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Snyder WE, Vértes PE, Kyriakopoulou V, Wagstyl K, Williams LZJ, Moraczewski D, Thomas AG, Karolis VR, Seidlitz J, Rivière D, Robinson EC, Mangin JF, Raznahan A, Bullmore ET. A bimodal taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients. Neuron 2024:S0896-6273(24)00568-3. [PMID: 39178859 DOI: 10.1016/j.neuron.2024.07.023] [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: 11/18/2023] [Revised: 05/22/2024] [Accepted: 07/29/2024] [Indexed: 08/26/2024]
Abstract
We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.
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Affiliation(s)
- William E Snyder
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA.
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Logan Z J Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Adam G Thomas
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette 91191, France
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Jean-Francois Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette 91191, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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2
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Bouhali F, Dubois J, Hoeft F, Weiner KS. Unique longitudinal contributions of sulcal interruptions to reading acquisition in children. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.30.605574. [PMID: 39131390 PMCID: PMC11312548 DOI: 10.1101/2024.07.30.605574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
A growing body of literature indicates strong associations between indentations of the cerebral cortex (i.e., sulci) and individual differences in cognitive performance. Interruptions, or gaps, of sulci (historically known as pli de passage) are particularly intriguing as previous work suggests that these interruptions have a causal effect on cognitive development. Here, we tested how the presence and morphology of sulcal interruptions in the left posterior occipitotemporal sulcus (pOTS) longitudinally impact the development of a culturally-acquired skill: reading. Forty-three children were successfully followed from age 5 in kindergarten, at the onset of literacy instruction, to ages 7 and 8 with assessments of cognitive, pre-literacy, and literacy skills, as well as MRI anatomical scans at ages 5 and 8. Crucially, we demonstrate that the presence of a left pOTS gap at 5 years is a specific and robust longitudinal predictor of better future reading skills in children, with large observed benefits on reading behavior ranging from letter knowledge to reading comprehension. The effect of left pOTS interruptions on reading acquisition accumulated through time, and was larger than the impact of benchmark cognitive and familial predictors of reading ability and disability. Finally, we show that increased local U-fiber white matter connectivity associated with such sulcal interruptions possibly underlie these behavioral benefits, by providing a computational advantage. To our knowledge, this is the first quantitative evidence supporting a potential integrative gray-white matter mechanism underlying the cognitive benefits of macro-anatomical differences in sulcal morphology related to longitudinal improvements in a culturally-acquired skill.
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Affiliation(s)
- Florence Bouhali
- Department of Psychiatry and Behavioral Sciences & Weil Institute of Neuroscience, University of California San Francisco, San Francisco, CA, USA
- Aix-Marseille University, CNRS, CRPN, Marseille, France
| | - Jessica Dubois
- University Paris Cité, NeuroDiderot, INSERM, Paris, France
- University Paris-Saclay, NeuroSpin, UNIACT, CEA, France
| | - Fumiko Hoeft
- Department of Psychological Sciences, University of Connecticut Waterbury, Waterbury, CT, USA
| | - Kevin S. Weiner
- Department of Psychology, Department of Neuroscience, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
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Zhong T, Wu X, Liang S, Ning Z, Wang L, Niu Y, Yang S, Kang Z, Feng Q, Li G, Zhang Y. nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species. Neuroimage 2024; 295:120652. [PMID: 38797384 DOI: 10.1016/j.neuroimage.2024.120652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 05/29/2024] Open
Abstract
Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) serves an indispensable role in understanding brain evolution, development, aging, and diseases. Despite the accumulation of diverse NHP brain MRI datasets at various developmental stages and from various imaging sites/scanners, existing computational tools designed for human MRI typically perform poor on NHP data, due to huge differences in brain sizes, morphologies, and imaging appearances across species, sites, and ages, highlighting the imperative for NHP-specialized MRI processing tools. To address this issue, in this paper, we present a robust, generic, and fully automated computational pipeline, called non-human primates Brain Extraction and Segmentation Toolbox (nBEST), whose main functionality includes brain extraction, non-cerebrum removal, and tissue segmentation. Building on cutting-edge deep learning techniques by employing lifelong learning to flexibly integrate data from diverse NHP populations and innovatively constructing 3D U-NeXt architecture, nBEST can well handle structural NHP brain MR images from multi-species, multi-site, and multi-developmental-stage (from neonates to the elderly). We extensively validated nBEST based on, to our knowledge, the largest assemblage dataset in NHP brain studies, encompassing 1,469 scans with 11 species (e.g., rhesus macaques, cynomolgus macaques, chimpanzees, marmosets, squirrel monkeys, etc.) from 23 independent datasets. Compared to alternative tools, nBEST outperforms in precision, applicability, robustness, comprehensiveness, and generalizability, greatly benefiting downstream longitudinal, cross-sectional, and cross-species quantitative analyses. We have made nBEST an open-source toolbox (https://github.com/TaoZhong11/nBEST) and we are committed to its continual refinement through lifelong learning with incoming data to greatly contribute to the research field.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
| | - Shihua Yang
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Zhuang Kang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qianjin Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.
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4
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Murillo C, Eixarch E, Rueda C, Larroya M, Boada D, Grau L, Ponce J, Aldecoa V, Monterde E, Ferrero S, Andreu-Fernández V, Arca G, Oleaga L, Ros O, Hernández MP, Gratacós E, Palacio M, Cobo T. Evidence of brain injury in fetuses of mothers with preterm labor with intact membranes and preterm premature rupture of membranes. Am J Obstet Gynecol 2024:S0002-9378(24)00531-3. [PMID: 38685550 DOI: 10.1016/j.ajog.2024.04.025] [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: 01/25/2024] [Revised: 04/10/2024] [Accepted: 04/23/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Brain injury and poor neurodevelopment have been consistently reported in infants and adults born before term. These changes occur, at least in part, prenatally and are associated with intra-amniotic inflammation. The pattern of brain changes has been partially documented by magnetic resonance imaging but not by neurosonography along with amniotic fluid brain injury biomarkers. OBJECTIVE This study aimed to evaluate the prenatal features of brain remodeling and injury in fetuses from patients with preterm labor with intact membranes or preterm premature rupture of membranes and to investigate the potential influence of intra-amniotic inflammation as a risk mediator. STUDY DESIGN In this prospective cohort study, fetal brain remodeling and injury were evaluated using neurosonography and amniocentesis in singleton pregnant patients with preterm labor with intact membranes or preterm premature rupture of membranes between 24.0 and 34.0 weeks of gestation, with (n=41) and without (n=54) intra-amniotic inflammation. The controls for neurosonography were outpatient pregnant patients without preterm labor or preterm premature rupture of membranes matched 2:1 by gestational age at ultrasound. Amniotic fluid controls were patients with an amniocentesis performed for indications other than preterm labor or preterm premature rupture of membranes without brain or genetic defects whose amniotic fluid was collected in our biobank for research purposes matched by gestational age at amniocentesis. The group with intra-amniotic inflammation included those with intra-amniotic infection (microbial invasion of the amniotic cavity and intra-amniotic inflammation) and those with sterile inflammation. Microbial invasion of the amniotic cavity was defined as a positive amniotic fluid culture and/or positive 16S ribosomal RNA gene. Inflammation was defined by amniotic fluid interleukin 6 concentrations of >13.4 ng/mL in preterm labor and >1.43 ng/mL in preterm premature rupture of membranes. Neurosonography included the evaluation of brain structure biometric parameters and cortical development. Neuron-specific enolase, protein S100B, and glial fibrillary acidic protein were selected as amniotic fluid brain injury biomarkers. Data were adjusted for cephalic biometrics, fetal growth percentile, fetal sex, noncephalic presentation, and preterm premature rupture of membranes at admission. RESULTS Fetuses from mothers with preterm labor with intact membranes or preterm premature rupture of membranes showed signs of brain remodeling and injury. First, they had a smaller cerebellum. Thus, in the intra-amniotic inflammation, non-intra-amniotic inflammation, and control groups, the transcerebellar diameter measurements were 32.7 mm (interquartile range, 29.8-37.6), 35.3 mm (interquartile range, 31.2-39.6), and 35.0 mm (interquartile range, 31.3-38.3), respectively (P=.019), and the vermian height measurements were 16.9 mm (interquartile range, 15.5-19.6), 17.2 mm (interquartile range, 16.0-18.9), and 17.1 mm (interquartile range, 15.7-19.0), respectively (P=.041). Second, they presented a lower corpus callosum area (0.72 mm2 [interquartile range, 0.59-0.81], 0.71 mm2 [interquartile range, 0.63-0.82], and 0.78 mm2 [interquartile range, 0.71-0.91], respectively; P=.006). Third, they showed delayed cortical maturation (the Sylvian fissure depth-to-biparietal diameter ratios were 0.14 [interquartile range, 0.12-0.16], 0.14 [interquartile range, 0.13-0.16], and 0.16 [interquartile range, 0.15-0.17], respectively [P<.001], and the right parieto-occipital sulci depth ratios were 0.09 [interquartile range, 0.07-0.12], 0.11 [interquartile range, 0.09-0.14], and 0.11 [interquartile range, 0.09-0.14], respectively [P=.012]). Finally, regarding amniotic fluid brain injury biomarkers, fetuses from mothers with preterm labor with intact membranes or preterm premature rupture of membranes had higher concentrations of neuron-specific enolase (11,804.6 pg/mL [interquartile range, 6213.4-21,098.8], 8397.7 pg/mL [interquartile range, 3682.1-17,398.3], and 2393.7 pg/mL [interquartile range, 1717.1-3209.3], respectively; P<.001), protein S100B (2030.6 pg/mL [interquartile range, 993.0-4883.5], 1070.3 pg/mL [interquartile range, 365.1-1463.2], and 74.8 pg/mL [interquartile range, 44.7-93.7], respectively; P<.001), and glial fibrillary acidic protein (1.01 ng/mL [interquartile range, 0.54-3.88], 0.965 ng/mL [interquartile range, 0.59-2.07], and 0.24 mg/mL [interquartile range, 0.20-0.28], respectively; P=.002). CONCLUSION Fetuses with preterm labor with intact membranes or preterm premature rupture of membranes had prenatal signs of brain remodeling and injury at the time of clinical presentation. These changes were more pronounced in fetuses with intra-amniotic inflammation.
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Affiliation(s)
- Clara Murillo
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - Elisenda Eixarch
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Center for Biomedical Research on Rare Diseases, Institute of Health Carlos III, Madrid, Spain
| | - Claudia Rueda
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - Marta Larroya
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - David Boada
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Laia Grau
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Júlia Ponce
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Victoria Aldecoa
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Elena Monterde
- Biosanitary Research Institute, Valencian International University (VIU), Valencia, Spain. Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer (IIS-FRCB-IDIBAPS), Universitat de Barcelona. Barcelona, Spain
| | - Silvia Ferrero
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Vicente Andreu-Fernández
- Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Biosanitary Research Institute, Valencian International University, Valencia, Spain
| | - Gemma Arca
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - Laura Oleaga
- Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Department of Radiology, Clinical Diagnostic Imaging Centre, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Olga Ros
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain
| | - Maria Pilar Hernández
- Department of Radiology, Clinical Diagnostic Imaging Centre, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Eduard Gratacós
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Center for Biomedical Research on Rare Diseases, Institute of Health Carlos III, Madrid, Spain.
| | - Montse Palacio
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Center for Biomedical Research on Rare Diseases, Institute of Health Carlos III, Madrid, Spain
| | - Teresa Cobo
- BCNatal Fetal Medicine Research Center, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic de Barcelona and Hospital Sant Joan de Déu), Institut Clínic de Ginecología, Obstetrícia i Neonatología, Barcelona, Spain; Fundació de Recerca Clínica Barcelona - Institut d'Investigacions Biomèdiques August Pi I Sunyer, Universitat de Barcelona, Barcelona, Spain; Center for Biomedical Research on Rare Diseases, Institute of Health Carlos III, Madrid, Spain
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5
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Kelly CE, Thompson DK, Adamson CL, Ball G, Dhollander T, Beare R, Matthews LG, Alexander B, Cheong JLY, Doyle LW, Anderson PJ, Inder TE. Cortical growth from infancy to adolescence in preterm and term-born children. Brain 2024; 147:1526-1538. [PMID: 37816305 PMCID: PMC10994536 DOI: 10.1093/brain/awad348] [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: 01/20/2023] [Revised: 08/10/2023] [Accepted: 09/30/2023] [Indexed: 10/12/2023] Open
Abstract
Early life experiences can exert a significant influence on cortical and cognitive development. Very preterm birth exposes infants to several adverse environmental factors during hospital admission, which affect cortical architecture. However, the subsequent consequence of very preterm birth on cortical growth from infancy to adolescence has never been defined; despite knowledge of critical periods during childhood for establishment of cortical networks. Our aims were to: chart typical longitudinal cortical development and sex differences in cortical development from birth to adolescence in healthy term-born children; estimate differences in cortical development between children born at term and very preterm; and estimate differences in cortical development between children with normal and impaired cognition in adolescence. This longitudinal cohort study included children born at term (≥37 weeks' gestation) and very preterm (<30 weeks' gestation) with MRI scans at ages 0, 7 and 13 years (n = 66 term-born participants comprising 34 with one scan, 18 with two scans and 14 with three scans; n = 201 very preterm participants comprising 56 with one scan, 88 with two scans and 57 with three scans). Cognitive assessments were performed at age 13 years. Cortical surface reconstruction and parcellation were performed with state-of-the-art, equivalent MRI analysis pipelines for all time points, resulting in longitudinal cortical volume, surface area and thickness measurements for 62 cortical regions. Developmental trajectories for each region were modelled in term-born children, contrasted between children born at term and very preterm, and contrasted between all children with normal and impaired cognition. In typically developing term-born children, we documented anticipated patterns of rapidly increasing cortical volume, area and thickness in early childhood, followed by more subtle changes in later childhood, with smaller cortical size in females than males. In contrast, children born very preterm exhibited increasingly reduced cortical volumes, relative to term-born children, particularly during ages 0-7 years in temporal cortical regions. This reduction in cortical volume in children born very preterm was largely driven by increasingly reduced cortical thickness rather than area. This resulted in amplified cortical volume and thickness reductions by age 13 years in individuals born very preterm. Alterations in cortical thickness development were found in children with impaired language and memory. This study shows that the neurobiological impact of very preterm birth on cortical growth is amplified from infancy to adolescence. These data further inform the long-lasting impact on cortical development from very preterm birth, providing broader insights into neurodevelopmental consequences of early life experiences.
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Affiliation(s)
- Claire E Kelly
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC 3800, Australia
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Deanne K Thompson
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC 3800, Australia
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Chris L Adamson
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Gareth Ball
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Richard Beare
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- National Centre for Healthy Ageing and Peninsula Clinical School, Faculty of Medicine, Monash University, Melbourne, VIC 3199, Australia
| | - Lillian G Matthews
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC 3800, Australia
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Bonnie Alexander
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Department of Neurosurgery, The Royal Children’s Hospital, Melbourne, VIC 3052, Australia
| | - Jeanie L Y Cheong
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, VIC 3052, Australia
- Newborn Research, The Royal Women’s Hospital, Melbourne, VIC 3052, Australia
- Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Lex W Doyle
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
- Newborn Research, The Royal Women’s Hospital, Melbourne, VIC 3052, Australia
- Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Peter J Anderson
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC 3800, Australia
- Victorian Infant Brain Studies (VIBeS), Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Terrie E Inder
- Center for Neonatal Research, Children's Hospital of Orange County, Orange, CA 92868, USA
- Department of Pediatrics, University of California, Irvine, Irvine, CA 92697, USA
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6
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Galdi P, Cabez MB, Farrugia C, Vaher K, Williams LZJ, Sullivan G, Stoye DQ, Quigley AJ, Makropoulos A, Thrippleton MJ, Bastin ME, Richardson H, Whalley H, Edwards AD, Bajada CJ, Robinson EC, Boardman JP. Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth. Hum Brain Mapp 2024; 45:e26660. [PMID: 38488444 PMCID: PMC10941526 DOI: 10.1002/hbm.26660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 01/18/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.
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Affiliation(s)
- Paola Galdi
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- School of InformaticsUniversity of EdinburghEdinburghUK
| | | | - Christine Farrugia
- Faculty of EngineeringUniversity of MaltaVallettaMalta
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
| | - Kadi Vaher
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | - Logan Z. J. Williams
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - Gemma Sullivan
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - David Q. Stoye
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
| | | | | | | | - Mark E. Bastin
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
| | - Hilary Richardson
- School of Philosophy, Psychology and Language SciencesUniversity of EdinburghEdinburghUK
| | - Heather Whalley
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Centre for Genomic and Experimental MedicineUniversity of EdinburghEdinburghUK
| | - A. David Edwards
- Centre for the Developing BrainKing's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Claude J. Bajada
- University of Malta Magnetic Resonance Imaging Platform (UMRI)VallettaMalta
- Department of Physiology and Biochemistry, Faculty of Medicine and SurgeryUniversity of MaltaVallettaMalta
| | - Emma C. Robinson
- Centre for the Developing BrainKing's College LondonLondonUK
- School of Biomedical Engineering and Imaging ScienceKing's College LondonLondonUK
| | - James P. Boardman
- MRC Centre for Reproductive HealthUniversity of EdinburghEdinburghUK
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
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7
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Demirci N, Holland MA. Scaling patterns of cortical folding and thickness in early human brain development in comparison with primates. Cereb Cortex 2024; 34:bhad462. [PMID: 38271274 DOI: 10.1093/cercor/bhad462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/02/2023] [Accepted: 11/04/2023] [Indexed: 01/27/2024] Open
Abstract
Across mammalia, brain morphology follows specific scaling patterns. Bigger bodies have bigger brains, with surface area outpacing volume growth, resulting in increased foldedness. We have recently studied scaling rules of cortical thickness, both local and global, finding that the cortical thickness difference between thick gyri and thin sulci also increases with brain size and foldedness. Here, we investigate early brain development in humans, using subjects from the Developing Human Connectome Project, scanned shortly after pre-term or full-term birth, yielding magnetic resonance images of the brain from 29 to 43 postmenstrual weeks. While the global cortical thickness does not change significantly during this development period, its distribution does, with sulci thinning, while gyri thickening. By comparing our results with our recent work on humans and 11 non-human primate species, we also compare the trajectories of primate evolution with human development, noticing that the 2 trends are distinct for volume, surface area, cortical thickness, and gyrification index. Finally, we introduce the global shape index as a proxy for gyrification index; while correlating very strongly with gyrification index, it offers the advantage of being calculated only from local quantities without generating a convex hull or alpha surface.
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Affiliation(s)
- Nagehan Demirci
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, United States
| | - Maria A Holland
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, United States
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, United States
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8
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Snyder WE, Vértes PE, Kyriakopoulou V, Wagstyl K, Williams LZJ, Moraczewski D, Thomas AG, Karolis VR, Seidlitz J, Rivière D, Robinson EC, Mangin JF, Raznahan A, Bullmore ET. A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572454. [PMID: 38168226 PMCID: PMC10760196 DOI: 10.1101/2023.12.19.572454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.
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Affiliation(s)
- William E Snyder
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Petra E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Logan Z J Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Adam G Thomas
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Jakob Seidlitz
- Lifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Science, King's College London, London, UK
| | - Jean-Francois Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, 91191, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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9
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Yehuda B, Rabinowich A, Link-Sourani D, Avisdris N, Ben-Zvi O, Specktor-Fadida B, Joskowicz L, Ben-Sira L, Miller E, Ben Bashat D. Automatic Quantification of Normal Brain Gyrification Patterns and Changes in Fetuses with Polymicrogyria and Lissencephaly Based on MRI. AJNR Am J Neuroradiol 2023; 44:1432-1439. [PMID: 38050002 PMCID: PMC10714858 DOI: 10.3174/ajnr.a8046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 09/23/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND AND PURPOSE The current imaging assessment of fetal brain gyrification is performed qualitatively and subjectively using sonography and MR imaging. A few previous studies have suggested methods for quantification of fetal gyrification based on 3D reconstructed MR imaging, which requires unique data and is time-consuming. In this study, we aimed to develop an automatic pipeline for gyrification assessment based on routinely acquired fetal 2D MR imaging data, to quantify normal changes with gestation, and to measure differences in fetuses with lissencephaly and polymicrogyria compared with controls. MATERIALS AND METHODS We included coronal T2-weighted MR imaging data of 162 fetuses retrospectively collected from 2 clinical sites: 134 controls, 12 with lissencephaly, 13 with polymicrogyria, and 3 with suspected lissencephaly based on sonography, yet with normal MR imaging diagnoses. Following brain segmentation, 5 gyrification parameters were calculated separately for each hemisphere on the basis of the area and ratio between the contours of the cerebrum and its convex hull. Seven machine learning classifiers were evaluated to differentiate control fetuses and fetuses with lissencephaly or polymicrogyria. RESULTS In control fetuses, all parameters changed significantly with gestational age (P < .05). Compared with controls, fetuses with lissencephaly showed significant reductions in all gyrification parameters (P ≤ .02). Similarly, significant reductions were detected for fetuses with polymicrogyria in several parameters (P ≤ .001). The 3 suspected fetuses showed normal gyrification values, supporting the MR imaging diagnosis. An XGBoost-linear algorithm achieved the best results for classification between fetuses with lissencephaly and control fetuses (n = 32), with an area under the curve of 0.90 and a recall of 0.83. Similarly, a random forest classifier showed the best performance for classification of fetuses with polymicrogyria and control fetuses (n = 33), with an area under the curve of 0.84 and a recall of 0.62. CONCLUSIONS This study presents a pipeline for automatic quantification of fetal brain gyrification and provides normal developmental curves from a large cohort. Our method significantly differentiated fetuses with lissencephaly and polymicrogyria, demonstrating lower gyrification values. The method can aid radiologic assessment, highlight fetuses at risk, and may improve early identification of fetuses with cortical malformations.
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Affiliation(s)
- Bossmat Yehuda
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience (B.Y., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
| | - Aviad Rabinowich
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sackler Faculty of Medicine (A.R., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
- Division of Radiology (A.R., L.B.-S.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Daphna Link-Sourani
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Netanell Avisdris
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- School of Computer Science and Engineering (N.A., L.J.), The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ori Ben-Zvi
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Bella Specktor-Fadida
- School of Computer Science and Engineering (B.S.-F.), The Hebrew University of Jerusalem, Israel
| | - Leo Joskowicz
- School of Computer Science and Engineering (N.A., L.J.), The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Liat Ben-Sira
- Sagol School of Neuroscience (B.Y., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
- Sackler Faculty of Medicine (A.R., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
- Division of Radiology (A.R., L.B.-S.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Elka Miller
- Department of Medical Imaging (E.M.), Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada
| | - Dafna Ben Bashat
- From the Sagol Brain Institute (B.Y., A.R., D.L.-S., N.A., O.B.-Z., D.B.B.), Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience (B.Y., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
- Sackler Faculty of Medicine (A.R., L.B.-S., D.B.B.), Tel Aviv University, Tel Aviv, Israel
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10
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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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11
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Rabanaque D, Regalado M, Benítez R, Rabanaque S, Agut T, Carreras N, Mata C. Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images. J Imaging 2023; 9:145. [PMID: 37504822 PMCID: PMC10381479 DOI: 10.3390/jimaging9070145] [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: 05/09/2023] [Revised: 07/06/2023] [Accepted: 07/12/2023] [Indexed: 07/29/2023] Open
Abstract
The third trimester of pregnancy is the most critical period for human brain development, during which significant changes occur in the morphology of the brain. The development of sulci and gyri allows for a considerable increase in the brain surface. In preterm newborns, these changes occur in an extrauterine environment that may cause a disruption of the normal brain maturation process. We hypothesize that a normalized atlas of brain maturation with cerebral ultrasound images from birth to term equivalent age will help clinicians assess these changes. This work proposes a semi-automatic Graphical User Interface (GUI) platform for segmenting the main cerebral sulci in the clinical setting from ultrasound images. This platform has been obtained from images of a cerebral ultrasound neonatal database images provided by two clinical researchers from the Hospital Sant Joan de Déu in Barcelona, Spain. The primary objective is to provide a user-friendly design platform for clinicians for running and visualizing an atlas of images validated by medical experts. This GUI offers different segmentation approaches and pre-processing tools and is user-friendly and designed for running, visualizing images, and segmenting the principal sulci. The presented results are discussed in detail in this paper, providing an exhaustive analysis of the proposed approach's effectiveness.
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Affiliation(s)
- David Rabanaque
- Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain
| | - Maria Regalado
- Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain
| | - Raul Benítez
- Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain
- Research Centre for Biomedical Engineering (CREB), Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
- Pediatric Computational Imaging Research Group, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
| | - Sonia Rabanaque
- Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain
| | - Thais Agut
- Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
- Neonatal Department, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
- Fundación NeNe, 28010 Madrid, Spain
| | - Nuria Carreras
- Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
- Neonatal Department, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
| | - Christian Mata
- Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain
- Research Centre for Biomedical Engineering (CREB), Barcelona East School of Engineering, Universitat Politècnica de Catalunya, 08028 Barcelona, Spain
- Pediatric Computational Imaging Research Group, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
- Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain
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12
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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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13
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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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14
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Vanes LD, Murray RM, Nosarti C. Adult outcome of preterm birth: Implications for neurodevelopmental theories of psychosis. Schizophr Res 2022; 247:41-54. [PMID: 34006427 DOI: 10.1016/j.schres.2021.04.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 12/22/2022]
Abstract
Preterm birth is associated with an elevated risk of developmental and adult psychiatric disorders, including psychosis. In this review, we evaluate the implications of neurodevelopmental, cognitive, motor, and social sequelae of preterm birth for developing psychosis, with an emphasis on outcomes observed in adulthood. Abnormal brain development precipitated by early exposure to the extra-uterine environment, and exacerbated by neuroinflammation, neonatal brain injury, and genetic vulnerability, can result in alterations of brain structure and function persisting into adulthood. These alterations, including abnormal regional brain volumes and white matter macro- and micro-structure, can critically impair functional (e.g. frontoparietal and thalamocortical) network connectivity in a manner characteristic of psychotic illness. The resulting executive, social, and motor dysfunctions may constitute the basis for behavioural vulnerability ultimately giving rise to psychotic symptomatology. There are many pathways to psychosis, but elucidating more precisely the mechanisms whereby preterm birth increases risk may shed light on that route consequent upon early neurodevelopmental insult.
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Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
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15
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Troiani V, Snyder W, Kozick S, Patti MA, Beiler D. Variability and concordance of sulcal patterns in the orbitofrontal cortex: A twin study. Psychiatry Res Neuroimaging 2022; 324:111492. [PMID: 35597228 DOI: 10.1016/j.pscychresns.2022.111492] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 03/15/2022] [Accepted: 05/13/2022] [Indexed: 10/18/2022]
Abstract
Sulcogyral patterns have been identified in the orbitofrontal cortex (OFC) based on the continuity of the medial and lateral orbital sulci. Pattern types are named according to their frequency in the population, with Type I present in ∼60%, Type II in ∼25%, Type III in ∼10%, and Type IV in ∼5%. Previous work has demonstrated that psychiatric conditions with high estimated heritability (e.g. schizophrenia, bipolar disorder) are associated with reduced frequency of Type I patterns, but the general heritability of the OFC sulcogyral patterns is unknown. We examined concordance of OFC patterns in 304 monozygotic (MZ) twins relative to 172 dizygotic (DZ) twins using structural magnetic resonance imaging data. We find that the frequency of pattern types within MZ and DZ twins are similar and bilateral concordance rates across all pattern types in DZ twins were 14% and 21% for MZ twins. Results from follow-up analyses confirm that continuity in the rostral-caudal direction is an important source of variability within the OFC, and subtype analyses indicate that variability is present in other sulci that are not represented by overall OFC pattern type. Overall, these results suggest that OFC sulcogyral patterns may reflect important variance that is not genetic in origin.
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Affiliation(s)
- Vanessa Troiani
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States.
| | - Will Snyder
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Shane Kozick
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Marisa A Patti
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Donielle Beiler
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
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16
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Associations of gestational age with gyrification and neurocognition in healthy adults. Eur Arch Psychiatry Clin Neurosci 2022; 273:467-479. [PMID: 35904633 PMCID: PMC10070217 DOI: 10.1007/s00406-022-01454-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022]
Abstract
Epidemiological studies have shown that gestational age and birth weight are linked to cognitive performance in adults. On a neurobiological level, this effect is hypothesized to be related to cortical gyrification, which is determined primarily during fetal development. The relationships between gestational age, gyrification and specific cognitive abilities in adults are still poorly understood. In 542 healthy participants, gyrification indices were calculated from structural magnetic resonance imaging T1 data at 3 T using CAT12. After applying a battery of neuropsychological tests, neuropsychological factors were extracted with a factor analysis. We conducted regressions to test associations between gyrification and gestational age as well as birth weight. Moderation analyses explored the relationships between gestational age, gyrification and neuropsychological factors. Gestational age is significantly positively associated with cortical folding in the left supramarginal, bilaterally in the superior frontal and the lingual cortex. We extracted two neuropsychological factors that describe language abilities and working memory/attention. The association between gyrification in the left superior frontal gyrus and working memory/attention was moderated by gestational age. Further, the association between gyrification in the left supramarginal cortex and both, working memory/attention as well as language, were moderated by gestational age. Gyrification is associated with gestational age and related to specific neuropsychological outcomes in healthy adulthood. Implications from these findings for the cortical neurodevelopment of cognitive domains and mental health are discussed.
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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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Vo Van P, Alison M, Morel B, Beck J, Bednarek N, Hertz-Pannier L, Loron G. Advanced Brain Imaging in Preterm Infants: A Narrative Review of Microstructural and Connectomic Disruption. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9030356. [PMID: 35327728 PMCID: PMC8947160 DOI: 10.3390/children9030356] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 02/21/2022] [Accepted: 03/02/2022] [Indexed: 11/16/2022]
Abstract
Preterm birth disrupts the in utero environment, preventing the brain from fully developing, thereby causing later cognitive and behavioral disorders. Such cerebral alteration occurs beneath an anatomical scale, and is therefore undetectable by conventional imagery. Prematurity impairs the microstructure and thus the histological process responsible for the maturation, including the myelination. Cerebral MRI diffusion tensor imaging sequences, based on water’s motion into the brain, allows a representation of this maturation process. Similarly, the brain’s connections become disorganized. The connectome gathers structural and anatomical white matter fibers, as well as functional networks referring to remote brain regions connected one over another. Structural and functional connectivity is illustrated by tractography and functional MRI, respectively. Their organizations consist of core nodes connected by edges. This basic distribution is already established in the fetal brain. It evolves greatly over time but is compromised by prematurity. Finally, cerebral plasticity is nurtured by a lifetime experience at microstructural and macrostructural scales. A preterm birth causes a negative and early disruption, though it can be partly mitigated by positive stimuli based on developmental neonatal care.
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Affiliation(s)
- Philippe Vo Van
- Department of Neonatology, Hospices Civils de Lyon, Femme Mère Enfant Hospital, 59 Boulevard Pinel, 69500 Bron, France
- Correspondence:
| | - Marianne Alison
- Service d’Imagerie Pédiatrique, Hôpital Robert Debré, APHP, 75019 Paris, France;
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
| | - Baptiste Morel
- Pediatric Radiology Department, Clocheville Hospital, CHRU of Tours, 37000 Tours, France;
- UMR 1253, iB-Rain, Université de Tours, Inserm, 37000 Tours, France
| | - Jonathan Beck
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Nathalie Bednarek
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Lucie Hertz-Pannier
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
- NeuroSpin, CEA-Saclay, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Gauthier Loron
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
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19
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de Vareilles H, Rivière D, Sun Z, Fischer C, Leroy F, Neumane S, Stopar N, Eijsermans R, Ballu M, Tataranno ML, Benders M, Mangin JF, Dubois J. Shape variability of the central sulcus in the developing brain: a longitudinal descriptive and predictive study in preterm infants. Neuroimage 2021; 251:118837. [PMID: 34965455 DOI: 10.1016/j.neuroimage.2021.118837] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 11/17/2021] [Accepted: 12/18/2021] [Indexed: 02/04/2023] Open
Abstract
Despite growing evidence of links between sulcation and function in the adult brain, the folding dynamics, occurring mostly before normal-term-birth, is vastly unknown. Looking into the development of cortical sulci in infants can give us keys to address fundamental questions: what is the sulcal shape variability in the developing brain? When are the shape features encoded? How are these morphological parameters related to further functional development? In this study, we aimed to investigate the shape variability of the developing central sulcus, which is the frontier between the primary somatosensory and motor cortices. We studied a cohort of 71 extremely preterm infants scanned twice using MRI - once around 30 weeks post-menstrual age (w PMA) and once at term-equivalent age, around 40w PMA -, in order to quantify the sulcus's shape variability using manifold learning, regardless of age-group or hemisphere. We then used these shape descriptors to evaluate the sulcus's variability at both ages and to assess hemispheric and age-group specificities. This led us to propose a description of ten shape features capturing the variability in the central sulcus of preterm infants. Our results suggested that most of these features (8/10) are encoded as early as 30w PMA. We unprecedentedly observed hemispheric asymmetries at both ages, and the one captured at term-equivalent age seems to correspond with the asymmetry pattern previously reported in adults. We further trained classifiers in order to explore the predictive value of these shape features on manual performance at 5 years of age (handedness and fine motor outcome). The central sulcus's shape alone showed a limited but relevant predictive capacity in both cases. The study of sulcal shape features during early neurodevelopment may participate to a better comprehension of the complex links between morphological and functional organization of the developing brain.
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Affiliation(s)
- H de Vareilles
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France.
| | - D Rivière
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - Z Sun
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - C Fischer
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - F Leroy
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France; Université Paris-Saclay, NeuroSpin-UNICOG, Inserm, CEA, Gif-sur-Yvette, France
| | - S Neumane
- Université de Paris, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
| | - N Stopar
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - R Eijsermans
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - M Ballu
- Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, United Kingdom
| | - M L Tataranno
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - Mjnl Benders
- Utrecht University, University Medical Center Utrecht, Department of Neonatology, Utrecht, the Netherlands
| | - J F Mangin
- Université Paris-Saclay, NeuroSpin-BAOBAB, CEA, Gif-sur-Yvette, France
| | - J Dubois
- Université de Paris, NeuroDiderot, Inserm, Paris, France; Université Paris-Saclay, NeuroSpin-UNIACT, CEA, Gif-sur-Yvette, France
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20
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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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21
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Abramian D, Larsson M, Eklund A, Aganj I, Westin CF, Behjat H. Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters. Neuroimage 2021; 237:118095. [PMID: 34000402 PMCID: PMC8356807 DOI: 10.1016/j.neuroimage.2021.118095] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 03/07/2021] [Accepted: 04/13/2021] [Indexed: 12/15/2022] Open
Abstract
Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject's unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project's 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.
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Affiliation(s)
- David Abramian
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
| | - Martin Larsson
- Centre of Mathematical Sciences, Lund University, Lund, Sweden
| | - Anders Eklund
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden; Department of Computer and Information Science, Linköping University, Linköping, Sweden
| | - Iman Aganj
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, USA
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Hamid Behjat
- Department of Biomedical Engineering, Lund University, Lund, Sweden; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
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22
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Sui Y, Afacan O, Gholipour A, Warfield SK. Fast and High-Resolution Neonatal Brain MRI Through Super-Resolution Reconstruction From Acquisitions With Variable Slice Selection Direction. Front Neurosci 2021; 15:636268. [PMID: 34220414 PMCID: PMC8242183 DOI: 10.3389/fnins.2021.636268] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 05/19/2021] [Indexed: 12/18/2022] Open
Abstract
The brain of neonates is small in comparison to adults. Imaging at typical resolutions such as one cubic mm incurs more partial voluming artifacts in a neonate than in an adult. The interpretation and analysis of MRI of the neonatal brain benefit from a reduction in partial volume averaging that can be achieved with high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is slow, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio. The purpose of this study is thus that using super-resolution reconstruction in conjunction with fast imaging protocols to construct neonatal brain MRI images at a suitable signal-to-noise ratio and with higher spatial resolution than can be practically obtained by direct Fourier encoding. We achieved high quality brain MRI at a spatial resolution of isotropic 0.4 mm with 6 min of imaging time, using super-resolution reconstruction from three short duration scans with variable directions of slice selection. Motion compensation was achieved by aligning the three short duration scans together. We applied this technique to 20 newborns and assessed the quality of the images we reconstructed. Experiments show that our approach to super-resolution reconstruction achieved considerable improvement in spatial resolution and signal-to-noise ratio, while, in parallel, substantially reduced scan times, as compared to direct high-resolution acquisitions. The experimental results demonstrate that our approach allowed for fast and high-quality neonatal brain MRI for both scientific research and clinical studies.
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Affiliation(s)
- Yao Sui
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Simon K. Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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23
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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24
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Eyre M, Fitzgibbon SP, Ciarrusta J, Cordero-Grande L, Price AN, Poppe T, Schuh A, Hughes E, O'Keeffe C, Brandon J, Cromb D, Vecchiato K, Andersson J, Duff EP, Counsell SJ, Smith SM, Rueckert D, Hajnal JV, Arichi T, O'Muircheartaigh J, Batalle D, Edwards AD. The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity. Brain 2021; 144:2199-2213. [PMID: 33734321 PMCID: PMC8370420 DOI: 10.1093/brain/awab118] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 12/11/2020] [Accepted: 12/16/2020] [Indexed: 12/23/2022] Open
Abstract
The Developing Human Connectome Project is an Open Science project that provides the
first large sample of neonatal functional MRI data with high temporal and spatial
resolution. These data enable mapping of intrinsic functional connectivity between
spatially distributed brain regions under normal and adverse perinatal circumstances,
offering a framework to study the ontogeny of large-scale brain organization in humans.
Here, we characterize in unprecedented detail the maturation and integrity of resting
state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm).
First, we applied group independent component analysis to define 11 RSNs in term-born
infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was
observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among
six higher-order, association RSNs, analogues of the adult networks for language and
ocular control were identified, but a complete default mode network precursor was not.
Next, we regressed the subject-level datasets from an independent cohort of infants
scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age,
sex and preterm birth. Brain mapping in term-born infants revealed areas of positive
association with age across four of six association RSNs, indicating active maturation in
functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased
connectivity in inferotemporal regions of the visual association network. Preterm birth
was associated with striking impairments of functional connectivity across all RSNs in a
dose-dependent manner; conversely, connectivity of the superior parietal lobules within
the lateral motor network was abnormally increased in preterm infants, suggesting a
possible mechanism for specific difficulties such as developmental coordination disorder,
which occur frequently in preterm children. Overall, we found a robust, modular,
symmetrical functional brain organization at normal term age. A complete set of
adult-equivalent primary RSNs is already instated, alongside emerging connectivity in
immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence
of brain development. The early developmental disruption imposed by preterm birth is
associated with extensive alterations in functional connectivity.
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Affiliation(s)
- Michael Eyre
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, UK
| | - Judit Ciarrusta
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.,Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Tanya Poppe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Andreas Schuh
- Biomedical Image Analysis Group, Imperial College London, London SW7 2AZ, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Camilla O'Keeffe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Jakki Brandon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.,Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Jesper Andersson
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, UK
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, UK.,Department of Paediatrics, University of Oxford, Oxford OX3 9DU, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Imperial College London, London SW7 2AZ, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.,Department of Bioengineering, Imperial College London, London SW7 2AZ, UK
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.,Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.,Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK
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DIKA-Nets: Domain-invariant knowledge-guided attention networks for brain skull stripping of early developing macaques. Neuroimage 2020; 227:117649. [PMID: 33338616 DOI: 10.1016/j.neuroimage.2020.117649] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 12/02/2020] [Accepted: 12/03/2020] [Indexed: 01/18/2023] Open
Abstract
As non-human primates, macaques have a close phylogenetic relationship to human beings and have been proven to be a valuable and widely used animal model in human neuroscience research. Accurate skull stripping (aka. brain extraction) of brain magnetic resonance imaging (MRI) is a crucial prerequisite in neuroimaging analysis of macaques. Most of the current skull stripping methods can achieve satisfactory results for human brains, but when applied to macaque brains, especially during early brain development, the results are often unsatisfactory. In fact, the early dynamic, regionally-heterogeneous development of macaque brains, accompanied by poor and age-related contrast between different anatomical structures, poses significant challenges for accurate skull stripping. To overcome these challenges, we propose a fully-automated framework to effectively fuse the age-specific intensity information and domain-invariant prior knowledge as important guiding information for robust skull stripping of developing macaques from 0 to 36 months of age. Specifically, we generate Signed Distance Map (SDM) and Center of Gravity Distance Map (CGDM) based on the intermediate segmentation results as guidance. Instead of using local convolution, we fuse all information using the Dual Self-Attention Module (DSAM), which can capture global spatial and channel-dependent information of feature maps. To extensively evaluate the performance, we adopt two relatively-large challenging MRI datasets from rhesus macaques and cynomolgus macaques, respectively, with a total of 361 scans from two different scanners with different imaging protocols. We perform cross-validation by using one dataset for training and the other one for testing. Our method outperforms five popular brain extraction tools and three deep-learning-based methods on cross-source MRI datasets without any transfer learning.
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26
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Wallois F, Routier L, Heberlé C, Mahmoudzadeh M, Bourel-Ponchel E, Moghimi S. Back to basics: the neuronal substrates and mechanisms that underlie the electroencephalogram in premature neonates. Neurophysiol Clin 2020; 51:5-33. [PMID: 33162287 DOI: 10.1016/j.neucli.2020.10.006] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 10/05/2020] [Accepted: 10/05/2020] [Indexed: 02/06/2023] Open
Abstract
Electroencephalography is the only clinically available technique that can address the premature neonate normal and pathological functional development week after week. The changes in the electroencephalogram (EEG) result from gradual structural and functional modifications that arise during the last trimester of pregnancy. Here, we review the structural changes over time that underlie the establishment of functional immature neural networks, the impact of certain anatomical specificities (fontanelles, connectivity, etc.) on the EEG, limitations in EEG interpretation, and the utility of high-resolution EEG (HR-EEG) in premature newborns (a promising technique with a high degree of spatiotemporal resolution). In particular, we classify EEG features according to whether they are manifestations of endogenous generators (i.e. theta activities that coalesce with a slow wave or delta brushes) or come from a broader network. Furthermore, we review publications on EEG in premature animals because the data provide a better understanding of what is happening in premature newborns. We then discuss the results and limitations of functional connectivity analyses in premature newborns. Lastly, we report on the magnetoelectroencephalographic studies of brain activity in the fetus. A better understanding of complex interactions at various structural and functional levels during normal neurodevelopment (as assessed using electroencephalography as a benchmark method) might lead to better clinical care and monitoring for premature neonates.
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Affiliation(s)
- Fabrice Wallois
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France.
| | - Laura Routier
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France
| | - Claire Heberlé
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France
| | - Mahdi Mahmoudzadeh
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France
| | - Emilie Bourel-Ponchel
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France
| | - Sahar Moghimi
- INSERM U1105, Research Group on Multimodal Analysis of Brain Function, Jules Verne University of Picardie, Amiens, France; Service d'Explorations Fonctionnelles du Système Nerveux Pédiatrique, Amiens-Picardie Medical Center, Amiens, France
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27
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Kruggel F, Solodkin A. Heritability of Structural Patterning in the Human Cerebral Cortex. Neuroimage 2020; 221:117169. [PMID: 32693166 DOI: 10.1016/j.neuroimage.2020.117169] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/29/2020] [Accepted: 07/11/2020] [Indexed: 01/11/2023] Open
Abstract
Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.
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Affiliation(s)
- Frithjof Kruggel
- Department of Biomedical Engineering, University of California, Irvine, USA.
| | - Ana Solodkin
- School of Behavioral and Brain Sciences, University of Texas, Dallas, USA
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28
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Mallela AN, Deng H, Bush A, Goldschmidt E. Different Principles Govern Different Scales of Brain Folding. Cereb Cortex 2020; 30:4938-4948. [PMID: 32347310 DOI: 10.1093/cercor/bhaa086] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Revised: 03/17/2020] [Accepted: 03/17/2020] [Indexed: 12/15/2022] Open
Abstract
The signature folds of the human brain are formed through a complex and developmentally regulated process. In vitro and in silico models of this process demonstrate a random pattern of sulci and gyri, unlike the highly ordered and conserved structure seen in the human cortex. Here, we account for the large-scale pattern of cortical folding by combining advanced fetal magnetic resonance imaging with nonlinear diffeomorphic registration and volumetric analysis. Our analysis demonstrates that in utero brain growth follows a logistic curve, in the absence of an external volume constraint. The Sylvian fissure forms from interlobar folding, where separate lobes overgrow and close an existing subarachnoid space. In contrast, other large sulci, which are the ones represented in existing models, fold through an invagination of a flat surface, a mechanistically different process. Cortical folding is driven by multiple spatially and temporally different mechanisms; therefore regionally distinct biological process may be responsible for the global geometry of the adult brain.
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Affiliation(s)
- Arka N Mallela
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Hansen Deng
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Alan Bush
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ezequiel Goldschmidt
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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29
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Legouhy A, Commowick O, Proisy M, Rousseau F, Barillot C. Regional brain development analysis through registration using anisotropic similarity, a constrained affine transformation. PLoS One 2020; 15:e0214174. [PMID: 32092061 PMCID: PMC7039415 DOI: 10.1371/journal.pone.0214174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 12/06/2019] [Indexed: 12/03/2022] Open
Abstract
We propose a novel method to quantify brain growth in 3 arbitrary orthogonal directions of the brain or its sub-regions through linear registration. This is achieved by introducing a 9 degrees of freedom (dof) transformation called anisotropic similarity which is an affine transformation with constrained scaling directions along arbitrarily chosen orthogonal vectors. This gives the opportunity to extract scaling factors describing brain growth along those directions by registering a database of subjects onto a common reference. This information about directional growth brings insights that are not usually available in longitudinal volumetric analysis. The interest of this method is illustrated by studying the anisotropic regional and global brain development of 308 healthy subjects betwen 0 and 19 years old. A gender comparison of those scaling factors is also performed for four age-intervals. We demonstrate through these applications the stability of the method to the chosen reference and its ability to highlight growth differences accros regions and gender.
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Affiliation(s)
- Antoine Legouhy
- CNRS, INRIA, INSERM, IRISA UMR 6074, Empenn ERL U-1228, Univ Rennes, Rennes, France
- * E-mail:
| | - Olivier Commowick
- CNRS, INRIA, INSERM, IRISA UMR 6074, Empenn ERL U-1228, Univ Rennes, Rennes, France
| | - Maïa Proisy
- CNRS, INRIA, INSERM, IRISA UMR 6074, Empenn ERL U-1228, Univ Rennes, Rennes, France
- Radiology Department, CHU Rennes, Rennes, France
| | | | - Christian Barillot
- CNRS, INRIA, INSERM, IRISA UMR 6074, Empenn ERL U-1228, Univ Rennes, Rennes, France
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30
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Adibpour P, Lebenberg J, Kabdebon C, Dehaene-Lambertz G, Dubois J. Anatomo-functional correlates of auditory development in infancy. Dev Cogn Neurosci 2020; 42:100752. [PMID: 32072930 PMCID: PMC6992933 DOI: 10.1016/j.dcn.2019.100752] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 10/23/2019] [Accepted: 12/20/2019] [Indexed: 10/29/2022] Open
Abstract
Infant brain development incorporates several intermingled mechanisms leading to intense and asynchronous maturation across cerebral networks and functional modalities. Combining electroencephalography (EEG) and diffusion magnetic resonance imaging (MRI), previous studies in the visual modality showed that the functional maturation of the event-related potentials (ERP) during the first postnatal semester relates to structural changes in the corresponding white matter pathways. Here investigated similar issues in the auditory modality. We measured ERPs to syllables in 1- to 6-month-old infants and related them to the maturational properties of underlying neural substrates measured with diffusion tensor imaging (DTI). We first observed a decrease in the latency of the auditory P2, and in the diffusivities in the auditory tracts and perisylvian regions with age. Secondly, we highlighted some of the early functional and structural substrates of lateralization. Contralateral responses to monoaural syllables were stronger and faster than ipsilateral responses, particularly in the left hemisphere. Besides, the acoustic radiations, arcuate fasciculus, middle temporal and angular gyri showed DTI asymmetries with a more complex and advanced microstructure in the left hemisphere, whereas the reverse was observed for the inferior frontal and superior temporal gyri. Finally, after accounting for the age-related variance, we correlated the inter-individual variability in P2 responses and in the microstructural properties of callosal fibers and inferior frontal regions. This study combining dedicated EEG and MRI approaches in infants highlights the complex relation between the functional responses to auditory stimuli and the maturational properties of the corresponding neural network.
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Affiliation(s)
- Parvaneh Adibpour
- Cognitive Neuroimaging Unit U992, NeuroSpin Center, Gif/Yvette, France.
| | - Jessica Lebenberg
- Cognitive Neuroimaging Unit U992, NeuroSpin Center, Gif/Yvette, France; UNATI, CEA DRF Institut Joliot, Gif/Yvette, France
| | - Claire Kabdebon
- Cognitive Neuroimaging Unit U992, NeuroSpin Center, Gif/Yvette, France
| | | | - Jessica Dubois
- Cognitive Neuroimaging Unit U992, NeuroSpin Center, Gif/Yvette, France; Université de Paris, NeuroDiderot, Inserm, F-75019 Paris, France
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31
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32
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Cortical neurodevelopment in pre-manifest Huntington's disease. NEUROIMAGE-CLINICAL 2019; 23:101913. [PMID: 31491822 PMCID: PMC6627026 DOI: 10.1016/j.nicl.2019.101913] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 06/26/2019] [Accepted: 06/27/2019] [Indexed: 11/20/2022]
Abstract
Background The expression of the HTT CAG repeat expansion mutation causes neurodegeneration in Huntington's disease (HD). Objectives: In light of the – mainly in-vitro – evidence suggesting an additional role of huntingtin in neurodevelopment we used 3T MRI to test the hypothesis that in CAG-expanded individuals without clinical signs of HD (preHD) there is evidence for neurodevelopmental abnormalities. Methods We specifically investigated the complexity of cortical folding, a measure of cortical neurodevelopment, employing a novel method to quantify local fractal dimension (FD) measures that uses spherical harmonic reconstructions. Results The complexity of cortical folding differed at a group level between preHD (n = 57) and healthy volunteers (n = 57) in areas of the motor and visual system as well as temporal cortical areas. However, there was no association between the complexity of cortical folding and the loss in putamen volume that was clearly evident in preHD. Conclusions Our results suggest that HTT CAG repeat length may have an influence on cortical folding without evidence that this leads to developmental pathology or was clinically meaningful. This suggests that the HTT CAG-repeat expansion mutation may influence the processes governing cortical neurodevelopment; however, that influence seems independent of the events that lead to neurodegeneration. Measures of cortical neurodevelopment in preclinical Huntington's disease (HD) gene carriers differ from healthy volunteers The influence on cortical folding of the HD gene was not associated with developmental pathology or clinically meaningful The influence of the HD gene on cortical neurodevelopment may differ from that on neurodegeneration
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33
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Xia J, Wang F, Benkarim OM, Sanroma G, Piella G, González Ballester MA, Hahner N, Eixarch E, Zhang C, Shen D, Li G. Fetal cortical surface atlas parcellation based on growth patterns. Hum Brain Mapp 2019; 40:3881-3899. [PMID: 31106942 DOI: 10.1002/hbm.24637] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 04/22/2019] [Accepted: 04/27/2019] [Indexed: 12/13/2022] Open
Abstract
Defining anatomically and functionally meaningful parcellation maps on cortical surface atlases is of great importance in surface-based neuroimaging analysis. The conventional cortical parcellation maps are typically defined based on anatomical cortical folding landmarks in adult surface atlases. However, they are not suitable for fetal brain studies, due to dramatic differences in brain size, shape, and properties between adults and fetuses. To address this issue, we propose a novel data-driven method for parcellation of fetal cortical surface atlases into distinct regions based on the dynamic "growth patterns" of cortical properties (e.g., surface area) from a population of fetuses. Our motivation is that the growth patterns of cortical properties indicate the underlying rapid changes of microstructures, which determine the molecular and functional principles of the cortex. Thus, growth patterns are well suitable for defining distinct cortical regions in development, structure, and function. To comprehensively capture the similarities of cortical growth patterns among vertices, we construct two complementary similarity matrices. One is directly based on the growth trajectories of vertices, and the other is based on the correlation profiles of vertices' growth trajectories in relation to a set of reference points. Then, we nonlinearly fuse these two similarity matrices into a single one, which can better capture both their common and complementary information than by simply averaging them. Finally, based on this fused similarity matrix, we perform spectral clustering to divide the fetal cortical surface atlases into distinct regions. By applying our method on 25 normal fetuses from 26 to 29 gestational weeks, we construct age-specific fetal cortical surface atlases equipped with biologically meaningful parcellation maps based on cortical growth patterns. Importantly, our generated parcellation maps reveal spatially contiguous, hierarchical and bilaterally relatively symmetric patterns of fetal cortical surface development.
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Affiliation(s)
- Jing Xia
- Department of Computer Science and Technology, Shandong University, Shandong, China.,Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hills, North Carolina
| | - Fan Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hills, North Carolina
| | | | - Gerard Sanroma
- BCN Medtech, Universitat Pompeu Fabra, Barcelona, Spain.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Gemma Piella
- BCN Medtech, Universitat Pompeu Fabra, Barcelona, Spain
| | | | - Nadine Hahner
- Fetal i+D Fetal Medicine Research Center, BCNatal, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), Institut Clínic de Ginecologia, Obstetricia i Neonatologia, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Spain
| | - Elisenda Eixarch
- Fetal i+D Fetal Medicine Research Center, BCNatal, Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Déu), Institut Clínic de Ginecologia, Obstetricia i Neonatologia, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Spain.,Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Caiming Zhang
- Digital Media Technology Key Lab of Shandong Province, Jinan, China.,Department of Software, Shandong University, Jinan, China
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hills, North Carolina.,Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hills, North Carolina
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34
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Kruggel F, Solodkin A. Determinants of structural segregation and patterning in the human cortex. Neuroimage 2019; 196:248-260. [PMID: 30995518 DOI: 10.1016/j.neuroimage.2019.04.031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 03/21/2019] [Accepted: 04/08/2019] [Indexed: 10/27/2022] Open
Abstract
This study aimed at uncovering mechanisms that govern the spatio-temporal patterning of the human cortex and its structural variability, and drawing links between fetal brain development and variability in adult brains. A data-driven analytic approach based on structural MR images revealed the following findings: (1) The cortical surface can be subdivided into 13 independent regions ("communities") based on macroscopic features. (2) Thirty centers of low inter-subject variability were found in major sulci on the cortical surface. Their variability showed a strong positive correlation with the known time points at which they appear in fetal development. Centers forming early induce a higher inter-subject regularity in a larger local vicinity, while those forming later result in smaller regions of higher variability. (3) The layout of sulcal and gyral patterns within a community is governed typically by two centers. Depending on the relative variability of each center, communities can be classified into structural sub-types. (4) Sub-types across ipsi-lateral communities are independent, but associated with the sub-type of the same community on the contra-lateral side. Results shown here integrate well with current knowledge about macroscopic, microscopic, and genetic determinants of brain development.
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Affiliation(s)
- Frithjof Kruggel
- Department of Biomedical Engineering, University of California, Irvine, USA.
| | - Ana Solodkin
- Department of Anatomy & Neurobiology, University of California, Irvine, USA
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