- Azrieli Adult Neurodevelopmental CentreCentre for Addiction and Mental HealthTorontoCanada
| | - Jarrad A. G. Lum
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
| | - Peter G. Enticott
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityGeelongAustralia
- Department of Psychiatry, Central Clinical SchoolMonash UniversityMelbourneAustralia
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4
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Su WC, Colacot R, Ahmed N, Nguyen T, George T, Gandjbakhche A. The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review. Front Psychiatry 2023; 14:1210000. [PMID: 37779610 PMCID: PMC10536152 DOI: 10.3389/fpsyt.2023.1210000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/24/2023] [Indexed: 10/03/2023] Open
Abstract
Understanding the neurodevelopmental trajectories of infants and children is essential for the early identification of neurodevelopmental disorders, elucidating the neural mechanisms underlying the disorders, and predicting developmental outcomes. Functional Near-Infrared Spectroscopy (fNIRS) is an infant-friendly neuroimaging tool that enables the monitoring of cerebral hemodynamic responses from the neonatal period. Due to its advantages, fNIRS is a promising tool for studying neurodevelopmental trajectories. Although many researchers have used fNIRS to study neural development in infants/children and have reported important findings, there is a lack of synthesized evidence for using fNIRS to track neurodevelopmental trajectories in infants and children. The current systematic review summarized 84 original fNIRS studies and showed a general trend of age-related increase in network integration and segregation, interhemispheric connectivity, leftward asymmetry, and differences in phase oscillation during resting-state. Moreover, typically developing infants and children showed a developmental trend of more localized and differentiated activation when processing visual, auditory, and tactile information, suggesting more mature and specialized sensory networks. Later in life, children switched from recruiting bilateral auditory to a left-lateralized language circuit when processing social auditory and language information and showed increased prefrontal activation during executive functioning tasks. The developmental trajectories are different in children with developmental disorders, with infants at risk for autism spectrum disorder showing initial overconnectivity followed by underconnectivity during resting-state; and children with attention-deficit/hyperactivity disorders showing lower prefrontal cortex activation during executive functioning tasks compared to their typically developing peers throughout childhood. The current systematic review supports the use of fNIRS in tracking the neurodevelopmental trajectories in children. More longitudinal studies are needed to validate the neurodevelopmental trajectories and explore the use of these neurobiomarkers for the early identification of developmental disorders and in tracking the effects of interventions.
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Affiliation(s)
| | | | | | | | | | - Amir Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
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5
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Cotter DL, Campbell CE, Sukumaran K, McConnell R, Berhane K, Schwartz J, Hackman DA, Ahmadi H, Chen JC, Herting MM. Effects of ambient fine particulates, nitrogen dioxide, and ozone on maturation of functional brain networks across early adolescence. ENVIRONMENT INTERNATIONAL 2023; 177:108001. [PMID: 37307604 PMCID: PMC10353545 DOI: 10.1016/j.envint.2023.108001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 04/14/2023] [Accepted: 05/28/2023] [Indexed: 06/14/2023]
Abstract
BACKGROUND Air pollution is linked to neurodevelopmental delays, but its association with longitudinal changes in brain network development has yet to be investigated. We aimed to characterize the effect of PM2.5, O3, and NO2 exposure at ages 9-10 years on changes in functional connectivity (FC) over a 2-year follow-up period, with a focus on the salience (SN), frontoparietal (FPN), and default-mode (DMN) brain networks as well as the amygdala and hippocampus given their importance in emotional and cognitive functioning. METHODS A sample of children (N = 9,497; with 1-2 scans each for a total of 13,824 scans; 45.6% with two brain scans) from the Adolescent Brain Cognitive Development (ABCD) Study® were included. Annual averages of pollutant concentrations were assigned to the child's primary residential address using an ensemble-based exposure modeling approach. Resting-state functional MRI was collected on 3T MRI scanners. First, developmental linear mixed-effect models were performed to characterize typical FC development within our sample. Next, single- and multi-pollutant linear mixed-effect models were constructed to examine the association between exposure and intra-network, inter-network, and subcortical-to-network FC change over time, adjusting for sex, race/ethnicity, income, parental education, handedness, scanner type, and motion. RESULTS Developmental profiles of FC over the 2-year follow-up included intra-network integration within the DMN and FPN as well as inter-network integration between the SN-FPN; along with intra-network segregation in the SN as well as subcortical-to-network segregation more broadly. Higher PM2.5 exposure resulted in greater inter-network and subcortical-to-network FC over time. In contrast, higher O3 concentrations resulted in greater intra-network, but less subcortical-to-network FC over time. Lastly, higher NO2 exposure led to less inter-network and subcortical-to-network FC over the 2-year follow-up period. CONCLUSION Taken together, PM2.5, O3, and NO2 exposure in childhood relate to distinct changes in patterns of network maturation over time. This is the first study to show outdoor ambient air pollution during childhood is linked to longitudinal changes in brain network connectivity development.
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Affiliation(s)
- Devyn L Cotter
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Claire E Campbell
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kirthana Sukumaran
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rob McConnell
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kiros Berhane
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel A Hackman
- USC Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Hedyeh Ahmadi
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jiu-Chiuan Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Children's Hospital Los Angeles, Los Angeles, CA, USA.
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Sanders AFP, Harms MP, Kandala S, Marek S, Somerville LH, Bookheimer SY, Dapretto M, Thomas KM, Van Essen DC, Yacoub E, Barch DM. Age-related differences in resting-state functional connectivity from childhood to adolescence. Cereb Cortex 2023; 33:6928-6942. [PMID: 36724055 PMCID: PMC10233258 DOI: 10.1093/cercor/bhad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 01/06/2023] [Accepted: 01/07/2023] [Indexed: 02/02/2023] Open
Abstract
The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development.
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Affiliation(s)
- Ashley F P Sanders
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Michael P Harms
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St Louis, MO 63119, USA
| | - Leah H Somerville
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Kathleen M Thomas
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
- Department of Psychological and Brain Sciences, Washington University, St Louis, MO 63130, USA
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7
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Perdue MV, DeMayo MM, Bell TK, Boudes E, Bagshawe M, Harris AD, Lebel C. Changes in brain metabolite levels across childhood. Neuroimage 2023; 274:120087. [PMID: 37080345 DOI: 10.1016/j.neuroimage.2023.120087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/05/2023] [Accepted: 04/03/2023] [Indexed: 04/22/2023] Open
Abstract
Metabolites play important roles in brain development and their levels change rapidly in the prenatal period and during infancy. Metabolite levels are thought to stabilize during childhood, but the development of neurochemistry across early-middle childhood remains understudied. We examined the developmental changes of key metabolites (total N-acetylaspartate, tNAA; total choline, tCho; total creatine, tCr; glutamate+glutamine, Glx; and myo-inositol, mI) using short echo-time magnetic resonance spectroscopy (MRS) in the anterior cingulate cortex (ACC) and the left temporo-parietal cortex (LTP) using a mixed cross-sectional/longitudinal design in children aged 2-11 years (ACC: N=101 children, 112 observations; LTP: N=95 children, 318 observations). We found age-related effects for all metabolites. tNAA increased with age in both regions, while tCho decreased with age in both regions. tCr increased with age in the LTP only, and mI decreased with age in the ACC only. Glx did not show linear age effects in either region, but a follow-up analysis in only participants with ≥3 datapoints in the LTP revealed a quadratic effect of age following an inverted U-shape. These substantial changes in neurochemistry throughout childhood likely underlie various processes of structural and functional brain development.
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Affiliation(s)
- Meaghan V Perdue
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | - Marilena M DeMayo
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary; Mathison Centre for Mental Health Research and Education; Department of Psychiatry, University of Calgary
| | - Tiffany K Bell
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | | | - Mercedes Bagshawe
- Alberta Children's Hospital Research Institute; Werklund School of Education, University of Calgary
| | - Ashley D Harris
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary
| | - Catherine Lebel
- Department of Radiology, University of Calgary; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary.
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8
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Hong SB. Brain regional homogeneity and its association with age and intelligence in typically developing youth. Asian J Psychiatr 2023; 82:103497. [PMID: 36764248 DOI: 10.1016/j.ajp.2023.103497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/21/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023]
Abstract
Accelerated synaptic pruning and weakening of short-range functional connectivity are characteristic of adolescent brain development. Based on these structural microscopic and system-level functional changes, it was hypothesized that regional homogeneity (ReHo) may decrease with age in the developing brain, and a differential association between ReHo and cognitive performance was expected to depend on age. ReHo maps of typically developing participants were provided by the Attention-Deficit/Hyperactivity Disorder (ADHD)-200 Preprocessed repository. Intelligence quotient was evaluated using the Wechsler Intelligence Scale for Chinese Children-Revised and Wechsler Abbreviated Scale of Intelligence at Peking University and New York University, respectively. Correlations between ReHo and age were examined, along with the interaction effects of ReHo and age on intelligence quotient (IQ), in 121 typically developing youth aged 8-14 years. Of the 400 ROIs tested, ReHo in 105 brain regions was significantly correlated with age (p < 0.05, false discovery rate-corrected), among which 102 showed that ReHo decreased with age. In addition, ReHo in 18 brain regions was negatively correlated with age at Bonferroni-corrected thresholds (p < 0.05), and most associations were observed in the prefrontal cortex. The interaction analyses suggested that higher ReHo was associated with higher IQ in children, whereas this association was attenuated or reversed in adolescents (p < 0.05, uncorrected). ReHo decreased with age in the developing brain and was differentially associated with intelligence in children and adolescents.
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Affiliation(s)
- Soon-Beom Hong
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea; Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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9
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Amalric M, Cantlon JF. Entropy, complexity, and maturity in children’s neural responses to naturalistic video lessons. Cortex 2023; 163:14-25. [PMID: 37037065 DOI: 10.1016/j.cortex.2023.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 11/29/2022] [Accepted: 02/17/2023] [Indexed: 03/19/2023]
Abstract
Temporal characteristics of neural signals are often overlooked in traditional fMRI developmental studies but are critical to studying brain functions in ecologically valid settings. In the present study, we explore the temporal properties of children's neural responses during naturalistic mathematics and grammar tasks. To do so, we introduce a novel measure in developmental fMRI: neural entropy, which indicates temporal complexity of BOLD signals. We show that temporal patterns of neural activity have lower complexity and greater variability in children than in adults in the association cortex but not in the sensory-motor cortex. We also show that neural entropy is associated with both child-adult similarity in functional connectivity and neural synchrony, and that neural entropy increases with the size of functionally connected networks in the association cortex. In addition, neural entropy increases with functional maturity (i.e., child-adult neural synchrony) in content-specific regions. These exploratory findings suggest the hypothesis that neural entropy indexes the increasing breadth and diversity of neural processes available to children for analyzing mathematical information over development.
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Affiliation(s)
- Marie Amalric
- Carnegie Mellon University, Department of Psychology, CAOs Laboratory, USA.
| | - Jessica F Cantlon
- Carnegie Mellon University, Department of Psychology, CAOs Laboratory, USA
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10
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Manning KY, Long X, Watts D, Tomfohr-Madsen L, Giesbrecht GF, Lebel C. Prenatal Maternal Distress During the COVID-19 Pandemic and Associations With Infant Brain Connectivity. Biol Psychiatry 2022; 92:701-708. [PMID: 35871095 PMCID: PMC9110020 DOI: 10.1016/j.biopsych.2022.05.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 04/25/2022] [Accepted: 05/09/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND The COVID-19 pandemic has caused substantially elevated distress in pregnant individuals, which has the potential to affect the developing infant brain. Our main objective was to understand how prenatal distress was related to infant brain structure and function and whether social support moderated the associations. METHODS The Pregnancy during the COVID-19 Pandemic (PdP) cohort study collected Patient-Reported Outcomes Measurement Information System Anxiety scale, Edinburgh Postnatal Depression Scale, and Social Support Effectiveness Questionnaire data from a population-based sample of pregnant individuals living in Canada (N = 8602). For a subsample of participants, their infants (n = 75) underwent magnetic resonance imaging at 3 months of age to examine whether prenatal maternal distress was associated with infant brain architecture, including the role of social support as a potential protective factor. RESULTS Overall, 33.4% of participants demonstrated clinically elevated depression symptoms and 47.1% of participants demonstrated clinically elevated anxiety symptoms. We identified lower social support as a significant predictor of clinically elevated prenatal maternal distress (t8598 = -22.3, p < .001). Fifty-eight diffusion image datasets (20 female/38 male, 92 ± 14 days old) and 41 functional datasets (13 female/28 male, 92 ± 14 days old) were included in our analysis after removal of poor-quality images and infants without postpartum maternal distress scores. We found significant relationships between prenatal maternal distress and infant amygdala-prefrontal microstructural and functional connectivity measures, and we demonstrate for the first time that social support moderates these relationships. CONCLUSIONS Our findings suggest a potentially long-lasting impact of the COVID-19 pandemic on children and show that social support acts as a possible mediator not just for pregnant individuals but also developing infants. These findings provide timely evidence to inform clinical practice and policy surrounding the care of pregnant individuals and highlight the importance of social support.
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Affiliation(s)
- Kathryn Y Manning
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Xiangyu Long
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Dana Watts
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Lianne Tomfohr-Madsen
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada; Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Department of Educational and Counselling Psychology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Gerald F Giesbrecht
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada; Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.
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11
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Bagdasarov A, Roberts K, Bréchet L, Brunet D, Michel CM, Gaffrey MS. Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects. Dev Cogn Neurosci 2022; 57:101134. [PMID: 35863172 PMCID: PMC9301511 DOI: 10.1016/j.dcn.2022.101134] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/13/2022] [Accepted: 07/08/2022] [Indexed: 11/22/2022] Open
Abstract
The ultrafast spatiotemporal dynamics of large-scale neural networks can be examined using resting-state electroencephalography (EEG) microstates, representing transient periods of synchronized neural activity that evolve dynamically over time. In adults, four canonical microstates have been shown to explain most topographic variance in resting-state EEG. Their temporal structures are age-, sex- and state-dependent, and are susceptible to pathological brain states. However, no studies have assessed the spatial and temporal properties of EEG microstates exclusively during early childhood, a critical period of rapid brain development. Here we sought to investigate EEG microstates recorded with high-density EEG in a large sample of 103, 4-8-year-old children. Using data-driven k-means cluster analysis, we show that the four canonical microstates reported in adult populations already exist in early childhood. Using multiple linear regressions, we demonstrate that the temporal dynamics of two microstates are associated with age and sex. Source localization suggests that attention- and cognitive control-related networks govern the topographies of the age- and sex-dependent microstates. These novel findings provide unique insights into functional brain development in children captured with EEG microstates.
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Affiliation(s)
- Armen Bagdasarov
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC 27708, USA.
| | - Kenneth Roberts
- Duke Institute for Brain Sciences, Duke University, 308 Research Drive, Durham, NC, USA
| | - Lucie Bréchet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Denis Brunet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland; Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, 1015 Lausanne Switzerland
| | - Christoph M Michel
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland; Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, 1015 Lausanne Switzerland
| | - Michael S Gaffrey
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC 27708, USA
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12
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Rosberg A, Tuulari JJ, Kumpulainen V, Lukkarinen M, Pulli EP, Silver E, Copeland A, Saukko E, Saunavaara J, Lewis JD, Karlsson L, Karlsson H, Merisaari H. Test-retest reliability of diffusion tensor imaging scalars in 5-year-olds. Hum Brain Mapp 2022; 43:4984-4994. [PMID: 36098477 PMCID: PMC9582361 DOI: 10.1002/hbm.26064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 08/08/2022] [Accepted: 08/21/2022] [Indexed: 11/22/2022] Open
Abstract
Diffusion tensor imaging (DTI) has provided great insights into the microstructural features of the developing brain. However, DTI images are prone to several artifacts and the reliability of DTI scalars is of paramount importance for interpreting and generalizing the findings of DTI studies, especially in the younger population. In this study, we investigated the intrascan test–retest repeatability of four DTI scalars: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in 5‐year‐old children (N = 67) with two different data preprocessing approaches: a volume censoring pipeline and an outlier replacement pipeline. We applied a region of interest (ROI) and a voxelwise analysis after careful quality control, tensor fitting and tract‐based spatial statistics. The data had three subsets and each subset included 31, 32, or 33 directions thus a total of 96 unique uniformly distributed diffusion encoding directions per subject. The repeatability of DTI scalars was evaluated with intraclass correlation coefficient (ICC(3,1)) and the variability between test and retest subsets. The results of both pipelines yielded good to excellent (ICC(3,1) > 0.75) reliability for most of the ROIs and an overall low variability (<10%). In the voxelwise analysis, FA and RD had higher ICC(3,1) values compared to AD and MD and the variability remained low (<12%) across all scalars. Our results suggest high intrascan repeatability in pediatric DTI and lend confidence to the use of the data in future cross‐sectional and longitudinal studies.
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Affiliation(s)
- Aylin Rosberg
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Department of Radiology, Turku University Hospital, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Minna Lukkarinen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
| | - Elmo P Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital and University of Turku, Turku, Finland
| | - John D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland.,Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Psychiatry, Turku University Hospital and University of Turku, Turku, Finland.,Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Centre, Department of Clinical Medicine, University of Turku, Turku, Finland.,Department of Radiology, Turku University Hospital, Turku, Finland
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13
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Manning KY, Reynolds JE, Long X, Llera A, Dewey D, Lebel C. Multimodal brain features at 3 years of age and their relationship with pre-reading measures 1 year later. Front Hum Neurosci 2022; 16:965602. [PMID: 36072890 PMCID: PMC9441575 DOI: 10.3389/fnhum.2022.965602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
Pre-reading language skills develop rapidly in early childhood and are related to brain structure and functional architecture in young children prior to formal education. However, the early neurobiological development that supports these skills is not well understood. Here we acquired anatomical, diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) from 35 children at 3.5 years of age. Children were assessed for pre-reading abilities using the NEPSY-II subtests 1 year later (4.5 years). We applied a data-driven linked independent component analysis (ICA) to explore the shared co-variation of gray and white matter measures. Two sources of structural variation at 3.5 years of age demonstrated relationships with Speeded Naming scores at 4.5 years of age. The first imaging component involved volumetric variability in reading-related cortical regions alongside microstructural features of the superior longitudinal fasciculus (SLF). The second component was dominated by cortical volumetric variations within the cerebellum and visual association area. In a subset of children with rs-fMRI data, we evaluated the inter-network functional connectivity of the left-lateralized fronto-parietal language network (FPL) and its relationship with pre-reading measures. Higher functional connectivity between the FPL and the default mode and visual networks at 3.5 years significantly predicted better Phonological Processing scores at 4.5 years. Together, these results suggest that the integration of functional networks, as well as the co-development of white and gray matter brain structures in early childhood, support the emergence of pre-reading measures in preschool children.
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Affiliation(s)
- Kathryn Y. Manning
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- *Correspondence: Kathryn Y. Manning,
| | - Jess E. Reynolds
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Telethon Kids Institute, The University of Western Australia, Perth, WA, Australia
| | - Xiangyu Long
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Alberto Llera
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Nijmegen, Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Deborah Dewey
- Alberta Children’s Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
- Community Health Sciences, University of Calgary, Calgary, AB, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children’s Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
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14
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Zhao X, Zhu S, Cao Y, Cheng P, Lin Y, Sun Z, Li Y, Jiang W, Du Y. Regional homogeneity of adolescents with high-functioning autism spectrum disorder and its association with symptom severity. Brain Behav 2022; 12:e2693. [PMID: 35816591 PMCID: PMC9392530 DOI: 10.1002/brb3.2693] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 05/13/2022] [Accepted: 06/23/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND AND PURPOSE Previous studies have revealed abnormal regional homogeneity (ReHo) in individuals with autism spectrum disorder (ASD); however, there is little consistency across the findings within these studies, partly due to small sample size and great heterogeneity among participants between studies. Additionally, few studies have explored the association between ReHo aberrance and clinical symptoms in individuals with ASD. METHODS Forty-eight adolescents with high-functioning ASD and 63 group-matched typically developing (TD) controls received functional magnetic resonance imaging at rest. Group-level analysis was performed to detect differences in ReHo between ASD and TD. Evaluation of symptom severity in individuals with ASD was based on the Autism Behavior Checklist (ABC). Voxel-wise correlation analysis was undergone to examine the correlations between the symptom severity and ReHo map in individuals with ASD within brain areas with ReHo abnormalities. RESULTS Compared with the TD controls, individuals with ASD exhibited increased ReHo in the bilateral anterior cingulate cortex, left caudate, right posterior cerebellum (cerebellar tonsil), and bilateral brainstem and decreased ReHo in the left precentral gyrus, left inferior parietal lobule, bilateral postcentral gyrus, and right anterior cerebellum (culmen). The correlation analysis indicated that the ReHo value in the brainstem was negatively associated with the ABC total scores and the scores of Relating factor, respectively. CONCLUSIONS Our findings indicated that widespread ReHo abnormalities occurred in ASD, shedding light on the underlying neurobiology of pathogenesis and symptomatology of ASD.
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Affiliation(s)
- Xiaoxin Zhao
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuyi Zhu
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Cao
- Department of Psychiatry, Suzhou Guangji Hospital, Suzhou, China
| | - Peipei Cheng
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuxiong Lin
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhixin Sun
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenqing Jiang
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yasong Du
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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15
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Tarchi L, Damiani S, Fantoni T, Pisano T, Castellini G, Politi P, Ricca V. Centrality and interhemispheric coordination are related to different clinical/behavioral factors in attention deficit/hyperactivity disorder: a resting-state fMRI study. Brain Imaging Behav 2022; 16:2526-2542. [PMID: 35859076 DOI: 10.1007/s11682-022-00708-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/10/2022] [Indexed: 11/26/2022]
Abstract
Eigenvector-Centrality (EC) has shown promising results in the field of Psychiatry, with early results also pertaining to ADHD. Parallel efforts have focused on the description of aberrant interhemispheric coordination in ADHD, as measured by Voxel-Mirrored-Homotopic-Connectivity (VMHC), with early evidence of altered Resting-State fMRI. A sample was collected from the ADHD200-NYU initiative: 86 neurotypicals and 89 participants with ADHD between 7 and 18 years old were included after quality control for motion. After preprocessing, voxel-wise EC and VMHC values between diagnostic groups were compared, and network-level values from 15 functional networks extracted. Age, ADHD severity (Connor's Parent Rating-Scale), IQ (Wechsler-Abbreviated-Scale), and right-hand dominance were correlated with EC/VMHC values in the whole sample and within groups, both at the voxel-wise and network-level. Motion was controlled by censoring time-points with Framewise-Displacement > 0.5 mm, as well as controlling for group differences in mean Framewise-Displacement values. EC was significantly higher in ADHD compared to neurotypicals in the left inferior Frontal lobe, Lingual gyri, Peri-Calcarine cortex, superior and middle Occipital lobes, right inferior Occipital lobe, right middle Temporal gyrus, Fusiform gyri, bilateral Cuneus, right Precuneus, and Cerebellum (FDR-corrected-p = 0.05). No differences were observed between groups in voxel-wise VMHC. EC was positively correlated with ADHD severity scores at the network level (at p-value < 0.01, Inattentive: Cerebellum rho = 0.273; Hyper/Impulsive: High-Visual Network rho = 0.242, Cerebellum rho = 0.273; Global Index Severity: High-Visual Network rho = 0.241, Cerebellum rho = 0.293). No differences were observed between groups for motion (p = 0.443). While EC was more related to ADHD psychopathology, VMHC was consistently and negatively correlated with age across all networks.
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Affiliation(s)
- Livio Tarchi
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy.
| | - Stefano Damiani
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Teresa Fantoni
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Tiziana Pisano
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories, Neuroscience Department, Meyer Children's Hospital, University of Florence, Florence, Italy
| | - Giovanni Castellini
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
| | - Pierluigi Politi
- Department of Brain and Behavioral Science, University of Pavia, 27100, Pavia, Italy
| | - Valdo Ricca
- Psychiatry Unit, Department of Health Sciences, University of Florence, Florence, FI, Italy
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16
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Subramoney S, Joshi SH, Wedderburn CJ, Lee D, Roos A, Woods RP, Zar HJ, Narr K, Stein DJ, Donald KA. The impact of prenatal alcohol exposure on gray matter volume and cortical surface area of 2 to 3-year-old children in a South African birth cohort. Alcohol Clin Exp Res 2022; 46:1233-1247. [PMID: 35581528 PMCID: PMC9357164 DOI: 10.1111/acer.14873] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 04/30/2022] [Accepted: 05/07/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND There is a growing literature that demonstrates the effects of prenatal alcohol exposure (PAE) on brain development in school-aged children. Less is known, however, on how PAE impacts the brain early in life. We investigated the effects of PAE and child sex on subcortical gray matter volume, cortical surface area (CSA), cortical volume (CV), and cortical thickness (CT) in children aged 2 to 3 years. METHODS The sample was recruited as a nested cross-sectional substudy of the Drakenstein Child Health Study. Images from T1-weighted magnetic resonance imaging were acquired on 47 alcohol-exposed and 124 control children (i.e., with no or minimal alcohol exposure), aged 2 to 3 years, some of whom were scanned as neonates. Brain images were processed through automated processing pipelines using FreeSurfer version 6.0. Subcortical and a priori selected cortical regions of interest were compared. RESULTS Subcortical volume analyses revealed a PAE by child sex interaction for bilateral putamen volumes (Left: p = 0.02; Right: p = 0.01). There was no PAE by child sex interaction effect on CSA, CV, and CT. Analyses revealed an impact of PAE on CSA (p = 0.04) and CV (p = 0.04), but not CT in this age group. Of note, the inferior parietal gyrus CSA was significantly smaller in children with PAE compared to control children. CONCLUSIONS Findings from this subgroup scanned at age 2 to 3 years build on previously described subcortical volume differences in neonates from this cohort. Findings suggest that PAE persistently affects gray matter development through the critical early years of life. The detectable influence of PAE on brain structure at this early age further highlights the importance of brain imaging studies on the impact of PAE on the young developing brain.
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Affiliation(s)
- Sivenesi Subramoney
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
| | - Shantanu H. Joshi
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
- Department of BioengineeringUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Catherine J. Wedderburn
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
- Department of Clinical ResearchLondon School of Hygiene and Tropical MedicineLondonUK
- The Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - David Lee
- Department of BioengineeringUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Annerine Roos
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
- The Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | - Roger P. Woods
- Departments of Neurology, Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Heather J. Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
- Unit on Child & Adolescent Health, South African Medical Research Council (SAMRC)University of Cape TownCape TownSouth Africa
| | - Katherine L. Narr
- Departments of Neurology, Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Dan J. Stein
- The Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- SU/UCT MRC Unit on Risk and Resilience in Mental DisordersUniversity of Cape TownCape TownSouth Africa
| | - Kirsten A. Donald
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's HospitalUniversity of Cape TownCape TownSouth Africa
- The Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
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Altered functional connectivity in children born very preterm at school age. Sci Rep 2022; 12:7308. [PMID: 35508563 PMCID: PMC9068715 DOI: 10.1038/s41598-022-11184-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 04/12/2022] [Indexed: 12/15/2022] Open
Abstract
Children born very preterm are at significant risk of neurodevelopmental impairment. This study sought to identify differences in cognitive function in children born very preterm compared to term-born controls and investigate alteration in white matter microstructure and functional connectivity (FC) based on tract-based spatial statistics (TBSS) and resting-state functional MRI, respectively. At 6 years of age, 36 children born very preterm (< 32 weeks' gestation) without major neurological disabilities and 26 term-born controls were tested using the Wechsler Intelligence Scale for Children, 4th edition, and Child Behavior Checklist. Whole-brain deterministic tractography and FC measurements were performed in both groups. The very preterm group had significantly lower intelligence scores than the term-born controls. The TBSS revealed no significant differences between the two groups, whereas FC was significantly increased between the frontoparietal network and the language network and was significantly decreased between the right salience network nodes in the very preterm group. The altered FC patterns between specific regions of the higher-order networks may reflect underlying deficits in the functional network architecture associated with cognitive function. Further studies are needed to demonstrate a direct connection between FC in these regions and cognitive function.
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Chyzhyk D, Varoquaux G, Milham M, Thirion B. How to remove or control confounds in predictive models, with applications to brain biomarkers. Gigascience 2022; 11:giac014. [PMID: 35277962 PMCID: PMC8917515 DOI: 10.1093/gigascience/giac014] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/19/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND With increasing data sizes and more easily available computational methods, neurosciences rely more and more on predictive modeling with machine learning, e.g., to extract disease biomarkers. Yet, a successful prediction may capture a confounding effect correlated with the outcome instead of brain features specific to the outcome of interest. For instance, because patients tend to move more in the scanner than controls, imaging biomarkers of a disease condition may mostly reflect head motion, leading to inefficient use of resources and wrong interpretation of the biomarkers. RESULTS Here we study how to adapt statistical methods that control for confounds to predictive modeling settings. We review how to train predictors that are not driven by such spurious effects. We also show how to measure the unbiased predictive accuracy of these biomarkers, based on a confounded dataset. For this purpose, cross-validation must be modified to account for the nuisance effect. To guide understanding and practical recommendations, we apply various strategies to assess predictive models in the presence of confounds on simulated data and population brain imaging settings. Theoretical and empirical studies show that deconfounding should not be applied to the train and test data jointly: modeling the effect of confounds, on the training data only, should instead be decoupled from removing confounds. CONCLUSIONS Cross-validation that isolates nuisance effects gives an additional piece of information: confound-free prediction accuracy.
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Affiliation(s)
- Darya Chyzhyk
- Parietal project-team, INRIA Saclay-île de France, France
- CEA/Neurospin bât 145, 91191 Gif-Sur-Yvette, France
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Gaël Varoquaux
- Parietal project-team, INRIA Saclay-île de France, France
- CEA/Neurospin bât 145, 91191 Gif-Sur-Yvette, France
| | - Michael Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
- Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Bertrand Thirion
- Parietal project-team, INRIA Saclay-île de France, France
- CEA/Neurospin bât 145, 91191 Gif-Sur-Yvette, France
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19
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Longitudinal maturation of resting state networks: Relevance to sustained attention and attention deficit/hyperactivity disorder. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2022; 22:1432-1446. [PMID: 35676491 PMCID: PMC9622522 DOI: 10.3758/s13415-022-01017-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/21/2022] [Indexed: 01/27/2023]
Abstract
The transition from childhood to adolescence involves important neural function, cognition, and behavior changes. However, the links between maturing brain function and sustained attention over this period could be better understood. This study examined typical changes in network functional connectivity over childhood to adolescence, developmental differences in attention deficit/hyperactivity disorder (ADHD), and how functional connectivity might underpin variability in sustained attention development in a longitudinal sample. A total of 398 resting state scans were collected from 173 children and adolescents (88 ADHD, 85 control) at up to three timepoints across ages 9-14 years. The effects of age, sex, and diagnostic group on changes in network functional connectivity were assessed, followed by relationships between functional connectivity and sustained attention development using linear mixed effects modelling. The ADHD group displayed greater decreases in functional connectivity between salience and visual networks compared with controls. Lower childhood functional connectivity between the frontoparietal and several brain networks was associated with more rapid sustained attention development, whereas frontoparietal to dorsal attention network connectivity related to attention trajectories in children with ADHD alone. Brain network segregation may increase into adolescence as predicted by key developmental theories; however, participants with ADHD demonstrated altered developmental trajectories between salience and visual networks. The segregation of the frontoparietal network from other brain networks may be a mechanism supporting sustained attention development. Frontoparietal to dorsal attention connectivity can be a focus for further work in ADHD.
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Qi T, Schaadt G, Friederici AD. Associated functional network development and language abilities in children. Neuroimage 2021; 242:118452. [PMID: 34358655 PMCID: PMC8463838 DOI: 10.1016/j.neuroimage.2021.118452] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/14/2021] [Accepted: 08/03/2021] [Indexed: 11/26/2022] Open
Abstract
During childhood, the brain is gradually converging to the efficient functional architecture observed in adults. How the brain's functional architecture evolves with age, particularly in young children, is however, not well understood. We examined the functional connectivity of the core language regions, in association with cortical growth and language abilities, in 175 young children in the age range of 4 to 9 years. We analyzed the brain's developmental changes using resting-state functional and T1-weighted structural magnetic resonance imaging data. The results showed increased functional connectivity strength with age between the pars triangularis of the left inferior frontal gyrus and left temporoparietal regions (cohen's d = 0.54, CI: 0.24 - 0.84), associated with children's language abilities. Stronger functional connectivity between bilateral prefrontal and temporoparietal regions was associated with better language abilities regardless of age. In addition, the stronger functional connectivity between the left inferior frontal and temporoparietal regions was associated with larger surface area and thinner cortical thickness in these regions, which in turn was associated with superior language abilities. Thus, using functional and structural brain indices, coupled with behavioral measures, we elucidate the association of functional language network development, language ability, and cortical growth, thereby adding to our understanding of the neural basis of language acquisition in young children.
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Affiliation(s)
- Ting Qi
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Gesa Schaadt
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Education and Psychology, Free University of Berlin, Berlin, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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21
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The longitudinal relationship between BOLD signal variability changes and white matter maturation during early childhood. Neuroimage 2021; 242:118448. [PMID: 34358659 DOI: 10.1016/j.neuroimage.2021.118448] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 07/03/2021] [Accepted: 08/02/2021] [Indexed: 10/20/2022] Open
Abstract
Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional integrity and information processing capacity. Here, we sought to explore across-participant and longitudinal relationships between BOLD variability, age, and white matter structure in early childhood. We measured standard deviation of BOLD signal, total white matter volume, global fractional anisotropy (FA) and mean diffusivity (MD) during passive movie viewing in a sample of healthy children (aged 2-8 years; N = 83). We investigated how age and white matter development related to changes in BOLD variability both across- and within-participants. Our across-participant analyses using behavioural partial least squares (bPLS) revealed that the influence of age and white matter maturation on BOLD variability was highly interrelated. BOLD variability increased in widespread frontal, temporal and parietal regions, and decreased in the hippocampus and parahippocampal gyrus with age and white matter development. Our longitudinal analyses using linear mixed effects modelling revealed significant associations between BOLD variability, age and white matter microstructure. Analyses using artificial neural networks demonstrated that BOLD variability and white matter micro and macro-structure at earlier ages were strong predictors of BOLD variability at later ages. By characterizing the across-participant and longitudinal features of the association between BOLD variability and white matter micro- and macrostructure in early childhood, our results provide a novel perspective to understand structure-function relationships in the developing brain.
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22
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Waters KA, Chawla J, Harris MA, Heussler H, Cheng AT, Black RJ. Sleep and Behavior 24 Months After Early Tonsillectomy for Mild OSA: An RCT. Pediatrics 2021; 148:peds.2020-038588. [PMID: 34257146 DOI: 10.1542/peds.2020-038588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/09/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The Preschool Obstructive Sleep Apnea Tonsillectomy and Adenoidectomy study is a prospective randomized controlled study of children aged 3 to 5 years. This follow-up evaluated postoperative outcomes 24 months after randomization. METHODS Baseline, 12-month, and 24-month assessments included intellectual ability, polysomnography, audiology, a pediatric sleep questionnaire, the parent rating scale of the Behavior Assessment System for Children, and the Behavior Rating Inventory of Executive Functioning. RESULTS In total, 117 (55% male) of 190 children, 61.6% of those initially randomly assigned, attended 24-month follow-up; 62 of 99 were assigned T/A within 2 months (eT/A); and 55 of 91 were assigned to T/A after the 12-month follow-up (T/A12). Intellectual ability, our primary outcome, did not differ according to the timing of T/A. Exploratory analyses revealed changes in both groups after T/A, including fewer children having day sleeps (eT/A from baseline 97% to 11%, T/A12 from 36% at 12 months to 9%), improved symptom scores (eT/A 0.62 to 0.25, T/A12 0.61 to 0.26; P < .001), improved behavior T-scores (eT/A 71.0 to 59.9, T/A12 63.6 to 50.5; P < .001), and improved polysomnography (obstructive apnea-hypopnea index eT/A 1.9 to 0.3 per hour, T/A12 1.3 to 0.3; P < .001). The eT/A group revealed temporary postoperative improvement of Woodcock-Johnson III subscales (sound blending and incomplete word scores) and behavioral withdrawal. CONCLUSIONS T/A for mild obstructive sleep apnea led to large improvements in sleep and behavior in preschool-aged children, regardless of the timing of surgery.
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Affiliation(s)
- Karen A Waters
- Sleep Medicine Service, The Children's Hospital at Westmead, Westmead, Australia .,Specialty of Child and Adolescent Health, School of Medicine, The University of Sydney, Sydney, Australia
| | - Jasneek Chawla
- Departments of Respiratory and Sleep Medicine.,Faculty of Medicine, Mater Medical Research Institute
| | | | - Helen Heussler
- Children's Health Research Centre, The University of Queensland, Brisbane, Australia
| | - Alan T Cheng
- Sleep Medicine Service, The Children's Hospital at Westmead, Westmead, Australia.,Specialty of Child and Adolescent Health, School of Medicine, The University of Sydney, Sydney, Australia
| | - Robert J Black
- Otolaryngology Head and Neck Surgery, Children's Health Queensland Hospital and Health Service, Brisbane, Australia
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Chen B, Linke A, Olson L, Ibarra C, Kinnear M, Fishman I. Resting state functional networks in 1-to-3-year-old typically developing children. Dev Cogn Neurosci 2021; 51:100991. [PMID: 34298412 PMCID: PMC8322300 DOI: 10.1016/j.dcn.2021.100991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Revised: 07/06/2021] [Accepted: 07/14/2021] [Indexed: 10/27/2022] Open
Abstract
Brain functional networks undergo substantial development and refinement during the first years of life. Yet, the maturational pathways of functional network development remain poorly understood. Using resting-state fMRI data acquired during natural sleep from 24 typically developing toddlers, ages 1.5-3.5 years, we aimed to examine the large-scale resting-state functional networks and their relationship with age and developmental skills. Specifically, two network organization indices reflecting network connectivity and spatial variability were derived. Our results revealed that reduced spatial variability or increased network homogeneity in one of the default mode network components was associated with age, with older children displaying less spatially variable posterior DMN subcomponent, consistent with the notion of increased spatial and functional specialization. Further, greater network homogeneity in higher-order functional networks, including the posterior default mode, salience, and language networks, was associated with more advanced developmental skills measured with a standardized assessment of early learning, regardless of age. These results not only improve our understanding of brain functional network development during toddler years, but also inform the relationship between brain network organization and emerging cognitive and behavioral skills.
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Affiliation(s)
- Bosi Chen
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States; SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, United States.
| | - Annika Linke
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States
| | - Lindsay Olson
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States; SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, United States
| | - Cynthia Ibarra
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States
| | - Mikaela Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, United States; SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, United States; SDSU Center for Autism and Developmental Disorders, San Diego State University, United States.
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24
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Pujol J, Blanco-Hinojo L, Macia D, Martínez-Vilavella G, Deus J, Pérez-Sola V, Cardoner N, Soriano-Mas C, Sunyer J. Differences between the child and adult brain in the local functional structure of the cerebral cortex. Neuroimage 2021; 237:118150. [PMID: 33984493 DOI: 10.1016/j.neuroimage.2021.118150] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 05/02/2021] [Accepted: 05/03/2021] [Indexed: 10/21/2022] Open
Abstract
Imaging studies on neuronal network formation provide relevant information as to how the brain matures during adolescence. We used a novel imaging approach combining well-established MRI measures of local functional connectivity that jointly provide qualitatively different information relating to the functional structure of the cerebral cortex. To investigate the adolescent transition into adulthood, we comparatively assessed 169 preadolescents aged 8-12 years and 121 healthy adults. Whole-brain functional connectivity maps were generated using multi-distance measures of intracortical neural activity coupling defined within iso-distant local areas. Such Iso-Distant Average Correlation (IDAC) measures therefore represent the average temporal correlation of a given brain unit, or voxel, with other units situated at increasingly separated iso-distant intervals. The results indicated that between-group differences in the functional structure of the cerebral cortex are extensive and implicate part of the lateral prefrontal cortex, a medial frontal/anterior cingulate region, the superior parietal lobe extending to the somatosensory strip and posterior cingulate cortex, and local connections within the visual cortex, hippocampus, amygdala and insula. We thus provided detail of the cerebral cortex functional structure maturation during the transition to adulthood, which may serve to establish more accurate links between adolescent performance gains and cerebral cortex maturation. Remarkably, our study provides new information as to the cortical maturation processes in prefrontal areas relevant to executive functioning and rational learning, medial frontal areas playing an active role in the cognitive appraisal of emotion and anxiety, and superior parietal cortices strongly associated with bodily self-consciousness in the context of body image formation.
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Affiliation(s)
- Jesus Pujol
- MRI Research Unit, Department of Radiology, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain; Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain.
| | - Laura Blanco-Hinojo
- MRI Research Unit, Department of Radiology, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain; Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain
| | - Didac Macia
- MRI Research Unit, Department of Radiology, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain
| | - Gerard Martínez-Vilavella
- MRI Research Unit, Department of Radiology, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain
| | - Joan Deus
- MRI Research Unit, Department of Radiology, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain; Department of Clinical and Health Psychology, Autonomous University of Barcelona, Spain
| | - Víctor Pérez-Sola
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain; Institute of Neuropsychiatry and Addictions, Hospital del Mar-IMIM, Spain; Department of Psychiatry, Autonomous University of Barcelona, Barcelona, Spain
| | - Narcís Cardoner
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain; Mental Health Department, Parc Taulí Sabadell University Hospital, Spain; Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Spain
| | - Carles Soriano-Mas
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain; Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Spain; Department of Psychobiology and Methodology in Health Sciences, Autonomous University of Barcelona, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain; Pompeu Fabra University, Barcelona, Catalonia, Spain; Ciber on Epidemiology and Public Health (CIBERESP), Madrid, Spain
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Sudre G, Bouyssi-Kobar M, Norman L, Sharp W, Choudhury S, Shaw P. Estimating the Heritability of Developmental Change in Neural Connectivity, and Its Association With Changing Symptoms of Attention-Deficit/Hyperactivity Disorder. Biol Psychiatry 2021; 89:443-450. [PMID: 32800380 PMCID: PMC7736233 DOI: 10.1016/j.biopsych.2020.06.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 06/03/2020] [Accepted: 06/03/2020] [Indexed: 01/02/2023]
Abstract
BACKGROUND Twin studies show that age-related change in symptoms of attention-deficit/hyperactivity disorder (ADHD) is heritable. However, we do not know the heritability of the development of the neural substrates underlying the disorder. Here, we estimated the heritability of developmental change in white matter tracts and the brain's intrinsic functional connectivity using longitudinal data. We further determined associations with change in ADHD symptoms. METHODS The study reports on 288 children, which included 127 siblings, 19 cousins, and 142 singletons; 150 (52%) had a diagnosis of ADHD (determined by clinician interview with parent); 188 were male. All had two clinical assessments (overall baseline mean age: 9.4 ± 2.4 years; follow-up: 12.5 ± 2.6 years). Diffusion tensor imaging estimated microstructural properties of white matter tracts on 252 participants. Resting-state functional magnetic resonance imaging estimated intrinsic connectivity within and between major brain networks on 226 participants. Total additive genetic heritability (h2) of the annual rate of change in these neural phenotypes was calculated using SOLAR (Sequential Oligogenic Linkage Analysis Routines). RESULTS Significant heritability was found for the rates of change of 6 white matter tract microstructural properties and for change in the connectivity between the ventral attention network and both the cognitive control and dorsal attention networks. Change in hyperactivity-impulsivity was associated with heritable change in white matter tracts metrics and change in the connectivity between the ventral attention and cognitive networks. CONCLUSIONS The relatively small number of heritable, ADHD-associated developmental neural phenotypes can serve as phenotypes for future gene discovery and understanding.
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Affiliation(s)
- Gustavo Sudre
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health
| | - Marine Bouyssi-Kobar
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health
| | - Luke Norman
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health
| | - Wendy Sharp
- National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Saadia Choudhury
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health
| | - Philip Shaw
- Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.
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26
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Donnici C, Long X, Dewey D, Letourneau N, Landman B, Huo Y, Lebel C. Prenatal and postnatal maternal anxiety and amygdala structure and function in young children. Sci Rep 2021; 11:4019. [PMID: 33597557 PMCID: PMC7889894 DOI: 10.1038/s41598-021-83249-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 02/01/2021] [Indexed: 12/19/2022] Open
Abstract
Anxiety symptoms are relatively common during pregnancy and are associated with behavioural problems in children. The amygdala is involved in emotion regulation, and its volume and function are associated with exposure to prenatal maternal depression. The associations between perinatal maternal anxiety and children's amygdala structure and function remain unclear. The objective of this study was to determine associations between prenatal and postnatal maternal anxiety and amygdala structure and function in children. Maternal anxiety was measured during the second trimester of pregnancy and 12 weeks postpartum. T1-weighted anatomical data and functional magnetic resonance imaging data were collected from 54 children (25 females), between the ages of 3-7 years. Amygdala volume was calculated and functional connectivity maps were created between the amygdalae and the rest of the brain. Spearman correlations were used to test associations between amygdala volume/functional connectivity and maternal anxiety symptoms, controlling for maternal depression symptoms. Second trimester maternal anxiety symptoms were negatively associated with functional connectivity between the left amygdala and clusters in bilateral parietal regions; higher maternal anxiety was associated with increased negative connectivity. Postnatal maternal anxiety symptoms were positively associated with child amygdala volume, but this finding did not remain significant while controlling for total brain volume. These functional connectivity differences may underlie behavioral outcomes in children exposed to maternal anxiety during pregnancy.
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Affiliation(s)
- Claire Donnici
- Neuroscience Program, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Hotchkiss Brain Institute, Calgary, AB, Canada
| | - Xiangyu Long
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Deborah Dewey
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Calgary, AB, Canada
- Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada
| | - Nicole Letourneau
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
- Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada
- Faculty of Nursing, University of Calgary, Calgary, AB, Canada
| | - Bennett Landman
- Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Yuankai Huo
- Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute, Calgary, AB, Canada.
- Department of Radiology, University of Calgary, Calgary, AB, Canada.
- Hotchkiss Brain Institute, Calgary, AB, Canada.
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Cordoni G, Favilli E, Palagi E. Earlier than previously thought: Yawn contagion in preschool children. Dev Psychobiol 2021; 63:931-944. [PMID: 33506489 DOI: 10.1002/dev.22094] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 12/22/2020] [Accepted: 12/26/2020] [Indexed: 12/18/2022]
Abstract
Yawning is a primitive and stereotyped motor action involving orofacial, laryngeal, pharyngeal, thoracic and abdominal muscles. Contagious yawning, an involuntarily action induced by viewing or listening to others' yawns, has been demonstrated in human and several non-human species. Previous studies with humans showed that infants and preschool children, socially separated during video experiments, were not infected by others' yawns. Here, we tested the occurrence of yawn contagion in 129 preschool children (ranging from 2.5 to 5.5 years) belonging to five different classes by video recording them in their classrooms during the ordinary school activities. As it occurs in adult humans, children of all ages were infected by others' yawns within the 2 min after the perception of the stimulus. The yawn contagion occurred earlier than previously thought. For children, it appears that the natural social setting is more conducive to yawn contagion than the inherently artificial experimental approach. Moreover, children's gender did not affect the level of contagious yawning. The neural, emotional and behavioural traits of preschool children are probably not sufficiently mature to express variability between boys and girls; nevertheless, children appeared to be already well equipped with the 'neural toolkit' necessary for expressing yawn contagion.
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Affiliation(s)
- Giada Cordoni
- Natural History Museum, University of Pisa, Calci Pisa, Italy
| | | | - Elisabetta Palagi
- Natural History Museum, University of Pisa, Calci Pisa, Italy.,Unit of Ethology, Department of Biology, University of Pisa, Pisa, Italy
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28
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Functional connectivity patterns predict naturalistic viewing versus rest across development. Neuroimage 2021; 229:117630. [PMID: 33401011 DOI: 10.1016/j.neuroimage.2020.117630] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 10/16/2020] [Accepted: 12/07/2020] [Indexed: 11/22/2022] Open
Abstract
Cognitive states, such as rest and task engagement, share an 'intrinsic' functional network organization that is subject to minimal variation over time and yields stable signatures within an individual. Importantly, there are also transient state-specific functional connectivity (FC) patterns that vary across neural states. Here, we examine functional brain organization differences that underlie distinct states in a cross-sectional developmental sample. We compare FC fMRI data acquired during naturalistic viewing (i.e., movie-watching) and resting-state paradigms in a large cohort of 157 children and young adults aged 6-20. Naturalistic paradigms are commonly implemented in pediatric research because they maintain the child's attention and contribute to reduced head motion. It remains unknown, however, to what extent the brain-wide functional network organization is comparable during movie-watching and rest across development. Here, we identify a widespread FC pattern that predicts whether individuals are watching a movie or resting. Specifically, we develop a model for prediction of multilevel neural effects (termed PrimeNet), which can with high reliability distinguish between movie-watching and rest irrespective of age and that generalizes across movies. In turn, we characterize FC patterns in the most predictive functional networks for movie-watching versus rest and show that these patterns can indeed vary as a function of development. Collectively, these effects highlight a 'core' FC pattern that is robustly associated with naturalistic viewing, which also exhibits change across age. These results, focused here on naturalistic viewing, provide a roadmap for quantifying state-specific functional neural organization across development, which may reveal key variation in neurodevelopmental trajectories associated with behavioral phenotypes.
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29
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Reliability map of individual differences reflected in inter-subject correlation in naturalistic imaging. Neuroimage 2020; 223:117277. [DOI: 10.1016/j.neuroimage.2020.117277] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 07/21/2020] [Accepted: 08/11/2020] [Indexed: 12/30/2022] Open
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30
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Huang Z, Wang Q, Zhou S, Tang C, Yi F, Nie J. Exploring functional brain activity in neonates: A resting-state fMRI study. Dev Cogn Neurosci 2020; 45:100850. [PMID: 32882651 PMCID: PMC7474406 DOI: 10.1016/j.dcn.2020.100850] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 07/23/2020] [Accepted: 08/25/2020] [Indexed: 11/17/2022] Open
Abstract
The human brain is born with a certain maturity, but quantitatively measuring the maturation and development of functional brain activity in neonates remains a topic of vigorous scientific research, especially the dynamic characteristics. To address this, T1w, T2w, and resting-state functional magnetic resonance imaging (rs-fMRI) data from 40 full-term healthy neonates and 38 adults were adopted in this study. Group differences of local brain activity and functional connectivity between neonates and adults from both static and dynamic perspectives were explored. We found that the neonatal brain is largely immature in general. Sensorimotor areas were the most active, well-connected, and temporally dynamic. Compared with adults, visual and primary auditory areas in neonates showed higher or similar local activity but lower static and dynamic connections with other brain regions. Our findings provide new references and valuable insights for time-varying and local brain functional activity in neonates.
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Affiliation(s)
- Ziyi Huang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China
| | - Qi Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China
| | - Senyu Zhou
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China
| | - Chao Tang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China
| | - Fa Yi
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China
| | - Jingxin Nie
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, China.
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31
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Benischek A, Long X, Rohr CS, Bray S, Dewey D, Lebel C. Pre-reading language abilities and the brain’s functional reading network in young children. Neuroimage 2020; 217:116903. [DOI: 10.1016/j.neuroimage.2020.116903] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 04/07/2020] [Accepted: 04/30/2020] [Indexed: 01/23/2023] Open
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32
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Edde M, Leroux G, Altena E, Chanraud S. Functional brain connectivity changes across the human life span: From fetal development to old age. J Neurosci Res 2020; 99:236-262. [PMID: 32557768 DOI: 10.1002/jnr.24669] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 05/11/2020] [Accepted: 05/15/2020] [Indexed: 01/02/2023]
Abstract
The dynamic of the temporal correlations between brain areas, called functional connectivity (FC), undergoes complex transformations through the life span. In this review, we aim to provide an overview of these changes in the nonpathological brain from fetal life to advanced age. After a brief description of the main methods, we propose that FC development can be divided into four main phases: first, before birth, a strong change in FC leads to the emergence of functional proto-networks, involving mainly within network short-range connections. Then, during the first years of life, there is a strong widespread organization of networks which starts with segregation processes followed by a continuous increase in integration. Thereafter, from adolescence to early adulthood, a refinement of existing networks in the brain occurs, characterized by an increase in integrative processes until about 40 years. Middle age constitutes a pivotal period associated with an inversion of the functional brain trajectories with a decrease in segregation process in conjunction to a large-scale reorganization of between network connections. Studies suggest that these processes are in line with the development of cognitive and sensory functions throughout life as well as their deterioration. During aging, results support the notion of dedifferentiation processes, which refer to the decrease in functional selectivity of the brain regions, resulting in more diffuse and less specialized FC, associated with the disruption of cognitive functions with age. The inversion of developmental processes during aging is in accordance with the developmental models of neuroanatomy for which the latest matured regions are the first to deteriorate.
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Affiliation(s)
- Manon Edde
- Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Gaëlle Leroux
- Université Claude-Bernard Lyon 1, Université de Lyon, CRNL, INSERM U1028, CNRS UMR5292, Lyon, France
| | - Ellemarije Altena
- UMR 5287 CNRS INCIA, Neuroimagerie et Cognition Humaine, Universitéde Bordeaux, Bordeaux, France
| | - Sandra Chanraud
- UMR 5287 CNRS INCIA, Neuroimagerie et Cognition Humaine, Universitéde Bordeaux, Bordeaux, France.,EPHE, PSL University, Paris, France
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33
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Camacho MC, Quiñones-Camacho LE, Perlman SB. Does the child brain rest?: An examination and interpretation of resting cognition in developmental cognitive neuroscience. Neuroimage 2020; 212:116688. [PMID: 32114148 PMCID: PMC7190083 DOI: 10.1016/j.neuroimage.2020.116688] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/04/2020] [Accepted: 02/25/2020] [Indexed: 02/02/2023] Open
Abstract
In cognitive neuroscience, measurements of "resting baseline" are often considered stable across age and used as a reference point against which to judge cognitive state. The task-based approach-comparing resting baseline to task conditions-implies that resting baseline is an equalizer across participants and-in the case of studies of developmental changes in cognition-across age groups. In contrast, network neuroscience explicitly examines the development of "resting state" networks across age, at odds with the idea of a consistent resting baseline. Little attention has been paid to how cognition during rest may shift across development, particularly in children under the age of eight. Childhood is marked by striking maturation of neural systems, including a protracted developmental period for cognitive control systems. To grow and shape these cognitive systems, children have a developmental imperative to engage their neural circuitry at every possible opportunity. Thus, periods of "rest" without specific instructions may require additional control for children as they fight against developmental expectation to move, speak, or otherwise engage. We therefore theorize that the child brain does not rest in a manner consistent with the adult brain as longer rest periods may represent increased cognitive control. To shape this theory, we first review the extant literature on neurodevelopment across early childhood within the context of cognitive development. Next, we present nascent evidence for a destabilized baseline for comparisons across age. Finally, we present recommendations for designing, analyzing, and interpreting tasks conducted with young children as well as for resting state. Future work must aim to tease apart the cognitive context under which we examine functional brain development in young children and take considerations into account unique to each age.
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Affiliation(s)
- M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University in St. Louis, St. Louis, MO, USA.
| | | | - Susan B Perlman
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University in St. Louis, St. Louis, MO, USA; Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
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34
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Dimond D, Rohr CS, Smith RE, Dhollander T, Cho I, Lebel C, Dewey D, Connelly A, Bray S. Early childhood development of white matter fiber density and morphology. Neuroimage 2020; 210:116552. [DOI: 10.1016/j.neuroimage.2020.116552] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 01/10/2020] [Accepted: 01/14/2020] [Indexed: 12/13/2022] Open
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35
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Reynolds JE, Long X, Paniukov D, Bagshawe M, Lebel C. Calgary Preschool magnetic resonance imaging (MRI) dataset. Data Brief 2020; 29:105224. [PMID: 32071993 PMCID: PMC7016255 DOI: 10.1016/j.dib.2020.105224] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/15/2020] [Accepted: 01/24/2020] [Indexed: 01/05/2023] Open
Abstract
The Calgary Preschool MRI Dataset in the Developmental Neuroimaging Lab at the University of Calgary uses magnetic resonance imaging (MRI) techniques to study brain structure and function in early childhood [1-3]. The dataset aims to characterise brain development in early childhood (2-8 years), and to understand links to cognitive and behavioral development, as well as provide a baseline from which to identify atypical development in children with diseases, disorders, or brain injuries. MRI data are provided for 126 children (61 males, 65 females). Children ranged from 1.95 to 6.22 years (mean = 3.98 ± 1.06 years) at the time of their first scan and were initially scanned at six month intervals, and now continue to be followed annually (1-20 scans per child, 431 total datasets; datasets do not always have all scan modalities available). All MRI scans were acquired on the same General Electric 3T MR750w system and 32-channel head coil (GE, Waukesha, WI) at the Alberta Children's Hospital in Calgary, Canada. The MRI protocols provided in this dataset include: T1-weighted images acquired using a FSPGR BRAVO sequence; arterial spin labeling (ASL) images acquired with the vendor supplied pseudo continuous 3D ASL sequence; diffusion tensor imaging data acquired using single shot spin echo echo-planar imaging; and passive viewing resting state functional MRI data acquired with a gradient-echo echo-planar imaging sequence.
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Affiliation(s)
- Jess E Reynolds
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, T2N 1N4, AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Owerko Centre, Alberta Children Hospital Research Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Hotchkiss Brain Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
| | - Xiangyu Long
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, T2N 1N4, AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Dmitrii Paniukov
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, T2N 1N4, AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Owerko Centre, Alberta Children Hospital Research Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Hotchkiss Brain Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Department of Pediatrics, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
| | - Mercedes Bagshawe
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, T2N 1N4, AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Owerko Centre, Alberta Children Hospital Research Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Hotchkiss Brain Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, T2N 1N4, AB, Canada.,Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Owerko Centre, Alberta Children Hospital Research Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Hotchkiss Brain Institute, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada
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36
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Paniukov D, Lebel RM, Giesbrecht G, Lebel C. Cerebral blood flow increases across early childhood. Neuroimage 2020; 204:116224. [PMID: 31561017 DOI: 10.1016/j.neuroimage.2019.116224] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 06/27/2019] [Accepted: 09/23/2019] [Indexed: 12/12/2022] Open
Abstract
Adequate cerebral blood flow (CBF) is essential to proper brain development and function. Detailed characterization of CBF developmental trajectories will lead to better understanding of the development of cognitive, motor, and sensory functions, as well as behaviour in children. Previous studies have shown CBF increases during infancy and decreases during adolescence; however, the trajectories during childhood, and in particular the timing of peak CBF, remain unclear. Here, we used arterial spin labeling to map age-related changes of CBF across a large longitudinal sample that included 279 scans on 96 participants (46 girls and 50 boys) aged 2-7 years. CBF maps were analyzed using hierarchical linear regression for every voxel inside the grey matter mask, controlling for multiple comparisons. The results revealed a significant positive linear association between CBF and age in distributed brain regions including prefrontal, temporal, parietal, and occipital cortex, and in the cerebellum. There were no differences in developmental trajectories between males and females. Our findings show that CBF continues to increase until the age of 7 years, likely supporting ongoing improvements in behaviour, cognition, motor, and sensory functions in early childhood.
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Affiliation(s)
- Dmitrii Paniukov
- Department of Pediatrics, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Alberta Children's Hospital Research Institute at Alberta Children's Hospital, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada
| | - R Marc Lebel
- Department of Radiology, University of Calgary, Canada; Alberta Children's Hospital Research Institute at Alberta Children's Hospital, Cumming School of Medicine, University of Calgary, Canada; GE Healthcare, Calgary, Canada
| | - Gerald Giesbrecht
- Department of Pediatrics, University of Calgary, Canada; Alberta Children's Hospital Research Institute at Alberta Children's Hospital, Cumming School of Medicine, University of Calgary, Canada
| | - Catherine Lebel
- Department of Radiology, University of Calgary, Canada; Alberta Children's Hospital Research Institute at Alberta Children's Hospital, Cumming School of Medicine, University of Calgary, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Canada.
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37
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Assari S, Akhlaghipour G, Saqib M, Boyce S, Bazargan M. Prefrontal Cortex Response to Threat: Race by Age Variation in 9-10 Year Old Children. JOURNAL OF MENTAL HEALTH & CLINICAL PSYCHOLOGY 2020; 4:1-12. [PMID: 33241232 DOI: 10.29245/2578-2959/2020/4.1209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
BACKGROUND Considerable research has suggested that race and age are two major determinants of brain development, including but not limited to development of the prefrontal cortex (PFC). Minorities' Diminished Returns (MDRs), however, suggests that race (as a proxy of racism) may interact with various determinants of human and brain development. Minimal knowledge, however, exists on whether age and race also interact on shaping PFC response to threat among American children. PURPOSE Using data from a task-based functional brain imaging study and considering race as a sociological rather than a biological construct, we investigated combined effects of race and age on prefrontal cortical (PFC) response to threat. We explored racial heterogeneities in the association between age and PFC response to threat by comparing Black and White children. METHODS This study used the task-based functional Magnetic Resonance Imaging (fMRI) data from the Adolescents Brain Cognitive Development (ABCD) study, a national, landmark, multi-center brain imaging investigation of 9-10 years old children in the US. The primary outcomes were mean beta weights of n-back runs measuring PFC response to threating versus neutral face contrast in the following regions of interest (ROIs): left hemisphere-lateral orbito-frontal, left hemisphere -superior-frontal, right hemisphere -caudal middle frontal, and right hemisphere -superior frontal cortex. The independent variable was age. Covariates were sex, ethnicity, family socioeconomic status, and neighborhood socioeconomic status. Race was the focal moderator. To analyze the data, we used linear regression models without and with interactions and SES as covariates. RESULTS We included 5,066 9-10 years old children. Age and race did not show direct effects on PFC response to threatening relative to neutral faces. While ethnicity, sex, and socioeconomic status were controlled, age and race showed a systematic interaction on PFC response to threatening relative to neutral faces. CONCLUSIONS For American children, race and age do not have direct effects but multiplicative effects on PFC response to threat. The results may be reflective of social inequalities in how Black and White children are socialized and developed. The results are important given the role of the PFC in regulating the limbic system response to threat. Coordinated work of the limbic system and PFC is a core element of children's behavioral and emotional development. Future research is needed on how social stratification and racism shape emotion processing and regulation of American children in response to threat.
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Affiliation(s)
- Shervin Assari
- Department of Family Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA.,Department of Urban Public Health, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA
| | | | - Mohammed Saqib
- Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, MI, USA
| | - Shanika Boyce
- Department of Pediatrics, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA
| | - Mohsen Bazargan
- Department of Family Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA
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38
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Long X, Kar P, Gibbard B, Tortorelli C, Lebel C. The brain's functional connectome in young children with prenatal alcohol exposure. NEUROIMAGE-CLINICAL 2019; 24:102082. [PMID: 31795047 PMCID: PMC6889793 DOI: 10.1016/j.nicl.2019.102082] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 10/30/2019] [Accepted: 11/06/2019] [Indexed: 11/18/2022]
Abstract
We used fMRI to study young children with prenatal alcohol exposure (PAE). We measured the functional connectome and its stability within and across participants. The PAE group had similar graph theory metrics to controls. The PAE group, but not controls, had increasing intra-participant stability with age. Controls, but not the PAE group, had increasing inter-participant stability with age.
Prenatal alcohol exposure (PAE) can lead to altered brain function and structure, as well as lifelong cognitive, behavioral, and mental health difficulties. Previous research has shown reduced brain network efficiency in older children and adolescents with PAE, but no imaging studies have examined brain differences in young children with PAE, at an age when cognitive and behavioral problems often first become apparent. The present study aimed to investigate the brain's functional connectome in young children with PAE using passive viewing fMRI. We analyzed 34 datasets from 26 children with PAE aged 2–7 years and 215 datasets from 87 unexposed typically-developing children in the same age range. The whole brain functional connectome was constructed using functional connectivity analysis across 90 regions for each dataset. We examined intra- and inter-participant stability of the functional connectome, graph theoretical measurements, and their correlations with age. Children with PAE had similar inter- and intra-participant stability to controls. However, children with PAE, but not controls, showed increasing intra-participant stability with age, suggesting a lack of variability of intrinsic brain activity over time. Inter-participant stability increased with age in controls but not in children with PAE, indicating more variability of brain function across the PAE population. Global graph metrics were similar between children with PAE and controls, in line with previous studies in older children. This study characterizes the functional connectome in young children with PAE for the first time, suggesting that the increased brain variability seen in older children develops early in childhood, when participants with PAE fail to show the expected age-related increases in inter-individual stability.
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Affiliation(s)
- Xiangyu Long
- Alberta Children's Hospital, 28 Oki Drive NW, Calgary T3B6A8, AB, Canada; Alberta Children's Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada
| | - Preeti Kar
- Alberta Children's Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada
| | - Ben Gibbard
- Alberta Children's Hospital Research Institute, Canada; Department of Pediatrics, University of Calgary, Canada
| | | | - Catherine Lebel
- Alberta Children's Hospital, 28 Oki Drive NW, Calgary T3B6A8, AB, Canada; Alberta Children's Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada.
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39
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Zhao X, Wu Q, Chen Y, Song X, Ni H, Ming D. Hub Patterns-Based Detection of Dynamic Functional Network Metastates in Resting State: A Test-Retest Analysis. Front Neurosci 2019; 13:856. [PMID: 31572105 PMCID: PMC6749078 DOI: 10.3389/fnins.2019.00856] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 07/30/2019] [Indexed: 11/13/2022] Open
Abstract
The spontaneous dynamic characteristics of resting-state functional networks contain much internal brain physiological or pathological information. The metastate analysis of brain functional networks is an effective technique to quantify the essence of brain functional connectome dynamics. However, the widely used functional connectivity-based metastate analysis ignored the topological structure, which could be locally reflected by node centrality. In this study, 23 healthy young volunteers (21-26 years) were recruited and scanned twice with a 1-week interval. Based on the time sequences of node centrality, we promoted a node centrality-based clustering method to find metastates of functional connectome and conducted a test-retest experiment to assess the stability of those identified metastates using the described method. The hub regions of metastates were further compared with the structural networks' organization to depict its potential relationship with brain structure. Results of extracted metastates showed repeatable dynamic features between repeated scans and high overlapping rate of hub regions with brain intrinsic sub-networks. These identified hub patterns from metastates further highly overlapped with the structural hub regions. These findings indicated that the proposed node centrality-based metastates detection method could reveal reliable and meaningful metastates of spontaneous dynamics and indicate the underlying nature of brain dynamics as well as the potential relationship between these dynamics and the organization of the brain connectome.
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Affiliation(s)
- Xin Zhao
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Qiong Wu
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Yuanyuan Chen
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xizi Song
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Hongyan Ni
- Department of Radiology, Tianjin First Center Hospital, Tianjin, China
| | - Dong Ming
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.,Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
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40
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Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. Neuroimage 2019; 202:116073. [PMID: 31386921 DOI: 10.1016/j.neuroimage.2019.116073] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 06/27/2019] [Accepted: 08/02/2019] [Indexed: 12/11/2022] Open
Abstract
The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.
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Reynolds JE, Long X, Grohs MN, Dewey D, Lebel C. Structural and functional asymmetry of the language network emerge in early childhood. Dev Cogn Neurosci 2019; 39:100682. [PMID: 31376589 PMCID: PMC6969356 DOI: 10.1016/j.dcn.2019.100682] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 06/18/2019] [Accepted: 07/17/2019] [Indexed: 11/15/2022] Open
Abstract
Macrostructural asymmetry of the arcuate fasciculus is present by age 2 years. Microstructural and functional asymmetry in the IFG increases across early childhood. Left arcuate microstructure is related to pre-reading language skills. Asymmetry is not related to pre-reading skills in early childhood.
Structural and functional neuroimaging studies show language and reading processes are left-lateralized, and associated with a dispersed group of left brain regions. However, it is unclear when and how asymmetry of these regions emerges. We characterized the development of structural and functional asymmetry of the language network in 386 datasets from 117 healthy children (58 male) across early childhood (2–7.5 years). Structural asymmetry was investigated using diffusion tensor imaging (DTI) and manual delineation of the arcuate fasciculus. Functional connectivity asymmetry was calculated from seed regions in the inferior frontal gyrus (IFG) and middle temporal gyrus (MTG). We show that macrostructural asymmetry of the arcuate fasciculus is present by age 2 years, while leftward asymmetry of microstructure and functional connectivity with the IFG increases across the age range. This emerging microstructural and functional asymmetry likely underlie the development of language and reading skills during this time.
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Affiliation(s)
- Jess E Reynolds
- Department of Radiology, Canada; Owerko Centre, Alberta Children Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada
| | - Xiangyu Long
- Department of Radiology, Canada; Owerko Centre, Alberta Children Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada
| | - Melody N Grohs
- Owerko Centre, Alberta Children Hospital Research Institute, Canada; Department of Neuroscience, Canada; Cumming School of Medicine, Canada
| | - Deborah Dewey
- Owerko Centre, Alberta Children Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada; Department of Pediatrics, Canada; Department of Community Health Sciences, Canada
| | - Catherine Lebel
- Department of Radiology, Canada; Owerko Centre, Alberta Children Hospital Research Institute, Canada; Hotchkiss Brain Institute, Canada.
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42
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Rohr CS, Dimond D, Schuetze M, Cho IY, Lichtenstein-Vidne L, Okon-Singer H, Dewey D, Bray S. Girls’ attentive traits associate with cerebellar to dorsal attention and default mode network connectivity. Neuropsychologia 2019; 127:84-92. [DOI: 10.1016/j.neuropsychologia.2019.02.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 02/14/2019] [Accepted: 02/18/2019] [Indexed: 10/27/2022]
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Vanderwal T, Eilbott J, Castellanos FX. Movies in the magnet: Naturalistic paradigms in developmental functional neuroimaging. Dev Cogn Neurosci 2019; 36:100600. [PMID: 30551970 PMCID: PMC6969259 DOI: 10.1016/j.dcn.2018.10.004] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 09/13/2018] [Accepted: 10/08/2018] [Indexed: 11/28/2022] Open
Abstract
The use of movie-watching as an acquisition state for functional connectivity (FC) MRI has recently enabled multiple groups to obtain rich data sets in younger children with both substantial sample sizes and scan durations. Using naturalistic paradigms such as movies has also provided analytic flexibility for these developmental studies that extends beyond conventional resting state approaches. This review highlights the advantages and challenges of using movies for developmental neuroimaging and explores some of the methodological issues involved in designing pediatric studies with movies. Emerging themes from movie-watching studies are discussed, including an emphasis on intersubject correlations, developmental changes in network interactions under complex naturalistic conditions, and dynamic age-related changes in both sensory and higher-order network FC even in narrow age ranges. Converging evidence suggests an enhanced ability to identify brain-behavior correlations in children when using movie-watching data relative to both resting state and conventional tasks. Future directions and cautionary notes highlight the potential and the limitations of using movies to study FC in pediatric populations.
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Affiliation(s)
- Tamara Vanderwal
- University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC, V6T 2A1, Canada; Yale Child Study Center, 230 South Frontage Road, New Haven CT, 06519, United States.
| | - Jeffrey Eilbott
- Yale Child Study Center, 230 South Frontage Road, New Haven CT, 06519, United States
| | - F Xavier Castellanos
- The Child Study Center at New York University Langone Medical Center, 1 Park Avenue, New York, NY, 10016, United States; Nathan Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY, 10962, United States
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Zhang H, Shen D, Lin W. Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts. Neuroimage 2019; 185:664-684. [PMID: 29990581 PMCID: PMC6289773 DOI: 10.1016/j.neuroimage.2018.07.004] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 05/19/2018] [Accepted: 07/02/2018] [Indexed: 12/16/2022] Open
Abstract
Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects. Recently, infant rs-fMRI studies have become an area of active research. After a decade of gap filling studies, many facets of the brain functional development from early infancy to toddler has been uncovered. However, infant rs-fMRI is still in its infancy. The image analysis tools for neonates and young infants can be quite different from those for adults. From data analysis to result interpretation, more questions and issues have been raised, and new hypotheses have been formed. With the anticipated availability of unprecedented high-resolution rs-fMRI and dedicated analysis pipelines from the Baby Connectome Project (BCP), it is important now to revisit previous findings and hypotheses, discuss and comment existing issues and problems, and make a "to-do-list" for the future studies. This review article aims to comprehensively review a decade of the findings, unveiling hidden jewels of the fields of developmental neuroscience and neuroimage computing. Emphases will be given to early infancy, particularly the first few years of life. In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is provided. A comprehensive summary of the rs-fMRI findings in developmental patterns is highlighted. Furthermore, an extensive summary of the neurodevelopmental disorders and the effects of other hazardous factors is provided. Finally, future research trends focusing on emerging dynamic functional connectivity and state-of-the-art functional connectome analysis are summarized. In next decade, early infant rs-fMRI and developmental connectome study could be one of the shining research topics.
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Affiliation(s)
- Han Zhang
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA
| | - Dinggang Shen
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea.
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA.
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45
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Chen Y, Liu YN, Zhou P, Zhang X, Wu Q, Zhao X, Ming D. The Transitions Between Dynamic Micro-States Reveal Age-Related Functional Network Reorganization. Front Physiol 2019; 9:1852. [PMID: 30662409 PMCID: PMC6328489 DOI: 10.3389/fphys.2018.01852] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2017] [Accepted: 12/07/2018] [Indexed: 01/23/2023] Open
Abstract
Normal dynamic change in human brain occurs with age increasing, yet much remains unknown regarding how brain develops, matures, and ages. Functional connectivity analysis of the resting-state brain is a powerful method for revealing the intrinsic features of functional networks, and micro-states, which are the intrinsic patterns of functional connectivity in dynamic network courses, and are suggested to be more informative of brain functional changes. The aim of this study is to explore the age-related changes in these micro-states of dynamic functional network. Three healthy groups were included: the young (ages 21-32 years), the adult (age 41-54 years), and the old (age 60-86 years). Sliding window correlation method was used to construct the dynamic connectivity networks, and then the micro-states were individually identified with clustering analysis. The distribution of age-related connectivity variations in several intrinsic networks for each micro-state was analyzed then. The micro-states showed substantial age-related changes in the transitions between states but not in the dwelling time. Also there was no age-related reorganization observed within any micro-state. But there were reorganizations observed in the transition between them. These results suggested that the identified micro-states represented certain underlying connectivity patterns in functional brain system, which are similar to the intrinsic cognitive networks or resources. In addition, the dynamic transitions between these states were probable mechanisms of reorganization or compensation in functional brain networks with age increasing.
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Affiliation(s)
- Yuanyuan Chen
- College of Microelectronics, Tianjin University, Tianjin, China
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Ya-nan Liu
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Peng Zhou
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xiong Zhang
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Qiong Wu
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xin Zhao
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
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46
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Kumral D, Schaare HL, Beyer F, Reinelt J, Uhlig M, Liem F, Lampe L, Babayan A, Reiter A, Erbey M, Roebbig J, Loeffler M, Schroeter ML, Husser D, Witte AV, Villringer A, Gaebler M. The age-dependent relationship between resting heart rate variability and functional brain connectivity. Neuroimage 2018; 185:521-533. [PMID: 30312808 DOI: 10.1016/j.neuroimage.2018.10.027] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 10/05/2018] [Accepted: 10/09/2018] [Indexed: 12/30/2022] Open
Abstract
Resting heart rate variability (HRV), an index of parasympathetic cardioregulation and an individual trait marker related to mental and physical health, decreases with age. Previous studies have associated resting HRV with structural and functional properties of the brain - mainly in cortical midline and limbic structures. We hypothesized that aging affects the relationship between resting HRV and brain structure and function. In 388 healthy subjects of three age groups (140 younger: 26.0 ± 4.2 years, 119 middle-aged: 46.3 ± 6.2 years, 129 older: 66.9 ± 4.7 years), gray matter volume (GMV, voxel-based morphometry) and resting state functional connectivity (eigenvector centrality mapping and exploratory seed-based functional connectivity) were related to resting HRV, measured as the root mean square of successive differences (RMSSD). Confirming previous findings, resting HRV decreased with age. For HRV-related GMV, there were no statistically significant differences between the age groups, nor similarities across all age groups. In whole-brain functional connectivity analyses, we found an age-dependent association between resting HRV and eigenvector centrality in the bilateral ventromedial prefrontal cortex (vmPFC), driven by the younger adults. Across all age groups, HRV was positively correlated with network centrality in the bilateral posterior cingulate cortex. Seed-based functional connectivity analysis using the vmPFC cluster revealed an HRV-related cortico-cerebellar network in younger but not in middle-aged or older adults. Our results indicate that the decrease of HRV with age is accompanied by changes in functional connectivity along the cortical midline. This extends our knowledge of brain-body interactions and their changes over the lifespan.
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Affiliation(s)
- D Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany.
| | - H L Schaare
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Subproject A1, Collaborative Research Centre 1052 "Obesity Mechanisms", University of Leipzig, Leipzig, Germany
| | - J Reinelt
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Uhlig
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - F Liem
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - L Lampe
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - A Babayan
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - A Reiter
- Lifespan Developmental Neuroscience, Technical University of Dresden, Dresden, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Erbey
- MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany
| | - J Roebbig
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Loeffler
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - M L Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Cognitive Neurology, University of Leipzig, Leipzig, Germany
| | - D Husser
- Department of Electrophysiology, Leipzig Heart Centre, University of Leipzig, Leipzig, Germany
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany; Subproject A1, Collaborative Research Centre 1052 "Obesity Mechanisms", University of Leipzig, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Center for Stroke Research Berlin, Charité - Universitaetsmedizin Berlin, Berlin, Germany
| | - M Gaebler
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; MindBrainBody Institute at the Berlin School of Mind and Brain, Humboldt-Universitaet zu Berlin, Berlin, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
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47
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On the relation between theory of mind and executive functioning: A developmental cognitive neuroscience perspective. Psychon Bull Rev 2018; 25:2119-2140. [DOI: 10.3758/s13423-018-1459-0] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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48
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Rohr CS, Arora A, Cho IYK, Katlariwala P, Dimond D, Dewey D, Bray S. Functional network integration and attention skills in young children. Dev Cogn Neurosci 2018; 30:200-211. [PMID: 29587178 PMCID: PMC6969078 DOI: 10.1016/j.dcn.2018.03.007] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 02/12/2018] [Accepted: 03/15/2018] [Indexed: 12/17/2022] Open
Abstract
Children acquire attention skills rapidly during early childhood as their brains undergo vast neural development. Attention is well studied in the adult brain, yet due to the challenges associated with scanning young children, investigations in early childhood are sparse. Here, we examined the relationship between age, attention and functional connectivity (FC) during passive viewing in multiple intrinsic connectivity networks (ICNs) in 60 typically developing girls between 4 and 7 years whose sustained, selective and executive attention skills were assessed. Visual, auditory, sensorimotor, default mode (DMN), dorsal attention (DAN), ventral attention (VAN), salience, and frontoparietal ICNs were identified via Independent Component Analysis and subjected to a dual regression. Individual spatial maps were regressed against age and attention skills, controlling for age. All ICNs except the VAN showed regions of increasing FC with age. Attention skills were associated with FC in distinct networks after controlling for age: selective attention positively related to FC in the DAN; sustained attention positively related to FC in visual and auditory ICNs; and executive attention positively related to FC in the DMN and visual ICN. These findings suggest distributed network integration across this age range and highlight how multiple ICNs contribute to attention skills in early childhood.
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Affiliation(s)
- Christiane S Rohr
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Anish Arora
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ivy Y K Cho
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Prayash Katlariwala
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Dennis Dimond
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Deborah Dewey
- Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Signe Bray
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
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49
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Long X, Little G, Beaulieu C, Lebel C. Sensorimotor network alterations in children and youth with prenatal alcohol exposure. Hum Brain Mapp 2018; 39:2258-2268. [PMID: 29436054 DOI: 10.1002/hbm.24004] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 01/30/2018] [Accepted: 02/05/2018] [Indexed: 01/06/2023] Open
Abstract
Children with prenatal alcohol exposure (PAE) often have impaired sensorimotor function. While altered brain structure has been noted in sensorimotor areas, the functional brain alterations remain unclear. This study aims to investigate sensorimotor brain networks in children and youth with PAE using resting-state functional magnetic resonance imaging (rs-fMRI). A parcellation-based network analysis was performed to identify brain networks related to hand/lower limb and face/upper limb function in 59 children and youth with PAE and 50 typically developing controls. Participants with PAE and controls had similar organization of the hand and face areas within the primary sensorimotor cortex, but participants with PAE had altered functional connectivity (FC) between the sensorimotor regions and the rest of the brain. The sensorimotor regions in the PAE group showed less connectivity to certain hubs of the default mode network and more connectivity to areas of the salience network. Overall, our results show that despite similar patterns of organization in the sensorimotor network, subjects with PAE have increased FC between this network and other brain areas, perhaps suggesting overcompensation. These alterations in the sensorimotor network lay the foundation for future studies to evaluate interventions and treatments to improve motor function in children with PAE.
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Affiliation(s)
- Xiangyu Long
- Department of Radiology, and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Graham Little
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Catherine Lebel
- Department of Radiology, and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
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50
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Chen Y, Zhao X, Zhang X, Liu Y, Zhou P, Ni H, Ma J, Ming D. Age-related early/late variations of functional connectivity across the human lifespan. Neuroradiology 2018; 60:403-412. [PMID: 29383434 DOI: 10.1007/s00234-017-1973-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Accepted: 12/28/2017] [Indexed: 12/18/2022]
Abstract
PURPOSE Many questions remain regarding how the brain develops, matures, and ages across the lifespan. The functional connectivity networks in the resting-state brain can reflect many of the characteristic changes in the brain that are associated with increasing age. Functional connectivity has been shown to be time-dependent over the course of a lifespan and even over the course of minutes. The lifespan strategies of all cognitive networks and how dynamic functional connectivity is associated with age are unclear. METHODS In this paper, studies employing both linear and quadratic models to define new specific lifespan strategies, including early/late increase/decrease models, were conducted to explore the lifespan functional changes. A large data sample was retrieved from the publicly available data from the Nathan Kline Institute (N = 149 and ages 9-85). Both static and dynamic functional connectivity indexes were calculated including the static functional connectivity, the mean of the dynamic functional connectivity and variations in dynamic functional connectivity. RESULTS The between-network connectivity results revealed early increases in the default-mode (DF) and cingulo-opercular network (CO)-associated network connectivities and a late increase in the fronto-parietal (FP)-associated network connectivity. These results depicted various lifespan strategies for different development stages and different cognitive networks across the lifespan. Additionally, the static FC and mean dynamic FC exhibited consistent results, and their variation exhibited a constant decrease with age across the entire age range. CONCLUSION These results (FDR-corrected p value < 0.05) suggest that the early/late variations in lifespan strategies could reflect an association between varied and complex circumstances and brain development.
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Affiliation(s)
- Yuanyuan Chen
- College of Microelectronics, Tianjin University, Tianjin, China.,Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Xin Zhao
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xiong Zhang
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Ya'nan Liu
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Peng Zhou
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Hongyan Ni
- Department of Radiology, Tianjin First Center Hospital, Tianjin, China
| | - Jianguo Ma
- College of Microelectronics, Tianjin University, Tianjin, China
| | - Dong Ming
- Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China. .,Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
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