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Sheng Y, Wang Y, Wang X, Zhang Z, Zhu D, Zheng W. No sex difference in maturation of brain morphology during the perinatal period. Brain Struct Funct 2024:10.1007/s00429-024-02828-x. [PMID: 39020216 DOI: 10.1007/s00429-024-02828-x] [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: 02/23/2024] [Accepted: 07/04/2024] [Indexed: 07/19/2024]
Abstract
Accumulating evidence have documented sex differences in brain anatomy from early childhood to late adulthood. However, whether sex difference of brain structure emerges in the neonatal brain and how sex modulates the development of cortical morphology during the perinatal stage remains unclear. Here, we utilized T2-weighted MRI from the Developing Human Connectome Project (dHCP) database, consisting of 41 male and 40 female neonates born between 35 and 43 postmenstrual weeks (PMW). Neonates of each sex were arranged in a continuous ascending order of age to capture the progressive changes in cortical thickness and curvature throughout the developmental continuum. The maturational covariance network (MCN) was defined as the coupled developmental fluctuations of morphology measures between cortical regions. We constructed MCNs based on the two features, respectively, to illustrate their developmental interdependencies, and then compared the network topology between sexes. Our results showed that cortical structural development exhibited a localized pattern in both males and females, with no significant sex differences in the developmental trajectory of cortical morphology, overall organization, nodal importance, and modular structure of the MCN. Furthermore, by merging male and female neonates into a unified cohort, we identified evident dependencies influences in structural development between different brain modules using the Granger causality analysis (GCA), emanating from high-order regions toward primary cortices. Our findings demonstrate that the maturational pattern of cortical morphology may not differ between sexes during the perinatal period, and provide evidence for the developmental causality among cortical structures in perinatal brains.
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Affiliation(s)
- Yucen Sheng
- School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou, People's Republic of China
| | - Ying Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, People's Republic of China
| | - Xiaomin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, People's Republic of China
| | - Zhe Zhang
- Institute of Brain Science, Hangzhou Normal University, Hangzhou, People's Republic of China
| | - Dalin Zhu
- Department of Medical Imaging Center, Gansu Provincial Maternity and Child-Care Hospital Lanzhou, Lanzhou, People's Republic of China.
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, People's Republic of China.
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2
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Torgerson C, Ahmadi H, Choupan J, Fan CC, Blosnich JR, Herting MM. Sex, gender diversity, and brain structure in early adolescence. Hum Brain Mapp 2024; 45:e26671. [PMID: 38590252 PMCID: PMC11002534 DOI: 10.1002/hbm.26671] [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: 07/28/2023] [Revised: 02/27/2024] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.
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Affiliation(s)
- Carinna Torgerson
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Hedyeh Ahmadi
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Jeiran Choupan
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Chun Chieh Fan
- Center for Population Neuroscience and GeneticsLaureate Institute for Brain ResearchTulsaOklahomaUSA
- Department of Radiology, School of MedicineUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - John R. Blosnich
- Suzanne Dworak‐Peck School of Social WorkUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Megan M. Herting
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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3
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Cornwell H, Toschi N, Hamilton-Giachritsis C, Staginnus M, Smaragdi A, Gonzalez-Madruga K, Mackes N, Rogers J, Martinelli A, Kohls G, Raschle NM, Konrad K, Stadler C, Freitag CM, De Brito SA, Fairchild G. Identifying cortical structure markers of resilience to adversity in young people using surface-based morphometry. Soc Cogn Affect Neurosci 2024; 19:nsae006. [PMID: 38287706 PMCID: PMC10868125 DOI: 10.1093/scan/nsae006] [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: 06/26/2023] [Revised: 11/28/2023] [Accepted: 01/23/2024] [Indexed: 01/31/2024] Open
Abstract
Previous research on the neurobiological bases of resilience in youth has largely used categorical definitions of resilience and voxel-based morphometry methods that assess gray matter volume. However, it is important to consider brain structure more broadly as different cortical properties have distinct developmental trajectories. To address these limitations, we used surface-based morphometry and data-driven, continuous resilience scores to examine associations between resilience and cortical structure. Structural MRI data from 286 youths (Mage = 13.6 years, 51% female) who took part in the European multi-site FemNAT-CD study were pre-processed and analyzed using surface-based morphometry. Continuous resilience scores were derived for each participant based on adversity exposure and levels of psychopathology using the residual regression method. Vertex-wise analyses assessed for correlations between resilience scores and cortical thickness, surface area, gyrification and volume. Resilience scores were positively associated with right lateral occipital surface area and right superior frontal gyrification and negatively correlated with left inferior temporal surface area. Moreover, sex-by-resilience interactions were observed for gyrification in frontal and temporal regions. Our findings extend previous research by revealing that resilience is related to surface area and gyrification in frontal, occipital and temporal regions that are implicated in emotion regulation and face or object recognition.
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Affiliation(s)
- Harriet Cornwell
- Department of Psychology, University of Bath, 10 West, Claverton Down, Bath, Somerset BA2 7AY, UK
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome ‘Tor Vergata’, Facoltà di Medicina e Chirurgia, Viale Montpellier, Rome 1 – 00133, Italy
- Martinos Center for Biomedical Imaging and Harvard Medical School, 149 13th Street Charlestown, Boston, MA 02129, USA
| | | | - Marlene Staginnus
- Department of Psychology, University of Bath, 10 West, Claverton Down, Bath, Somerset BA2 7AY, UK
| | - Areti Smaragdi
- Child Development Institute, 197 Euclid Ave., Toronto, Ontario, M6J 2J8, Canada
| | - Karen Gonzalez-Madruga
- Department of Psychology, Middlesex University, The Burroughs, Hendon, London NW4 4BT, UK
| | - Nuria Mackes
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, De Crespigny Park, London SE5 8AF, UK
| | - Jack Rogers
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Anne Martinelli
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstrasse 50, Frankfurt am Main 60528, Germany
- Fresenius University of Applied Sciences, School of Psychology, Marienburgstrasse 6, Frankfurt am Main 60528, Germany
| | - Gregor Kohls
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, RWTH Aachen, Pauwelsstrasse 30, Aachen 52074, Germany
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Fetscherstrasse 74, Dresden 01307, Germany
| | - Nora Maria Raschle
- Department of Child and Adolescent Psychiatry, University of Basel, Psychiatric University Hospital, Wilhelm Klein-Strasse 27, Basel 4002, Switzerland
- Jacobs Center for Productive Youth Development at the University of Zurich, Andreasstrasse 15, Zurich 8050, Switzerland
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, RWTH Aachen, Pauwelsstrasse 30, Aachen 52074, Germany
- JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging, RWTH Aachen and Research Centre Juelich, Wilhelm-Johnen-Straße, Juelich 52425, Germany
| | - Christina Stadler
- Department of Child and Adolescent Psychiatry, University of Basel, Psychiatric University Hospital, Wilhelm Klein-Strasse 27, Basel 4002, Switzerland
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstrasse 50, Frankfurt am Main 60528, Germany
| | - Stephane A De Brito
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Graeme Fairchild
- Department of Psychology, University of Bath, 10 West, Claverton Down, Bath, Somerset BA2 7AY, UK
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4
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Andescavage N, Lu YC, Wu Y, Kapse K, Keller J, Von Kohorn I, Afifi A, Vezina G, Henderson D, Wessel DL, du Plessis AJ, Limperopoulos C. Intrauterine exposure to SARS-CoV-2 infection and early newborn brain development. Cereb Cortex 2024; 34:bhae041. [PMID: 38385890 PMCID: PMC10883413 DOI: 10.1093/cercor/bhae041] [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: 10/30/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 02/23/2024] Open
Abstract
Epidemiologic studies suggest that prenatal exposures to certain viruses may influence early neurodevelopment, predisposing offspring to neuropsychiatric conditions later in life. The long-term effects of maternal COVID-19 infection in pregnancy on early brain development, however, remain largely unknown. We prospectively enrolled infants in an observational cohort study for a single-site study in the Washington, DC Metropolitan Area from June 2020 to November 2021 and compared these infants to pre-pandemic controls (studied March 2014-February 2020). The primary outcomes are measures of cortical morphometry (tissue-specific volumes), along with global and regional measures of local gyrification index, and sulcal depth. We studied 210 infants (55 infants of COVID-19 unexposed mothers, 47 infants of COVID-19-positive mothers, and 108 pre-pandemic healthy controls). We found increased cortical gray matter volume (182.45 ± 4.81 vs. 167.29 ± 2.92) and accelerated sulcal depth of the frontal lobe (5.01 ± 0.19 vs. 4.40 ± 0.13) in infants of COVID-19-positive mothers compared to controls. We found additional differences in infants of COVID-19 unexposed mothers, suggesting both maternal viral exposures, as well as non-viral stressors associated with the pandemic, may influence early development and warrant ongoing follow-up.
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Affiliation(s)
- Nickie Andescavage
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
- Division of Neonatology, Children’s National Hospital, 111 Michigavn Ave. NW, Washington, DC 20010, United States
- Department of Pediatrics, School of Medicine and Health Sciences, George Washington University, 2300 Eye St. NW Washington, DC 20052, United States
| | - Yuan-Chiao Lu
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Yao Wu
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Kushal Kapse
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Jennifer Keller
- Department of Obstetrics and Gynecology, School of Medicine and Health Sciences, George Washington University, 2300 Eye Ste. NW, Washington, DC 20052, United States
| | - Isabelle Von Kohorn
- Department of Neonatology, Holy Cross Hospital, 1500 Forest Glen Rd. Silver Spring, MD 20910, United States
| | - Ashraf Afifi
- Department of Hospital-Based Regional Neonatology at Woodbridge, Children’s National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Gilbert Vezina
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Deidtra Henderson
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - David L Wessel
- Department of Pediatrics, School of Medicine and Health Sciences, George Washington University, 2300 Eye St. NW Washington, DC 20052, United States
- Critical Care Medicine, Children’s National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
| | - Adre J du Plessis
- Department of Pediatrics, School of Medicine and Health Sciences, George Washington University, 2300 Eye St. NW Washington, DC 20052, United States
- Prenatal Pediatrics Institute, Children’s National Hospital, 111 Michigan Ave. NW Washington, DC 20010, United States
| | - Catherine Limperopoulos
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC 20010, United States
- Department of Pediatrics, School of Medicine and Health Sciences, George Washington University, 2300 Eye St. NW Washington, DC 20052, United States
- Prenatal Pediatrics Institute, Children’s National Hospital, 111 Michigan Ave. NW Washington, DC 20010, United States
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5
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Napolitano A, Guerrera S, Lucignani M, Parrillo C, Baldassari G, Bottino F, Moltoni G, Espagnet MCR, Talamanca LF, Valeri G, Vicari S. Assessing cortical features in early stage ASD children. Front Psychiatry 2024; 14:1098265. [PMID: 38268563 PMCID: PMC10806120 DOI: 10.3389/fpsyt.2023.1098265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 12/15/2023] [Indexed: 01/26/2024] Open
Abstract
Autism Spectrum Disorder (ASD) is defined as a neurodevelopmental disorder largely investigated in the neurologic field. Recently, neuroimaging studies have been conducted in order to investigate cerebral morphologic alterations in ASD patients, demonstrating an atypical brain development before the clinical manifestations of the disorder. Cortical Thickness (CT) and Local Gyrification Index (LGI) distribution for ASD children were investigated in this study, with the aim to evaluate possible relationship between brain measures and individual characteristics (i.e., IQ and verbal ability). 3D T1-w sequences from 129 ASD and 58 age-matched Healthy Controls (HC) were acquired and processed in order to assess CT and LGI for each subject. Intergroup differences between ASD and HC were investigated, including analyses of 2 ASD subgroups, split according to patient verbal ability and IQ. When compared to HC, ASD showed increased CT and LGI within several brain areas, both as an overall group and as verbal ability an IQ subgroups. Moreover, when comparing language characteristics of the ASD subjects, those patients with verbal ability exhibit significant CT and LGI increase was found within the occipital lobe of right hemisphere. No significant results occurred when comparing ASD patients according to their IQ value. These results support the hypothesis of abnormal brain maturation in ASD since early childhood with differences among clinical subgroups suggesting different anatomical substrates underlying an aberrant connectivity.
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Affiliation(s)
- Antonio Napolitano
- Medical Physics Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Silvia Guerrera
- Neuroscience Department, Child Neuropsychiatric Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Martina Lucignani
- Medical Physics Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Chiara Parrillo
- Medical Physics Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Giulia Baldassari
- Medical Physics Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Francesca Bottino
- Medical Physics Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Giulia Moltoni
- Imaging Department, Neuroradiology Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
- Department of Neuroradiology, NEMOS S. Andrea Hospital, University Sapienza, Rome, Italy
| | | | - Lorenzo Figà Talamanca
- Imaging Department, Neuroradiology Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Giovanni Valeri
- Child and Adolescent Neuropsychiatry Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Stefano Vicari
- Child and Adolescent Neuropsychiatry Unit, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
- Department of Life Science and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
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6
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Duan D, Wen D. MRI-based structural covariance network in early human brain development. Front Neurosci 2023; 17:1302069. [PMID: 38027513 PMCID: PMC10646325 DOI: 10.3389/fnins.2023.1302069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Affiliation(s)
- Dingna Duan
- 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
| | - Dong Wen
- School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China
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7
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Huang Y, Wu Z, Li T, Wang X, Wang Y, Xing L, Zhu H, Lin W, Wang L, Guo L, Gilmore JH, Li G. Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains. J Neurosci 2023; 43:6010-6020. [PMID: 37369585 PMCID: PMC10451118 DOI: 10.1523/jneurosci.1841-22.2023] [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: 09/26/2022] [Revised: 06/05/2023] [Accepted: 06/10/2023] [Indexed: 06/29/2023] Open
Abstract
Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology.SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development.
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Affiliation(s)
- Ying Huang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Tengfei Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27516
| | - Ya Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Lei Xing
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27516
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an, Shaanxi 710129, China
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
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8
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Wang F, Zhang H, Wu Z, Hu D, Zhou Z, Girault JB, Wang L, Lin W, Li G. Fine-grained functional parcellation maps of the infant cerebral cortex. eLife 2023; 12:e75401. [PMID: 37526293 PMCID: PMC10393291 DOI: 10.7554/elife.75401] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 07/17/2023] [Indexed: 08/02/2023] Open
Abstract
Resting-state functional MRI (rs-fMRI) is widely used to examine the dynamic brain functional development of infants, but these studies typically require precise cortical parcellation maps, which cannot be directly borrowed from adult-based functional parcellation maps due to the substantial differences in functional brain organization between infants and adults. Creating infant-specific cortical parcellation maps is thus highly desired but remains challenging due to difficulties in acquiring and processing infant brain MRIs. In this study, we leveraged 1064 high-resolution longitudinal rs-fMRIs from 197 typically developing infants and toddlers from birth to 24 months who participated in the Baby Connectome Project to develop the first set of infant-specific, fine-grained, surface-based cortical functional parcellation maps. To establish meaningful cortical functional correspondence across individuals, we performed cortical co-registration using both the cortical folding geometric features and the local gradient of functional connectivity (FC). Then we generated both age-related and age-independent cortical parcellation maps with over 800 fine-grained parcels during infancy based on aligned and averaged local gradient maps of FC across individuals. These parcellation maps reveal complex functional developmental patterns, such as changes in local gradient, network size, and local efficiency, especially during the first 9 postnatal months. Our generated fine-grained infant cortical functional parcellation maps are publicly available at https://www.nitrc.org/projects/infantsurfatlas/ for advancing the pediatric neuroimaging field.
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Affiliation(s)
- Fan Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anChina
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Han Zhang
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Dan Hu
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Zhen Zhou
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Jessica B Girault
- Department of Psychiatry, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, the University of North Carolina at Chapel HillChapel HillUnited States
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9
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Torgerson C, Ahmadi H, Choupan J, Fan CC, Blosnich JR, Herting MM. Sex, gender diversity, and brain structure in children ages 9 to 11 years old. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.28.551036. [PMID: 37546960 PMCID: PMC10402171 DOI: 10.1101/2023.07.28.551036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.
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Affiliation(s)
- Carinna Torgerson
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
- Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Hedyeh Ahmadi
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Jeiran Choupan
- Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Chun Chieh Fan
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Radiology, School of Medicine, University of California, San Diego
| | - John R. Blosnich
- Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Megan M. Herting
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
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10
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Chavoshnejad P, Chen L, Yu X, Hou J, Filla N, Zhu D, Liu T, Li G, Razavi MJ, Wang X. An integrated finite element method and machine learning algorithm for brain morphology prediction. Cereb Cortex 2023; 33:9354-9366. [PMID: 37288479 PMCID: PMC10393506 DOI: 10.1093/cercor/bhad208] [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: 03/30/2023] [Revised: 05/18/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023] Open
Abstract
The human brain development experiences a complex evolving cortical folding from a smooth surface to a convoluted ensemble of folds. Computational modeling of brain development has played an essential role in better understanding the process of cortical folding, but still leaves many questions to be answered. A major challenge faced by computational models is how to create massive brain developmental simulations with affordable computational sources to complement neuroimaging data and provide reliable predictions for brain folding. In this study, we leveraged the power of machine learning in data augmentation and prediction to develop a machine-learning-based finite element surrogate model to expedite brain computational simulations, predict brain folding morphology, and explore the underlying folding mechanism. To do so, massive finite element method (FEM) mechanical models were run to simulate brain development using the predefined brain patch growth models with adjustable surface curvature. Then, a GAN-based machine learning model was trained and validated with these produced computational data to predict brain folding morphology given a predefined initial configuration. The results indicate that the machine learning models can predict the complex morphology of folding patterns, including 3-hinge gyral folds. The close agreement between the folding patterns observed in FEM results and those predicted by machine learning models validate the feasibility of the proposed approach, offering a promising avenue to predict the brain development with given fetal brain configurations.
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Affiliation(s)
- Poorya Chavoshnejad
- Department of Mechanical Engineering, Binghamton University, Binghamton, NY 13902, United States
| | - Liangjun Chen
- Department of Radiology and BRIC, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Xiaowei Yu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, United States
| | - Jixin Hou
- School of ECAM, University of Georgia, Athens, GA 30602, United States
| | - Nicholas Filla
- School of ECAM, University of Georgia, Athens, GA 30602, United States
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, United States
| | - Tianming Liu
- School of Computing, University of Georgia, Athens, GA 30602, United States
| | - Gang Li
- Department of Radiology and BRIC, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Mir Jalil Razavi
- Department of Mechanical Engineering, Binghamton University, Binghamton, NY 13902, United States
| | - Xianqiao Wang
- School of ECAM, University of Georgia, Athens, GA 30602, United States
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11
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de Vareilles H, Rivière D, Mangin JF, Dubois J. Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates. Dev Cogn Neurosci 2023; 61:101249. [PMID: 37141790 DOI: 10.1016/j.dcn.2023.101249] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/28/2023] [Accepted: 04/21/2023] [Indexed: 05/06/2023] Open
Abstract
The folding of the human brain mostly takes place in utero, making it challenging to study. After a few pioneer studies looking into it in post-mortem foetal specimen, modern approaches based on neuroimaging have allowed the community to investigate the folding process in vivo, its normal progression, its early disturbances, and its relationship to later functional outcomes. In this review article, we aimed to first give an overview of the current hypotheses on the mechanisms governing cortical folding. After describing the methodological difficulties raised by its study in fetuses, neonates and infants with magnetic resonance imaging (MRI), we reported our current understanding of sulcal pattern emergence in the developing brain. We then highlighted the functional relevance of early sulcal development, through recent insights about hemispheric asymmetries and early factors influencing this dynamic such as prematurity. Finally, we outlined how longitudinal studies have started to relate early folding markers and the child's sensorimotor and cognitive outcome. Through this review, we hope to raise awareness on the potential of studying early sulcal patterns both from a fundamental and clinical perspective, as a window into early neurodevelopment and plasticity in relation to growth in utero and postnatal environment of the child.
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Affiliation(s)
- H de Vareilles
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France.
| | - D Rivière
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France
| | - J F Mangin
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, CNRS, Gif-sur-Yvette, France
| | - J Dubois
- Université Paris Cité, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
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12
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Basavaraju R, France J, Sigmon HC, Girgis RR, Brucato G, Lieberman JA, Small SA, Provenzano FA. Increased parietal and occipital lobe gyrification predicts conversion to syndromal psychosis in a clinical high-risk cohort. Schizophr Res 2023; 255:246-255. [PMID: 37043842 DOI: 10.1016/j.schres.2023.03.027] [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: 07/23/2021] [Revised: 02/15/2023] [Accepted: 03/12/2023] [Indexed: 04/14/2023]
Abstract
BACKGROUND Local gyrification index (lGI), indicative of the degree of cortical folding is a proxy marker for early cortical neurodevelopmental abnormalities. We studied the difference in lGI between those who do and do not convert to psychosis (non-converters) in a clinical high-risk (CHR) cohort, and whether lGI predicts conversion to psychosis. METHODS Seventy-two CHR participants with attenuated positive symptom syndrome were followed up for two years. The difference in baseline whole-brain lGI was examined on the T1-weighted MRIs between, i)CHR (N = 72) and healthy controls (N = 19), ii)Converters to psychosis (N = 24) and non-converters (N = 48), adjusting for age and sex, on Freesurfer-6.0. The significant cluster obtained in the converters versus non-converters comparison was registered as a region of interest to individual images of all 72 participants and lGI values were extracted from this region. A cox proportional hazards model was applied with these values to study whether lGI predicts conversion to psychosis. RESULTS lGI was not different between CHR and healthy controls. lGI was increased in converters in the right-sided inferior parietal and lateral occipital areas (corrected cluster-wise-p-value = 0.009, cohen's f = 0.42) compared to non-converters, which significantly increased the risk of onset of psychosis (p = 0.029, hazard ratio = 1.471). CONCLUSIONS Increased gyrification in the right-sided inferior parietal and lateral occipital area differentiates converters to psychosis in CHR, significantly increasing the risk of conversion to psychosis. This measure may reflect underlying traits in parts of the brain that develop earliest in-utero (parietal and occipital), conferring a heightened vulnerability to convert to syndromal psychosis subsequently.
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Affiliation(s)
- Rakshathi Basavaraju
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, USA
| | - Jeanelle France
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, USA
| | - Hannah C Sigmon
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, USA
| | - Ragy R Girgis
- Department of Psychiatry, College of Physicians and Surgeons, New York State Psychiatric Institute, Columbia University Medical Center, USA
| | - Gary Brucato
- Department of Psychiatry, College of Physicians and Surgeons, New York State Psychiatric Institute, Columbia University Medical Center, USA
| | - Jeffrey A Lieberman
- Department of Psychiatry, College of Physicians and Surgeons, New York State Psychiatric Institute, Columbia University Medical Center, USA
| | - Scott A Small
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, USA
| | - Frank A Provenzano
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, USA.
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13
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Fenske SJ, Liu J, Chen H, Diniz MA, Stephens RL, Cornea E, Gilmore JH, Gao W. Sex differences in resting state functional connectivity across the first two years of life. Dev Cogn Neurosci 2023; 60:101235. [PMID: 36966646 PMCID: PMC10066534 DOI: 10.1016/j.dcn.2023.101235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 02/17/2023] [Accepted: 03/19/2023] [Indexed: 03/29/2023] Open
Abstract
Sex differences in behavior have been reported from infancy through adulthood, but little is known about sex effects on functional circuitry in early infancy. Moreover, the relationship between early sex effects on the functional architecture of the brain and later behavioral performance remains to be elucidated. In this study, we used resting-state fMRI and a novel heatmap analysis to examine sex differences in functional connectivity with cross-sectional and longitudinal mixed models in a large cohort of infants (n = 319 neonates, 1-, and 2-year-olds). An adult dataset (n = 92) was also included for comparison. We investigated the relationship between sex differences in functional circuitry and later measures of language (collected in 1- and 2-year-olds) as well as indices of anxiety, executive function, and intelligence (collected in 4-year-olds). Brain areas showing the most significant sex differences were age-specific across infancy, with two temporal regions demonstrating consistent differences. Measures of functional connectivity showing sex differences in infancy were significantly associated with subsequent behavioral scores of language, executive function, and intelligence. Our findings provide insights into the effects of sex on dynamic neurodevelopmental trajectories during infancy and lay an important foundation for understanding the mechanisms underlying sex differences in health and disease.
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14
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Cao C, Li Y, Zhang L, Hu F, Gao X. Identification for the cortical 3-Hinges folding pattern based on cortical morphological and structural features. Front Neurosci 2023; 17:1125666. [PMID: 36968484 PMCID: PMC10034048 DOI: 10.3389/fnins.2023.1125666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/22/2023] [Indexed: 03/11/2023] Open
Abstract
The Cortical 3-Hinges Folding Pattern (i.e., 3-Hinges) is one of the brain's hallmarks, and it is of great reference for predicting human intelligence, diagnosing eurological diseases and understanding the brain functional structure differences among gender. Given the significant morphological variability among individuals, it is challenging to identify 3-Hinges, but current 3-Hinges researches are mainly based on the computationally expensive Gyral-net method. To address this challenge, this paper aims to develop a deep network model to realize the fast identification of 3-Hinges based on cortical morphological and structural features. The main work includes: (1) The morphological and structural features of the cerebral cortex are extracted to relieve the imbalance between the number of 3-Hinges and each brain image's voxels; (2) The feature vector is constructed with the K nearest neighbor algorithm from the extracted scattered features of the morphological and structural features to alleviate over-fitting in training; (3) The squeeze excitation module combined with the deep U-shaped network structure is used to learn the correlation of the channels among the feature vectors; (4) The functional structure roles that 3-Hinges plays between adolescent males and females are discussed in this work. The experimental results on both adolescent and adult MRI datasets show that the proposed model achieves better performance in terms of time consumption. Moreover, this paper reveals that cortical sulcus information plays a critical role in the procedure of identification, and the cortical thickness, cortical surface area, and volume characteristics can supplement valuable information for 3-Hinges identification to some extent. Furthermore, there are significant structural differences on 3-Hinges among adolescent gender.
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Affiliation(s)
- Chunhong Cao
- The MOE Key Laboratory of Intelligent Computing and Information Processing, Xiangtan University, Xiangtan, China
| | - Yongquan Li
- The MOE Key Laboratory of Intelligent Computing and Information Processing, Xiangtan University, Xiangtan, China
| | - Lele Zhang
- The MOE Key Laboratory of Intelligent Computing and Information Processing, Xiangtan University, Xiangtan, China
| | - Fang Hu
- Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province, Xiangnan University, Chenzhou, China
- *Correspondence: Fang Hu
| | - Xieping Gao
- Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China
- Xieping Gao
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15
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Wang L, Wu Z, Chen L, Sun Y, Lin W, Li G. iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction. Nat Protoc 2023; 18:1488-1509. [PMID: 36869216 DOI: 10.1038/s41596-023-00806-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 11/03/2022] [Indexed: 03/05/2023]
Abstract
The human cerebral cortex undergoes dramatic and critical development during early postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic resonance imaging (MRI) datasets have been collected from multiple imaging sites with different scanners and imaging protocols for the investigation of normal and abnormal early brain development. However, it is extremely challenging to precisely process and quantify infant brain development with these multisite imaging data because infant brain MRI scans exhibit (a) extremely low and dynamic tissue contrast caused by ongoing myelination and maturation and (b) inter-site data heterogeneity resulting from the use of diverse imaging protocols/scanners. Consequently, existing computational tools and pipelines typically perform poorly on infant MRI data. To address these challenges, we propose a robust, multisite-applicable, infant-tailored computational pipeline that leverages powerful deep learning techniques. The main functionality of the proposed pipeline includes preprocessing, brain skull stripping, tissue segmentation, topology correction, cortical surface reconstruction and measurement. Our pipeline can handle both T1w and T2w structural infant brain MR images well in a wide age range (from birth to 6 years of age) and is effective for different imaging protocols/scanners, despite being trained only on the data from the Baby Connectome Project. Extensive comparisons with existing methods on multisite, multimodal and multi-age datasets demonstrate superior effectiveness, accuracy and robustness of our pipeline. We have maintained a website, iBEAT Cloud, for users to process their images with our pipeline ( http://www.ibeat.cloud ), which has successfully processed over 16,000 infant MRI scans from more than 100 institutions with various imaging protocols/scanners.
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Affiliation(s)
- Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Liangjun Chen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Sun
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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16
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Huang F, Xia P, Vardhanabhuti V, Hui SK, Lau KK, Ka-Fung Mak H, Cao P. Semisupervised white matter hyperintensities segmentation on MRI. Hum Brain Mapp 2023; 44:1344-1358. [PMID: 36214210 PMCID: PMC9921214 DOI: 10.1002/hbm.26109] [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: 12/03/2021] [Revised: 08/25/2022] [Accepted: 09/07/2022] [Indexed: 11/10/2022] Open
Abstract
This study proposed a semisupervised loss function named level-set loss (LSLoss) for cerebral white matter hyperintensities (WMHs) segmentation on fluid-attenuated inversion recovery images. The training procedure did not require manually labeled WMH masks. Our image preprocessing steps included biased field correction, skull stripping, and white matter segmentation. With the proposed LSLoss, we trained a V-Net using the MRI images from both local and public databases. Local databases were the small vessel disease cohort (HKU-SVD, n = 360) and the multiple sclerosis cohort (HKU-MS, n = 20) from our institutional imaging center. Public databases were the Medical Image Computing Computer-assisted Intervention (MICCAI) WMH challenge database (MICCAI-WMH, n = 60) and the normal control cohort of the Alzheimer's Disease Neuroimaging Initiative database (ADNI-CN, n = 15). We achieved an overall dice similarity coefficient (DSC) of 0.81 on the HKU-SVD testing set (n = 20), DSC = 0.77 on the HKU-MS testing set (n = 5), and DSC = 0.78 on MICCAI-WMH testing set (n = 30). The segmentation results obtained by our semisupervised V-Net were comparable with the supervised methods and outperformed the unsupervised methods in the literature.
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Affiliation(s)
- Fan Huang
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Peng Xia
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Varut Vardhanabhuti
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Sai-Kam Hui
- Department of Rehabilitation Science, The Hong Kong Polytechnic University, Hong Kong, China
| | - Kui-Kai Lau
- Department of Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Peng Cao
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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17
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Nwosu EC, Holmes MJ, Cotton MF, Dobbels E, Little F, Laughton B, van der Kouwe A, Robertson F, Meintjes EM. Similar cortical morphometry trajectories from 5 to 9 years in children with perinatal HIV who started treatment before age 2 years and uninfected controls. BMC Neurosci 2023; 24:15. [PMID: 36829110 PMCID: PMC9951512 DOI: 10.1186/s12868-023-00783-7] [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: 10/25/2022] [Accepted: 02/14/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Life-long early ART (started before age 2 years), often with periods of treatment interruption, is now the standard of care in pediatric HIV infection. Although cross-sectional studies have investigated HIV-related differences in cortical morphology in the setting of early ART and ART interruption, the long-term impact on cortical developmental trajectories is unclear. This study compares the longitudinal trajectories of cortical thickness and folding (gyrification) from age 5 to 9 years in a subset of children perinatally infected with HIV (CPHIV) from the Children with HIV Early antiRetroviral therapy (CHER) trial to age-matched children without HIV infection. METHODS 75 CHER participants in follow-up care at FAMCRU (Family Centre for Research with Ubuntu), as well as 66 age-matched controls, received magnetic resonance imaging (MRI) on a 3 T Siemens Allegra at ages 5, 7 and/or 9 years. MR images were processed, and cortical surfaces reconstructed using the FreeSurfer longitudinal processing stream. Vertex-wise linear mixed effects (LME) analyses were performed across the whole brain to compare the means and linear rates of change of cortical thickness and gyrification from 5 to 9 years between CPHIV and controls, as well as to examine effects of ART interruption. RESULTS Children without HIV demonstrated generalized cortical thinning from 5 to 9 years, with the rate of thinning varying by region, as well as regional age-related gyrification increases. Overall, the means and developmental trajectories of cortical thickness and gyrification were similar in CPHIV. However, at an uncorrected p < 0.005, 6 regions were identified where the cortex of CPHIV was thicker than in uninfected children, namely bilateral insula, left supramarginal, lateral orbitofrontal and superior temporal, and right medial superior frontal regions. Planned ART interruption did not affect development of cortical morphometry. CONCLUSIONS Although our results suggest that normal development of cortical morphometry between the ages of 5 and 9 years is preserved in CPHIV who started ART early, these findings require further confirmation with longitudinal follow-up through the vulnerable adolescent period.
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Affiliation(s)
- Emmanuel C Nwosu
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, 7925, South Africa.
| | - Martha J Holmes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, 7925, South Africa.,Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Mark F Cotton
- Department of Pediatrics & Child Health, Family Centre for Research With Ubuntu (FAMCRU), Tygerberg Hospital, Stellenbosch University, Cape Town, South Africa
| | - Els Dobbels
- Department of Pediatrics & Child Health, Family Centre for Research With Ubuntu (FAMCRU), Tygerberg Hospital, Stellenbosch University, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Barbara Laughton
- Department of Pediatrics & Child Health, Family Centre for Research With Ubuntu (FAMCRU), Tygerberg Hospital, Stellenbosch University, Cape Town, South Africa
| | - Andre van der Kouwe
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, 7925, South Africa.,A.A. Martinos Centre for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Frances Robertson
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, 7925, South Africa.,Neuroscience Institute, University of Cape Town, Cape Town, South Africa.,Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Ernesta M Meintjes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory, Cape Town, 7925, South Africa. .,Neuroscience Institute, University of Cape Town, Cape Town, South Africa. .,Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa.
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18
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De Vareilles H, Rivière D, Pascucci M, Sun ZY, Fischer C, Leroy F, Tataranno ML, Benders MJ, Dubois J, Mangin JF. Exploring the emergence of morphological asymmetries around the brain's Sylvian fissure: a longitudinal study of shape variability in preterm infants. Cereb Cortex 2023:7005629. [PMID: 36702802 DOI: 10.1093/cercor/bhac533] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/28/2022] [Accepted: 12/21/2022] [Indexed: 01/28/2023] Open
Abstract
Brain folding patterns vary within the human species, but some folding properties are common across individuals, including the Sylvian fissure's inter-hemispheric asymmetry. Contrarily to the other brain folds (sulci), the Sylvian fissure develops through the process of opercularization, with the frontal, parietal, and temporal lobes growing over the insular lobe. Its asymmetry may be related to the leftward functional lateralization for language processing, but the time course of these asymmetries' development is still poorly understood. In this study, we investigated refined shape features of the Sylvian fissure and their longitudinal development in 71 infants born extremely preterm (mean gestational age at birth: 26.5 weeks) and imaged once before and once at term-equivalent age (TEA). We additionally assessed asymmetrical sulcal patterns at TEA in the perisylvian and inferior frontal regions, neighbor to the Sylvian fissure. While reproducing renowned strong asymmetries in the Sylvian fissure, we captured an early encoding of its main asymmetrical shape features, and we observed global asymmetrical shape features representative of a more pronounced opercularization in the left hemisphere, contrasting with the previously reported right hemisphere advance in sulcation around birth. This added novel insights about the processes governing early-life brain folding mechanisms, potentially linked to the development of language-related capacities.
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Affiliation(s)
| | - Denis Rivière
- NeuroSpin-BAOBAB, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Marco Pascucci
- NeuroSpin-BAOBAB, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Zhong-Yi Sun
- NeuroSpin-BAOBAB, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Clara Fischer
- NeuroSpin-BAOBAB, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - François Leroy
- NeuroSpin-BAOBAB, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France.,NeuroSpin-UNICOG, Inserm, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Maria-Luisa Tataranno
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, Netherlands
| | - Manon J Benders
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, Netherlands
| | - Jessica Dubois
- NeuroDiderot, Inserm, Université Paris Cité, Paris 75019, France.,NeuroSpin-UNIACT, CEA, Université Paris-Saclay, Gif-sur-Yvette 91191, France
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19
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Developmental Inhibitory Changes in the Primary Somatosensory Cortex of the Stargazer Mouse Model of Absence Epilepsy. Biomolecules 2023; 13:biom13010186. [PMID: 36671571 PMCID: PMC9856073 DOI: 10.3390/biom13010186] [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: 12/18/2022] [Revised: 01/08/2023] [Accepted: 01/11/2023] [Indexed: 01/19/2023] Open
Abstract
Childhood absence epilepsy seizures arise in the cortico-thalamocortical network due to multiple cellular and molecular mechanisms, which are still under investigation. Understanding the precise mechanisms is imperative given that treatment fails in ~30% of patients while adverse neurological sequelae remain common. Impaired GABAergic neurotransmission is commonly reported in research models investigating these mechanisms. Recently, we reported a region-specific reduction in the whole-tissue and synaptic GABAA receptor (GABAAR) α1 subunit and an increase in whole-tissue GAD65 in the primary somatosensory cortex (SoCx) of the adult epileptic stargazer mouse compared with its non-epileptic (NE) littermate. The current study investigated whether these changes occurred prior to the onset of seizures on postnatal days (PN) 17-18, suggesting a causative role. Synaptic and cytosolic fractions were biochemically isolated from primary SoCx lysates followed by semiquantitative Western blot analyses for GABAAR α1 and GAD65. We found no significant changes in synaptic GABAAR α1 and cytosolic GAD65 in the primary SoCx of the stargazer mice at the critical developmental stages of PN 7-9, 13-15, and 17-18. This indicates that altered levels of GABAAR α1 and GAD65 in adult mice do not directly contribute to the initial onset of absence seizures but are a later consequence of seizure activity.
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20
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Howes OD, Cummings C, Chapman GE, Shatalina E. Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology 2023; 48:151-167. [PMID: 36056106 PMCID: PMC9700830 DOI: 10.1038/s41386-022-01426-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 11/09/2022]
Abstract
Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.
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Affiliation(s)
- Oliver D Howes
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- South London and Maudsley NHS Foundation Trust, London, UK.
| | - Connor Cummings
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
- Clare Hall (College), University of Cambridge, Cambridge, UK
| | - George E Chapman
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Ekaterina Shatalina
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
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21
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Zhang L, Zhao L, Liu D, Wu Z, Wang X, Liu T, Zhu D. Cortex2vector: anatomical embedding of cortical folding patterns. Cereb Cortex 2022; 33:5851-5862. [PMID: 36487182 PMCID: PMC10183757 DOI: 10.1093/cercor/bhac465] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 12/13/2022] Open
Abstract
Abstract
Current brain mapping methods highly depend on the regularity, or commonality, of anatomical structure, by forcing the same atlas to be matched to different brains. As a result, individualized structural information can be overlooked. Recently, we conceptualized a new type of cortical folding pattern called the 3-hinge gyrus (3HG), which is defined as the conjunction of gyri coming from three directions. Many studies have confirmed that 3HGs are not only widely existing on different brains, but also possess both common and individual patterns. In this work, we put further effort, based on the identified 3HGs, to establish the correspondences of individual 3HGs. We developed a learning-based embedding framework to encode individual cortical folding patterns into a group of anatomically meaningful embedding vectors (cortex2vector). Each 3HG can be represented as a combination of these embedding vectors via a set of individual specific combining coefficients. In this way, the regularity of folding pattern is encoded into the embedding vectors, while the individual variations are preserved by the multi-hop combination coefficients. Results show that the learned embeddings can simultaneously encode the commonality and individuality of cortical folding patterns, as well as robustly infer the complicated many-to-many anatomical correspondences among different brains.
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Affiliation(s)
- Lu Zhang
- Department of Computer Science and Engineering, The University of Texas at Arlington , Arlington, 76010, USA
| | - Lin Zhao
- Department of Computer Science, The University of Georgia , Athens, 30602, USA
| | | | - Zihao Wu
- Department of Computer Science, The University of Georgia , Athens, 30602, USA
| | - Xianqiao Wang
- College of Engineering, The University of Georgia , Athens, 30602, USA
| | - Tianming Liu
- Department of Computer Science, The University of Georgia , Athens, 30602, USA
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington , Arlington, 76010, USA
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22
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Huang Z, Gao W, Wu Z, Li G, Nie J. Functional brain activity is highly associated with cortical myelination in neonates. Cereb Cortex 2022; 33:3985-3995. [PMID: 36030387 DOI: 10.1093/cercor/bhac321] [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: 03/15/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/12/2022] Open
Abstract
Functional organization of the human cerebral cortex is highly constrained by underlying brain structures, but how functional activity is associated with different brain structures during development is not clear, especially at the neonatal stage. Since long-range functional connectivity is far from mature in the dynamically developing neonatal brain, it is of great scientific significance to investigate the relationship between different structural and functional features at the local level. To this end, for the first time, correlation and regression analyses were performed to examine the relationship between cortical morphology, cortical myelination, age, and local brain functional activity, as well as functional connectivity strength using high-resolution structural and resting-state functional MRI data of 177 neonates (29-44 postmenopausal weeks, 98 male and 79 female) from both static and dynamic perspectives. We found that cortical myelination was most strongly associated with local brain functional activity across the cerebral cortex than other cortical structural features while controlling the age effect. These findings suggest the crucial role of cortical myelination in local brain functional development at birth, providing valuable insights into the fundamental biological basis of functional activity at this early developmental stage.
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Affiliation(s)
- Ziyi Huang
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Wenjian Gao
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University,Guangzhou 510631, China
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jingxin Nie
- School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
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23
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Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age. Proc Natl Acad Sci U S A 2022; 119:e2121748119. [PMID: 35939665 PMCID: PMC9388141 DOI: 10.1073/pnas.2121748119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.
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24
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Gharehgazlou A, Jetly R, Rhind SG, Reichelt AC, Da Costa L, Dunkley BT. Cortical Gyrification Morphology in Adult Males with Mild Traumatic Brain Injury. Neurotrauma Rep 2022; 3:299-307. [PMID: 36060456 PMCID: PMC9438439 DOI: 10.1089/neur.2021.0032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Cortical gyrification, as a specific measure derived from magnetic resonance imaging, remains understudied in mild traumatic brain injury (mTBI). Local gyrification index (lGI) and mean curvature are related measures indexing the patterned folding of the cortex,ml which reflect distinct properties of cortical morphology and geometry. Using both metrics, we examined cortical gyrification morphology in 59 adult males with mTBI (n = 29) versus those without (n = 30) mTBI in the subacute phase of injury (between 2 weeks and 3 months). The effect of IQ on lGI and brain-symptom relations were also examined. General linear models revealed greater lGI in mTBI versus controls in the frontal lobes bilaterally, but reduced lGI in mTBI of the left temporal lobe. An age-related decrease in lGI was found in numerous areas, with no significant group-by-age interaction effects observed. Including other factors (i.e., mTBI severity, symptoms, and IQ) in the lGI model yielded similar results with few exceptions. Mean curvature analyses depicted a significant group-by-age interaction with the absence of significant main effects of group or age. Our results suggest that cortical gyrification morphology is adversely affected by mTBI in both frontal and temporal lobes, which are thought of as highly susceptible regions to mTBI. These findings contribute to understanding the effects of mTBI on neuromorphological properties, such as alterations in cortical gyrification, which reflect underlying microstructural changes (i.e., apoptosis, neuronal number, or white matter alterations). Future studies are needed to infer causal relationships between micro- and macrostructural changes after an mTBI and investigate potential sex differences.
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Affiliation(s)
- Avideh Gharehgazlou
- Neurosciences and Mental Health, The Hospital for Sick Children (SickKids) Research Institute, Toronto, Ontario, Canada
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
| | - Rakesh Jetly
- Directorate of Mental Health, Canadian Forces Health Services HQ, Ottawa, Ontario, Canada
- Defence Research and Development Canada–Toronto Research Centre, Toronto, Ontario, Canada
| | - Shawn G. Rhind
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Amy C. Reichelt
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Leodante Da Costa
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
- Department of Diagnostic Imaging, The Hospital for Sick Children (SickKids) Research Institute, Toronto, Ontario, Canada
| | - Benjamin T. Dunkley
- Neurosciences and Mental Health, The Hospital for Sick Children (SickKids) Research Institute, Toronto, Ontario, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Diagnostic Imaging, The Hospital for Sick Children (SickKids) Research Institute, Toronto, Ontario, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
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25
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Cheng J, Zhang X, Ni H, Li C, Xu X, Wu Z, Wang L, Lin W, Li G. Path Signature Neural Network of Cortical Features for Prediction of Infant Cognitive Scores. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1665-1676. [PMID: 35089858 PMCID: PMC9246848 DOI: 10.1109/tmi.2022.3147690] [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] [Indexed: 06/14/2023]
Abstract
Studies have shown that there is a tight connection between cognition skills and brain morphology during infancy. Nonetheless, it is still a great challenge to predict individual cognitive scores using their brain morphological features, considering issues like the excessive feature dimension, small sample size and missing data. Due to the limited data, a compact but expressive feature set is desirable as it can reduce the dimension and avoid the potential overfitting issue. Therefore, we pioneer the path signature method to further explore the essential hidden dynamic patterns of longitudinal cortical features. To form a hierarchical and more informative temporal representation, in this work, a novel cortical feature based path signature neural network (CF-PSNet) is proposed with stacked differentiable temporal path signature layers for prediction of individual cognitive scores. By introducing the existence embedding in path generation, we can improve the robustness against the missing data. Benefiting from the global temporal receptive field of CF-PSNet, characteristics consisted in the existing data can be fully leveraged. Further, as there is no need for the whole brain to work for a certain cognitive ability, a top K selection module is used to select the most influential brain regions, decreasing the model size and the risk of overfitting. Extensive experiments are conducted on an in-house longitudinal infant dataset within 9 time points. By comparing with several recent algorithms, we illustrate the state-of-the-art performance of our CF-PSNet (i.e., root mean square error of 0.027 with the time latency of 518 milliseconds for each sample).
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26
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Maternal psychological distress during the COVID-19 pandemic and structural changes of the human fetal brain. COMMUNICATIONS MEDICINE 2022; 2:47. [PMID: 35647608 PMCID: PMC9135751 DOI: 10.1038/s43856-022-00111-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 04/11/2022] [Indexed: 12/12/2022] Open
Abstract
Abstract
Background
Elevated maternal psychological distress during pregnancy is linked to adverse outcomes in offspring. The potential effects of intensified levels of maternal distress during the COVID-19 pandemic on the developing fetal brain are currently unknown.
Methods
We prospectively enrolled 202 pregnant women: 65 without known COVID-19 exposures during the pandemic who underwent 92 fetal MRI scans, and 137 pre-pandemic controls who had 182 MRI scans. Multi-plane, multi-phase single shot fast spin echo T2-weighted images were acquired on a GE 1.5 T MRI Scanner. Volumes of six brain tissue types were calculated. Cortical folding measures, including brain surface area, local gyrification index, and sulcal depth were determined. At each MRI scan, maternal distress was assessed using validated stress, anxiety, and depression scales. Generalized estimating equations were utilized to compare maternal distress measures, brain volume and cortical folding differences between pandemic and pre-pandemic cohorts.
Results
Stress and depression scores are significantly higher in the pandemic cohort, compared to the pre-pandemic cohort. Fetal white matter, hippocampal, and cerebellar volumes are decreased in the pandemic cohort. Cortical surface area and local gyrification index are also decreased in all four lobes, while sulcal depth is lower in the frontal, parietal, and occipital lobes in the pandemic cohort, indicating delayed brain gyrification.
Conclusions
We report impaired fetal brain growth and delayed cerebral cortical gyrification in COVID-19 pandemic era pregnancies, in the setting of heightened maternal psychological distress. The potential long-term neurodevelopmental consequences of altered fetal brain development in COVID-era pregnancies merit further study.
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27
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Janssen J, Alloza C, Díaz-Caneja CM, Santonja J, Pina-Camacho L, Gordaliza PM, Fernández-Pena A, Lois NG, Buimer EEL, van Haren NEM, Cahn W, Vieta E, Castro-Fornieles J, Bernardo M, Arango C, Kahn RS, Hulshoff Pol HE, Schnack HG. Longitudinal Allometry of Sulcal Morphology in Health and Schizophrenia. J Neurosci 2022; 42:3704-3715. [PMID: 35318286 PMCID: PMC9087719 DOI: 10.1523/jneurosci.0606-21.2022] [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: 03/11/2021] [Revised: 02/24/2022] [Accepted: 03/01/2022] [Indexed: 11/21/2022] Open
Abstract
Scaling between subcomponents of folding and total brain volume (TBV) in healthy individuals (HIs) is allometric. It is unclear whether this is true in schizophrenia (SZ) or first-episode psychosis (FEP). This study confirmed normative allometric scaling norms in HIs using discovery and replication samples. Cross-sectional and longitudinal diagnostic differences in folding subcomponents were then assessed using an allometric framework. Structural imaging from a longitudinal (Sample 1: HI and SZ, nHI Baseline = 298, nSZ Baseline = 169, nHI Follow-up = 293, nSZ Follow-up = 168, totaling 1087 images, all individuals ≥ 2 images, age 16-69 years) and a cross-sectional sample (Sample 2: nHI = 61 and nFEP = 89, age 10-30 years), all human males and females, is leveraged to calculate global folding and its nested subcomponents: sulcation index (SI, total sulcal/cortical hull area) and determinants of sulcal area: sulcal length and sulcal depth. Scaling of SI, sulcal area, and sulcal length with TBV in SZ and FEP was allometric and did not differ from HIs. Longitudinal age trajectories demonstrated steeper loss of SI and sulcal area through adulthood in SZ. Longitudinal allometric analysis revealed that both annual change in SI and sulcal area was significantly stronger related to change in TBV in SZ compared with HIs. Our results detail the first evidence of the disproportionate contribution of changes in SI and sulcal area to TBV changes in SZ. Longitudinal allometric analysis of sulcal morphology provides deeper insight into lifespan trajectories of cortical folding in SZ.SIGNIFICANCE STATEMENT Psychotic disorders are associated with deficits in cortical folding and brain size, but we lack knowledge of how these two morphometric features are related. We leverage cross-sectional and longitudinal samples in which we decompose folding into a set of nested subcomponents: sulcal and hull area, and sulcal depth and length. We reveal that, in both schizophrenia and first-episode psychosis, (1) scaling of subcomponents with brain size is different from expected scaling laws and (2) caution is warranted when interpreting results from traditional methods for brain size correction. Longitudinal allometric scaling points to loss of sulcal area as a principal contributor to loss of brain size in schizophrenia. These findings advance the understanding of cortical folding atypicalities in psychotic disorders.
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Affiliation(s)
- Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - Javier Santonja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
| | - Laura Pina-Camacho
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - Pedro M Gordaliza
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, 28911 Madrid, Spain
| | - Alberto Fernández-Pena
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, 28911 Madrid, Spain
| | - Noemi González Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
| | - Elizabeth E L Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Sophia Children's Hospital, 3015 GD Rotterdam, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Eduard Vieta
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Bipolar Disorders Unit, Clinical Institute of Neurosciences, Hospital Clínic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, 08036 Barcelona, Spain
| | - Josefina Castro-Fornieles
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Department of Child and Adolescent Psychiatry and Psychology, Clinical Institute of Neurosciences, Hospital Clínic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, 08036 Barcelona, Spain
| | - Miquel Bernardo
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- Barcelona Clinic Schizophrenia Unit, Hospital Clinic of Barcelona, Neuroscience Institute, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, 08036 Barcelona, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, 28007 Madrid, Spain
- Ciber del Área de Salud Mental, 28007 Madrid, Spain
- School of Medicine, Universidad Complutense, 28040 Madrid, Spain
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 10029 New York
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
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28
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BRADSHAW JESSICA, SHI DEXIN, HENDRIX CASSANDRAL, SAULNIER CELINE, KLAIMAN CHERYL. Neonatal neurobehavior in infants with autism spectrum disorder. Dev Med Child Neurol 2022; 64:600-607. [PMID: 34713902 PMCID: PMC9209845 DOI: 10.1111/dmcn.15096] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/23/2021] [Indexed: 11/29/2022]
Abstract
AIM To investigate neurobehavioral maturation for neonates who are later diagnosed with autism spectrum disorder (ASD). METHOD In a prospective longitudinal design, neonatal neurobehavior was examined monthly in 1- to 3-month-old infants at elevated and low familial likelihood of ASD (n=60). At 2 years, infants were seen for a clinical best-estimate evaluation, resulting in 18 infants with ASD and 36 typically developing infants. Repeated-measures analysis of variance models were conducted to examine the effects of age, diagnostic group, and their interactions. RESULTS Neurobehavioral maturation of infants diagnosed with ASD was largely comparable to typically developing infants from 1 to 3 months, with the exception of the development of attention. Object-focused attention was significantly attenuated for infants with ASD beginning at 2 to 3 months and was predictive of social-communication skills 2 years later. INTERPRETATION This is the first study to prospectively examine neonatal neurobehavior of infants at an elevated familial likelihood of ASD who later received a diagnosis. Despite relatively intact neurological and behavioral maturation in the neonatal period, attention to objects emerged as a key early indicator of ASD. This suggests a complex attentional vulnerability within the first 3 months of life that may be associated with cascading sequelae of social-communication challenges and the emergence of ASD.
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Affiliation(s)
- JESSICA BRADSHAW
- Department of Psychology, University of South Carolina, Columbia, SC
| | - DEXIN SHI
- Department of Psychology, University of South Carolina, Columbia, SC
| | - CASSANDRA L HENDRIX
- Department of Child and Adolescent Psychiatry, New York University, Langone Health, New York, NY
| | - CELINE SAULNIER
- Neurodevelopmental Assessment & Consulting Services, Decatur, GA,Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - CHERYL KLAIMAN
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
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29
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Wei D, Ahmad S, Guo Y, Chen L, Huang Y, Ma L, Wu Z, Li G, Wang L, Lin W, Yap PT, Shen D, Wang Q. Recurrent Tissue-Aware Network for Deformable Registration of Infant Brain MR Images. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:1219-1229. [PMID: 34932474 PMCID: PMC9064923 DOI: 10.1109/tmi.2021.3137280] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Deformable registration is fundamental to longitudinal and population-based image analyses. However, it is challenging to precisely align longitudinal infant brain MR images of the same subject, as well as cross-sectional infant brain MR images of different subjects, due to fast brain development during infancy. In this paper, we propose a recurrently usable deep neural network for the registration of infant brain MR images. There are three main highlights of our proposed method. (i) We use brain tissue segmentation maps for registration, instead of intensity images, to tackle the issue of rapid contrast changes of brain tissues during the first year of life. (ii) A single registration network is trained in a one-shot manner, and then recurrently applied in inference for multiple times, such that the complex deformation field can be recovered incrementally. (iii) We also propose both the adaptive smoothing layer and the tissue-aware anti-folding constraint into the registration network to ensure the physiological plausibility of estimated deformations without degrading the registration accuracy. Experimental results, in comparison to the state-of-the-art registration methods, indicate that our proposed method achieves the highest registration accuracy while still preserving the smoothness of the deformation field. The implementation of our proposed registration network is available online https://github.com/Barnonewdm/ACTA-Reg-Net.
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30
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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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31
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Wu Y, Espinosa KM, Barnett SD, Kapse A, Quistorff JL, Lopez C, Andescavage N, Pradhan S, Lu YC, Kapse K, Henderson D, Vezina G, Wessel D, du Plessis AJ, Limperopoulos C. Association of Elevated Maternal Psychological Distress, Altered Fetal Brain, and Offspring Cognitive and Social-Emotional Outcomes at 18 Months. JAMA Netw Open 2022; 5:e229244. [PMID: 35486403 PMCID: PMC9055453 DOI: 10.1001/jamanetworkopen.2022.9244] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
IMPORTANCE Prenatal maternal psychological distress is associated with disturbances in fetal brain development. However, the association between altered fetal brain development, prenatal maternal psychological distress, and long-term neurodevelopmental outcomes is unknown. OBJECTIVE To determine the association of fetal brain development using 3-dimensional magnetic resonance imaging (MRI) volumes, cortical folding, and metabolites in the setting of maternal psychological distress with infant 18-month neurodevelopment. DESIGN, SETTING, AND PARTICIPANTS Healthy mother-infant dyads were prospectively recruited into a longitudinal observational cohort study from January 2016 to October 2020 at Children's National Hospital in Washington, DC. Data analysis was performed from January 2016 to July 2021. EXPOSURES Prenatal maternal stress, anxiety, and depression. MAIN OUTCOMES AND MEASURES Prenatal maternal stress, anxiety, and depression were measured using validated self-report questionnaires. Fetal brain volumes and cortical folding were measured from 3-dimensional, reconstructed T2-weighted MRI scans. Fetal brain creatine and choline were quantified using proton magnetic resonance spectroscopy. Infant neurodevelopment at 18 months was measured using Bayley Scales of Infant and Toddler Development III and Infant-Toddler Social and Emotional Assessment. The parenting stress in the parent-child dyad was measured using the Parenting Stress Index-Short Form at 18-month testing. RESULTS The cohort consisted of 97 mother-infant dyads (mean [SD] maternal age, 34.79 [5.64] years) who underwent 184 fetal MRI visits (87 participants with 2 fetal studies each) with maternal psychological distress measures between 24 and 40 gestational weeks and completed follow-up infant neurodevelopmental testing. Prenatal maternal stress was negatively associated with infant cognitive performance (β = -0.51; 95% CI, -0.92 to -0.09; P = .01), and this association was mediated by fetal left hippocampal volume. In addition, prenatal maternal anxiety, stress, and depression were positively associated with all parenting stress measures at 18-month testing. Finally, fetal cortical local gyrification index and sulcal depth were negatively associated with infant social-emotional performance (local gyrification index: β = -54.62; 95% CI, -85.05 to -24.19; P < .001; sulcal depth: β = -14.22; 95% CI, -23.59 to -4.85; P = .002) and competence scores (local gyrification index: β = -24.01; 95% CI, -40.34 to -7.69; P = .003; sulcal depth: β = -7.53; 95% CI, -11.73 to -3.32; P < .001). CONCLUSIONS AND RELEVANCE In this cohort study of 97 mother-infant dyads, fetal cortical local gyrification index and sulcal depth were associated with infant 18-month social-emotional and competence outcomes, and fetal left hippocampal volume mediated the association between prenatal maternal stress and infant cognitive outcome. These findings suggest that altered prenatal brain development in the setting of elevated maternal distress has adverse infant sociocognitive outcomes, and identifying early biomarkers associated with long-term neurodevelopment may assist in early targeted interventions.
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Affiliation(s)
- Yao Wu
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | | | - Scott D. Barnett
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | - Anushree Kapse
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | | | - Catherine Lopez
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | | | - Subechhya Pradhan
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | - Yuan-Chiao Lu
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | - Kushal Kapse
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | - Diedtra Henderson
- Developing Brain Institute, Children’s National Hospital, Washington, DC
| | - Gilbert Vezina
- Department of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC
| | - David Wessel
- Hospital and Specialty Services, Children’s National Hospital, Washington, DC
| | - Adré J. du Plessis
- Prenatal Pediatrics Institute, Children’s National Hospital, Washington, DC
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National Hospital, Washington, DC
- Department of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC
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32
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Liu X, Beheshti I, Zheng W, Li Y, Li S, Zhao Z, Yao Z, Hu B. Brain age estimation using multi-feature-based networks. Comput Biol Med 2022; 143:105285. [PMID: 35158116 DOI: 10.1016/j.compbiomed.2022.105285] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 02/03/2022] [Accepted: 02/03/2022] [Indexed: 12/17/2022]
Abstract
Studying brain aging improves our understanding in differentiating typical and atypical aging. Directly utilizing traditional morphological features for brain age estimation did not show significant performance in healthy controls (HCs), which may be due to the negligence of the information of structural similarities among cortical regions. For this issue, the multi-feature-based network (MFN) built upon morphological features can be employed to describe these similarities. Based on this, we hypothesized that the MFN is more efficient and robust than traditional morphological features in brain age estimating. In this work, we used six different types of morphological features (i.e., cortical volume, cortical thickness, curvature index, folding index, local gyrification index, and surface area) to build individual MFN for brain age estimation. The efficacy of MFN was estimated on 2501 HCs with T1-weighted structural magnetic resonance imaging (sMRI) data and compared with traditional morphological features. We attained a mean absolute error (MAE) of 3.73 years using the proposed method on an independent test set, whereas a mean absolute error of 5.30 years was derived from morphological features. Our experimental results demonstrated that the MFN is an efficient and robust metric for estimating brain age.
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Affiliation(s)
- Xia Liu
- School of Computer Science, Qinghai Normal University, Xining, Qinghai Province, China
| | - Iman Beheshti
- Department of Human Anatomy and Cell Science, University of Manitoba, Canada
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Yongchao Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Shan Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Ziyang Zhao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China
| | - Zhijun Yao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China.
| | - Bin Hu
- School of Computer Science, Qinghai Normal University, Xining, Qinghai Province, China; Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China; Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors, Chinese Academy of Sciences, China; Engineering Research Center of Open Source Software and Real-Time System (Lanzhou University), Ministry of Education, Lanzhou, China.
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33
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Fehlbaum LV, Peters L, Dimanova P, Roell M, Borbás R, Ansari D, Raschle NM. Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain's reading network. Dev Cogn Neurosci 2022; 53:101058. [PMID: 34999505 PMCID: PMC8749220 DOI: 10.1016/j.dcn.2022.101058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/19/2021] [Accepted: 01/03/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads. METHODS Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children's age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit. RESULTS Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT. CONCLUSION Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.
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Affiliation(s)
- Lynn V Fehlbaum
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Lien Peters
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Plamina Dimanova
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Margot Roell
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Réka Borbás
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Daniel Ansari
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Nora M Raschle
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland.
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34
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Li X, Zhang S, Jiang X, Zhang S, Han J, Guo L, Zhang T. Cortical development coupling between surface area and sulcal depth on macaque brains. Brain Struct Funct 2022; 227:1013-1029. [PMID: 34989870 DOI: 10.1007/s00429-021-02444-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 12/15/2021] [Indexed: 02/06/2023]
Abstract
Postnatal development of cerebral cortex is associated with a variety of neuronal processes and is thus critical to development of brain function and cognition. Longitudinal changes of cortical morphology and topology, such as postnatal cortical thinning and flattening have been widely studied. However, thorough and systematic investigation of such cortical change, including how to quantify it from multiple spatial directions and how to relate it to surface topology, is rarely found. In this work, based on a longitudinal macaque neuroimaging dataset, we quantified local changes in gyral white matter's surface area and sulcal depth during early development. We also investigated how these two metrics are coupled and how this coupling is linked to cortical surface topology, underlying white matter, and positions of functional areas. Semi-parametric generalized additive models were adopted to quantify the longitudinal changes of surface area (A) and sulcal depth (D), and the coupling patterns between them. This resulted in four classes of regions, according to how they change compared with global change throughout early development: slower surface area change and slower sulcal depth change (slowA_slowD), slower surface area change and faster sulcal depth change (slowA_fastD), faster surface area change and slower sulcal depth change (fastA_slowD), and faster surface area change and faster sulcal depth change (fastA_fastD). We found that cortex-related metrics, including folding pattern and cortical thickness, vary along slowA_fastD-fastA_slowD axis, and structural connection-related metrics vary along fastA_fastD-slowA_slowD axis, with which brain functional sites align better. It is also found that cortical landmarks, including sulcal pits and gyral hinges, spatially reside on the borders of the four patterns. These findings shed new lights on the relationship between cortex development, surface topology, axonal wiring pattern and brain functions.
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Affiliation(s)
- Xiao Li
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Songyao Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Xi Jiang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shu Zhang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, China
| | - Junwei Han
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an, China.
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35
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Natsuyama T, Okamoto N, Watanabe K, Chibaatar E, Tesen H, Hayasaki G, Ikenouchi A, Kakeda S, Yoshimura R. Gyrification patterns in first-episode, drug-naïve major depression: Associations with plasma levels of brain-derived neurotrophic factor and psychiatric symptoms. Front Psychiatry 2022; 13:1031386. [PMID: 36684011 PMCID: PMC9852994 DOI: 10.3389/fpsyt.2022.1031386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/06/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Cortical structural changes in major depressive disorder (MDD) are usually studied using a voxel-based morphometry approach to delineate the cortical gray matter volume. Among cortical structures, gyrification patterns are considered a relatively stable indicator. In this study, we investigated differences in gyrification patterns between MDD patients and healthy controls (HCs) and explored the association of gyrification patterns with plasma brain-derived neurotrophic factor (BDNF) levels and depressive symptoms in MDD patients. METHODS We evaluated 79 MDD patients and 94 HCs and assessed depression severity in the patients using the 17-item Hamilton Depression Rating Scale (HAM-D). Blood samples of both groups were collected to measure plasma BDNF levels. Magnetic resonance imaging (MRI) data were obtained using three-dimensional fast-spoiled gradient-recalled acquisition. Differences in plasma BDNF levels between groups were examined using the Mann-Whitney U test. Principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to investigate the gyrification patterns which were significantly different between the groups, i.e., those with variable importance in projection (VIP) scores of >1.5 and p-value < 0.05 in multiple regression analyses adjusted for age and sex. Finally, multiple regression analysis was performed on the selected gyrification patterns to examine their association with BDNF levels in the two groups and HAM-D in the patients. RESULTS There were no significant differences in plasma BDNF levels between the groups. We found that 108 (71.0%) of 152 total local gyrification indices were MDD < HC. We identified 10 disease-differentiating factors based on critical gyrification features (VIP > 1.5 and p-value adjusted for age and sex < 0.05). However, we found no significant correlations between the 10 gyrification patterns and plasma BDNF levels and no interaction with group. Moreover, no significant correlations were observed between the local gyrification indices and HAM-D total scores. CONCLUSION These results suggest that abnormal early cortical neurodevelopment may mediate vulnerability to MDD, independent of plasma BDNF levels and depressive symptoms.
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Affiliation(s)
- Tomoya Natsuyama
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Naomichi Okamoto
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Enkhmurun Chibaatar
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Hirofumi Tesen
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Gaku Hayasaki
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan.,Medical Center for Dementia, Hospital of University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
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36
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NAS-optimized topology-preserving transfer learning for differentiating cortical folding patterns. Med Image Anal 2021; 77:102316. [PMID: 34979433 DOI: 10.1016/j.media.2021.102316] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 11/21/2021] [Accepted: 11/23/2021] [Indexed: 11/21/2022]
Abstract
Increasing evidence suggests that cortical folding patterns of human cerebral cortex manifest overt structural and functional differences. However, for interpretability, few studies leverage advanced techniques (e.g., deep learning) to investigate the difference among cortical folds, resulting in more differences yet to be extensively explored. To this end, we proposed an effective topology-preserving transfer learning framework to differentiate cortical fMRI time series extracted from cortical folds. Our framework consists of three main parts: (1) Neural architecture search (NAS), which is used to devise a well-performing network structure based on an initialized hand-designed super-graph in an image dataset; (2) Topology-preserving transfer, which takes the model searched by NAS as the source network, keeping the topological connectivity in the network unchanged, while transforming all 2D operations including convolution and pooling into 1D, therefore resulting in a topology-preserving network, named TPNAS-Net; (3) Classification and correlation analysis, which involves using the TPNAS-Net to classify 1D cortical fMRI time series for each individual brain, and performing a group difference analysis between autism spectrum disorder (ASD) and healthy control (HC) and correlation analysis with clinical information (i.e., age). Extensive experiments on two ASD datasets obtain consistent results, demonstrating that the TPNAS-Net not only discriminates cortical folding patterns at high classification accuracy, but also captures subtle differences between ASD and HC (p-value = 0.042). In addition, we discover that there is a positive correlation between the classification accuracy and age in ASD (r = 0.39, p-value = 0.04). These findings together suggest that structural and functional differences in cortical folding patterns between ASD and HC may provide a potentially useful biomarker for the diagnosis of ASD.
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37
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Blinkouskaya Y, Caçoilo A, Gollamudi T, Jalalian S, Weickenmeier J. Brain aging mechanisms with mechanical manifestations. Mech Ageing Dev 2021; 200:111575. [PMID: 34600936 PMCID: PMC8627478 DOI: 10.1016/j.mad.2021.111575] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 09/09/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.
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Affiliation(s)
- Yana Blinkouskaya
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Trisha Gollamudi
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Shima Jalalian
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
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38
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Dhari Z, Leonetti C, Lin S, Prince A, Howick J, Zurakowski D, Wang PC, Jonas RA, Ishibashi N. Impact of Cardiopulmonary Bypass on Neurogenesis and Cortical Maturation. Ann Neurol 2021; 90:913-926. [PMID: 34590341 DOI: 10.1002/ana.26235] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/22/2021] [Accepted: 09/26/2021] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Neurodevelopmental delays and frontal lobe cortical dysmaturation are widespread among children with congenital heart disease (CHD). The subventricular zone (SVZ) is the largest pool of neural stem/progenitor cells in the postnatal brain. Our aim is to determine the effects of cardiopulmonary bypass (CPB) on neurogenesis and cortical maturation in piglets whose SVZ development is similar to human infants. METHODS Three-week-old piglets (n = 29) were randomly assigned to control (no surgery), mild-CPB (34°C full flow for 60 minutes) and severe-CPB groups (25°C circulatory-arrest for 60 minutes). The SVZ and frontal lobe were analyzed with immunohistochemistry 3 days and 4 weeks postoperatively. MRI of the frontal lobe was used to assess cortical development. RESULTS SVZ neurogenic activity was reduced up to 4 weeks after both mild and severe CPB-induced insults. CPB also induced decreased migration of young neurons to the frontal lobe, demonstrating that CPB impairs postnatal neurogenesis. MRI 4 weeks after CPB displayed a decrease in gyrification index and cortical volume of the frontal lobe. Cortical fractional anisotropy was increased after severe CPB injury, indicating a prolonged deleterious impact of CPB on cortical maturation. Both CPB-induced insults displayed a significant change in densities of three major inhibitory neurons, suggesting excitatory-inhibitory imbalance in the frontal cortex. In addition, different CPB insults altered different subpopulations of inhibitory neurons. INTERPRETATION Our results provide novel insights into cellular mechanisms contributing to CHD-induced neurological impairments. Further refinement of CPB hardware and techniques is necessary to improve long-term frontal cortical dysmaturation observed in children with CHD. ANN NEUROL 2021.
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Affiliation(s)
- Zaenab Dhari
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - Camille Leonetti
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - Stephen Lin
- Department of Radiology, Howard University, Washington, DC
| | - Arianna Prince
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
| | - James Howick
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC
| | - David Zurakowski
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Paul C Wang
- Department of Radiology, Howard University, Washington, DC.,Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan
| | - Richard A Jonas
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
| | - Nobuyuki Ishibashi
- Children's National Heart Institute, Center for Neuroscience Research, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC.,George Washington University School of Medicine and Health Science, Washington, DC
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39
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Cachia A, Borst G, Jardri R, Raznahan A, Murray GK, Mangin JF, Plaze M. Towards Deciphering the Fetal Foundation of Normal Cognition and Cognitive Symptoms From Sulcation of the Cortex. Front Neuroanat 2021; 15:712862. [PMID: 34650408 PMCID: PMC8505772 DOI: 10.3389/fnana.2021.712862] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/31/2021] [Indexed: 01/16/2023] Open
Abstract
Growing evidence supports that prenatal processes play an important role for cognitive ability in normal and clinical conditions. In this context, several neuroimaging studies searched for features in postnatal life that could serve as a proxy for earlier developmental events. A very interesting candidate is the sulcal, or sulco-gyral, patterns, macroscopic features of the cortex anatomy related to the fold topology-e.g., continuous vs. interrupted/broken fold, present vs. absent fold-or their spatial organization. Indeed, as opposed to quantitative features of the cortical sheet (e.g., thickness, surface area or curvature) taking decades to reach the levels measured in adult, the qualitative sulcal patterns are mainly determined before birth and stable across the lifespan. The sulcal patterns therefore offer a window on the fetal constraints on specific brain areas on cognitive abilities and clinical symptoms that manifest later in life. After a global review of the cerebral cortex sulcation, its mechanisms, its ontogenesis along with methodological issues on how to measure the sulcal patterns, we present a selection of studies illustrating that analysis of the sulcal patterns can provide information on prenatal dispositions to cognition (with a focus on cognitive control and academic abilities) and cognitive symptoms (with a focus on schizophrenia and bipolar disorders). Finally, perspectives of sulcal studies are discussed.
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Affiliation(s)
- Arnaud Cachia
- Université de Paris, LaPsyDÉ, CNRS, Paris, France
- Université de Paris, IPNP, INSERM, Paris, France
| | - Grégoire Borst
- Université de Paris, LaPsyDÉ, CNRS, Paris, France
- Institut Universitaire de France, Paris, France
| | - Renaud Jardri
- Univ Lille, INSERM U-1172, CHU Lille, Lille Neuroscience & Cognition Centre, Plasticity & SubjectivitY (PSY) team, Lille, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, United States
| | - Graham K. Murray
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | | | - Marion Plaze
- Université de Paris, IPNP, INSERM, Paris, France
- GHU PARIS Psychiatrie & Neurosciences, site Sainte-Anne, Service Hospitalo-Universitaire, Pôle Hospitalo-Universitaire Paris, Paris, France
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40
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Gharehgazlou A, Vandewouw M, Ziolkowski J, Wong J, Crosbie J, Schachar R, Nicolson R, Georgiades S, Kelley E, Ayub M, Hammill C, Ameis SH, Taylor MJ, Lerch JP, Anagnostou E. Cortical Gyrification Morphology in ASD and ADHD: Implication for Further Similarities or Disorder-Specific Features? Cereb Cortex 2021; 32:2332-2342. [PMID: 34550324 PMCID: PMC9157290 DOI: 10.1093/cercor/bhab326] [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] [Indexed: 11/13/2022] Open
Abstract
Shared etiological pathways are suggested in ASD and ADHD given high rates of comorbidity, phenotypic overlap and shared genetic susceptibility. Given the peak of cortical gyrification expansion and emergence of ASD and ADHD symptomology in early development, we investigated gyrification morphology in 539 children and adolescents (6–17 years of age) with ASD (n=197) and ADHD (n=96) compared to typically developing controls (n=246) using the local Gyrification Index (lGI) to provide insight into contributing etiopathological factors in these two disorders. We also examined IQ effects and functional implications of gyrification by exploring the relation between lGI and ASD and ADHD symptomatology beyond diagnosis. General Linear Models yielded no group differences in lGI, and across groups, we identified an age-related decrease of lGI and greater lGI in females compared to males. No diagnosis-by-age interactions were found. Accounting for IQ variability in the model (n=484) yielded similar results. No significant associations were found between lGI and social communication deficits, repetitive and restricted behaviours, inattention or adaptive functioning. By examining both disorders and controls using shared methodology, we found no evidence of atypicality in gyrification as measured by the lGI in these conditions.
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Affiliation(s)
- Avideh Gharehgazlou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto M4G 1R8, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto M5S 1A8, Canada
| | - Marlee Vandewouw
- Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada.,Diagnostic Imaging, The Hospital for Sick Children, Toronto M5G 1X8, Canada.,Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto M4G 1R8, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto M5S 3G9, Canada
| | - Justine Ziolkowski
- Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada.,Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal H4H 1R3, Canada.,Integrated Program in Neuroscience, McGill University, Montreal H3A 1A1, Canada
| | - Jimmy Wong
- Centre for Addiction and Mental Health, Toronto M6J 1H4, Canada
| | - Jennifer Crosbie
- Department of Psychiatry, University of Toronto, Toronto M5T 1R8, Canada.,Psychiatry Research, The Hospital for Sick Children, Toronto M5G 1X8, Canada
| | - Russell Schachar
- Department of Psychiatry, University of Toronto, Toronto M5T 1R8, Canada.,Department of Psychiatry, The Hospital for Sick Children, Toronto M5G 1X8, Canada
| | - Rob Nicolson
- The Children's Health Research Institute and Western University, London N6C 2V5, Canada
| | - Stelios Georgiades
- Offord Centre for Child Studies & Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton L8N 3K7, Canada
| | - Elizabeth Kelley
- Department of Psychology, Queen's University, Kingston K7L 3N6, Canada
| | - Muhammad Ayub
- Department of Psychiatry, Queen's University, Kingston K7L7X3, Canada
| | - Christopher Hammill
- Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada.,Mouse Imaging Centre, Hospital for Sick Children, Toronto M5T 3H7, Canada
| | - Stephanie H Ameis
- Program in Brain and Mental Health, The Hospital for Sick Children, Toronto M5G 1X8 , Canada.,The Margaret and Wallace McCain Centre for Child, Youth, & Family Mental Health, Campbell Family Mental Health Research Institute, The Centre for Addiction and Mental Health, Toronto M6J 1H4, Canada.,Department of Psychiatry, University of Toronto, Toronto M5T 1R8, Canada
| | - Margot J Taylor
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto M5S 1A8, Canada.,Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada.,Diagnostic Imaging, The Hospital for Sick Children, Toronto M5G 1X8, Canada.,Department of Medical Imaging, University of Toronto, Toronto M5T 1W7, Canada
| | - Jason P Lerch
- Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada.,Department of Medical Biophysics, University of Toronto, Toronto M5G 1L7, Canada.,Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto M4G 1R8, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto M5S 1A8, Canada.,Department of Pediatrics, University of Toronto, Toronto M5G 1X8, Canada.,Neuroscience & Mental Health Program, Hospital for Sick Children Research Institute, Toronto M5G 0A4, Canada
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41
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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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42
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Li L, Zuo Y, Chen Y. Relationship between local gyrification index and age, intelligence quotient, symptom severity with Autism Spectrum Disorder: A large-scale MRI study. J Clin Neurosci 2021; 91:193-199. [PMID: 34373026 DOI: 10.1016/j.jocn.2021.07.003] [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: 01/23/2021] [Revised: 06/28/2021] [Accepted: 07/04/2021] [Indexed: 11/25/2022]
Abstract
Gyrification is one of the most important characteristics in the cerebral cortex and the local gyrification index (LGI) was used to quantify the regional changes in gyrification. The aim of this study was to evaluate LGI alterations in autism spectrum disorder (ASD) individuals in comparison with typically developing (TD) controls and the association of the LGI with age, intelligence quotient (IQ), and symptom severity in a large multicenter dataset. Structural MRI datasets selected from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) repository (606 ASD individuals and 765 age-matched TD controls) were used to calculate LGI values. The correlation between the LGI and age, IQ, and other clinical measurements were assessed. No differences in LGI were found between ASD individuals and TD controls after FDR multiple comparison correction, however, LGI decreased with age in both ASD and TD groups. In the TD group, a significant positive correlation was found between the LGI and full IQ (FIQ) in the parahippocampal gyrus, parsopercularis of left hemisphere and entorhinal cortex, parahippocampal, superior temporal gyrus of right hemisphere, but was not observed in the ASD group. Furthermore, a positive correlation between the LGI and Autism Diagnostic Interview-Revised (ADI-R) Repetitive and Restrictive Behaviors (RRB) score was found in the left inferior parietal lobule, lateral occipital cortex, superior frontal gyrus and right superior frontal gyrus, inferior temporal gyrus. In summary, these results demonstrate that the ASD is a truly heterogeneous neurodevelopmental disorder. Future investigations are required that group ASD patients into more homogeneous subtypes.
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Affiliation(s)
- Lin Li
- Human Anatomy Department, Nanjing Medical University, No.101 Longmian Avenue, Jiangning District, Nanjing 211166, Jiangsu, PR China.
| | - Yizhi Zuo
- Human Anatomy Department, Nanjing Medical University, No.101 Longmian Avenue, Jiangning District, Nanjing 211166, Jiangsu, PR China.
| | - Yiyong Chen
- School of Medicine, Ningbo University, No. 818 Fenghua Road, Jiangbei District, Ningbo 315211, Zhejiang, PR China.
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43
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Copeland A, Silver E, Korja R, Lehtola SJ, Merisaari H, Saukko E, Sinisalo S, Saunavaara J, Lähdesmäki T, Parkkola R, Nolvi S, Karlsson L, Karlsson H, Tuulari JJ. Infant and Child MRI: A Review of Scanning Procedures. Front Neurosci 2021; 15:666020. [PMID: 34321992 PMCID: PMC8311184 DOI: 10.3389/fnins.2021.666020] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/04/2021] [Indexed: 12/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a safe method to examine human brain. However, a typical MR scan is very sensitive to motion, and it requires the subject to lie still during the acquisition, which is a major challenge for pediatric scans. Consequently, in a clinical setting, sedation or general anesthesia is often used. In the research setting including healthy subjects anesthetics are not recommended for ethical reasons and potential longer-term harm. Here we review the methods used to prepare a child for an MRI scan, but also on the techniques and tools used during the scanning to enable a successful scan. Additionally, we critically evaluate how studies have reported the scanning procedure and success of scanning. We searched articles based on special subject headings from PubMed and identified 86 studies using brain MRI in healthy subjects between 0 and 6 years of age. Scan preparations expectedly depended on subject's age; infants and young children were scanned asleep after feeding and swaddling and older children were scanned awake. Comparing the efficiency of different procedures was difficult because of the heterogeneous reporting of the used methods and the success rates. Based on this review, we recommend more detailed reporting of scanning procedure to help find out which are the factors affecting the success of scanning. In the long term, this could help the research field to get high quality data, but also the clinical field to reduce the use of anesthetics. Finally, we introduce the protocol used in scanning 2 to 5-week-old infants in the FinnBrain Birth Cohort Study, and tips for calming neonates during the scans.
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Affiliation(s)
- Anni Copeland
- 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
| | - Eero Silver
- 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
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Satu J. Lehtola
- 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, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Susanne Sinisalo
- 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, 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
| | - 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, University of Turku, Turku, Finland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology and Speech-Language Pathology, Turku Institute for Advanced Studies, 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 Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, 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
| | - 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
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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44
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Fu X, Richards JE. Investigating developmental changes in scalp-to-cortex correspondence using diffuse optical tomography sensitivity in infancy. NEUROPHOTONICS 2021; 8:035003. [PMID: 34322572 PMCID: PMC8305752 DOI: 10.1117/1.nph.8.3.035003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 07/09/2021] [Indexed: 05/25/2023]
Abstract
Significance: Diffuse optical tomography (DOT) uses near-infrared light spectroscopy (NIRS) to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of NIRS data require accurate descriptions of the cranio-cerebral relations and DOT sensitivity to the underlying cortical structures. Such information is limited for pediatric populations because they undergo rapid head and brain development. Aim: We aim to investigate age-related differences in scalp-to-cortex distance and mapping between scalp locations and cortical regions of interest (ROIs) among infants (2 weeks to 24 months with narrow age bins), children (4 and 12 years), and adults (20 to 24 years). Approach: We used spatial scalp projection and photon propagation simulation methods with age-matched realistic head models based on MRIs. Results: There were age-group differences in the scalp-to-cortex distances in infancy. The developmental increase was magnified in children and adults. There were systematic age-related differences in the probabilistic mappings between scalp locations and cortical ROIs. Conclusions: Our findings have important implications in the design of sensor placement and making anatomical interpretations in NIRS and fNIRS research. Age-appropriate, realistic head models should be used to provide anatomical guidance for standalone DOT data in infants.
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Affiliation(s)
- Xiaoxue Fu
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
| | - John E. Richards
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
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45
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Gajawelli N, Deoni SCL, Ramsy N, Dean DC, O'Muircheartaigh J, Nelson MD, Lepore N, Coulon O. Developmental changes of the central sulcus morphology in young children. Brain Struct Funct 2021; 226:1841-1853. [PMID: 34043074 DOI: 10.1007/s00429-021-02292-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 05/06/2021] [Indexed: 12/01/2022]
Abstract
The human brain grows rapidly in early childhood, reaching 95% of its final volume by age 6. Understanding brain growth in childhood is important both to answer neuroscience questions about anatomical changes in development, and as a comparison metric for neurological disorders. Metrics for neuroanatomical development including cortical measures pertaining to the sulci can be instrumental in early diagnosis, monitoring, and intervention for neurological diseases. In this paper, we examine the development of the central sulcus in children aged 12-60 months from structural magnetic resonance images. The central sulcus is one of the earliest sulci to develop at the fetal stage and is implicated in diseases such as Attention Deficit Hyperactive Disorder and Williams syndrome. We investigate the relationship between the changes in the depth of the central sulcus with respect to age. In our results, we observed a pattern of depth present early on, that had been previously observed in adults. Results also reveal the presence of a rightward depth asymmetry at 12 months of age at a location related to orofacial movements. That asymmetry disappears gradually, mostly between 12 and 24 months, and we suggest that it is related to the development of language skills.
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Affiliation(s)
- Niharika Gajawelli
- CIBORG Laboratory, Department of Radiology, Children's Hospital of Los Angeles, 4650 Sunset Blvd, Los Angeles, CA, 90027, USA
| | - Sean C L Deoni
- Advanced Baby Imaging Lab, Hasbro Children's Hospital, 593 Eddy Street Ground Level, Providence, RI, 02903, USA
- Pediatrics and Radiology, Warren Alpert Medical School, Brown University, 222 Richmond St, Providence, RI, 02903, USA
- Maternal, Newborn & Child Health Discovery & Tools at the Bill and Melinda Gates Foundation, 500 5th Ave N, Seattle, WA, 98109, USA
| | - Natalie Ramsy
- Carle Illinois College of Medicine, 807 S Wright St, Champaign, IL, 61820, USA
| | - Douglas C Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI, 53705, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI, 53792, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53705, USA
| | - Jonathan O'Muircheartaigh
- Department for Forensic and Neurodevelopmental Sciences, Centre for Neuroimaging Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 2nd FloorDenmark Hill, London, UK
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, 4th Floor, Lambeth Wing St. Thomas' Hospital Westminster Bridge Road SE17EH, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London, SE1 1UL, UK
| | - Marvin D Nelson
- CIBORG Laboratory, Department of Radiology, Children's Hospital of Los Angeles, 4650 Sunset Blvd, Los Angeles, CA, 90027, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo Street, Los Angeles, CA, 90033, USA
| | - Natasha Lepore
- CIBORG Laboratory, Department of Radiology, Children's Hospital of Los Angeles, 4650 Sunset Blvd, Los Angeles, CA, 90027, USA.
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo Street, Los Angeles, CA, 90033, USA.
| | - Olivier Coulon
- Faculty of Medicine, Institut de Neurosciences de la Timone, Aix-Marseille University, CNRS UMR7289, 27, boulevard Jean Moulin, 13005, Marseille, France
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46
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Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
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Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
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47
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Nwosu EC, Holmes MJ, Cotton MF, Dobbels E, Little F, Laughton B, van der Kouwe A, Meintjes EM, Robertson F. Cortical structural changes related to early antiretroviral therapy (ART) interruption in perinatally HIV-infected children at 5 years of age. IBRO Neurosci Rep 2021; 10:161-170. [PMID: 34179869 PMCID: PMC8211921 DOI: 10.1016/j.ibneur.2021.02.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 02/03/2021] [Indexed: 12/21/2022] Open
Abstract
ART interruption in children can occur especially in resource-limited settings for reasons including poor adherence, stock-outs, ART intolerance of non-pediatric formulas and pill size, as well as ultimately to test for HIV remission. Although early ART initiation is now standard of care in pediatric HIV management, very little is known on the effect of early ART initiation or subsequent interruption on brain development. This study aimed to investigate the effect of ART interruption on brain cortical thickness (CT) and folding in a subset of children from the Children with HIV Early antiRetroviral therapy (CHER) trial cohort who all started ART before 18 months of age. CHER participants in the neuroimaging follow-up study had magnetic resonance (MRI) scans on a 3T Siemens Allegra brain scanner at age 5.44 ± 0.37 years. MR images were processed using the automated cross-sectional stream in FreeSurfer v6.0 and vertex wise comparisons of CT and local gyrification indices (LGIs) were performed between HIV+ children and HIV- controls, as well as between HIV+ children on interrupted or continuous ART and controls. HIV+ children (n = 46) showed thicker cortex than HIV- children (n = 29) in bilateral frontal and left temporo-insular regions but lower LGIs in left superior and bilateral medial orbitofrontal cortex extending into rostral anterior cingulate. Children on interrupted ART (n = 21) had thicker cortex than HIV- controls in left frontal and right insular regions, but children on continuous treatment (n = 25) showed no difference from controls. Children on both interrupted and continuous ART showed region-specific alterations in LGI relative to controls. Cortical folding appears more sensitive than CT to early life events including early ART and interruption. However, immune health resilience in children can translate to long term preservation of morphometric brain development, especially for those on early and continuous treatment.
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Affiliation(s)
- Emmanuel C. Nwosu
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, South Africa
- Neuroscience Institute, Faculty of Health Sciences, University of Cape Town, South Africa
| | - Martha J. Holmes
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, South Africa
- Neuroscience Institute, Faculty of Health Sciences, University of Cape Town, South Africa
| | - Mark F. Cotton
- Family Centre for Research with Ubuntu, Department of Paediatrics & Child Health, Tygerberg Children’s Hospital and Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Els Dobbels
- Family Centre for Research with Ubuntu, Department of Paediatrics & Child Health, Tygerberg Children’s Hospital and Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, Faculty of Sciences, University of Cape Town, South Africa
| | - Barbara Laughton
- Family Centre for Research with Ubuntu, Department of Paediatrics & Child Health, Tygerberg Children’s Hospital and Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Andre van der Kouwe
- A.A. Martinos Centre for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Ernesta M. Meintjes
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, South Africa
- Neuroscience Institute, Faculty of Health Sciences, University of Cape Town, South Africa
| | - Frances Robertson
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, South Africa
- Neuroscience Institute, Faculty of Health Sciences, University of Cape Town, South Africa
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Besson P, Parrish T, Katsaggelos AK, Bandt SK. Geometric deep learning on brain shape predicts sex and age. Comput Med Imaging Graph 2021; 91:101939. [PMID: 34082280 DOI: 10.1016/j.compmedimag.2021.101939] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/24/2021] [Accepted: 05/04/2021] [Indexed: 10/21/2022]
Abstract
The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.
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Affiliation(s)
- Pierre Besson
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States; Department of Neurological Surgery, Northwestern University, Feinberg School of Medicine, Chicago IL, United States
| | - Todd Parrish
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Aggelos K Katsaggelos
- Department of Electrical Engineering & Computer Science, Northwestern University, McCormick School of Engineering, Evanston, IL, United States
| | - S Kathleen Bandt
- Department of Neurological Surgery, Northwestern University, Feinberg School of Medicine, Chicago IL, United States.
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Gao L, Ruan Z, Xiao Y, Xu H. Surface-based Cortical Morphometry, White Matter Hyperintensity, and Multidomain Cognitive Performance in Asymptomatic Carotid Stenosis. Neuroscience 2021; 467:16-27. [PMID: 34022325 DOI: 10.1016/j.neuroscience.2021.05.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 12/27/2022]
Abstract
Carotid stenosis is a major contributor to vascular dementia. Recent studies suggest that even clinically "asymptomatic" carotid stenosis is linked with cognitive decline and neuroimaging changes. Here we examined surface-based cortical morphometry, white matter hyperintensity (WMH), and multidomain cognitive performance in unilateral severe (>70% narrowing) asymptomatic carotid stenosis (SACS). We included 24 SACS patients (19 males/5 females; 64.25 ± 7.18 years) and 24 comorbidities-matched controls (19 males/5 females; 67.16 ± 6.10 years), and measured cortical thickness, sulcal depth, gyrification, cortical complexity, and WMH loads with structural MRI images. The SACS patients exhibited: (1) thinner cortex in bilateral somatosensory/motor, bilateral inferior frontal, bilateral fusiform, and left lateral temporal areas; (2) shallower sulci in left lateral temporal, parietal, insular and somatosensory/motor areas; (3) both hyper- and hypo-gyrification in lateral temporal and frontal cortices; (4) lower complexity (fractal dimension) in left insular and right superior temporal areas. Further association analyses showed that the cortical alterations were significantly correlated with verbal memory and WMH burden in SACS. These results suggest that SACS patients present a left-dominated damage tendency, especially in the Perisylvian cortices that span across several large-scale systems of somatosensory/motor and language. Our findings also provide cortical anatomy evidence for cognitive impairment in SACS, suggesting a neuroanatomical predisposition to dementia and cerebrovascular events.
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Affiliation(s)
- Lei Gao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, Wuhan City 430071, Hubei Province, China
| | - Zhao Ruan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, Wuhan City 430071, Hubei Province, China
| | - Yaqiong Xiao
- Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen 518057, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, Wuhan City 430071, Hubei Province, China.
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Kovacs-Balint ZA, Payne C, Steele J, Li L, Styner M, Bachevalier J, Sanchez MM. Structural development of cortical lobes during the first 6 months of life in infant macaques. Dev Cogn Neurosci 2021; 48:100906. [PMID: 33465553 PMCID: PMC7815644 DOI: 10.1016/j.dcn.2020.100906] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 12/06/2020] [Accepted: 12/17/2020] [Indexed: 12/20/2022] Open
Abstract
This study mapped the developmental trajectories of cortical regions in comparison to overall brain growth in typically developing, socially-housed infant macaques. Volumetric changes of cortical brain regions were examined longitudinally between 2-24 weeks of age (equivalent to the first 2 years in humans) in 21 male rhesus macaques. Growth of the prefrontal, frontal, parietal, occipital, and temporal cortices (visual and auditory) was examined using MRI and age-specific infant macaque brain atlases developed by our group. Results indicate that cortical volumetric development follows a cubic growth curve, but maturational timelines and growth rates are region-specific. Total intracranial volume (ICV) increased significantly during the first 5 months of life, leveling off thereafter. Prefrontal and temporal visual cortices showed fast volume increases during the first 16 weeks, followed by a plateau, and significant growth again between 20-24 weeks. Volume of the frontal and temporal auditory cortices increased substantially between 2-24 weeks. The parietal cortex showed a significant volume increase during the first 4 months, whereas the volume of the occipital lobe increased between 2-12 weeks and plateaued thereafter. These developmental trajectories show similarities to cortical growth in human infants, providing foundational information necessary to build nonhuman primate (NHP) models of human neurodevelopmental disorders.
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Affiliation(s)
- Z A Kovacs-Balint
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, United States
| | - C Payne
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, United States; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, 30329, United States
| | - J Steele
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, United States
| | - L Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, 30329, United States; Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA, 30322, United States
| | - M Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, 27514, United States
| | - J Bachevalier
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, United States; Department of Psychology, Emory University, Atlanta, GA, 30322, United States
| | - M M Sanchez
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30329, United States; Department of Psychiatry & Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA, 30322, United States.
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