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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol K, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Christopher Edgar J. Functional and structural maturation of auditory cortex from 2 months to 2 years old. Clin Neurophysiol 2024; 166:232-243. [PMID: 39213880 DOI: 10.1016/j.clinph.2024.08.007] [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] [Received: 06/13/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. METHODS AND PARTICIPANTS The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints. RESULTS In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. CONCLUSIONS Findings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency. SIGNIFICANCE Infant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jeffrey I Berman
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mary E Putt
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katharina Otten
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Faculty of Medicine, RWTH Aachen University, Aachen, 52074, Germany
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Tess Yount
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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DiPiero MA, Rodrigues PG, Justman M, Roche S, Bond E, Gonzalez JG, Davidson RJ, Planalp EM, Dean DC. Gray matter based spatial statistics framework in the 1-month brain: insights into gray matter microstructure in infancy. Brain Struct Funct 2024:10.1007/s00429-024-02853-w. [PMID: 39313671 DOI: 10.1007/s00429-024-02853-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024]
Abstract
The neurodevelopmental epoch from fetal stages to early life embodies a critical window of peak growth and plasticity in which differences believed to be associated with many neurodevelopmental and psychiatric disorders first emerge. Obtaining a detailed understanding of the developmental trajectories of the cortical gray matter microstructure is necessary to characterize differential patterns of neurodevelopment that may subserve future intellectual, behavioral, and psychiatric challenges. The neurite orientation dispersion density imaging (NODDI) Gray-Matter Based Spatial Statistics (GBSS) framework leverages information from the NODDI model to enable sensitive characterization of the gray matter microstructure while limiting partial volume contamination and misregistration errors between images collected in different spaces. However, limited contrast of the underdeveloped brain poses challenges for implementing this framework with infant diffusion MRI (dMRI) data. In this work, we aim to examine the development of cortical microstructure in infants. We utilize the NODDI GBSS framework and propose refinements to the original framework that aim to improve the delineation and characterization of gray matter in the infant brain. Taking this approach, we cross-sectionally investigate age relationships in the developing gray matter microstructural organization in infants within the first month of life and reveal widespread relationships with the gray matter architecture.
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Affiliation(s)
- Marissa A DiPiero
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | | | - McKaylie Justman
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Sophia Roche
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Elizabeth Bond
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Jose Guerrero Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard J Davidson
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth M Planalp
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA.
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA.
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Blanchett R, Chen H, Vlasova RM, Cornea E, Maza M, Davenport M, Reinhartsen D, DeRamus M, Edmondson Pretzel R, Gilmore JH, Hooper SR, Styner MA, Gao W, Knickmeyer RC. White matter microstructure and functional connectivity in the brains of infants with Turner syndrome. Cereb Cortex 2024; 34:bhae351. [PMID: 39256896 PMCID: PMC11387115 DOI: 10.1093/cercor/bhae351] [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: 07/03/2023] [Revised: 08/01/2024] [Accepted: 08/13/2024] [Indexed: 09/12/2024] Open
Abstract
Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.
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Affiliation(s)
- Reid Blanchett
- Genetics and Genome Sciences, Michigan State University, Biomedical & Physical Sciences, Room 2165, East Lansing, MI 48824, United States
- Department of Epigenetics, Van Andel Research Institute, 33 Bostwick Ave NE, Grand Rapids, MI 49503, United States
| | - Haitao Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Roza M Vlasova
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Emil Cornea
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Maria Maza
- Department of Psychology and Neuroscience, Campus Box #3270, 235 E. Cameron Avenue, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Marsha Davenport
- Department of Pediatrics, 333 South Columbia Street, Suite 260 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Debra Reinhartsen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Margaret DeRamus
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Rebecca Edmondson Pretzel
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - John H Gilmore
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Stephen R Hooper
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Health Sciences, Bondurant Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Martin A Styner
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Computer Science, Campus Box 3175, Brooks Computer Science Building, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Rebecca C Knickmeyer
- Department of Pediatrics and Human Development, Life Sciences Bldg. 1355 Bogue, #B240B, Michigan State University, East Lansing, MI 48824, United States
- Institute for Quantitative Health Sciences and Engineering, Room 2114, 775 Woodlot Dr., East Lansing, MI 48824, United States
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Demers CH, Hankin BL, Haase MH, Todd E, Hoffman MC, Epperson CN, Styner MA, Davis EP. Maternal adverse childhood experiences and infant visual-limbic white matter development. J Affect Disord 2024; 367:49-57. [PMID: 39191307 DOI: 10.1016/j.jad.2024.08.146] [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: 05/02/2024] [Revised: 08/06/2024] [Accepted: 08/23/2024] [Indexed: 08/29/2024]
Abstract
BACKGROUND Maternal adverse childhood experiences (ACEs) are robust predictors of mental health for both the exposed individual and the next generation; however, the pathway through which such intergenerational risk is conferred remains unknown. The current study evaluated the association between maternal ACEs and infant brain development, including an a priori focus on circuits implicated in emotional and sensory processing. METHODS The sample included 101 mother-infant dyads from a longitudinal study. Maternal ACEs were assessed with the Adverse Childhood Questionnaire dichotomized into low (0 or 1) and high (≥2) groups. White matter microstructure, as indexed by fractional anisotropy (FA), was assessed using structural magnetic resonance imaging in infants (41.6-46.0 weeks' postconceptional age) within a priori tracts (the cingulum, fornix, uncinate, inferior frontal occipital fasciculus, and inferior longitudinal fasciculus). Exploratory analyses were also conducted across the whole brain. RESULTS High maternal ACEs (≥2) were associated with decreased infant left inferior longitudinal fasciculus (ILF) FA (F(1,94) = 7.78, p < .006) relative to infants of low ACE mothers. No group difference was observed within the right ILF following correction for multiple comparisons (F(1,95) = 4.29, p < .041). Follow-up analyses within the left ILF demonstrated associations between high maternal ACEs and increased left radial diffusivity (F(1,95) = 5.10, p < .006). Exploratory analyses demonstrated preliminary support for differences in visual processing networks (e.g., optic tract) as well as additional circuits less frequently examined in the context of early life adversity exposure (e.g., corticothalamic tract). CONCLUSIONS Maternal ACEs predict neural circuit development of the inferior longitudinal fasciculus. Findings suggest that early developing sensory circuits within the infant brain are susceptible to maternal adverse childhood experiences and may have implications for the maturation of higher-order emotional and cognitive circuits.
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Affiliation(s)
- Catherine H Demers
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America; Department of Psychology, University of Denver, Denver, CO, United States of America.
| | - Benjamin L Hankin
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, United States of America
| | - Mercedes Hoeflich Haase
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Erin Todd
- Department of Psychology, University of Denver, Denver, CO, United States of America
| | - M Camille Hoffman
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America; Department of Obstetrics and Gynecology, Division of Maternal and Fetal Medicine, University of Colorado Denver School of Medicine, Aurora, CO, United States of America
| | - C Neill Epperson
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Elysia Poggi Davis
- Department of Psychology, University of Denver, Denver, CO, United States of America; Department of Psychiatry and Human Behavior, University of California, Irvine, CA, United States of America
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Chan SY, Fitzgerald E, Ngoh ZM, Lee J, Chuah J, Chia JSM, Fortier MV, Tham EH, Zhou JH, Silveira PP, Meaney MJ, Tan AP. Examining the associations between microglia genetic capacity, early life exposures and white matter development at the level of the individual. Brain Behav Immun 2024; 119:781-791. [PMID: 38677627 DOI: 10.1016/j.bbi.2024.04.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/17/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024] Open
Abstract
There are inter-individual differences in susceptibility to the influence of early life experiences for which the underlying neurobiological mechanisms are poorly understood. Microglia play a role in environmental surveillance and may influence individual susceptibility to environmental factors. As an index of neurodevelopment, we estimated individual slopes of mean white matter fractional anisotropy (WM-FA) across three time-points (age 4.5, 6.0, and 7.5 years) for 351 participants. Individual variation in microglia reactivity was derived from an expression-based polygenic score(ePGS) comprised of Single Nucleotide Polymorphisms (SNPs) functionally related to the expression of microglia-enriched genes.A higher ePGS denotes an increased genetic capacity for the expression of microglia-related genes, and thus may confer a greater capacity to respond to the early environment and to influence brain development. We hypothesized that this ePGS would associate with the WM-FA index of neurodevelopment and moderate the influence of early environmental factors.Our findings show sex dependency, where a significant association between WM-FA and microglia ePGS was only obtained for females.We then examined associations with perinatal factors known to decrease (optimal birth outcomes and familial conditions) or increase (systemic inflammation) the risk for later mental health problems.In females, individuals with high microglia ePGS showed a negative association between systemic inflammation and WM-FA and a positive association between more advantageous environmental conditions and WM-FA. The microglia ePGS in females thus accounted for variations in the influence of the quality of the early environment on WM-FA.Finally, WM-FA slopes mediated the association of microglia ePGS with interpersonal problems and social hostility in females. Our findings suggest the genetic capacity for microglia function as a potential factor underlying differential susceptibility to early life exposuresthrough influences on neurodevelopment.
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Affiliation(s)
- Shi Yu Chan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Eamon Fitzgerald
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, 1010 Rue Sherbrooke O, QC H3A 2R7, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Janice Lee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Jasmine Chuah
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Joanne S M Chia
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, 100 Bukit Timah Rd, Singapore 229899, Singapore; Duke-NUS Medical School, 8 College Rd, Singapore 169857, Singapore
| | - Elizabeth H Tham
- Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Khoo Teck Puat-National University Children's Medical Institute, National University Health System (NUHS), 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Juan H Zhou
- Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
| | - Patricia P Silveira
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, 1010 Rue Sherbrooke O, QC H3A 2R7, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Brain - Body Initiative Program, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, Connexis North Tower, Singapore 138632, Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Brain - Body Initiative Program, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, Connexis North Tower, Singapore 138632, Singapore; Department of Diagnostic Imaging, National University Health System, 1E Kent Ridge Rd, Singapore 119228, Singapore.
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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol KL, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Edgar JC. Functional and structural maturation of auditory cortex from 2 months to 2 years old. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597426. [PMID: 38895425 PMCID: PMC11185738 DOI: 10.1101/2024.06.05.597426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.
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Nyakonda CN, Wedderburn CJ, Williams SR, Stein DJ, Donald KA. Understanding the impact of congenital infections and perinatal viral exposures on the developing brain using white matter magnetic resonance imaging: a scoping review. BMC Med Imaging 2024; 24:119. [PMID: 38783187 PMCID: PMC11119575 DOI: 10.1186/s12880-024-01282-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Magnetic Resonance Imaging (MRI)-based imaging techniques are useful for assessing white matter (WM) structural and microstructural integrity in the context of infection and inflammation. The purpose of this scoping review was to assess the range of work on the use of WM neuroimaging approaches to understand the impact of congenital and perinatal viral infections or exposures on the developing brain. METHODS This scoping review was conducted according to the Arksey and O' Malley framework. A literature search was performed in Web of Science, Scopus and PubMed for primary research articles published from database conception up to January 2022. Studies evaluating the use of MRI-based WM imaging techniques in congenital and perinatal viral infections or exposures were included. Results were grouped by age and infection. RESULTS A total of 826 articles were identified for screening and 28 final articles were included. Congenital and perinatal infections represented in the included studies were cytomegalovirus (CMV) infection (n = 12), human immunodeficiency virus (HIV) infection (n = 11) or exposure (n = 2) or combined (n = 2), and herpes simplex virus (HSV) infection (n = 1). The represented MRI-based WM imaging methods included structural MRI and diffusion-weighted and diffusion tensor MRI (DWI/ DTI). Regions with the most frequently reported diffusion metric group differences included the cerebellar region, corticospinal tract and association fibre WM tracts in both children with HIV infection and children who are HIV-exposed uninfected. In qualitative imaging studies, WM hyperintensities were the most frequently reported brain abnormality in children with CMV infection and children with HSV infection. CONCLUSION There was evidence that WM imaging techniques can play a role as diagnostic and evaluation tools assessing the impact of congenital infections and perinatal viral exposures on the developing brain. The high sensitivity for identifying WM hyperintensities suggests structural brain MRI is a useful neurodiagnostic modality in assessing children with congenital CMV infection, while the DTI changes associated with HIV suggest metrics such as fractional anisotropy have the potential to be specific markers of subtle impairment or WM damage in neuroHIV.
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Affiliation(s)
- Charmaine Natasha Nyakonda
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Capetown, South Africa.
| | - Catherine J Wedderburn
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK
- Neuroscience Institute, University of Cape Town, Capetown, South Africa
| | - Simone R Williams
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Capetown, South Africa
| | - Dan J Stein
- Department of Psychiatry and Mental Health and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- MRC Unit of Risk and Resilience, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Capetown, South Africa
| | - Kirsten A Donald
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Capetown, South Africa.
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8
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Maw KJ, Beattie G, Burns EJ. Cognitive strengths in neurodevelopmental disorders, conditions and differences: A critical review. Neuropsychologia 2024; 197:108850. [PMID: 38467371 DOI: 10.1016/j.neuropsychologia.2024.108850] [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] [Received: 06/05/2023] [Revised: 03/04/2024] [Accepted: 03/07/2024] [Indexed: 03/13/2024]
Abstract
Neurodevelopmental disorders are traditionally characterised by a range of associated cognitive impairments in, for example, sensory processing, facial recognition, visual imagery, attention, and coordination. In this critical review, we propose a major reframing, highlighting the variety of unique cognitive strengths that people with neurodevelopmental differences can exhibit. These include enhanced visual perception, strong spatial, auditory, and semantic memory, superior empathy and theory of mind, along with higher levels of divergent thinking. Whilst we acknowledge the heterogeneity of cognitive profiles in neurodevelopmental conditions, we present a more encouraging and affirmative perspective of these groups, contrasting with the predominant, deficit-based position prevalent throughout both cognitive and neuropsychological research. In addition, we provide a theoretical basis and rationale for these cognitive strengths, arguing for the critical role of hereditability, behavioural adaptation, neuronal-recycling, and we draw on psychopharmacological and social explanations. We present a table of potential strengths across conditions and invite researchers to systematically investigate these in their future work. This should help reduce the stigma around neurodiversity, instead promoting greater social inclusion and significant societal benefits.
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Hong Y, Cornea E, Girault JB, Bagonis M, Foster M, Kim SH, Prieto JC, Chen H, Gao W, Styner MA, Gilmore JH. Structural and functional connectome relationships in early childhood. Dev Cogn Neurosci 2023; 64:101314. [PMID: 37898019 PMCID: PMC10630618 DOI: 10.1016/j.dcn.2023.101314] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/27/2023] [Accepted: 10/12/2023] [Indexed: 10/30/2023] Open
Abstract
There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual's functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.
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Affiliation(s)
- Yoonmi Hong
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America.
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, United States of America
| | - Maria Bagonis
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
| | - Mark Foster
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
| | - Sun Hyung Kim
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
| | - Juan Carlos Prieto
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
| | - Haitao Chen
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, United States of America
| | - Wei Gao
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, United States of America
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America; Department of Computer Science, University of North Carolina at Chapel Hill, United States of America
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, United States of America
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10
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De Benedictis A, Rossi-Espagnet MC, de Palma L, Sarubbo S, Marras CE. Structural networking of the developing brain: from maturation to neurosurgical implications. Front Neuroanat 2023; 17:1242757. [PMID: 38099209 PMCID: PMC10719860 DOI: 10.3389/fnana.2023.1242757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023] Open
Abstract
Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.
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Affiliation(s)
| | | | - Luca de Palma
- Clinical and Experimental Neurology, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Silvio Sarubbo
- Department of Neurosurgery, Santa Chiara Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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11
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Bagonis M, Cornea E, Girault JB, Stephens RL, Kim S, Prieto JC, Styner M, Gilmore JH. Early Childhood Development of Node Centrality in the White Matter Connectome and Its Relationship to IQ at Age 6 Years. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1024-1032. [PMID: 36162754 PMCID: PMC10033460 DOI: 10.1016/j.bpsc.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND The white matter (WM) connectome is important for cognitive development and intelligence and is altered in neuropsychiatric illnesses. Little is known about how the WM connectome develops or its relationship to IQ in early childhood. METHODS The development of node centrality in the WM connectome was studied in a longitudinal cohort of 226 (123 female) children from the University of North Carolina Early Brain Development Study. Structural and diffusion-weighted images were acquired after birth and at 1, 2, 4, and 6 years, and IQ was assessed at 6 years. Eigenvector centrality, betweenness centrality, and the global graph metrics of global efficiency, small worldness, and modularity were determined at each age. RESULTS The greatest developmental change in eigenvector centrality and betweenness centrality occurred during the first year of life, with relative stability between ages 1 and 6 years. Most of the high-centrality hubs at age 6 were also high-centrality hubs at 1 year, and many were already high-centrality hubs at birth. There were generally small but significant changes in global efficiency and modularity from birth to 6 years, while small worldness increased between 2 and 4 years. Individual node centrality was not significantly correlated with IQ at 6 years. CONCLUSIONS Node centrality in the WM connectome is established very early in childhood and is relatively stable from age 1 to 6 years. Many high-centrality hubs are established before birth, and most are present by age 1.
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Affiliation(s)
- Maria Bagonis
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Rebecca L Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - SunHyung Kim
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Juan Carlos Prieto
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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12
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Grotheer M, Bloom D, Kruper J, Richie-Halford A, Zika S, Aguilera González VA, Yeatman JD, Grill-Spector K, Rokem A. Human white matter myelinates faster in utero than ex utero. Proc Natl Acad Sci U S A 2023; 120:e2303491120. [PMID: 37549280 PMCID: PMC10438384 DOI: 10.1073/pnas.2303491120] [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: 03/02/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023] Open
Abstract
The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.
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Affiliation(s)
- Mareike Grotheer
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - David Bloom
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - John Kruper
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Adam Richie-Halford
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Stephanie Zika
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Vicente A. Aguilera González
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Jason D. Yeatman
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
- Graduate School of Education, Stanford University, Stanford, CA94305
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA94305
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
| | - Ariel Rokem
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
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13
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Chen Y, Green HL, Putt ME, Allison O, Kuschner ES, Kim M, Blaskey L, Mol K, McNamee M, Bloy L, Liu S, Huang H, Roberts TPL, Edgar JC. Maturation of auditory cortex neural responses during infancy and toddlerhood. Neuroimage 2023; 275:120163. [PMID: 37178820 DOI: 10.1016/j.neuroimage.2023.120163] [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: 09/28/2022] [Revised: 04/28/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023] Open
Abstract
The infant auditory system rapidly matures across the first years of life, with a primary goal of obtaining ever-more-accurate real-time representations of the external world. Our understanding of how left and right auditory cortex neural processes develop during infancy, however, is meager, with few studies having the statistical power to detect potential hemisphere and sex differences in primary/secondary auditory cortex maturation. Using infant magnetoencephalography (MEG) and a cross-sectional study design, left and right auditory cortex P2m responses to pure tones were examined in 114 typically developing infants and toddlers (66 males, 2 to 24 months). Non-linear maturation of P2m latency was observed, with P2m latencies decreasing rapidly as a function of age during the first year of life, followed by slower changes between 12 and 24 months. Whereas in younger infants auditory tones were encoded more slowly in the left than right hemisphere, similar left and right P2m latencies were observed by ∼21 months of age due to faster maturation rate in the left than right hemisphere. No sex differences in the maturation of the P2m responses were observed. Finally, an earlier left than right hemisphere P2m latency predicted better language performance in older infants (12 to 24 months). Findings indicate the need to consider hemisphere when examining the maturation of auditory cortex neural activity in infants and toddlers and show that the pattern of left-right hemisphere P2m maturation is associated with language performance.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Mary E Putt
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Lisa Blaskey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Hao Huang
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
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14
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Lawton W, Araujo O, Kufaishi Y. Language Environment and Infants' Brain Structure. J Neurosci 2023; 43:5129-5131. [PMID: 37438100 PMCID: PMC10342219 DOI: 10.1523/jneurosci.0787-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/05/2023] [Accepted: 06/08/2023] [Indexed: 07/14/2023] Open
Affiliation(s)
- Will Lawton
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Ozzy Araujo
- Undergraduate Life Sciences Program, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Yousif Kufaishi
- Undergraduate Life Sciences Program, Queen's University, Kingston, Ontario K7L 3N6, Canada
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15
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Kumpulainen V, Merisaari H, Silver E, Copeland A, Pulli EP, Lewis JD, Saukko E, Shulist SJ, Saunavaara J, Parkkola R, Lähdesmäki T, Karlsson L, Karlsson H, Tuulari JJ. Sex differences, asymmetry, and age-related white matter development in infants and 5-year-olds as assessed with tract-based spatial statistics. Hum Brain Mapp 2023; 44:2712-2725. [PMID: 36946076 PMCID: PMC10089102 DOI: 10.1002/hbm.26238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/24/2023] [Accepted: 02/08/2023] [Indexed: 03/23/2023] Open
Abstract
The rapid white matter (WM) maturation of first years of life is followed by slower yet long-lasting development, accompanied by learning of more elaborate skills. By the age of 5 years, behavioural and cognitive differences between females and males, and functions associated with brain lateralization such as language skills are appearing. Diffusion tensor imaging (DTI) can be used to quantify fractional anisotropy (FA) within the WM and increasing values correspond to advancing brain development. To investigate the normal features of WM development during early childhood, we gathered a DTI data set of 166 healthy infants (mean 3.8 wk, range 2-5 wk; 89 males; born on gestational week 36 or later) and 144 healthy children (mean 5.4 years, range 5.1-5.8 years; 76 males). The sex differences, lateralization patterns and age-dependent changes were examined using tract-based spatial statistics (TBSS). In 5-year-olds, females showed higher FA in wide-spread regions in the posterior and the temporal WM and more so in the right hemisphere, while sex differences were not detected in infants. Gestational age showed stronger association with FA values compared to age after birth in infants. Additionally, child age at scan associated positively with FA around the age of 5 years in the body of corpus callosum, the connections of which are important especially for sensory and motor functions. Lastly, asymmetry of WM microstructure was detected already in infants, yet significant changes in lateralization pattern seem to occur during early childhood, and in 5-year-olds the pattern already resembles adult-like WM asymmetry.
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Affiliation(s)
- Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Elmo P Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - John D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Satu J Shulist
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital and University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatric Neurology, Turku University Hospital, University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Paediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & 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 Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital & University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, UK
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16
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Kumpulainen V, Merisaari H, Copeland A, Silver E, Pulli EP, Lewis JD, Saukko E, Saunavaara J, Karlsson L, Karlsson H, Tuulari JJ. Effect of number of diffusion-encoding directions in diffusion metrics of 5-year-olds using tract-based spatial statistical analysis. Eur J Neurosci 2022; 56:4843-4868. [PMID: 35904522 PMCID: PMC9545012 DOI: 10.1111/ejn.15785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 06/21/2022] [Accepted: 07/26/2022] [Indexed: 11/29/2022]
Abstract
Methodological aspects and effects of different imaging parameters on DTI (diffusion tensor imaging) results and their reproducibility have been recently studied comprehensively in adult populations. Although MR imaging of children's brains has become common, less interest has been focussed on researching whether adult-based optimised parameters and pre-processing protocols can be reliably applied to paediatric populations. Furthermore, DTI scalar values of preschool aged children are rarely reported. We gathered a DTI dataset from 5-year-old children (N = 49) to study the effect of the number of diffusion-encoding directions on the reliability of resultant scalar values with TBSS (tract-based spatial statistics) method. Additionally, the potential effect of within-scan head motion on DTI scalars was evaluated. Reducing the number of diffusion-encoding directions deteriorated both the accuracy and the precision of all DTI scalar values. To obtain reliable scalar values, a minimum of 18 directions for TBSS was required. For TBSS fractional anisotropy values, the intraclass correlation coefficient with two-way random-effects model (ICC[2,1]) for the subsets of 6 to 66 directions ranged between 0.136 [95%CI 0.0767;0.227] and 0.639 [0.542;0.740], whereas the corresponding values for subsets of 18 to 66 directions were 0.868 [0.815;0.913] and 0.995 [0.993;0.997]. Following the exclusion of motion-corrupted volumes, minor residual motion did not associate with the scalar values. A minimum of 18 diffusion directions is recommended to result in reliable DTI scalar results with TBSS. We suggest gathering extra directions in paediatric DTI to enable exclusion of volumes with motion artefacts and simultaneously preserve the overall data quality.
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Affiliation(s)
- Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Department of RadiologyTurku University HospitalTurkuFinland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
| | - Elmo P. Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
| | - John D. Lewis
- Montreal Neurological InstituteMcGill UniversityMontrealQuebecCanada
| | | | - Jani Saunavaara
- Department of Medical PhysicsTurku University Hospital and University of TurkuTurkuFinland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Department of Paediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Turku Collegium for Science and MedicineUniversity of TurkuTurkuFinland
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17
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Tsuzuki D, Taga G, Watanabe H, Homae F. Individual variability in the nonlinear development of the corpus callosum during infancy and toddlerhood: a longitudinal MRI analysis. Brain Struct Funct 2022; 227:1995-2013. [PMID: 35396953 DOI: 10.1007/s00429-022-02485-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 03/22/2022] [Indexed: 11/29/2022]
Abstract
The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.
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Affiliation(s)
- Daisuke Tsuzuki
- Department of Language Sciences, Tokyo Metropolitan University, Hachioji, Tokyo, 192-0397, Japan. .,Graduate School of Education, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan.
| | - Gentaro Taga
- Graduate School of Education, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Hama Watanabe
- Graduate School of Education, The University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Fumitaka Homae
- Department of Language Sciences, Tokyo Metropolitan University, Hachioji, Tokyo, 192-0397, Japan.,Research Center for Language, Brain and Genetics, Tokyo Metropolitan University, Hachioji, Tokyo, 192-0397, Japan
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 94] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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19
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Short SJ, Jang DK, Steiner RJ, Stephens RL, Girault JB, Styner M, Gilmore JH. Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations. Front Neurosci 2022; 16:806268. [PMID: 35401073 PMCID: PMC8985548 DOI: 10.3389/fnins.2022.806268] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 01/27/2022] [Indexed: 01/14/2023] Open
Abstract
Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available.
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Affiliation(s)
- Sarah J. Short
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Dae Kun Jang
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
| | - Rachel J. Steiner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rebecca L. Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jessica B. Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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20
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White matter myelination during early infancy is linked to spatial gradients and myelin content at birth. Nat Commun 2022; 13:997. [PMID: 35194018 PMCID: PMC8863985 DOI: 10.1038/s41467-022-28326-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 01/12/2022] [Indexed: 12/25/2022] Open
Abstract
Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.
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21
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Volumetric Segmentation of White Matter Tracts with Label Embedding. Neuroimage 2022; 250:118934. [PMID: 35091078 DOI: 10.1016/j.neuroimage.2022.118934] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 01/04/2022] [Accepted: 01/24/2022] [Indexed: 11/23/2022] Open
Abstract
Convolutional neural networks have achieved state-of-the-art performance for white matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with thin bodies or complicated shapes; the segmentation is even more problematic in challenging scenarios with reduced data quality or domain shift between training and test data, which can be easily encountered in clinical settings. In this work, we seek to improve the segmentation of WM tracts, especially for challenging WM tracts in challenging scenarios. In particular, our method is based on volumetric WM tract segmentation, where voxels are directly labeled without performing tractography. To improve the segmentation, we exploit the characteristics of WM tracts that different tracts can cross or overlap and revise the network design accordingly. Specifically, because multiple tracts can co-exist in a voxel, we hypothesize that the different tract labels can be correlated. The tract labels at a single voxel are concatenated as a label vector, the length of which is the number of tract labels. Due to the tract correlation, this label vector can be projected into a lower-dimensional space-referred to as the embedded space-for each voxel, which allows the segmentation network to solve a simpler problem. By predicting the coordinate in the embedded space for the tracts at each voxel and subsequently mapping the coordinate to the label vector with a reconstruction module, the segmentation result can be achieved. To facilitate the learning of the embedded space, an auxiliary label reconstruction loss is integrated with the segmentation accuracy loss during network training, and network training and inference are end-to-end. Our method was validated on two dMRI datasets under various settings. The results show that the proposed method improves the accuracy of WM tract segmentation, and the improvement is more prominent for challenging tracts in challenging scenarios.
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22
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Demers CH, Bagonis MM, Al-Ali K, Garcia SE, Styner MA, Gilmore JH, Hoffman MC, Hankin BL, Davis EP. Exposure to prenatal maternal distress and infant white matter neurodevelopment. Dev Psychopathol 2021; 33:1526-1538. [PMID: 35586027 PMCID: PMC9109943 DOI: 10.1017/s0954579421000742] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The prenatal period represents a critical time for brain growth and development. These rapid neurological advances render the fetus susceptible to various influences with life-long implications for mental health. Maternal distress signals are a dominant early life influence, contributing to birth outcomes and risk for offspring psychopathology. This prospective longitudinal study evaluated the association between prenatal maternal distress and infant white matter microstructure. Participants included a racially and socioeconomically diverse sample of 85 mother-infant dyads. Prenatal distress was assessed at 17 and 29 weeks' gestational age (GA). Infant structural data were collected via diffusion tensor imaging at 42-45 weeks' postconceptional age. Findings demonstrated that higher prenatal maternal distress at 29 weeks' GA was associated with increased fractional anisotropy (b = .283, t(64) = 2.319, p = .024) and with increased axial diffusivity (b = .254, t(64) = 2.067, p = .043) within the right anterior cingulate white matter tract. No other significant associations were found with prenatal distress exposure and tract fractional anisotropy or axial diffusivity at 29 weeks' GA, nor earlier in gestation.
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Affiliation(s)
- Catherine H. Demers
- Department of Psychology University of Denver, Denver CO,
USA
- Department of Psychiatry, University of Colorado Anschutz
Medical Campus, Aurora CO, USA
| | - Maria M. Bagonis
- Department of Psychiatry, University of North Carolina at
Chapel Hill, Chapel Hill NC, USA
| | - Khalid Al-Ali
- Department of Psychiatry, University of North Carolina at
Chapel Hill, Chapel Hill NC, USA
| | - Sarah E. Garcia
- Department of Psychology University of Denver, Denver CO,
USA
| | - Martin A. Styner
- Department of Psychiatry, University of North Carolina at
Chapel Hill, Chapel Hill NC, USA
- Department of Computer Science, University of North
Carolina at Chapel Hill, Chapel Hill NC, USA
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at
Chapel Hill, Chapel Hill NC, USA
| | - M. Camille Hoffman
- Department of Psychiatry, University of Colorado Anschutz
Medical Campus, Aurora CO, USA
- Department of Obstetrics and Gynecology, Division of
Maternal and Fetal Medicine, University of Colorado Denver School of Medicine,
Aurora, Colorado, USA
| | - Benjamin L. Hankin
- Department of Psychology, University of Illinois at
Urbana-Champaign, Champaign IL, USA
| | - Elysia Poggi Davis
- Department of Psychology University of Denver, Denver CO,
USA
- Department of Psychiatry and Human Behavior, University of
California, Irvine, CA, USA
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