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Calixto C, Taymourtash A, Karimi D, Snoussi H, Velasco-Annis C, Jaimes C, Gholipour A. Advances in Fetal Brain Imaging. Magn Reson Imaging Clin N Am 2024; 32:459-478. [PMID: 38944434 PMCID: PMC11216711 DOI: 10.1016/j.mric.2024.03.004] [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] [Indexed: 07/01/2024]
Abstract
Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.
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Affiliation(s)
- Camilo Calixto
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA.
| | - Athena Taymourtash
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Spitalgasse 23, Wien 1090, Austria
| | - Davood Karimi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Haykel Snoussi
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Camilo Jaimes
- Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02215, USA
| | - Ali Gholipour
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, 401 Park Dr, 7th Floor West, Boston, MA 02215, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
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de Groot ER, Dudink J, Austin T. Sleep as a driver of pre- and postnatal brain development. Pediatr Res 2024:10.1038/s41390-024-03371-5. [PMID: 38956219 DOI: 10.1038/s41390-024-03371-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024]
Abstract
In 1966, Howard Roffwarg proposed the ontogenic sleep hypothesis, relating neural plasticity and development to rapid eye movement (REM) sleep, a hypothesis that current fetal and neonatal sleep research is still exploring. Recently, technological advances have enabled researchers to automatically quantify neonatal sleep architecture, which has caused a resurgence of research in this field as attempts are made to further elucidate the important role of sleep in pre- and postnatal brain development. This article will review our current understanding of the role of sleep as a driver of brain development and identify possible areas for future research. IMPACT: The evidence to date suggests that Roffwarg's ontogenesis hypothesis of sleep and brain development is correct. A better understanding of the relationship between sleep and the development of functional connectivity is needed. Reliable, non-invasive tools to assess sleep in the NICU and at home need to be tested in a real-world environment and the best way to promote healthy sleep needs to be understood before clinical trials promoting and optimizing sleep quality in neonates could be undertaken.
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Affiliation(s)
- Eline R de Groot
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Topun Austin
- NeoLab, Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals, Cambridge, UK.
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Zhao Z, Shuai Y, Wu Y, Xu X, Li M, Wu D. Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study. Neuroimage 2024; 297:120669. [PMID: 38852805 DOI: 10.1016/j.neuroimage.2024.120669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/01/2024] [Accepted: 06/05/2024] [Indexed: 06/11/2024] Open
Abstract
The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.
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Affiliation(s)
- Zhiyong Zhao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yifan Shuai
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yihan Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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Damera SR, De Asis-Cruz J, Cook KM, Kapse K, Spoehr E, Murnick J, Basu S, Andescavage N, Limperopoulos C. Regional homogeneity as a marker of sensory cortex dysmaturity in preterm infants. iScience 2024; 27:109662. [PMID: 38665205 PMCID: PMC11043889 DOI: 10.1016/j.isci.2024.109662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 01/23/2024] [Accepted: 04/01/2024] [Indexed: 04/28/2024] Open
Abstract
Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.
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Affiliation(s)
- Srikanth R. Damera
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kevin M. Cook
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kushal Kapse
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Jon Murnick
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Sudeepta Basu
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
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Ufkes S, Kennedy E, Poppe T, Miller SP, Thompson B, Guo J, Harding JE, Crowther CA. Prenatal Magnesium Sulfate and Functional Connectivity in Offspring at Term-Equivalent Age. JAMA Netw Open 2024; 7:e2413508. [PMID: 38805222 PMCID: PMC11134217 DOI: 10.1001/jamanetworkopen.2024.13508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/26/2024] [Indexed: 05/29/2024] Open
Abstract
Importance Understanding the effect of antenatal magnesium sulfate (MgSO4) treatment on functional connectivity will help elucidate the mechanism by which it reduces the risk of cerebral palsy and death. Objective To determine whether MgSO4 administered to women at risk of imminent preterm birth at a gestational age between 30 and 34 weeks is associated with increased functional connectivity and measures of functional segregation and integration in infants at term-equivalent age, possibly reflecting a protective mechanism of MgSO4. Design, Setting, and Participants This cohort study was nested within a randomized placebo-controlled trial performed across 24 tertiary maternity hospitals. Participants included infants born to women at risk of imminent preterm birth at a gestational age between 30 and 34 weeks who participated in the MAGENTA (Magnesium Sulphate at 30 to 34 Weeks' Gestational Age) trial and underwent magnetic resonance imaging (MRI) at term-equivalent age. Ineligibility criteria included illness precluding MRI, congenital or genetic disorders likely to affect brain structure, and living more than 1 hour from the MRI center. One hundred and fourteen of 159 eligible infants were excluded due to incomplete or motion-corrupted MRI. Recruitment occurred between October 22, 2014, and October 25, 2017. Participants were followed up to 2 years of age. Analysis was performed from February 1, 2021, to February 27, 2024. Observers were blind to patient groupings during data collection and processing. Exposures Women received 4 g of MgSO4 or isotonic sodium chloride solution given intravenously over 30 minutes. Main Outcomes and Measures Prior to data collection, it was hypothesized that infants who were exposed to MgSO4 would show enhanced functional connectivity compared with infants who were not exposed. Results A total of 45 infants were included in the analysis: 24 receiving MgSO4 treatment and 21 receiving placebo; 23 (51.1%) were female and 22 (48.9%) were male; and the median gestational age at scan was 40.0 (IQR, 39.1-41.1) weeks. Treatment with MgSO4 was associated with greater voxelwise functional connectivity in the temporal and occipital lobes and deep gray matter structures and with significantly greater clustering coefficients (Hedge g, 0.47 [95% CI, -0.13 to 1.07]), transitivity (Hedge g, 0.51 [95% CI, -0.10 to 1.11]), local efficiency (Hedge g, 0.40 [95% CI, -0.20 to 0.99]), and global efficiency (Hedge g, 0.31 [95% CI, -0.29 to 0.90]), representing enhanced functional segregation and integration. Conclusions and Relevance In this cohort study, infants exposed to MgSO4 had greater voxelwise functional connectivity and functional segregation, consistent with increased brain maturation. Enhanced functional connectivity is a possible mechanism by which MgSO4 protects against cerebral palsy and death.
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Affiliation(s)
- Steven Ufkes
- Department of Pediatrics, British Columbia Children’s Hospital, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
| | - Eleanor Kennedy
- Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Tanya Poppe
- Centre for the Developing Brain, Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Steven P. Miller
- Department of Pediatrics, British Columbia Children’s Hospital, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
| | - Benjamin Thompson
- Liggins Institute, University of Auckland, Auckland, New Zealand
- School of Optometry and Vision Science, University of Waterloo, Waterloo, Ontario, Canada
- Centre for Eye and Vision Research, Hong Kong
| | - Jessie Guo
- Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - Jane E. Harding
- Liggins Institute, University of Auckland, Auckland, New Zealand
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Wu Y, De Asis-Cruz J, Limperopoulos C. Brain structural and functional outcomes in the offspring of women experiencing psychological distress during pregnancy. Mol Psychiatry 2024:10.1038/s41380-024-02449-0. [PMID: 38418579 DOI: 10.1038/s41380-024-02449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 01/19/2024] [Accepted: 01/23/2024] [Indexed: 03/01/2024]
Abstract
In-utero exposure to maternal psychological distress is increasingly linked with disrupted fetal and neonatal brain development and long-term neurobehavioral dysfunction in children and adults. Elevated maternal psychological distress is associated with changes in fetal brain structure and function, including reduced hippocampal and cerebellar volumes, increased cerebral cortical gyrification and sulcal depth, decreased brain metabolites (e.g., choline and creatine levels), and disrupted functional connectivity. After birth, reduced cerebral and cerebellar gray matter volumes, increased cerebral cortical gyrification, altered amygdala and hippocampal volumes, and disturbed brain microstructure and functional connectivity have been reported in the offspring months or even years after exposure to maternal distress during pregnancy. Additionally, adverse child neurodevelopment outcomes such as cognitive, language, learning, memory, social-emotional problems, and neuropsychiatric dysfunction are being increasingly reported after prenatal exposure to maternal distress. The mechanisms by which prenatal maternal psychological distress influences early brain development include but are not limited to impaired placental function, disrupted fetal epigenetic regulation, altered microbiome and inflammation, dysregulated hypothalamic pituitary adrenal axis, altered distribution of the fetal cardiac output to the brain, and disrupted maternal sleep and appetite. This review will appraise the available literature on the brain structural and functional outcomes and neurodevelopmental outcomes in the offspring of pregnant women experiencing elevated psychological distress. In addition, it will also provide an overview of the mechanistic underpinnings of brain development changes in stress response and discuss current treatments for elevated maternal psychological distress, including pharmacotherapy (e.g., selective serotonin reuptake inhibitors) and non-pharmacotherapy (e.g., cognitive-behavior therapy). Finally, it will end with a consideration of future directions in the field.
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Affiliation(s)
- Yao Wu
- Developing Brain Institute, Children's National Hospital, Washington, DC, 20010, USA
| | | | - Catherine Limperopoulos
- Developing Brain Institute, Children's National Hospital, Washington, DC, 20010, USA.
- Department of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, 20010, USA.
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Cook KM, De Asis-Cruz J, Kim JH, Basu SK, Andescavage N, Murnick J, Spoehr E, Liggett M, du Plessis AJ, Limperopoulos C. Experience of early-life pain in premature infants is associated with atypical cerebellar development and later neurodevelopmental deficits. BMC Med 2023; 21:435. [PMID: 37957651 PMCID: PMC10644599 DOI: 10.1186/s12916-023-03141-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/30/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Infants born very and extremely premature (V/EPT) are at a significantly elevated risk for neurodevelopmental disorders and delays even in the absence of structural brain injuries. These risks may be due to earlier-than-typical exposure to the extrauterine environment, and its bright lights, loud noises, and exposures to painful procedures. Given the relative underdeveloped pain modulatory responses in these infants, frequent pain exposures may confer risk for later deficits. METHODS Resting-state fMRI scans were collected at term equivalent age from 148 (45% male) infants born V/EPT and 99 infants (56% male) born at term age. Functional connectivity analyses were performed between functional regions correlating connectivity to the number of painful skin break procedures in the NICU, including heel lances, venipunctures, and IV placements. Subsequently, preterm infants returned at 18 months, for neurodevelopmental follow-up and completed assessments for autism risk and general neurodevelopment. RESULTS We observed that V/EPT infants exhibit pronounced hyperconnectivity within the cerebellum and between the cerebellum and both limbic and paralimbic regions correlating with the number of skin break procedures. Moreover, skin breaks were strongly associated with autism risk, motor, and language scores at 18 months. Subsample analyses revealed that the same cerebellar connections strongly correlating with breaks at term age were associated with language dysfunction at 18 months. CONCLUSIONS These results have significant implications for the clinical care of preterm infants undergoing painful exposures during routine NICU care, which typically occurs without anesthesia. Repeated pain exposures appear to have an increasingly detrimental effect on brain development during a critical period, and effects continue to be seen even 18 months later.
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Affiliation(s)
- Kevin M Cook
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Jung-Hoon Kim
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Sudeepta K Basu
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Jonathan Murnick
- Dept. of Diagnostic Imaging & Radiology, Children's National Hospital, 111 Michigan Ave. NW, Washington, D.C, 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Melissa Liggett
- Division of Psychology, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC, 20010, USA
| | - Adré J du Plessis
- Prenatal Pediatrics Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
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Sun H, Jiang R, Dai W, Dufford AJ, Noble S, Spann MN, Gu S, Scheinost D. Network controllability of structural connectomes in the neonatal brain. Nat Commun 2023; 14:5820. [PMID: 37726267 PMCID: PMC10509217 DOI: 10.1038/s41467-023-41499-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 09/06/2023] [Indexed: 09/21/2023] Open
Abstract
White matter connectivity supports diverse cognitive demands by efficiently constraining dynamic brain activity. This efficiency can be inferred from network controllability, which represents the ease with which the brain moves between distinct mental states based on white matter connectivity. However, it remains unclear how brain networks support diverse functions at birth, a time of rapid changes in connectivity. Here, we investigate the development of network controllability during the perinatal period and the effect of preterm birth in 521 neonates. We provide evidence that elements of controllability are exhibited in the infant's brain as early as the third trimester and develop rapidly across the perinatal period. Preterm birth disrupts the development of brain networks and altered the energy required to drive state transitions at different levels. In addition, controllability at birth is associated with cognitive ability at 18 months. Our results suggest network controllability develops rapidly during the perinatal period to support cognitive demands but could be altered by environmental impacts like preterm birth.
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Affiliation(s)
- Huili Sun
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
| | - Rongtao Jiang
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Wei Dai
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, 06510, USA
| | - Alexander J Dufford
- Department of Psychiatry and Center for Mental Health Innovation, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Stephanie Noble
- Department of Psychology, Northeastern University, Boston, MA, 02115, USA
- Department of Bioengineering, Northeastern University, Boston, MA, 02115, USA
- Center for Cognitive and Brain Health, Northeastern University, Boston, USA
| | - Marisa N Spann
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
- New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Shi Gu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
- Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China
| | - Dustin Scheinost
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA.
- Wu Tsai Institute, Yale University, 100 College Street, New Haven, CT, 06510, USA.
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Cook KM, De Asis-Cruz J, Basu SK, Andescavage N, Murnick J, Spoehr E, du Plessis AJ, Limperopoulos C. Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm. Front Neurosci 2023; 17:1214080. [PMID: 37719160 PMCID: PMC10502339 DOI: 10.3389/fnins.2023.1214080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 08/22/2023] [Indexed: 09/19/2023] Open
Abstract
Introduction The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike in-utero fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored. Methods From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex. Results A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r2Adj range 0.143-0.401, p < 0048), with C and LE exhibited trending increases with age. Discussion This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to in utero fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.
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Affiliation(s)
- Kevin M. Cook
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | | | - Sudeepta K. Basu
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Jonathan Murnick
- Department of Diagnostic Imaging & Radiology, Children’s National Health System, Children’s National Hospital, Washington, DC, United States
| | - Emma Spoehr
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Adré J. du Plessis
- Prenatal Pediatrics Institute, Children’s National Hospital, Washington, DC, United States
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Arimitsu T, Fukutomi R, Kumagai M, Shibuma H, Yamanishi Y, Takahashi KI, Gima H, Seto Y, Adachi H, Arai H, Higuchi M, Ohgi S, Ohta H. Designing artificial circadian environments with multisensory cares for supporting preterm infants' growth in NICUs. Front Neurosci 2023; 17:1152959. [PMID: 37694118 PMCID: PMC10491019 DOI: 10.3389/fnins.2023.1152959] [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: 01/28/2023] [Accepted: 07/26/2023] [Indexed: 09/12/2023] Open
Abstract
Previous studies suggest the importance of stable circadian environments for fetuses to achieve sound physiology and intrauterine development. This idea is also supported by epidemiological and animal studies, in which pregnant females exposed to repeated shifting of light-dark cycles had increased rates of reproductive abnormalities and adverse pregnancy outcomes. In response to such findings, artificial circadian environments with light-dark (LD) cycles have been introduced to NICUs to promote better physical development of preterm infants. Such LD cycles, however, may not be fully effective for preterm infants who are less than 30 weeks gestational age (WGA) since they are too premature to be adequately responsive to light. Instead, circadian rhythmicity of incubated preterm infants less than 30 WGA may be able to be developed through stimulation of the non-visual senses such as touch and sound.
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Affiliation(s)
- Takeshi Arimitsu
- Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan
- The Japan Developmental Care Study Group, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
| | - Rika Fukutomi
- Section of Pediatric Nursing, Graduate School of Nursing Science, St. Luke's International University, Tokyo, Japan
| | - Mayuko Kumagai
- Department of Nursing, Akita University Graduate School of Medicine, Akita, Japan
| | - Hayato Shibuma
- Department of Rehabilitation, Yamagata Saisei Hospital, Yamagata, Japan
| | - Yoko Yamanishi
- Department of Occupational Therapy, Faculty of Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Kei-ichi Takahashi
- Department of Occupational Therapy, Akita University Graduate School of Medicine, Akita, Japan
| | - Hirotaka Gima
- The Japan Developmental Care Study Group, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
- Department of Physical Therapy, Faculty of Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Yoshitaka Seto
- Maternity and Perinatal Care Center, Hokkaido University Hospital, Sapporo, Japan
| | - Hiroyuki Adachi
- Department of Pediatrics, Akita University Graduate School of Medicine, Akita, Japan
| | - Hirokazu Arai
- Department of Neonatology, Akita Red Cross Hospital, Akita, Japan
| | - Masakatsu Higuchi
- The Japan Developmental Care Study Group, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
- Department of Occupational Therapy, Faculty of Health and Medical Science, Teikyo Heisei University, Tokyo, Japan
| | - Shohei Ohgi
- The Japan Developmental Care Study Group, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
- Department of Physical Therapy, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
| | - Hidenobu Ohta
- The Japan Developmental Care Study Group, School of Rehabilitation Sciences, Seirei Christopher University, Hamamatsu, Japan
- Department of Occupational Therapy, Akita University Graduate School of Medicine, Akita, Japan
- Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
- Department of Psychiatry, Asai Hospital, Chiba, Japan
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Basu SK, Pradhan S, Sharker YM, Kapse KJ, Murnick J, Chang T, Lopez CA, Andescavage N, duPlessis AJ, Limperopoulos C. Severity of prematurity and age impact early postnatal development of GABA and glutamate systems. Cereb Cortex 2023; 33:7386-7394. [PMID: 36843135 PMCID: PMC10267637 DOI: 10.1093/cercor/bhad046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 02/28/2023] Open
Abstract
Gamma-aminobutyric acid (GABA) and glutamatergic system perturbations following premature birth may explain neurodevelopmental deficits in the absence of structural brain injury. Using GABA-edited spectroscopy (MEscher-GArwood Point Resolved Spectroscopy [MEGA-PRESS] on 3 T MRI), we have described in-vivo brain GABA+ (+macromolecules) and Glx (glutamate + glutamine) concentrations in term-born infants. We report previously unavailable comparative data on in-vivo GABA+ and Glx concentrations in the cerebellum, the right basal ganglia, and the right frontal lobe of preterm-born infants without structural brain injury. Seventy-five preterm-born (gestational age 27.8 ± 2.9 weeks) and 48 term-born (39.6 ± 0.9 weeks) infants yielded reliable MEGA-PRESS spectra acquired at post-menstrual age (PMA) of 40.2 ± 2.3 and 43.0 ± 2 weeks, respectively. GABA+ (median 2.44 institutional units [i.u.]) concentrations were highest in the cerebellum and Glx higher in the cerebellum (5.73 i.u.) and basal ganglia (5.16 i.u.), with lowest concentrations in the frontal lobe. Metabolite concentrations correlated positively with advancing PMA and postnatal age at MRI (Spearman's rho 0.2-0.6). Basal ganglia Glx and NAA, and frontal GABA+ and NAA concentrations were lower in preterm compared with term infants. Moderate preterm infants had lower metabolite concentrations than term and extreme preterm infants. Our findings emphasize the impact of premature extra-uterine stimuli on GABA-glutamate system development and may serve as early biomarkers of neurodevelopmental deficits.
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Affiliation(s)
- Sudeepta K Basu
- Neonatology, Children’s National Hospital, Washington, D.C., United States
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
| | - Subechhya Pradhan
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
| | - Yushuf M Sharker
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Kushal J Kapse
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Jonathan Murnick
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
- Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Taeun Chang
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
- Division of Neurology, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Catherine A Lopez
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Nickie Andescavage
- Neonatology, Children’s National Hospital, Washington, D.C., United States
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
- Perinatal Pediatrics institute, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Adre J duPlessis
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
- Division of Neurology, Children’s National Hospital, Washington, D.C. 20010, United States
- Perinatal Pediatrics institute, Children’s National Hospital, Washington, D.C. 20010, United States
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. 20010, United States
- The George Washington University School of Medicine, Washington, D.C. 20037, United States
- Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, D.C. 20010, United States
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12
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Witteveen IF, McCoy E, Holsworth TD, Shen CZ, Chang W, Nance MG, Belkowitz AR, Dougald A, Puglia MH, Ribic A. Preterm birth accelerates the maturation of spontaneous and resting activity in the visual cortex. Front Integr Neurosci 2023; 17:1149159. [PMID: 37255843 PMCID: PMC10225509 DOI: 10.3389/fnint.2023.1149159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 04/25/2023] [Indexed: 06/01/2023] Open
Abstract
Prematurity is among the leading risks for poor neurocognitive outcomes. The brains of preterm infants show alterations in structure and electrical activity, but the underlying circuit mechanisms are unclear. To address this, we performed a cross-species study of the electrophysiological activity in the visual cortices of prematurely born infants and mice. Using electroencephalography (EEG) in a sample of healthy preterm (N = 29) and term (N = 28) infants, we found that the maturation of the aperiodic EEG component was accelerated in the preterm cohort, with a significantly flatter 1/f slope when compared to the term infants. The flatter slope was a result of decreased spectral power in the theta and alpha bands and was correlated with the degree of prematurity. To determine the circuit and cellular changes that potentially mediate the changes in 1/f slope after preterm birth, we used in vivo electrophysiology in preterm mice and found that, similar to infants, preterm birth results in a flattened 1/f slope. We analyzed neuronal activity in the visual cortex of preterm (N = 6) and term (N = 9) mice and found suppressed spontaneous firing of neurons. Using immunohistochemistry, we further found an accelerated maturation of inhibitory circuits. In both preterm mice and infants, the functional maturation of the cortex was accelerated, underscoring birth as a critical checkpoint in cortical maturation. Our study points to a potential mechanism of preterm birth-related changes in resting neural activity, highlighting the utility of a cross-species approach in studying the neural circuit mechanisms of preterm birth-related neurodevelopmental conditions.
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Affiliation(s)
- Isabelle F. Witteveen
- Department of Psychology, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
| | - Emily McCoy
- Department of Psychology, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
- Program in Fundamental Neuroscience, University of Virginia, Charlottesville, VA, United States
| | - Troy D. Holsworth
- Department of Psychology, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
| | - Catherine Z. Shen
- Department of Psychology, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
| | - Winnie Chang
- Department of Neurology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Madelyn G. Nance
- Department of Neurology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Allison R. Belkowitz
- Department of Neurology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Avery Dougald
- Department of Neurology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Meghan H. Puglia
- Program in Fundamental Neuroscience, University of Virginia, Charlottesville, VA, United States
- Department of Neurology, School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Adema Ribic
- Department of Psychology, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
- Program in Fundamental Neuroscience, University of Virginia, Charlottesville, VA, United States
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13
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Fenn-Moltu S, Fitzgibbon SP, Ciarrusta J, Eyre M, Cordero-Grande L, Chew A, Falconer S, Gale-Grant O, Harper N, Dimitrova R, Vecchiato K, Fenchel D, Javed A, Earl M, Price AN, Hughes E, Duff EP, O’Muircheartaigh J, Nosarti C, Arichi T, Rueckert D, Counsell S, Hajnal JV, Edwards AD, McAlonan G, Batalle D. Development of neonatal brain functional centrality and alterations associated with preterm birth. Cereb Cortex 2023; 33:5585-5596. [PMID: 36408638 PMCID: PMC10152096 DOI: 10.1093/cercor/bhac444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 09/21/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022] Open
Abstract
Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.
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Affiliation(s)
- Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Michael Eyre
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, 28040, Spain
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Nicholas Harper
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Katy Vecchiato
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Daphna Fenchel
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Ayesha Javed
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Megan Earl
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Paediatric Liver, GI and Nutrition Centre and MowatLabs, King’s College London, London, SE5 9RS, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
- Department of Paediatrics, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Jonathan O’Muircheartaigh
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
- Paediatric Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, SE1 7EH, United Kingdom
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Imperial College London, London, SW7 2AZ, United Kingdom
- Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, 81675, Germany
| | - Serena Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
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14
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Kim JH, De Asis-Cruz J, Cook KM, Limperopoulos C. Gestational age-related changes in the fetal functional connectome: in utero evidence for the global signal. Cereb Cortex 2023; 33:2302-2314. [PMID: 35641159 PMCID: PMC9977380 DOI: 10.1093/cercor/bhac209] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 05/06/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
The human brain begins to develop in the third gestational week and rapidly grows and matures over the course of pregnancy. Compared to fetal structural neurodevelopment, less is known about emerging functional connectivity in utero. Here, we investigated gestational age (GA)-associated in vivo changes in functional brain connectivity during the second and third trimesters in a large dataset of 110 resting-state functional magnetic resonance imaging scans from a cohort of 95 healthy fetuses. Using representational similarity analysis, a multivariate analytical technique that reveals pair-wise similarity in high-order space, we showed that intersubject similarity of fetal functional connectome patterns was strongly related to between-subject GA differences (r = 0.28, P < 0.01) and that GA sensitivity of functional connectome was lateralized, especially at the frontal area. Our analysis also revealed a subnetwork of connections that were critical for predicting age (mean absolute error = 2.72 weeks); functional connectome patterns of individual fetuses reliably predicted their GA (r = 0.51, P < 0.001). Lastly, we identified the primary principal brain network that tracked fetal brain maturity. The main network showed a global synchronization pattern resembling global signal in the adult brain.
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Affiliation(s)
- Jung-Hoon Kim
- Developing Brain Institue, Children’s National Hospital, 111 Michigan Avenue, N.W., Washington, DC, 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institue, Children’s National Hospital, 111 Michigan Avenue, N.W., Washington, DC, 20010, USA
| | - Kevin M Cook
- Developing Brain Institue, Children’s National Hospital, 111 Michigan Avenue, N.W., Washington, DC, 20010, USA
| | - Catherine Limperopoulos
- Corresponding author: Developing Brain Institute, Children’s National, 111 Michigan Ave. N.W., Washington D.C. 20010.
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15
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Li Y, Zhang Z, Mo Y, Wei Q, Jing L, Li W, Luo M, Zou L, Liu X, Meng D, Shi Y. A prediction model for short-term neurodevelopmental impairment in preterm infants with gestational age less than 32 weeks. Front Neurosci 2023; 17:1166800. [PMID: 37168928 PMCID: PMC10166208 DOI: 10.3389/fnins.2023.1166800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/03/2023] [Indexed: 05/13/2023] Open
Abstract
Introduction Early identification and intervention of neurodevelopmental impairment in preterm infants may significantly improve their outcomes. This study aimed to build a prediction model for short-term neurodevelopmental impairment in preterm infants using machine learning method. Methods Preterm infants with gestational age < 32 weeks who were hospitalized in The Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, and were followed-up to 18 months corrected age were included to build the prediction model. The training set and test set are divided according to 8:2 randomly by Microsoft Excel. We firstly established a logistic regression model to screen out the indicators that have a significant effect on predicting neurodevelopmental impairment. The normalized weights of each indicator were obtained by building a Support Vector Machine, in order to measure the importance of each predictor, then the dimension of the indicators was further reduced by principal component analysis methods. Both discrimination and calibration were assessed with a bootstrap of 505 resamples. Results In total, 387 eligible cases were collected, 78 were randomly selected for external validation. Multivariate logistic regression demonstrated that gestational age(p = 0.0004), extrauterine growth restriction (p = 0.0367), vaginal delivery (p = 0.0009), and hyperbilirubinemia (0.0015) were more important to predict the occurrence of neurodevelopmental impairment in preterm infants. The Support Vector Machine had an area under the curve of 0.9800 on the training set. The results of the model were exported based on 10-fold cross-validation. In addition, the area under the curve on the test set is 0.70. The external validation proves the reliability of the prediction model. Conclusion A support vector machine based on perinatal factors was developed to predict the occurrence of neurodevelopmental impairment in preterm infants with gestational age < 32 weeks. The prediction model provides clinicians with an accurate and effective tool for the prevention and early intervention of neurodevelopmental impairment in this population.
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Affiliation(s)
- Yan Li
- Department of Neonatology, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
| | - Zhihui Zhang
- Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Yan Mo
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
- Guangxi Clinical Research Center for Pediatric Diseases, Nanning, China
| | - Qiufen Wei
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
- Guangxi Clinical Research Center for Pediatric Diseases, Nanning, China
| | - Lianfang Jing
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Wei Li
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Mengmeng Luo
- Department of Biological Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Linxia Zou
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
- Guangxi Clinical Research Center for Pediatric Diseases, Nanning, China
| | - Xin Liu
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Danhua Meng
- Neonatal Medical Centre, Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Yuan Shi
- Department of Neonatology, Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China
- *Correspondence: Yuan Shi,
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De Asis-Cruz J, Limperopoulos C. Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders. Biol Psychiatry 2022; 93:867-879. [PMID: 36804195 DOI: 10.1016/j.biopsych.2022.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/03/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.
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17
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Vulnerability of the Neonatal Connectome following Postnatal Stress. J Neurosci 2022; 42:8948-8959. [PMID: 36376077 PMCID: PMC9732827 DOI: 10.1523/jneurosci.0176-22.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/29/2022] [Accepted: 07/07/2022] [Indexed: 11/16/2022] Open
Abstract
Stress following preterm birth can disrupt the emerging foundation of the neonatal brain. The current study examined how structural brain development is affected by a stressful early environment and whether changes in topological architecture at term-equivalent age could explain the increased vulnerability for behavioral symptoms during early childhood. Longitudinal changes in structural brain connectivity were quantified using diffusion-weighted imaging (DWI) and tractography in preterm born infants (gestational age <28 weeks), imaged at 30 and/or 40 weeks of gestation (N = 145, 43.5% female). A global index of postnatal stress was determined based on the number of invasive procedures during hospitalization (e.g., heel lance). Higher stress levels impaired structural connectivity growth in a subnetwork of 48 connections (p = 0.003), including the amygdala, insula, hippocampus, and posterior cingulate cortex. Findings were replicated in an independent validation sample (N = 123, 39.8% female, n = 91 with follow-up). Classifying infants into vulnerable and resilient based on having more or less internalizing symptoms at two to five years of age (n = 71) revealed lower connectivity in the hippocampus and amygdala for vulnerable relative to resilient infants (p < 0.001). Our findings suggest that higher stress exposure during hospital admission is associated with slower growth of structural connectivity. The preservation of global connectivity of the amygdala and hippocampus might reflect a stress-buffering or resilience-enhancing factor against a stressful early environment and early-childhood internalizing symptoms.SIGNIFICANCE STATEMENT The preterm brain is exposed to various external stimuli following birth. The effects of early chronic stress on neonatal brain networks and the remarkable degree of resilience are not well understood. The current study aims to provide an increased understanding of the impact of postnatal stress on third-trimester brain development and describe the topological architecture of a resilient brain. We observed a sparser neonatal brain network in infants exposed to higher postnatal stress. Limbic regulatory regions, including the hippocampus and amygdala, may play a key role as crucial convergence sites of protective factors. Understanding how stress-induced alterations in early brain development might lead to brain (re)organization may provide essential insights into resilient functioning.
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18
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Jang YH, Kim H, Lee JY, Ahn JH, Chung AW, Lee HJ. Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants. Cereb Cortex 2022; 33:5507-5523. [PMID: 36408630 DOI: 10.1093/cercor/bhac438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.
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Affiliation(s)
- Yong Hun Jang
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Hyuna Kim
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Joo Young Lee
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Ja-Hye Ahn
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
| | - Ai Wern Chung
- Harvard Medical School Fetal Neonatal-Neuroimaging and Developmental Science Center, Boston Children’s Hospital, , Boston, MA 02115 , USA
- Harvard Medical School Department of Pediatrics, Boston Children’s Hospital, , Boston, MA 02115 , USA
| | - Hyun Ju Lee
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
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19
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RS-FetMRI: a MATLAB-SPM Based Tool for Pre-processing Fetal Resting-State fMRI Data. Neuroinformatics 2022; 20:1137-1154. [PMID: 35834105 DOI: 10.1007/s12021-022-09592-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/25/2022] [Indexed: 12/31/2022]
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) most recently has proved to open a measureless window on functional neurodevelopment in utero. Fetal brain activation and connectivity maps can be heavily influenced by 1) fetal-specific motion effects on the time-series and 2) the accuracy of time-series spatial normalization to a standardized gestational-week (GW) specific fetal template space.Due to the absence of a standardized and generalizable image processing protocol, the objective of the present work was to implement a validated fetal rs-fMRI preprocessing pipeline (RS-FetMRI) divided into 6 inter-dependent preprocessing modules (i.e., M1 to M6) and designed to work entirely as an extension for Statistical Parametric Mapping (SPM).RS-FetMRI pipeline output analyses on rs-fMRI time-series sampled from a cohort of fetuses acquired on both 1.5 T and 3 T MRI scanning systems showed increased efficacy of estimation of the degree of movement coupled with an efficient motion censoring procedure, resulting in increased number of motion-uncorrupted volumes and temporal continuity in fetal rs-fMRI time-series data. Moreover, a "structural-free" SPM-based spatial normalization procedure granted a high degree of spatial overlap with high reproducibility and a significant improvement in whole-brain and parcellation-specific Temporal Signal-to-Noise Ratio (TSNR) mirrored by functional connectivity analysis.To our knowledge, the RS-FetMRI pipeline is the first semi-automatic and easy-to-use standardized fetal rs-fMRI preprocessing pipeline completely integrated in MATLAB-SPM able to remove entry barriers for new research groups into the field of fetal rs-fMRI, for both research or clinical purposes, and ultimately to make future fetal brain connectivity investigations more suitable for comparison and cross-validation.
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20
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Polese D, Riccio ML, Fagioli M, Mazzetta A, Fagioli F, Parisi P, Fagioli M. The Newborn's Reaction to Light as the Determinant of the Brain's Activation at Human Birth. Front Integr Neurosci 2022; 16:933426. [PMID: 36118115 PMCID: PMC9478760 DOI: 10.3389/fnint.2022.933426] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 06/16/2022] [Indexed: 11/13/2022] Open
Abstract
Developmental neuroscience research has not yet fully unveiled the dynamics involved in human birth. The trigger of the first breath, often assumed to be the marker of human life, has not been characterized nor has the process entailing brain modification and activation at birth been clarified yet. To date, few researchers only have investigated the impact of the extrauterine environment, with its strong stimuli, on birth. This ‘hypothesis and theory' article assumes the role of a specific stimulus activating the central nervous system (CNS) at human birth. This stimulus must have specific features though, such as novelty, efficacy, ubiquity, and immediacy. We propose light as a robust candidate for the CNS activation via the retina. Available data on fetal and neonatal neurodevelopment, in particular with reference to retinal light-responsive pathways, will be examined together with the GABA functional switch, and the subplate disappearance, which, at an experimental level, differentiate the neonatal brain from the fetal brain. In this study, we assume how a very rapid activation of retinal photoreceptors at birth initiates a sudden brain shift from the prenatal pattern of functions to the neonatal setup. Our assumption implies the presence of a photoreceptor capable of capturing and transducing light/photon stimulus, transforming it into an effective signal for the activation of new brain functions at birth. Opsin photoreception or, more specifically, melanopsin-dependent photoreception, which is provided by intrinsically photosensitive retinal ganglion cells (ipRGCs), is considered as a valid candidate. Although what is assumed herein cannot be verified in humans based on knowledge available so far, proposing an important and novel function can trigger a broad range of diversified research in different domains, from neurophysiology to neurology and psychiatry.
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Affiliation(s)
- Daniela Polese
- PhD Program on Sensorineural Plasticity, Department of Neuroscience, Mental Health and Sensory Organs NESMOS, Sant'Andrea Hospital, Sapienza University of Rome, Rome, Italy
- *Correspondence: Daniela Polese
| | | | - Marcella Fagioli
- Department of Mental Health, National Health System ASL Rome 1, Rome, Italy
| | - Alessandro Mazzetta
- PhD Program on Neuroscience, Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Francesca Fagioli
- Department of Mental Health, National Health System ASL Rome 1, Rome, Italy
| | - Pasquale Parisi
- Chair of Pediatrics, Department of Neuroscience, Mental Health and Sensory Organs NESMOS, Sant'Andrea Hospital, Sapienza University of Rome, Rome, Italy
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21
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De Asis-Cruz J, Andescavage N, Limperopoulos C. Adverse Prenatal Exposures and Fetal Brain Development: Insights From Advanced Fetal Magnetic Resonance Imaging. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:480-490. [PMID: 34848383 DOI: 10.1016/j.bpsc.2021.11.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/26/2021] [Accepted: 11/09/2021] [Indexed: 10/19/2022]
Abstract
Converging evidence from clinical and preclinical studies suggests that fetal vulnerability to adverse prenatal exposures increases the risk for neuropsychiatric diseases such as autism spectrum disorder, schizophrenia, and depression. Recent advances in fetal magnetic resonance imaging have allowed us to characterize typical fetal brain growth trajectories in vivo and to interrogate structural and functional alterations associated with intrauterine exposures, such as maternal stress, environmental toxins, drugs, and obesity. Here, we review proposed mechanisms for how prenatal influences disrupt neurodevelopment, including the role played by maternal and fetal inflammatory responses. We summarize insights from magnetic resonance imaging research in fetuses, highlight recent discoveries in normative fetal development using quantitative magnetic resonance imaging techniques (i.e., three-dimensional volumetry, proton magnetic resonance spectroscopy, placental diffusion imaging, and functional imaging), and discuss how baseline trajectories are shaped by prenatal exposures.
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Affiliation(s)
- Josepheen De Asis-Cruz
- Developing Brain Institute, Department of Radiology, Children's National Hospital, Washington, DC
| | - Nickie Andescavage
- Developing Brain Institute, Department of Radiology, Children's National Hospital, Washington, DC; Department of Neonatology, Children's National Hospital, Washington, DC
| | - Catherine Limperopoulos
- Developing Brain Institute, Department of Radiology, Children's National Hospital, Washington, DC.
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22
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Sobotka D, Ebner M, Schwartz E, Nenning KH, Taymourtash A, Vercauteren T, Ourselin S, Kasprian G, Prayer D, Langs G, Licandro R. Motion correction and volumetric reconstruction for fetal functional magnetic resonance imaging data. Neuroimage 2022; 255:119213. [PMID: 35430359 DOI: 10.1016/j.neuroimage.2022.119213] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 10/18/2022] Open
Abstract
Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose a single 3D volume from a specific acquisition timepoint with least motion artefacts as reference volume, and perform interpolation for the reconstruction of the motion corrected time series. The results can suffer, if no low-motion frame is available, and if reconstruction does not exploit any assumptions about the continuity of the fMRI signal. Here, we propose a novel framework, which estimates a high-resolution reference volume by using outlier-robust motion correction, and by utilizing Huber L2 regularization for intra-stack volumetric reconstruction of the motion-corrected fetal brain fMRI. We performed an extensive parameter study to investigate the effectiveness of motion estimation and present in this work benchmark metrics to quantify the effect of motion correction and regularised volumetric reconstruction approaches on functional connectivity computations. We demonstrate the proposed framework's ability to improve functional connectivity estimates, reproducibility and signal interpretability, which is clinically highly desirable for the establishment of prognostic noninvasive imaging biomarkers. The motion correction and volumetric reconstruction framework is made available as an open-source package of NiftyMIC.
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Affiliation(s)
- Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Ebner
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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23
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Sato J, Vandewouw MM, Safar K, Ng DVY, Bando N, O’Connor DL, Unger SL, Pang E, Taylor MJ. Social-Cognitive Network Connectivity in Preterm Children and Relations With Early Nutrition and Developmental Outcomes. Front Syst Neurosci 2022; 16:812111. [PMID: 35465192 PMCID: PMC9022474 DOI: 10.3389/fnsys.2022.812111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 02/18/2022] [Indexed: 11/13/2022] Open
Abstract
Infants born very low birth weight (VLBW, < 1,500 g) are at a heightened risk for structural brain abnormalities and social-cognitive deficits, which can impair behavioural functioning. Resting-state fMRI, reflecting a baseline level of brain activity and underlying social-cognitive processes, has also been reported to be altered in children born VLBW. Yet very little is known about the functional networks underlying social cognition using magnetoencephalography (MEG) and how it relates to neonatal factors and developmental outcomes. Thus, we investigated functional connectivity at rest in VLBW children and the associations with early nutrition and IQ and behavioural problems. We collected resting-state MEG recordings and measures of IQ and social-cognitive behaviour, as well as macronutrient/energy intakes during initial hospitalisation in 5-year-old children born VLBW (n = 37) compared to full-term (FT; n = 27) controls. We examined resting-state network differences controlling for sex and age at scan. Functional connectivity was estimated using the weighted phase lag index. Associations between functional connectivity with outcome measures and postnatal nutrition were also assessed using regression analyses. We found increased resting-state functional connectivity in VLBW compared to FT children in the gamma frequency band (65–80 Hz). This hyper-connected network was primarily anchored in frontal regions known to underlie social-cognitive functions such as emotional processing. In VLBW children, increased functional connectivity was related to higher IQ scores, while reduced connectivity was related to increased behavioural problems at 5 years of age. These within-group associations were found in the slower frequency bands of theta (4–7 Hz) and alpha (8–12 Hz), frequently linked to higher-order cognitive functions. We also found significant associations between macronutrient (protein and lipid) and energy intakes during the first postnatal month with functional connectivity at preschool-age, highlighting the long-term impacts of postnatal nutrition on preterm brain development. Our findings demonstrate that at preschool-age, VLBW children show altered resting-state connectivity despite IQ and behaviour being in the average range, possibly reflecting functional reorganisation of networks to support social-cognitive and behavioural functioning. Further, our results highlight an important role of early postnatal nutrition in the development of resting-state networks, which in turn may improve neurodevelopmental outcomes in this vulnerable population.
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Affiliation(s)
- Julie Sato
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Toronto, ON, Canada
- Division of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- *Correspondence: Julie Sato,
| | - Marlee M. Vandewouw
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
- Division of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, Toronto, ON, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Kristina Safar
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
- Division of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
| | - Dawn V. Y. Ng
- Division of Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Nicole Bando
- Division of Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Deborah L. O’Connor
- Division of Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
- Department of Paediatrics, Sinai Health, Toronto, ON, Canada
| | - Sharon L. Unger
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
- Department of Paediatrics, Sinai Health, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
- Division of Neonatology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Elizabeth Pang
- Division of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- Division of Neurology, Hospital for Sick Children, Toronto, ON, Canada
| | - Margot J. Taylor
- Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychology, University of Toronto, Toronto, ON, Canada
- Division of Neurosciences and Mental Health, Hospital for Sick Children, Toronto, ON, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON, Canada
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
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24
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Pollatou A, Filippi CA, Aydin E, Vaughn K, Thompson D, Korom M, Dufford AJ, Howell B, Zöllei L, Martino AD, Graham A, Scheinost D, Spann MN. An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field. Dev Cogn Neurosci 2022; 54:101083. [PMID: 35184026 PMCID: PMC8861425 DOI: 10.1016/j.dcn.2022.101083] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/17/2021] [Accepted: 02/04/2022] [Indexed: 12/14/2022] Open
Abstract
Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.
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Affiliation(s)
- Angeliki Pollatou
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Courtney A Filippi
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA; Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
| | - Ezra Aydin
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Kelly Vaughn
- Department of Pediatrics, University of Texas Health Sciences Center, Houston, TX, USA
| | - Deanne Thompson
- Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA
| | - Alexander J Dufford
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Human Development and Family Science, Virginia Tech, Blacksburg, VA, USA
| | - Lilla Zöllei
- Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Alice Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | | | - Dustin Scheinost
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Marisa N Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.
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25
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Liao G. Artificial Intelligence-Based MRI in Diagnosis of Injury of Cranial Nerves of Premature Infant and Its Correlation with Inflammation of Placenta. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:4550079. [PMID: 35414800 PMCID: PMC8977307 DOI: 10.1155/2022/4550079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/25/2022] [Accepted: 02/28/2022] [Indexed: 12/14/2022]
Abstract
The study focused on the effects of artificial intelligence algorithms in magnetic resonance imaging (MRI) for diagnosing cranial nerve inflammation of placenta and the correlation between cranial nerve injury with placental inflammation was explored. The subjects were selected from 132 premature infants in the hospital. According to the pathological examination of placenta, 81 cases with chorioamnionitis were taken as the experimental group and 51 cases without chorioamnionitis were taken as the control group. The incidence of cranial nerve injury in different groups of premature infants was analyzed by MRI diagnosis based on the principal component analysis (PCA) artificial intelligence algorithm, so as to analyze the correlation between cranial nerve injury and placental inflammation in premature infants. It was found that when the PCA artificial intelligence algorithm was incorporated into MRI examination of cranial nerve injury of premature infant, the A (accuracy), P (precision), R (recall), and F1 values under the PCA algorithm were 92%, 93.75%, 90%, and 92.87%, respectively. The A, P, R, and F1 of the control group were 54%, 54.1%, 52%, and 53.03%, respectively; there were statistically significant differences between the two groups, P < 0.05. As for the correlation of placental inflammation and cranial nerve injury, the positive detection rate of the experimental group was 53.09%, and the positive detection rate of the control group was 15.69%, and the difference was statistically significant, P < 0.05. In conclusion, the PCA artificial intelligence algorithm has high effectiveness and high accuracy in auxiliary diagnosis of premature brain nerve injury, and placental inflammation greatly increases the chance of premature infant suffering from brain nerve injury.
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Affiliation(s)
- Gui Liao
- Department of Pediatrics, The Third People's Hospital of Yunnan Province, Kunming 650011, Yunnan, China
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26
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Molloy MF, Saygin ZM. Individual variability in functional organization of the neonatal brain. Neuroimage 2022; 253:119101. [PMID: 35304265 DOI: 10.1016/j.neuroimage.2022.119101] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 02/28/2022] [Accepted: 03/14/2022] [Indexed: 11/25/2022] Open
Abstract
The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? And what is the individual variability in this organization in neonates? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We quantified individual variability across neonates, and found the most individual variability in the ventral attention networks. Crucially, the variability of these networks was not driven by SNR differences or differences from adult networks (Yeo et al., 2011). Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks and identified potential genes of interest for future developmental and individual variability research. Overall, we found neonatal connectomes (even at the voxel-level) can reveal broad individual-specific information processing units. The presence of individual differences in neonates and the framework for personalized parcellations demonstrated here has the potential to improve prediction of behavior and future outcomes from neonatal and infant brain data.
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Affiliation(s)
- M Fiona Molloy
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, United States
| | - Zeynep M Saygin
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, United States.
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27
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Bosch-Bayard J, Biscay RJ, Fernandez T, Otero GA, Ricardo-Garcell J, Aubert-Vazquez E, Evans AC, Harmony T. EEG effective connectivity during the first year of life mirrors brain synaptogenesis, myelination, and early right hemisphere predominance. Neuroimage 2022; 252:119035. [PMID: 35218932 DOI: 10.1016/j.neuroimage.2022.119035] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 11/25/2021] [Accepted: 02/22/2022] [Indexed: 10/19/2022] Open
Abstract
INTRODUCTION The maturation of electroencephalogram (EEG) effective connectivity in healthy infants during the first year of life is described. METHODS Participants: A cross-sectional sample of 125 healthy at-term infants, from 0 to 12 months of age, underwent EEG in a state of quiet sleep. PROCEDURES The EEG primary currents at the source were described with the sLoreta method. An unmixing algorithm was applied to reduce the leakage, and the isolated effective coherence, a direct and directed measurement of information flow, was calculated. RESULTS AND DISCUSSION Initially, the highest indices of connectivity are at the subcortical nuclei, continuing to the parietal lobe, predominantly the right hemisphere, then expanding to temporal, occipital, and finally the frontal areas, which is consistent with the myelination process. Age-related connectivity changes were mostly long-range and bilateral. Connections increased with age, mainly in the right hemisphere, while they mainly decreased in the left hemisphere. Increased connectivity from 20 to 30 Hz, mostly at the right hemisphere. These findings were consistent with right hemisphere predominance during the first three years of life. Theta and alpha connections showed the greatest changes with age. Strong connectivity was found between the parietal, temporal, and occipital regions to the frontal lobes, responsible for executive functions and consistent with behavioral development during the first year. The thalamus exchanges information bidirectionally with all cortical regions and frequency bands. CONCLUSIONS The maturation of EEG connectivity during the first year in healthy infants is very consistent with synaptogenesis, reductions in synaptogenesis, myelination, and functional and behavioral development.
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Affiliation(s)
- Jorge Bosch-Bayard
- McGill Center for Integrative Neuroscience (MCIN), Ludmer Center for Neuroinformatics and Mental Health, Montreal Neurological Institute (MNI), McGill University, Montreal H3A2B4, Canada
| | - Rolando J Biscay
- Centro de Investigación en Matemáticas, Guanajuato 36023, Mexico
| | - Thalia Fernandez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Boulevard Juriquilla 3001, Querétaro 76230, Mexico
| | - Gloria A Otero
- Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca de Lerdo 50180, Mexico
| | - Josefina Ricardo-Garcell
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Boulevard Juriquilla 3001, Querétaro 76230, Mexico
| | | | - Alan C Evans
- McGill Center for Integrative Neuroscience (MCIN), Ludmer Center for Neuroinformatics and Mental Health, Montreal Neurological Institute (MNI), McGill University, Montreal H3A2B4, Canada
| | - Thalia Harmony
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Boulevard Juriquilla 3001, Querétaro 76230, Mexico.
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28
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Schmidt Mellado G, Pillay K, Adams E, Alarcon A, Andritsou F, Cobo MM, Evans Fry R, Fitzgibbon S, Moultrie F, Baxter L, Slater R. The impact of premature extrauterine exposure on infants' stimulus-evoked brain activity across multiple sensory systems. Neuroimage Clin 2021; 33:102914. [PMID: 34915328 PMCID: PMC8683775 DOI: 10.1016/j.nicl.2021.102914] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/10/2021] [Accepted: 12/09/2021] [Indexed: 11/03/2022]
Abstract
Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions.
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Affiliation(s)
| | - Kirubin Pillay
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Eleri Adams
- Newborn Care Unit, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Ana Alarcon
- Newborn Care Unit, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Department of Neonatology, Hospital Sant Joan de Deu, Institut de Recerca Sant Joan de Deu, Universitat de Barcelona, Barcelona, Spain
| | | | - Maria M Cobo
- Department of Paediatrics, University of Oxford, Oxford, UK; Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biologicas y Ambientales, Quito, Ecuador
| | - Ria Evans Fry
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK.
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK.
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Functional Connectivity-Derived Optimal Gestational-Age Cut Points for Fetal Brain Network Maturity. Brain Sci 2021; 11:brainsci11070921. [PMID: 34356155 PMCID: PMC8304646 DOI: 10.3390/brainsci11070921] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 07/06/2021] [Accepted: 07/08/2021] [Indexed: 01/08/2023] Open
Abstract
The architecture of the human connectome changes with brain maturation. Pivotal to understanding these changes is defining developmental periods when transitions in network topology occur. Here, using 110 resting-state functional connectivity data sets from healthy fetuses between 19 and 40 gestational weeks, we estimated optimal gestational-age (GA) cut points for dichotomizing fetuses into 'young' and 'old' groups based on global network features. We computed the small-world index, normalized clustering and path length, global and local efficiency, and modularity from connectivity matrices comprised 200 regions and their corresponding pairwise connectivity. We modeled the effect of GA at scan on each metric using separate repeated-measures generalized estimating equations. Our modeling strategy involved stratifying fetuses into 'young' and 'old' based on the scan occurring before or after a selected GA (i.e., 28 to 33). We then used the quasi-likelihood independence criterion statistic to compare model fit between 'old' and 'young' cohorts and determine optimal cut points for each graph metric. Trends for all metrics, except for global efficiency, decreased with increasing gestational age. Optimal cut points fell within 30-31 weeks for all metrics coinciding with developmental events that include a shift from endogenous neuronal activity to sensory-driven cortical patterns.
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Basu SK, Pradhan S, du Plessis AJ, Ben-Ari Y, Limperopoulos C. GABA and glutamate in the preterm neonatal brain: In-vivo measurement by magnetic resonance spectroscopy. Neuroimage 2021; 238:118215. [PMID: 34058332 PMCID: PMC8404144 DOI: 10.1016/j.neuroimage.2021.118215] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/30/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022] Open
Abstract
Cognitive and behavioral disabilities in preterm infants, even without obvious brain injury on conventional neuroimaging, underscores a critical need to identify the subtle underlying microstructural and biochemical derangements. The gamma-aminobutyric acid (GABA) and glutamatergic neurotransmitter systems undergo rapid maturation during the crucial late gestation and early postnatal life, and are at-risk of disruption after preterm birth. Animal and human autopsy studies provide the bulk of current understanding since non-invasive specialized proton magnetic resonance spectroscopy (1H-MRS) to measure GABA and glutamate are not routinely available for this vulnerable population due to logistical and technical challenges. We review the specialized 1H-MRS techniques including MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS), special challenges and considerations needed for interpretation of acquired data from the developing brain of preterm infants. We summarize the limited in-vivo preterm data, highlight the gaps in knowledge, and discuss future directions for optimal integration of available in-vivo approaches to understand the influence of GABA and glutamate on neurodevelopmental outcomes after preterm birth.
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Affiliation(s)
- Sudeepta K Basu
- Neonatology, Children's National Hospital, Washington, D.C., United States; Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Subechhya Pradhan
- Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Adre J du Plessis
- Fetal Medicine institute, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Yehezkel Ben-Ari
- Division of Neurology, Children's National Hospital, Washington, D.C., United States; Neurochlore, Marseille, France
| | - Catherine Limperopoulos
- Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States.
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De Asis-Cruz J, Andersen N, Kapse K, Khrisnamurthy D, Quistorff J, Lopez C, Vezina G, Limperopoulos C. Global Network Organization of the Fetal Functional Connectome. Cereb Cortex 2021; 31:3034-3046. [PMID: 33558873 DOI: 10.1093/cercor/bhaa410] [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: 06/17/2020] [Revised: 12/11/2020] [Accepted: 12/11/2020] [Indexed: 12/21/2022] Open
Abstract
Recent advances in brain imaging have enabled non-invasive in vivo assessment of the fetal brain. Characterizing brain development in healthy fetuses provides baseline measures for identifying deviations in brain function in high-risk clinical groups. We examined 110 resting state MRI data sets from fetuses at 19 to 40 weeks' gestation. Using graph-theoretic techniques, we characterized global organizational features of the fetal functional connectome and their prenatal trajectories. Topological features related to network integration (i.e., global efficiency) and segregation (i.e., clustering) were assessed. Fetal networks exhibited small-world topology, showing high clustering and short average path length relative to reference networks. Likewise, fetal networks' quantitative small world indices met criteria for small-worldness (σ > 1, ω = [-0.5 0.5]). Along with this, fetal networks demonstrated global and local efficiency, economy, and modularity. A right-tailed degree distribution, suggesting the presence of central areas that are more highly connected to other regions, was also observed. Metrics, however, were not static during gestation; measures associated with segregation-local efficiency and modularity-decreased with advancing gestational age. Altogether, these suggest that the neural circuitry underpinning the brain's ability to segregate and integrate information exists as early as the late 2nd trimester of pregnancy and reorganizes during the prenatal period. Significance statement. Mounting evidence for the fetal origins of some neurodevelopmental disorders underscores the importance of identifying features of healthy fetal brain functional development. Alterations in prenatal brain connectomics may serve as early markers for identifying fetal-onset neurodevelopmental disorders, which in turn provide improved surveillance of at-risk fetuses and support the initiation of early interventions.
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Affiliation(s)
- Josepheen De Asis-Cruz
- Developing Brain Institute, Children's National, 111 Michigan Ave NW, Washington DC 20010
| | - Nicole Andersen
- Developing Brain Institute, Children's National, 111 Michigan Ave NW, Washington DC 20010
| | - Kushal Kapse
- Developing Brain Institute, Children's National, 111 Michigan Ave NW, Washington DC 20010
| | | | - Jessica Quistorff
- Developing Brain Institute, Children's National, 111 Michigan Ave NW, Washington DC 20010
| | - Catherine Lopez
- Developing Brain Institute, Children's National, 111 Michigan Ave NW, Washington DC 20010
| | - Gilbert Vezina
- Division of Diagnostic Imaging and Radiology, 111 Michigan Ave NW, Washington DC 20010
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