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Luppi AI, Gellersen HM, Liu ZQ, Peattie ARD, Manktelow AE, Adapa R, Owen AM, Naci L, Menon DK, Dimitriadis SI, Stamatakis EA. Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics. Nat Commun 2024; 15:4745. [PMID: 38834553 PMCID: PMC11150439 DOI: 10.1038/s41467-024-48781-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 05/10/2024] [Indexed: 06/06/2024] Open
Abstract
Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines' suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline's performance across criteria and datasets, to inform future best practices in functional connectomics.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, University of Cambridge, Cambridge, UK.
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- St John's College, University of Cambridge, Cambridge, UK.
- Montreal Neurological Institute, McGill University, Montreal, Canada.
| | - Helena M Gellersen
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Zhen-Qi Liu
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Alexander R D Peattie
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Anne E Manktelow
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Ram Adapa
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Adrian M Owen
- Department of Psychology, Western Institute for Neuroscience (WIN), Western University, London, ON, Canada
- Department of Physiology and Pharmacology, Western Institute for Neuroscience (WIN), Western University, London, ON, Canada
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Stavros I Dimitriadis
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
- Neuroinformatics Group, Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff, Wales, UK
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK
- Neuroscience and Mental Health Research Institute, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, College of Biomedical and Life Sciences, Cardiff University, Cardiff, Wales, UK
- Integrative Neuroimaging Lab, Thessaloniki, Greece
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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Arichi T. Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging. Cold Spring Harb Perspect Biol 2024; 16:a041496. [PMID: 38438187 PMCID: PMC11146311 DOI: 10.1101/cshperspect.a041496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.
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Affiliation(s)
- Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London SE1 1UL, United Kingdom
- Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London SE1 7EH, United Kingdom
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Wu M, Wang Y, Zhao X, Xin T, Wu K, Liu H, Wu S, Liu M, Chai X, Li J, Wei C, Zhu C, Liu Y, Zhang YX. Anti-phasic oscillatory development for speech and noise processing in cochlear implanted toddlers. Child Dev 2024. [PMID: 38742715 DOI: 10.1111/cdev.14105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Human brain demonstrates amazing readiness for speech and language learning at birth, but the auditory development preceding such readiness remains unknown. Cochlear implanted (CI) children (n = 67; mean age 2.77 year ± 1.31 SD; 28 females) with prelingual deafness provide a unique opportunity to study this stage. Using functional near-infrared spectroscopy, it was revealed that the brain of CI children was irresponsive to sounds at CI hearing onset. With increasing CI experiences up to 32 months, the brain demonstrated function, region and hemisphere specific development. Most strikingly, the left anterior temporal lobe showed an oscillatory trajectory, changing in opposite phases for speech and noise. The study provides the first longitudinal brain imaging evidence for early auditory development preceding speech acquisition.
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Affiliation(s)
- Meiyun Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yuyang Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Otolaryngology Head and Neck Surgery, Hunan Provincial People's Hospital (First Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Xue Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tianyu Xin
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing, China
| | - Kun Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haotian Liu
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Otolaryngology Head and Neck Surgery, West China Hospital of Sichuan University, Chengdu, China
| | - Shinan Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Min Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaoke Chai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jinhong Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chaogang Wei
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing, China
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yuhe Liu
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yu-Xuan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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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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Beeghly M. Toward a multi-level approach to the study of the intergenerational transmission of trauma: Current findings and future directions. Dev Psychopathol 2024:1-6. [PMID: 38516836 DOI: 10.1017/s0954579424000555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
A central goal in the field of developmental psychopathology is to evaluate the complex, dynamic transactions occurring among biological, psychological, and broader social-cultural contexts that predict adaptive and maladaptive outcomes across ontogeny. Here, I briefly review research on the effects of a history of childhood maltreatment on parental, child, and dyadic functioning, along with more recent studies on the intergenerational transmission of trauma. Because the experience and sequelae of child maltreatment and the intergenerational transmission of trauma are embedded in complex biopsychosocial contexts, this research is best conceptualized in a developmental psychopathology framework. Moreover, there is a pressing need for investigators in this area of study to adopt dynamic, multi-level perspectives as well as using developmentally guided, sophisticated research methods. Other directions for research in this field are suggested, including the implementation of collaborative interdisciplinary team science approaches, as well as community-based participatory research, to increase representation, inclusion, and equity of community stakeholders. A greater focus on cultural and global perspectives is also recommended.
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Affiliation(s)
- Marjorie Beeghly
- Department of Psychology, Wayne State University, Detroit, MI, USA
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Liu J, Zhang Y, Jia F, Zhang H, Luo L, Liao Y, Ouyang M, Yi X, Zhu R, Bai W, Ning G, Li X, Qu H. Sex differences in fetal brain functional network topology. Cereb Cortex 2024; 34:bhae111. [PMID: 38517172 DOI: 10.1093/cercor/bhae111] [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: 12/14/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 03/23/2024] Open
Abstract
The fetal period is a critical stage in brain development, and understanding the characteristics of the fetal brain is crucial. Although some studies have explored aspects of fetal brain functional networks, few have specifically focused on sex differences in brain network characteristics. We adopted the graph theory method to calculate brain network functional connectivity and topology properties (including global and nodal properties), and further compared the differences in these parameters between male and female fetuses. We found that male fetuses showed an increased clustering coefficient and local efficiency than female fetuses, but no significant group differences concerning other graph parameters and the functional connectivity matrix. Our study suggests the existence of sex-related distinctions in the topological properties of the brain network at the fetal stage of development and demonstrates an increase in brain network separation in male fetuses compared with female fetuses.
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Affiliation(s)
- Jing Liu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Yujin Zhang
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Fenglin Jia
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Hongding Zhang
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Lekai Luo
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Yi Liao
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Minglei Ouyang
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Xiaoxue Yi
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Ruixi Zhu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Wanjing Bai
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Gang Ning
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Xuesheng Li
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
| | - Haibo Qu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, Sichuan, P.R. China
- Ministry of Education, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Chengdu 610041, Sichuan, P.R. China
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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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Momoi MY. Overview: Research on the Genetic Architecture of the Developing Cerebral Cortex in Norms and Diseases. Methods Mol Biol 2024; 2794:1-12. [PMID: 38630215 DOI: 10.1007/978-1-0716-3810-1_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
The human brain is characterized by high cell numbers, diverse cell types with diverse functions, and intricate connectivity with an exceedingly broad surface of the cortex. Human-specific brain development was accomplished by a long timeline for maturation from the prenatal period to the third decade of life. The long timeline makes complicated architecture and circuits of human cerebral cortex possible, and it makes human brain vulnerable to intrinsic and extrinsic insults resulting in the development of variety of neuropsychiatric disorders. Unraveling the molecular and cellular processes underlying human brain development under the elaborate regulation of gene expression in a spatiotemporally specific manner, especially that of the cortex will provide a biological understanding of human cognition and behavior in health and diseases. Global research consortia and the advancing technologies in brain science including functional genomics equipped with emergent neuroinformatics such as single-cell multiomics, novel human models, and high-volume databases with high-throughput computation facilitate the biological understanding of the development of the human brain cortex. Knowing the process of interplay of the genome and the environment in cortex development will lead us to understand the human-specific cognitive function and its individual diversity. Thus, it is worthwhile to overview the recent progress in neurotechnology to foresee further understanding of the human brain and norms and diseases.
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Affiliation(s)
- Mariko Y Momoi
- Ryomo Seishi Ryogoen Rehabilitation Hospital for Children with Disabilities, Gunma, Japan
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9
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Dipasquale F, Blandini M, Gueli R, Fecarotta P, Magnano P. On the Construct of Functional Psychology's Developmental Theory: Basic Experiences of the Self (BEsS). Eur J Investig Health Psychol Educ 2023; 13:2863-2876. [PMID: 38131897 PMCID: PMC10742788 DOI: 10.3390/ejihpe13120198] [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: 10/18/2023] [Revised: 11/18/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023] Open
Abstract
According to the neo-functional developmental theory, newborns and infants exhibit complex psycho-bodily functioning. The Basic Experiences of the Self (BEsS) refer to how they fulfil their essential life needs by organising their psycho-bodily functions in a typical configuration. As part of our research study, we developed a prototype psychometric tool called the BEsS Assessment Form (BAF) to assess the BEsS in infants aged zero to three years. We collected video recordings of their spontaneous behaviour and used the BAF to evaluate function polarity. In the BAF, thirty pairs of words represent functions in their dyadic polarity. To estimate the level of function polarity, we used the Osgood semantic differential scale, which ranges from seven to one. The study's results confirm that functions can be assessed by grading along the opposite polarity spectrum. Moreover, in accordance with the theory, the functions can be grouped into four domains: the emotional, postural motor, physiological, and cognitive-symbolic planes. Our findings suggest that the characteristics of BEsS are significantly influenced by the activation of the physiological and postural motor functions, which are related to the early regulation of the autonomic nervous system and can be used to evaluate infant arousal.
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Affiliation(s)
| | - Marta Blandini
- Functional Psychotherapy Centre “Wilhelm Reich”, 95124 Catania, Italy; (M.B.); (R.G.); (P.F.)
| | - Raffaele Gueli
- Functional Psychotherapy Centre “Wilhelm Reich”, 95124 Catania, Italy; (M.B.); (R.G.); (P.F.)
| | - Paola Fecarotta
- Functional Psychotherapy Centre “Wilhelm Reich”, 95124 Catania, Italy; (M.B.); (R.G.); (P.F.)
| | - Paola Magnano
- Faculty of Human and Social Sciences, Kore University of Enna, 94100 Enna, Italy;
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10
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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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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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12
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Correa S, Nichols ES, Mueller ME, de Vrijer B, Eagleson R, McKenzie CA, de Ribaupierre S, Duerden EG. Default mode network functional connectivity strength in utero and the association with fetal subcortical development. Cereb Cortex 2023; 33:9144-9153. [PMID: 37259175 PMCID: PMC10350815 DOI: 10.1093/cercor/bhad190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/02/2023] Open
Abstract
The default mode network is essential for higher-order cognitive processes and is composed of an extensive network of functional and structural connections. Early in fetal life, the default mode network shows strong connectivity with other functional networks; however, the association with structural development is not well understood. In this study, resting-state functional magnetic resonance imaging and anatomical images were acquired in 30 pregnant women with singleton pregnancies. Participants completed 1 or 2 MR imaging sessions, on average 3 weeks apart (43 data sets), between 28- and 39-weeks postconceptional ages. Subcortical volumes were automatically segmented. Activation time courses from resting-state functional magnetic resonance imaging were extracted from the default mode network, medial temporal lobe network, and thalamocortical network. Generalized estimating equations were used to examine the association between functional connectivity strength between default mode network-medial temporal lobe, default mode network-thalamocortical network, and subcortical volumes, respectively. Increased functional connectivity strength in the default mode network-medial temporal lobe network was associated with smaller right hippocampal, left thalamic, and right caudate nucleus volumes, but larger volumes of the left caudate. Increased functional connectivity strength in the default mode network-thalamocortical network was associated with smaller left thalamic volumes. The strong associations seen among the default mode network functional connectivity networks and regionally specific subcortical volume development indicate the emergence of short-range connectivity in the third trimester.
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Affiliation(s)
- Susana Correa
- Neuroscience Program, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
| | - Emily S Nichols
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
| | - Megan E Mueller
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
| | - Barbra de Vrijer
- Obstetrics & Gynaecology, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Roy Eagleson
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Biomedical Engineering, Western University, London, ON N6A 3K7, Canada
- Electrical and Computer Engineering, Western University, London, ON N6A 3K7, Canada
| | - Charles A McKenzie
- Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Sandrine de Ribaupierre
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Biomedical Engineering, Western University, London, ON N6A 3K7, Canada
- Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Clinical Neurological Sciences, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Anatomy and Cell Biology, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Emma G Duerden
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
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13
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Na X, Glasier CM, Andres A, Bellando J, Chen H, Gao W, Livingston LW, Badger TM, Ou X. Associations between mother's depressive symptoms during pregnancy and newborn's brain functional connectivity. Cereb Cortex 2023; 33:8980-8989. [PMID: 37218652 PMCID: PMC10350841 DOI: 10.1093/cercor/bhad176] [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: 02/28/2023] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/24/2023] Open
Abstract
Depression during pregnancy is common and the prevalence further increased during the COVID pandemic. Recent findings have shown potential impact of antenatal depression on children's neurodevelopment and behavior, but the underlying mechanisms are unclear. Nor is it clear whether mild depressive symptoms among pregnant women would impact the developing brain. In this study, 40 healthy pregnant women had their depressive symptoms evaluated by the Beck Depression Inventory-II at ~12, ~24, and ~36 weeks of pregnancy, and their healthy full-term newborns underwent a brain MRI without sedation including resting-state fMRI for evaluation of functional connectivity development. The relationships between functional connectivities and maternal Beck Depression Inventory-II scores were evaluated by Spearman's rank partial correlation tests using appropriate multiple comparison correction with newborn's gender and gestational age at birth controlled. Significant negative correlations were identified between neonatal brain functional connectivity and mother's Beck Depression Inventory-II scores in the third trimester, but not in the first or second trimester. Higher depressive symptoms during the third trimester of pregnancy were associated with lower neonatal brain functional connectivity in the frontal lobe and between frontal/temporal lobe and occipital lobe, indicating a potential impact of maternal depressive symptoms on offspring brain development, even in the absence of clinical depression.
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Affiliation(s)
- Xiaoxu Na
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
| | - Charles M Glasier
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
| | - Aline Andres
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
- Arkansas Children’s Nutrition Center, Little Rock 72202, AR, United States
- Arkansas Children’s Research Institute, Little Rock 72202, AR, United States
| | - Jayne Bellando
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
| | - Haitao Chen
- Department of Biomedical Sciences and Imaging, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States
- Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States
- Department of Bioengineering, University of California at Los Angeles, Los Angeles, CA 90095, United States
| | - Wei Gao
- Department of Biomedical Sciences and Imaging, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States
- Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Luke W Livingston
- College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
| | - Thomas M Badger
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
- Arkansas Children’s Nutrition Center, Little Rock 72202, AR, United States
- Arkansas Children’s Research Institute, Little Rock 72202, AR, United States
| | - Xiawei Ou
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States
- Arkansas Children’s Nutrition Center, Little Rock 72202, AR, United States
- Arkansas Children’s Research Institute, Little Rock 72202, AR, United States
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14
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Nordvik T, Server A, Espeland CN, Schumacher EM, Larsson PG, Pripp AH, Stiris T. Combining MRI and Spectral EEG for Assessment of Neurocognitive Outcomes in Preterm Infants. Neonatology 2023; 120:482-490. [PMID: 37290419 DOI: 10.1159/000530648] [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: 02/02/2023] [Accepted: 03/31/2023] [Indexed: 06/10/2023]
Abstract
INTRODUCTION Predicting impairment in preterm children is challenging. Our aim is to explore the association between MRI at term-equivalent age (TEA) and neurocognitive outcomes in late childhood and to assess whether the addition of EEG improves prognostication. METHODS This prospective observational study included forty infants with gestational age 24 + 0-30 + 6. Children were monitored with multichannel EEG for 72 h after birth. Total absolute band power for the delta band on day 2 was calculated. Brain MRI was performed at TEA and scored according to the Kidokoro scoring system. At 10-12 years of age, we evaluated neurocognitive outcomes with Wechsler Intelligence Scale for Children 4th edition, Vineland adaptive behavior scales 2nd edition and Behavior Rating Inventory of Executive Function. We performed linear regression analysis to examine the association between outcomes and MRI and EEG, respectively, and multiple regression analysis to explore the combination of MRI and EEG. RESULTS Forty infants were included. There was a significant association between global brain abnormality score and composite outcomes of WISC and Vineland test, but not the BRIEF test. The adjusted R2 was 0.16 and 0.08, respectively. For EEG, adjusted R2 was 0.34 and 0.15, respectively. When combining MRI and EEG data, adjusted R2 changed to 0.36 for WISC and 0.16 for the Vineland test. CONCLUSION There was a small association between TEA MRI and neurocognitive outcomes in late childhood. Adding EEG to the model improved the explained variance. Combining EEG and MRI data did not have any additional benefit over EEG alone.
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Affiliation(s)
- Tone Nordvik
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Andres Server
- Section of Neuroradiology, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Cathrine N Espeland
- Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Eva M Schumacher
- Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Pål G Larsson
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
| | - Are H Pripp
- Oslo Center of Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway
| | - Tom Stiris
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
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15
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Kim JH, De Asis-Cruz J, Krishnamurthy D, Limperopoulos C. Toward a more informative representation of the fetal-neonatal brain connectome using variational autoencoder. eLife 2023; 12:e80878. [PMID: 37184067 PMCID: PMC10241511 DOI: 10.7554/elife.80878] [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: 06/07/2022] [Accepted: 05/09/2023] [Indexed: 05/16/2023] Open
Abstract
Recent advances in functional magnetic resonance imaging (fMRI) have helped elucidate previously inaccessible trajectories of early-life prenatal and neonatal brain development. To date, the interpretation of fetal-neonatal fMRI data has relied on linear analytic models, akin to adult neuroimaging data. However, unlike the adult brain, the fetal and newborn brain develops extraordinarily rapidly, far outpacing any other brain development period across the life span. Consequently, conventional linear computational models may not adequately capture these accelerated and complex neurodevelopmental trajectories during this critical period of brain development along the prenatal-neonatal continuum. To obtain a nuanced understanding of fetal-neonatal brain development, including nonlinear growth, for the first time, we developed quantitative, systems-wide representations of brain activity in a large sample (>500) of fetuses, preterm, and full-term neonates using an unsupervised deep generative model called variational autoencoder (VAE), a model previously shown to be superior to linear models in representing complex resting-state data in healthy adults. Here, we demonstrated that nonlinear brain features, that is, latent variables, derived with the VAE pretrained on rsfMRI of human adults, carried important individual neural signatures, leading to improved representation of prenatal-neonatal brain maturational patterns and more accurate and stable age prediction in the neonate cohort compared to linear models. Using the VAE decoder, we also revealed distinct functional brain networks spanning the sensory and default mode networks. Using the VAE, we are able to reliably capture and quantify complex, nonlinear fetal-neonatal functional neural connectivity. This will lay the critical foundation for detailed mapping of healthy and aberrant functional brain signatures that have their origins in fetal life.
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Affiliation(s)
- Jung-Hoon Kim
- Developing Brain Institute, Children's National HospitalWashingtonUnited States
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16
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Proshchina A, Kharlamova A, Krivova Y, Godovalova O, Otlyga D, Gulimova V, Otlyga E, Junemann O, Sonin G, Saveliev S. Neuromorphological Atlas of Human Prenatal Brain Development: White Paper. Life (Basel) 2023; 13:life13051182. [PMID: 37240827 DOI: 10.3390/life13051182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/06/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023] Open
Abstract
Recent morphological data on human brain development are quite fragmentary. However, they are highly requested for a number of medical practices, educational programs, and fundamental research in the fields of embryology, cytology and histology, neurology, physiology, path anatomy, neonatology, and others. This paper provides the initial information on the new online Human Prenatal Brain Development Atlas (HBDA). The Atlas will start with forebrain annotated hemisphere maps, based on human fetal brain serial sections at the different stages of prenatal ontogenesis. Spatiotemporal changes in the regional-specific immunophenotype profiles will also be demonstrated on virtual serial sections. The HBDA can serve as a reference database for the neurological research, which provides opportunity to compare the data obtained by noninvasive techniques, such as neurosonography, X-ray computed tomography and magnetic resonance imaging, functional magnetic resonance imaging, 3D high-resolution phase-contrast computed tomography visualization techniques, as well as spatial transcriptomics data. It could also become a database for the qualitative and quantitative analysis of individual variability in the human brain. Systemized data on the mechanisms and pathways of prenatal human glio- and neurogenesis could also contribute to the search for new therapy methods for a large spectrum of neurological pathologies, including neurodegenerative and cancer diseases. The preliminary data are now accessible on the special HBDA website.
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Affiliation(s)
- Alexandra Proshchina
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Anastasia Kharlamova
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Yuliya Krivova
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Olga Godovalova
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Dmitriy Otlyga
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Victoria Gulimova
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Ekaterina Otlyga
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Olga Junemann
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Gleb Sonin
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
| | - Sergey Saveliev
- Avtsyn Research Institute of Human Morphology of Federal State Budgetary Scientific Institution "Petrovsky National Research Centre of Surgery", Tsurupi Street, 3, 117418 Moscow, Russia
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17
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Li YT, Kuo DP, Tseng P, Chen YC, Cheng SJ, Wu CW, Hsieh LC, Chiang YH, Chung HW, Lui YW, Chen CY. Thalamocortical Coherence Predicts Persistent Postconcussive Symptoms. Prog Neurobiol 2023; 226:102464. [PMID: 37169275 DOI: 10.1016/j.pneurobio.2023.102464] [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: 12/16/2022] [Revised: 04/10/2023] [Accepted: 05/07/2023] [Indexed: 05/13/2023]
Abstract
The pathogenetic mechanism of persistent post-concussive symptoms (PCS) following concussion remains unclear. Thalamic damage is known to play a role in PCS prolongation while the evidence and biomarkers that trigger persistent PCS have never been elucidated. We collected longitudinal neuroimaging and behavior data from patients and rodents after concussion, complemented with rodents' histological staining data, to unravel the early biomarkers of persistent PCS. Diffusion tensor imaging (DTI) were acquired to investigated the thalamic damage, while quantitative thalamocortical coherence was derived through resting-state functional MRI for evaluating thalamocortical functioning and predicting long-term behavioral outcome. Patients with prolonged symptoms showed abnormal DTI-derived indices at the boundaries of bilateral thalami (peri-thalamic regions). Both patients and rats with persistent symptoms demonstrated enhanced thalamocortical coherence between different thalamocortical circuits, which disrupted thalamocortical multifunctionality. In rodents, the persistent DTI abnormalities were validated in thalamic reticular nucleus (TRN) through immunohistochemistry, and correlated with enhanced thalamocortical coherence. Strong predictive power of these coherence biomarkers for long-term PCS was also validated using another patient cohort. Postconcussive events may begin with persistent TRN injury, followed by disrupted thalamocortical coherence and prolonged PCS. Functional MRI-based coherence measures can be surrogate biomarkers for early prediction of long-term PCS.
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Affiliation(s)
- Yi-Tien Li
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Neuroscience Research Center, Taipei Medical University, Taipei 11031, Taiwan
| | - Duen-Pang Kuo
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Philip Tseng
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei 11031, Taiwan; Brain and Consciousness Research Center, Shuang-Ho Hospital, Taipei Medical University, New Taipei 23561, Taiwan; Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei 11031, Taiwan
| | - Yung-Chieh Chen
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Sho-Jen Cheng
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Changwei W Wu
- Graduate Institute of Mind, Brain, and Consciousness, Taipei Medical University, Taipei 11031, Taiwan; Brain and Consciousness Research Center, Shuang-Ho Hospital, Taipei Medical University, New Taipei 23561, Taiwan
| | - Li-Chun Hsieh
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Yung-Hsiao Chiang
- Neuroscience Research Center, Taipei Medical University, Taipei 11031, Taiwan; Center for Neurotrauma and Neuroregeneration, Taipei Medical University, Taipei 11031, Taiwan; Department of Neurosurgery, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Hsiao-Wen Chung
- Graduate Institute of Biomedical Electrics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan
| | - Yvonne W Lui
- Department of Radiology, NYU Langone Health, New York University School of Medicine, New York, NY, 10016, USA; Department of Radiology, NYU Grossman School of Medicine, New York University, New York, NY, 10016, USA
| | - Cheng-Yu Chen
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Medical Imaging, Taipei Medical University Hospital, Taipei 11031, Taiwan; Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan; Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei 11031, Taiwan.
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18
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Taymourtash A, Schwartz E, Nenning KH, Sobotka D, Licandro R, Glatter S, Diogo MC, Golland P, Grant E, Prayer D, Kasprian G, Langs G. Fetal development of functional thalamocortical and cortico-cortical connectivity. Cereb Cortex 2023; 33:5613-5624. [PMID: 36520481 PMCID: PMC10152101 DOI: 10.1093/cercor/bhac446] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 12/23/2022] Open
Abstract
Measuring and understanding functional fetal brain development in utero is critical for the study of the developmental foundations of our cognitive abilities, possible early detection of disorders, and their prevention. Thalamocortical connections are an intricate component of shaping the cortical layout, but so far, only ex-vivo studies provide evidence of how axons enter the sub-plate and cortex during this highly dynamic phase. Evidence for normal in-utero development of the functional thalamocortical connectome in humans is missing. Here, we modeled fetal functional thalamocortical connectome development using in-utero functional magnetic resonance imaging in fetuses observed from 19th to 40th weeks of gestation (GW). We observed a peak increase of thalamocortical functional connectivity strength between 29th and 31st GW, right before axons establish synapses in the cortex. The cortico-cortical connectivity increases in a similar time window, and exhibits significant functional laterality in temporal-superior, -medial, and -inferior areas. Homologous regions exhibit overall similar mirrored connectivity profiles, but this similarity decreases during gestation giving way to a more diverse cortical interconnectedness. Our results complement the understanding of structural development of the human connectome and may serve as the basis for the investigation of disease and deviations from a normal developmental trajectory of connectivity development.
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Affiliation(s)
- Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140, Old Orangeburg Road, Orangeburg, NY 10962, United States
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Laboratory for Computational Neuroimaging, A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Bldg. 149, 13th Street, Charlestown, MA 02129, United States
| | - Sarah Glatter
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Mariana Cardoso Diogo
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Radiology Department, Hospital CUF Tejo, Av. 24 de Julho 171A, 1350-352 Lisboa, Portugal
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77, Massachusetts Avenue, Cambridge, MA 02139, United States
| | - Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300, Longwood Avenue, Boston, MA 02115, United States
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77, Massachusetts Avenue, Cambridge, MA 02139, United States
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19
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Nielsen AN, Kaplan S, Meyer D, Alexopoulos D, Kenley JK, Smyser TA, Wakschlag LS, Norton ES, Raghuraman N, Warner BB, Shimony JS, Luby JL, Neil JJ, Petersen SE, Barch DM, Rogers CE, Sylvester CM, Smyser CD. Maturation of large-scale brain systems over the first month of life. Cereb Cortex 2023; 33:2788-2803. [PMID: 35750056 PMCID: PMC10016041 DOI: 10.1093/cercor/bhac242] [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: 01/20/2022] [Revised: 04/29/2022] [Accepted: 05/23/2022] [Indexed: 01/14/2023] Open
Abstract
The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.
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Affiliation(s)
- Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dominique Meyer
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Tara A Smyser
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Lauren S Wakschlag
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Feinberg School of Medicine, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Elizabeth S Norton
- Institute for Innovations and Developmental Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Medical Social Sciences, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
| | - Nandini Raghuraman
- Department of Obstetrics and Gynecology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joshua S Shimony
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Jeffery J Neil
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Cynthia E Rogers
- Department of Communication Sciences and Disorders, Northwestern University, 420 E Superior, Chicago, IL, 60611, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Pediatrics, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
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20
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Cook KM, De Asis-Cruz J, Lopez C, Quistorff J, Kapse K, Andersen N, Vezina G, Limperopoulos C. Robust sex differences in functional brain connectivity are present in utero. Cereb Cortex 2023; 33:2441-2454. [PMID: 35641152 PMCID: PMC10016060 DOI: 10.1093/cercor/bhac218] [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: 11/22/2021] [Revised: 05/09/2022] [Accepted: 05/09/2022] [Indexed: 11/14/2022] Open
Abstract
Sex-based differences in brain structure and function are observable throughout development and are thought to contribute to differences in behavior, cognition, and the presentation of neurodevelopmental disorders. Using multiple support vector machine (SVM) models as a data-driven approach to assess sex differences, we sought to identify regions exhibiting sex-dependent differences in functional connectivity and determine whether they were robust and sufficiently reliable to classify sex even prior to birth. To accomplish this, we used a sample of 110 human fetal resting state fMRI scans from 95 fetuses, performed between 19 and 40 gestational weeks. Functional brain connectivity patterns classified fetal sex with 73% accuracy. Across SVM models, we identified features (functional connections) that reliably differentiated fetal sex. Highly consistent predictors included connections in the somatomotor and frontal areas alongside the hippocampus, cerebellum, and basal ganglia. Moreover, high consistency features also implicated a greater magnitude of cross-region connections in females, while male weighted features were predominately within anatomically bounded regions. Our findings indicate that these differences, which have been observed later in childhood, are present and reliably detectable even before birth. These results show that sex differences arise before birth in a manner that is consistent and reliable enough to be highly identifiable.
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Affiliation(s)
- Kevin M Cook
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Catherine Lopez
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Jessica Quistorff
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Kushal Kapse
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Nicole Andersen
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Gilbert Vezina
- Division of Diagnostic Imaging and Radiology, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National, 111 Michigan Ave NW, Washington DC 20010, USA
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21
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Ji L, Majbri A, Hendrix CL, Thomason ME. Fetal behavior during MRI changes with age and relates to network dynamics. Hum Brain Mapp 2023; 44:1683-1694. [PMID: 36564934 PMCID: PMC9921243 DOI: 10.1002/hbm.26167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/31/2022] [Accepted: 11/23/2022] [Indexed: 12/25/2022] Open
Abstract
Fetal motor behavior is an important clinical indicator of healthy development. However, our understanding of associations between fetal behavior and fetal brain development is limited. To fill this gap, this study introduced an approach to automatically and objectively classify long durations of fetal movement from a continuous four-dimensional functional magnetic resonance imaging (fMRI) data set, and paired behavior features with brain activity indicated by the fMRI time series. Twelve-minute fMRI scans were conducted in 120 normal fetuses. Postnatal motor function was evaluated at 7 and 36 months age. Fetal motor behavior was quantified by calculating the frame-wise displacement (FD) of fetal brains extracted by a deep-learning model along the whole time series. Analyzing only low motion data, we characterized the recurring coactivation patterns (CAPs) of the supplementary motor area (SMA). Results showed reduced motor activity with advancing gestational age (GA), likely due in part to loss of space (r = -.51, p < .001). Evaluation of individual variation in motor movement revealed a negative association between movement and the occurrence of coactivations within the left parietotemporal network, controlling for age and sex (p = .003). Further, we found that the occurrence of coactivations between the SMA to posterior brain regions, including visual cortex, was prospectively associated with postnatal motor function at 7 months (r = .43, p = .03). This is the first study to pair fetal movement and fMRI, highlighting potential for comparisons of fetal behavior and neural network development to enhance our understanding of fetal brain organization.
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Affiliation(s)
- Lanxin Ji
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Amyn Majbri
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Cassandra L. Hendrix
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Moriah E. Thomason
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
- Department of Population HealthNew York University School of MedicineNew YorkNew YorkUSA
- Neuroscience InstituteNew York University School of MedicineNew YorkNew YorkUSA
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22
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Sylvester CM, Kaplan S, Myers MJ, Gordon EM, Schwarzlose RF, Alexopoulos D, Nielsen AN, Kenley JK, Meyer D, Yu Q, Graham AM, Fair DA, Warner BB, Barch DM, Rogers CE, Luby JL, Petersen SE, Smyser CD. Network-specific selectivity of functional connections in the neonatal brain. Cereb Cortex 2023; 33:2200-2214. [PMID: 35595540 PMCID: PMC9977389 DOI: 10.1093/cercor/bhac202] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 11/13/2022] Open
Abstract
The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.
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Affiliation(s)
- Chad M Sylvester
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Sydney Kaplan
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Michael J Myers
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Evan M Gordon
- Department of Radiology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Rebecca F Schwarzlose
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Ashley N Nielsen
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Jeanette K Kenley
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Dominique Meyer
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Qiongru Yu
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, 6363 Alvarado Court, Suite 103, San Diego, CA 92120, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Department of Pediatrics, and Institute of Child Development, University of Minnesota, 2025 E. River Parkway, Minneapolis, MN 55414, USA
| | - Barbara B Warner
- Department of Pediatrics, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
- Department of Radiology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
- Department of Psychological and Brain Sciences, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Cynthia E Rogers
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Joan L Luby
- Department of Psychiatry, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
| | - Christopher D Smyser
- Department of Neurology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
- Department of Radiology, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University, 660 S. Euclid Avenue, St. Louis, MO 63110, USA
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23
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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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24
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Wang S, Ding C, Dou C, Zhu Z, Zhang D, Yi Q, Wu H, Xie L, Zhu Z, Song D, Li H. Associations between maternal prenatal depression and neonatal behavior and brain function - Evidence from the functional near-infrared spectroscopy. Psychoneuroendocrinology 2022; 146:105896. [PMID: 36037574 DOI: 10.1016/j.psyneuen.2022.105896] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 08/08/2022] [Accepted: 08/19/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Maternal prenatal depression is a significant public health issue associated with mental disorders of offspring. This study aimed to determine if maternal prenatal depressive symptoms are associated with changes in neonatal behaviors and brain function at the resting state. METHODS A total of 204 pregnant women were recruited during the third trimester and were evaluated by Edinburgh Postpartum Depression Scale (EPDS). The mother-infant pairs were divided into the depressed group (n = 75) and control group (n = 129) based on the EPDS, using a cut-off value of 10. Cortisol levels in the cord blood and maternal blood collected on admission for delivery were measured. On day three of life, all study newborns were evaluated by the Neonatal Behavior Assessment Scale (NBAS) and 165 infants were evaluated by resting-state functional near-infrared spectroscopy (rs-fNIRS). To minimize the influences of potential bias on the rs-fNIRS results, we used a binary logistic regression model to carry out propensity score matching between the depressed group and the control group. Rs-fNIRS data from 21 pairs of propensity score-matched newborns were used for analysis. The associations between maternal EPDS scores, neonatal NBAS scores, and cortisol levels were analyzed using linear regressions and the mediation analysis models. RESULTS Compared to the control group, the newborns in the depressed group had lower scores in the social-interaction and autonomic system dimensions of NBAS (P < 0.01). Maternal and umbilical cord plasma cortisol levels in the depressed group were higher (P < 0.01) than in the control group. However, only umbilical cord plasma cortisol played a negative mediating role in the relationship between maternal EPDS and NBAS in the social-interaction and autonomic system (β med = -0.054 [-0.115,-0.018] and -0.052 [-0.105,-0.019]. Proportional mediation was 13.57 % and 12.33 for social-interaction and autonomic systems, respectively. The newborns in the depressed group showed decreases in the strength of rs-fNIRS functional connections, primarily the connectivity of the left frontal-parietal and temporal-parietal regions. However, infants in the depressed and control groups showed no differences in topological characteristics of the brain network, including standardized clustering coefficient, characteristic path length, small-world property, global efficiency, and local efficiency (P > 0.05). The social-interaction Z-scores had positive correlations with functional connectivity strength of left prefrontal cortex-left parietal lobe (r = 0.57, p < 0.01),prefrontal cortex-left parietal lobe - left temporal lobe (r = 0.593, p < 0.01) and left parietal lobe - left temporal lobe (r = 0.498, p < 0.01). Autonomic system Z-scores were also significantly positive correlation with prefrontal cortex-left parietal lobe (r = 0.509, p < 0.01),prefrontal cortex-left parietal lobe - left temporal lobe (r = 0.464, p < 0.01), left parietal lobe - left temporal lobe (r = 0.381, p < 0.05), and right temporal lobe and left temporal lobe (r = 0.310, p < 0.05). CONCLUSION This study shows that maternal prenatal depression may affect the development of neonatal social-interaction and autonomic system and the strength of neonatal brain functional connectivity. The fetal cortisol may play a role in behavioral development in infants exposed to maternal prenatal depression. Our findings highlight the importance of prenatal screening for maternal depression and early postnatal behavioral evaluation that provide the opportunity for early diagnosis and intervention to improve neurodevelopmental outcomes.
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Affiliation(s)
- Shan Wang
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China; Department of Neonatology, the Affiliated Children Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chenxi Ding
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chengyin Dou
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zeen Zhu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Dan Zhang
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qiqi Yi
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Haoyue Wu
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Longshan Xie
- Department of Functional Neuroscience, The First People's Hospital of Foshan (The Affiliated Foshan Hospital of Sun Yat -sen University), Guangdong, China
| | - Zhongliang Zhu
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, Maternal and Infant Health Research Institute and Medical College, Northwestern University, Xi'an, China
| | - Dongli Song
- Division of Neonatology, Department of Pediatrics, Santa Clara Valley Medical Center, San Jose, CA, USA.
| | - Hui Li
- Department of Neonatology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China; Department of Neonatology, the Affiliated Children Hospital of Xi'an Jiaotong University, Xi'an, China.
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25
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Zhang X. Magnetic resonance imaging of the monkey fetal brain in utero. INVESTIGATIVE MAGNETIC RESONANCE IMAGING 2022; 26:177-190. [PMID: 36937817 PMCID: PMC10019598 DOI: 10.13104/imri.2022.26.4.177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Non-human primates (NHPs) are the closest living relatives of the human and play a critical role in investigating the effects of maternal viral infection and consumption of medicines, drugs, and alcohol on fetal development. With the advance of contemporary fast MRI techniques with parallel imaging, fetal MRI is becoming a robust tool increasingly used in clinical practice and preclinical studies to examine congenital abnormalities including placental dysfunction, congenital heart disease (CHD), and brain abnormalities non-invasively. Because NHPs are usually scanned under anesthesia, the motion artifact is reduced substantially, allowing multi-parameter MRI techniques to be used intensively to examine the fetal development in a single scanning session or longitudinal studies. In this paper, the MRI techniques for scanning monkey fetal brains in utero in biomedical research are summarized. Also, a fast imaging protocol including T2-weighted imaging, diffusion MRI, resting-state functional MRI (rsfMRI) to examine rhesus monkey fetal brains in utero on a clinical 3T scanner is introduced.
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Affiliation(s)
- Xiaodong Zhang
- EPC Imaging Center and Division of Neuropharmacology and Neurologic Diseases, Emory National Primate Research Center, Emory University, Atlanta, Georgia, 30329, USA
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26
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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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27
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Tooley UA, Park AT, Leonard JA, Boroshok AL, McDermott CL, Tisdall MD, Bassett DS, Mackey AP. The Age of Reason: Functional Brain Network Development during Childhood. J Neurosci 2022; 42:8237-8251. [PMID: 36192151 PMCID: PMC9653278 DOI: 10.1523/jneurosci.0511-22.2022] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 07/25/2022] [Accepted: 09/03/2022] [Indexed: 01/27/2023] Open
Abstract
Human childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood because of methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years ([Formula: see text]; 50 female, 42 male). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it.SIGNIFICANCE STATEMENT Anthropologists have called the transition from early to middle childhood the "age of reason", when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.
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Affiliation(s)
- Ursula A Tooley
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Anne T Park
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Julia A Leonard
- Department of Psychology, Yale University, New Haven, Connecticut 06520
| | - Austin L Boroshok
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Cassidy L McDermott
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Matthew D Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Santa Fe Institute, Santa Fe, New Mexico 87501
| | - Allyson P Mackey
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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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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Vishnubhotla RV, Zhao Y, Wen Q, Dietrich J, Sokol GM, Sadhasivam S, Radhakrishnan R. Brain structural connectome in neonates with prenatal opioid exposure. Front Neurosci 2022; 16:952322. [PMID: 36188457 PMCID: PMC9523134 DOI: 10.3389/fnins.2022.952322] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
Abstract
IntroductionInfants with prenatal opioid exposure (POE) are shown to be at risk for poor long-term neurobehavioral and cognitive outcomes. Early detection of brain developmental alterations on neuroimaging could help in understanding the effect of opioids on the developing brain. Recent studies have shown altered brain functional network connectivity through the application of graph theoretical modeling, in infants with POE. In this study, we assess global brain structural connectivity through diffusion tensor imaging (DTI) metrics and apply graph theoretical modeling to brain structural connectivity in infants with POE.MethodsIn this prospective observational study in infants with POE and control infants, brain MRI including DTI was performed before completion of 3 months corrected postmenstrual age. Tractography was performed on the whole brain using a deterministic fiber tracking algorithm. Pairwise connectivity and network measure were calculated based on fiber count and fractional anisotropy (FA) values. Graph theoretical metrics were also derived.ResultsThere were 11 POE and 18 unexposed infants included in the analysis. Pairwise connectivity based on fiber count showed alterations in 32 connections. Pairwise connectivity based on FA values showed alterations in 24 connections. Connections between the right superior frontal gyrus and right paracentral lobule and between the right superior occipital gyrus and right fusiform gyrus were significantly different after adjusting for multiple comparisons between POE infants and unexposed controls. Additionally, alterations in graph theoretical network metrics were identified with fiber count and FA value derived tracts.ConclusionComparisons show significant differences in fiber count in two structural connections. The long-term clinical outcomes related to these findings may be assessed in longitudinal follow-up studies.
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Affiliation(s)
- Ramana V. Vishnubhotla
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Jonathan Dietrich
- Indiana University School of Medicine, Indianapolis, IN, United States
| | - Gregory M. Sokol
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Senthilkumar Sadhasivam
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh Medical Center, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | - Rupa Radhakrishnan
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States
- *Correspondence: Rupa Radhakrishnan,
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Davis BR, Garza A, Church JA. Key considerations for child and adolescent MRI data collection. FRONTIERS IN NEUROIMAGING 2022; 1:981947. [PMID: 36312216 PMCID: PMC9615104 DOI: 10.3389/fnimg.2022.981947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 08/16/2022] [Indexed: 11/15/2022]
Abstract
Cognitive neuroimaging researchers' ability to infer accurate statistical conclusions from neuroimaging depends greatly on the quality of the data analyzed. This need for quality control is never more evident than when conducting neuroimaging studies with children and adolescents. Developmental neuroimaging requires patience, flexibility, adaptability, extra time, and effort. It also provides us a unique, non-invasive way to understand the development of cognitive processes, individual differences, and the changing relations between brain and behavior over the lifespan. In this discussion, we focus on collecting magnetic resonance imaging (MRI) data, as it is one of the more complex protocols used with children and youth. Through our extensive experience collecting MRI datasets with children and families, as well as a review of current best practices, we will cover three main topics to help neuroimaging researchers collect high-quality datasets. First, we review key recruitment and retention techniques, and note the importance for consistency and inclusion across groups. Second, we discuss ways to reduce scan anxiety for families and ways to increase scan success by describing the pre-screening process, use of a scanner simulator, and the need to focus on participant and family comfort. Finally, we outline several important design considerations in developmental neuroimaging such as asking a developmentally appropriate question, minimizing data loss, and the applicability of public datasets. Altogether, we hope this article serves as a useful tool for those wishing to enter or learn more about developmental cognitive neuroscience.
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Affiliation(s)
| | | | - Jessica A. Church
- Department of Psychology, The University of Texas at Austin, Austin, TX, United States
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Scheinost D, Chang J, Lacadie C, Brennan-Wydra E, Constable RT, Chawarska K, Ment LR. Functional connectivity for the language network in the developing brain: 30 weeks of gestation to 30 months of age. Cereb Cortex 2022; 32:3289-3301. [PMID: 34875024 PMCID: PMC9340393 DOI: 10.1093/cercor/bhab415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/20/2021] [Accepted: 10/12/2021] [Indexed: 11/14/2022] Open
Abstract
Although the neural scaffolding for language is putatively present before birth, the maturation of functional connections among the key nodes of the language network, Broca's and Wernicke's areas, is less known. We leveraged longitudinal and cross-sectional data from three sites collected through six studies to track the development of functional circuits between Broca's and Wernicke's areas from 30 weeks of gestation through 30 months of age in 127 unique participants. Using resting-state fMRI data, functional connectivity was calculated as the correlation between fMRI time courses from pairs of regions, defined as Broca's and Wernicke's in both hemispheres. The primary analysis evaluated 23 individuals longitudinally imaged from 30 weeks postmenstrual age (fetal) through the first postnatal month (neonatal). A secondary analysis in 127 individuals extended these curves into older infants and toddlers. These data demonstrated significant growth of interhemispheric connections including left Broca's and its homolog and left Wernicke's and its homolog from 30 weeks of gestation through the first postnatal month. In contrast, intrahemispheric connections did not show significant increases across this period. These data represent an important baseline for language systems in the developing brain against which to compare those neurobehavioral disorders with the potential fetal onset of disease.
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Affiliation(s)
- Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, 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
| | - Joseph Chang
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
| | - Cheryl Lacadie
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - R Todd Constable
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, USA
| | - Katarzyna Chawarska
- Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Laura R Ment
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
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32
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Brady RG, Rogers CE, Prochaska T, Kaplan S, Lean RE, Smyser TA, Shimony JS, Slavich GM, Warner BB, Barch DM, Luby JL, Smyser CD. The Effects of Prenatal Exposure to Neighborhood Crime on Neonatal Functional Connectivity. Biol Psychiatry 2022; 92:139-148. [PMID: 35428496 PMCID: PMC9257309 DOI: 10.1016/j.biopsych.2022.01.020] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/20/2021] [Accepted: 01/29/2022] [Indexed: 02/08/2023]
Abstract
BACKGROUND Maternal exposure to adversity during pregnancy has been found to affect infant brain development; however, the specific effect of prenatal crime exposure on neonatal brain connectivity remains unclear. Based on existing research, we hypothesized that living in a high-crime neighborhood during pregnancy would affect neonatal frontolimbic connectivity over and above other individual- and neighborhood-level adversity and that these associations would be mediated by maternal psychosocial stress. METHODS Participants included 399 pregnant women, recruited as part of the eLABE (Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental Disorders) study. In the neonatal period, 319 healthy, nonsedated infants were scanned using resting-state functional magnetic resonance imaging (repetition time = 800 ms; echo time = 37 ms; voxel size = 2.0 × 2.0 × 2.0 mm3; multiband = 8) on a Prisma 3T scanner and had at least 10 minutes of high-quality data. Crime data at the block group level were obtained from Applied Geographic Solution. Linear regressions and mediation models tested associations between crime, frontolimbic connectivity, and psychosocial stress. RESULTS Living in a neighborhood with high property crime during pregnancy was related to weaker neonatal functional connectivity between the thalamus-anterior default mode network (aDMN) (β = -0.15, 95% CI = -0.25 to -0.04, p = .008). Similarly, high neighborhood violent crime was related to weaker functional connectivity between the thalamus-aDMN (β = -0.16, 95% CI = -0.29 to -0.04, p = .01) and amygdala-hippocampus (β = -0.16, 95% CI = -0.29 to -0.03, p = .02), controlling for other types of adversity. Psychosocial stress partially mediated relationships between the thalamus-aDMN and both violent and property crime. CONCLUSIONS These findings suggest that prenatal exposure to crime is associated with weaker neonatal limbic and frontal functional brain connections, providing another reason for targeted public policy interventions to reduce crime.
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Affiliation(s)
- Rebecca G Brady
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, Missouri; Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
| | - Cynthia E Rogers
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Trinidi Prochaska
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Sydney Kaplan
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
| | - Rachel E Lean
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Tara A Smyser
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Joshua S Shimony
- Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California
| | - Barbara B Warner
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri; Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri
| | - Joan L Luby
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Christopher D Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri; Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri; Mallinckrot Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
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Ji L, Hendrix CL, Thomason ME. Empirical evaluation of human fetal fMRI preprocessing steps. Netw Neurosci 2022; 6:702-721. [PMID: 36204420 PMCID: PMC9531599 DOI: 10.1162/netn_a_00254] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 05/09/2022] [Indexed: 11/04/2022] Open
Abstract
Increased study and methodological innovation have led to growth in the field of fetal brain fMRI. An important gap yet to be addressed is optimization of fetal fMRI preprocessing. Rapid developmental changes, imaged within the maternal compartment using an abdominal coil, introduce novel constraints that challenge established methods used in adult fMRI. This study evaluates the impact of (1) normalization to a group mean-age template versus normalization to an age-matched template; (2) independent components analysis (ICA) denoising at two criterion thresholds; and (3) smoothing using three kernel sizes. Data were collected from 121 fetuses (25-39 weeks, 43.8% female). Results indicate that the mean age template is superior in older fetuses, but less optimal in younger fetuses. ICA denoising at a more stringent threshold is superior to less stringent denoising. A larger smoothing kernel can enhance cross-hemisphere functional connectivity. Overall, this study provides improved understanding of the impact of specific steps on fetal image quality. Findings can be used to inform a common set of best practices for fetal fMRI preprocessing.
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Affiliation(s)
- Lanxin Ji
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Cassandra L. Hendrix
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
| | - Moriah E. Thomason
- Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
- Department of Population Health, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
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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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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: 4] [Impact Index Per Article: 2.0] [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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Turk E, Vroomen J, Fonken Y, Levy J, van den Heuvel MI. In sync with your child: The potential of parent-child electroencephalography in developmental research. Dev Psychobiol 2022; 64:e22221. [PMID: 35312051 DOI: 10.1002/dev.22221] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 09/29/2021] [Accepted: 10/29/2021] [Indexed: 12/25/2022]
Abstract
Healthy interaction between parent and child is foundational for the child's socioemotional development. Recently, an innovative paradigm shift in electroencephalography (EEG) research has enabled the simultaneous measurement of neural activity in caregiver and child. This dual-EEG or hyperscanning approach, termed parent-child dual-EEG, combines the strength of both behavioral observations and EEG methods. In this review, we aim to inform on the potential of dual-EEG in parents and children (0-6 years) for developmental researchers. We first provide a general overview of the dual-EEG technique and continue by reviewing the first empirical work on the emerging field of parent-child dual-EEG, discussing the limited but fascinating findings on parent-child brain-to-behavior and brain-to-brain synchrony. We then continue by providing an overview of dual-EEG analysis techniques, including the technical challenges and solutions one may encounter. We finish by discussing the potential of parent-child dual-EEG for the future of developmental research. The analysis of multiple EEG data is technical and challenging, but when performed well, parent-child EEG may transform the way we understand how caregiver and child connect on a neurobiological level. Importantly, studying objective physiological measures of parent-child interactions could lead to the identification of novel brain-to-brain synchrony markers of interaction quality.
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Affiliation(s)
- Elise Turk
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands
| | - Jean Vroomen
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands
| | - Yvonne Fonken
- Department of Cognitive Neuropsychology, Tilburg University, Tilburg, The Netherlands
| | - Jonathan Levy
- Baruch Ivcher School of Psychology, Interdisciplinary Center Herzliya (IDC), Herzliya, Israel.,Department of Neuroscience and Biomedical Engineering, Aalto University, Aalto, Finland
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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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Cui W, Wang S, Chen B, Fan G. Altered Functional Network in Infants With Profound Bilateral Congenital Sensorineural Hearing Loss: A Graph Theory Analysis. Front Neurosci 2022; 15:810833. [PMID: 35095404 PMCID: PMC8795617 DOI: 10.3389/fnins.2021.810833] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/22/2021] [Indexed: 12/17/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.
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Abstract
Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.
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Nordvik T, Schumacher EM, Larsson PG, Pripp AH, Løhaugen GC, Stiris T. Early spectral EEG in preterm infants correlates with neurocognitive outcomes in late childhood. Pediatr Res 2022; 92:1132-1139. [PMID: 35013563 PMCID: PMC9586859 DOI: 10.1038/s41390-021-01915-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 10/04/2021] [Accepted: 10/31/2021] [Indexed: 11/09/2022]
Abstract
BACKGROUND Evidence regarding the predictive value of early amplitude-integrated electroencephalography (aEEG)/EEG on neurodevelopmental outcomes at school age and beyond is lacking. We aimed to investigate whether there is an association between early postnatal EEG and neurocognitive outcomes in late childhood. METHODS This study is an observational prospective cohort study of premature infants with a gestational age <28 weeks. The total absolute band powers (tABP) of the delta, theta, alpha, and beta bands were analyzed from EEG recordings during the first three days of life. At 10-12 years of age, neurocognitive outcomes were assessed using the Wechsler Intelligence Scale for Children 4th edition (WISC-IV), Vineland adaptive behavior scales 2nd edition, and Behavior Rating Inventory of Executive Function (BRIEF). The mean differences in tABP were assessed for individuals with normal versus unfavorable neurocognitive scores. RESULTS Twenty-two infants were included. tABP values in all four frequency bands were significantly lower in infants with unfavorable results in the main composite scores (full intelligence quotient, adaptive behavior composite score, and global executive composite score) on all three tests (p < 0.05). CONCLUSIONS Early postnatal EEG has the potential to assist in predicting cognitive outcomes at 10-12 years of age in extremely premature infants <28 weeks' gestation. IMPACT Evidence regarding the value of early postnatal EEG in long-term prognostication in preterm infants is limited. Our study suggests that early EEG spectral analysis correlates with neurocognitive outcomes in late childhood in extremely preterm infants. Early identification of infants at-risk of later impairment is important to initiate early and targeted follow-up and intervention.
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Affiliation(s)
- Tone Nordvik
- grid.5510.10000 0004 1936 8921Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Eva M. Schumacher
- grid.55325.340000 0004 0389 8485Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Pål G. Larsson
- grid.55325.340000 0004 0389 8485Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
| | - Are H. Pripp
- grid.55325.340000 0004 0389 8485Oslo Center of Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway
| | - Gro C. Løhaugen
- grid.414311.20000 0004 0414 4503Department of Pediatrics, Sørlandet Hospital, Arendal, Norway
| | - Tom Stiris
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway. .,Department of Neonatal Intensive Care, Oslo University Hospital, Ullevål, Oslo, Norway.
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41
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Hu H, Cusack R, Naci L. OUP accepted manuscript. Brain Commun 2022; 4:fcac071. [PMID: 35425900 PMCID: PMC9006044 DOI: 10.1093/braincomms/fcac071] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/29/2021] [Accepted: 03/16/2022] [Indexed: 11/12/2022] Open
Abstract
One of the great frontiers of consciousness science is understanding how early consciousness arises in the development of the human infant. The reciprocal relationship between the default mode network and fronto-parietal networks—the dorsal attention and executive control network—is thought to facilitate integration of information across the brain and its availability for a wide set of conscious mental operations. It remains unknown whether the brain mechanism of conscious awareness is instantiated in infants from birth. To address this gap, we investigated the development of the default mode and fronto-parietal networks and of their reciprocal relationship in neonates. To understand the effect of early neonate age on these networks, we also assessed neonates born prematurely or before term-equivalent age. We used the Developing Human Connectome Project, a unique Open Science dataset which provides a large sample of neonatal functional MRI data with high temporal and spatial resolution. Resting state functional MRI data for full-term neonates (n = 282, age 41.2 weeks ± 12 days) and preterm neonates scanned at term-equivalent age (n = 73, 40.9 weeks ± 14.5 days), or before term-equivalent age (n = 73, 34.6 weeks ± 13.4 days), were obtained from the Developing Human Connectome Project, and for a reference adult group (n = 176, 22–36 years), from the Human Connectome Project. For the first time, we show that the reciprocal relationship between the default mode and dorsal attention network was present at full-term birth or term-equivalent age. Although different from the adult networks, the default mode, dorsal attention and executive control networks were present as distinct networks at full-term birth or term-equivalent age, but premature birth was associated with network disruption. By contrast, neonates before term-equivalent age showed dramatic underdevelopment of high-order networks. Only the dorsal attention network was present as a distinct network and the reciprocal network relationship was not yet formed. Our results suggest that, at full-term birth or by term-equivalent age, infants possess key features of the neural circuitry that enables integration of information across diverse sensory and high-order functional modules, giving rise to conscious awareness. Conversely, they suggest that this brain infrastructure is not present before infants reach term-equivalent age. These findings improve understanding of the ontogeny of high-order network dynamics that support conscious awareness and of their disruption by premature birth.
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Affiliation(s)
- Huiqing Hu
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Rhodri Cusack
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
- Correspondence to: Lorina Naci School of Psychology Trinity College Institute of Neuroscience Global Brain Health Institute Trinity College Dublin Dublin, Ireland E-mail:
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Oldham S, Ball G, Fornito A. Early and late development of hub connectivity in the human brain. Curr Opin Psychol 2021; 44:321-329. [PMID: 34896927 DOI: 10.1016/j.copsyc.2021.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/14/2021] [Accepted: 10/28/2021] [Indexed: 12/28/2022]
Abstract
Human brain networks undergo pronounced changes during development. The emergence of highly connected hub regions that can support integrated brain function is central to this maturational process, with these areas undergoing a particularly protracted period of development that extends into adulthood. The location of cortical network hubs emerges early but connections to and from hubs continue to strengthen throughout childhood and adolescence. Patterns of functional coupling in cortical association hubs are immature and incomplete at birth, but gradually strengthen during development. Early establishment of hub connectivity may provide a stable substrate that is refined by changes in tissue organization and microstructure, resulting in the emergence of complex functional dynamics by adulthood.
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Affiliation(s)
- Stuart Oldham
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; Developmental Imaging, Murdoch Children's Research Institute, Victoria, Australia.
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Victoria, Australia; Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
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43
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Stout JN, Bedoya MA, Grant PE, Estroff JA. Fetal Neuroimaging Updates. Magn Reson Imaging Clin N Am 2021; 29:557-581. [PMID: 34717845 PMCID: PMC8562558 DOI: 10.1016/j.mric.2021.06.007] [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: 11/29/2022]
Abstract
MR imaging is used in conjunction with ultrasound screening for fetal brain abnormalities because it offers better contrast, higher resolution, and has multiplanar capabilities that increase the accuracy and confidence of diagnosis. Fetal motion still severely limits the MR imaging sequences that can be acquired. We outline the current acquisition strategies for fetal brain MR imaging and discuss the near term advances that will improve its reliability. Prospective and retrospective motion correction aim to make the complement of MR neuroimaging modalities available for fetal diagnosis, improve the performance of existing modalities, and open new horizons to understanding in utero brain development.
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Affiliation(s)
- Jeffrey N Stout
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - M Alejandra Bedoya
- Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - P Ellen Grant
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Judy A Estroff
- Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Maternal Fetal Care Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
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44
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Thomason ME, Palopoli AC, Jariwala NN, Werchan DM, Chen A, Adhikari S, Espinoza-Heredia C, Brito NH, Trentacosta CJ. Miswiring the brain: Human prenatal Δ9-tetrahydrocannabinol use associated with altered fetal hippocampal brain network connectivity. Dev Cogn Neurosci 2021; 51:101000. [PMID: 34388638 PMCID: PMC8363827 DOI: 10.1016/j.dcn.2021.101000] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 08/03/2021] [Accepted: 08/03/2021] [Indexed: 01/16/2023] Open
Abstract
Increasing evidence supports a link between maternal prenatal cannabis use and altered neural and physiological development of the child. However, whether cannabis use relates to altered human brain development prior to birth, and specifically, whether maternal prenatal cannabis use relates to connectivity of fetal functional brain systems, remains an open question. The major objective of this study was to identify whether maternal prenatal cannabis exposure (PCE) is associated with variation in human brain hippocampal functional connectivity prior to birth. Prenatal drug toxicology and fetal fMRI data were available in a sample of 115 fetuses [43 % female; mean age 32.2 weeks (SD = 4.3)]. Voxelwise hippocampal connectivity analysis in a subset of age and sex-matched fetuses revealed that PCE was associated with alterations in fetal dorsolateral, medial and superior frontal, insula, anterior temporal, and posterior cingulate connectivity. Classification of group differences by age 5 outcomes suggest that compared to the non-PCE group, the PCE group is more likely to have increased connectivity to regions associated with less favorable outcomes and to have decreased connectivity to regions associated with more favorable outcomes. This is preliminary evidence that altered fetal neural connectome may contribute to neurobehavioral vulnerability observed in children exposed to cannabis in utero.
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Affiliation(s)
- Moriah E Thomason
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA; Department of Population Health, New York University Medical Center, New York, NY, USA; Neuroscience Institute, New York University Medical Center, New York, NY, USA.
| | - Ava C Palopoli
- Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Nicki N Jariwala
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA
| | - Denise M Werchan
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA
| | - Alan Chen
- Department of Population Health, New York University Medical Center, New York, NY, USA
| | - Samrachana Adhikari
- Department of Population Health, New York University Medical Center, New York, NY, USA
| | - Claudia Espinoza-Heredia
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA
| | - Natalie H Brito
- Department of Applied Psychology, New York University, New York, NY, USA
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45
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Rajagopalan V, Deoni S, Panigrahy A, Thomason ME. Is fetal MRI ready for neuroimaging prime time? An examination of progress and remaining areas for development. Dev Cogn Neurosci 2021; 51:100999. [PMID: 34391003 PMCID: PMC8365463 DOI: 10.1016/j.dcn.2021.100999] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 11/25/2022] Open
Abstract
A major challenge in designing large-scale, multi-site studies is developing a core, scalable protocol that retains the innovation of scientific advances while also lending itself to the variability in experience and resources across sites. In the development of a common Healthy Brain and Child Development (HBCD) protocol, one of the chief questions is "is fetal MRI ready for prime-time?" While there is agreement about the value of prenatal data obtained non-invasively through MRI, questions about practicality abound. There has been rapid progress over the past years in fetal and placental MRI methodology but there is uncertainty about whether the gains afforded outweigh the challenges in supporting fetal MRI protocols at scale. Here, we will define challenges inherent in building a common protocol across sites with variable expertise and will propose a tentative framework for evaluation of design decisions. We will compare and contrast various design considerations for both normative and high-risk populations, in the setting of the post-COVID era. We will conclude with articulation of the benefits of overcoming these challenges and would lend to the primary questions articulated in the HBCD initiative.
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Affiliation(s)
- Vidya Rajagopalan
- Department of Radiology, Keck School of Medicine, University of Southern California and Childrens Hospital of Los Angeles, United States.
| | - Sean Deoni
- Department of Pediatrics, Memorial Hospital of Rhode Island, United States
| | - Ashok Panigrahy
- Department of Radiology, University of Pittsburgh Medical School and Children's Hospital of Pittsburgh, United States
| | - Moriah E Thomason
- Departments of Child and Adolescent Psychiatry and Population Health, Hassenfeld Children's Hospital at NYU Langone, United States
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46
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Moody JF, Adluru N, Alexander AL, Field AS. The Connectomes: Methods of White Matter Tractography and Contributions of Resting State fMRI. Semin Ultrasound CT MR 2021; 42:507-522. [PMID: 34537118 DOI: 10.1053/j.sult.2021.07.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
A comprehensive mapping of the structural and functional circuitry of the brain is a major unresolved problem in contemporary neuroimaging research. Diffusion-weighted and functional MRI have provided investigators with the capability to assess structural and functional connectivity in-vivo, driven primarily by methods of white matter tractography and resting-state fMRI, respectively. These techniques have paved the way for the construction of the functional and structural connectomes, which are quantitative representations of brain architecture as neural networks, comprised of nodes and edges. The connectomes, typically depicted as matrices or graphs, possess topological properties that inherently characterize the strength, efficiency, and organization of the connections between distinct brain regions. Graph theory, a general mathematical framework for analyzing networks, can be implemented to derive metrics from the connectomes that are sensitive to changes in brain connectivity associated with age, sex, cognitive function, and disease. These quantities can be assessed at either the global (whole brain) or local levels, allowing for the identification of distinct regional connectivity hubs and associated localized brain networks, which together serve crucial roles in establishing the structural and functional architecture of the brain. As a result, structural and functional connectomes have each been employed to study the brain circuitry underlying early brain development, neuroplasticity, developmental disorders, psychopathology, epilepsy, aging, neurodegenerative disorders, and traumatic brain injury. While these studies have yielded important insights into brain structure, function, and pathology, a precise description of the innate relationship between functional and structural networks across the brain remains unachieved. To date, connectome research has merely scratched the surface of potential clinical applications and related characterizations of brain-wide connectivity. Continued advances in diffusion and functional MRI acquisition, the delineation of functional and structural networks, and the quantification of neural network properties in specific brain regions, will be invaluable to future progress in neuroimaging science.
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Affiliation(s)
- Jason F Moody
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI; Waisman Center, University of Wisconsin-Madison, Madison, WI
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI; Department of Radiology, University of Wisconsin-Madison, Madison, WI
| | - Andrew L Alexander
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI; Waisman Center, University of Wisconsin-Madison, Madison, WI
| | - Aaron S Field
- Department of Radiology, University of Wisconsin-Madison, Madison, WI.
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47
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Zhang J, Kucyi A, Raya J, Nielsen AN, Nomi JS, Damoiseaux JS, Greene DJ, Horovitz SG, Uddin LQ, Whitfield-Gabrieli S. What have we really learned from functional connectivity in clinical populations? Neuroimage 2021; 242:118466. [PMID: 34389443 DOI: 10.1016/j.neuroimage.2021.118466] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 07/06/2021] [Accepted: 08/09/2021] [Indexed: 02/09/2023] Open
Abstract
Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.
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Affiliation(s)
- Jiahe Zhang
- Department of Psychology, 125 Nightingale Hall, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA.
| | - Aaron Kucyi
- Department of Psychology, 125 Nightingale Hall, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA
| | - Jovicarole Raya
- Department of Psychology, 125 Nightingale Hall, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA
| | - Ashley N Nielsen
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jason S Nomi
- Department of Psychology, University of Miami, Miami, FL 33124, USA
| | - Jessica S Damoiseaux
- Institute of Gerontology and Department of Psychology, Wayne State University, Detroit, MI 48202, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, USA
| | | | - Lucina Q Uddin
- Department of Psychology, University of Miami, Miami, FL 33124, USA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, 125 Nightingale Hall, Northeastern University, 360 Huntington Ave, Boston, MA 02115, USA
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48
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Martini FJ, Guillamón-Vivancos T, Moreno-Juan V, Valdeolmillos M, López-Bendito G. Spontaneous activity in developing thalamic and cortical sensory networks. Neuron 2021; 109:2519-2534. [PMID: 34293296 DOI: 10.1016/j.neuron.2021.06.026] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 05/05/2021] [Accepted: 06/23/2021] [Indexed: 11/19/2022]
Abstract
Developing sensory circuits exhibit different patterns of spontaneous activity, patterns that are related to the construction and refinement of functional networks. During the development of different sensory modalities, spontaneous activity originates in the immature peripheral sensory structures and in the higher-order central structures, such as the thalamus and cortex. Certainly, the perinatal thalamus exhibits spontaneous calcium waves, a pattern of activity that is fundamental for the formation of sensory maps and for circuit plasticity. Here, we review our current understanding of the maturation of early (including embryonic) patterns of spontaneous activity and their influence on the assembly of thalamic and cortical sensory networks. Overall, the data currently available suggest similarities between the developmental trajectory of brain activity in experimental models and humans, which in the future may help to improve the early diagnosis of developmental disorders.
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Affiliation(s)
- Francisco J Martini
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d'Alacant, Spain.
| | - Teresa Guillamón-Vivancos
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d'Alacant, Spain
| | - Verónica Moreno-Juan
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d'Alacant, Spain
| | - Miguel Valdeolmillos
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d'Alacant, Spain
| | - Guillermina López-Bendito
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), Sant Joan d'Alacant, Spain.
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Ghio M, Cara C, Tettamanti M. The prenatal brain readiness for speech processing: A review on foetal development of auditory and primordial language networks. Neurosci Biobehav Rev 2021; 128:709-719. [PMID: 34274405 DOI: 10.1016/j.neubiorev.2021.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 07/02/2021] [Accepted: 07/09/2021] [Indexed: 10/20/2022]
Abstract
Despite consolidated evidence for the prenatal ability to elaborate and respond to sounds and speech stimuli, the ontogenetic functional brain maturation of language responsiveness in the foetus is still poorly understood. Recent advances in in-vivo foetal neuroimaging have contributed to a finely detailed picture of the anatomo-functional hallmarks that define the prenatal neurodevelopment of auditory and language-related networks. Here, we first outline available evidence for the prenatal development of auditory and language-related brain structures and of their anatomical connections. Second, we focus on functional connectivity data showing the emergence of auditory and primordial language networks in the foetal brain. Third, we recapitulate functional neuroimaging studies assessing the prenatal readiness for sound processing, as a crucial prerequisite for the foetus to experientially respond to spoken language. In conclusion, we suggest that the state of the art has reached sufficient maturity to directly assess the neural mechanisms underlying the prenatal readiness for speech processing and to evaluate whether foetal neuromarkers can predict the postnatal development of language acquisition abilities and disabilities.
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Affiliation(s)
- Marta Ghio
- CIMeC - Center for Mind/Brain Sciences, University of Trento, Italy
| | - Cristina Cara
- CIMeC - Center for Mind/Brain Sciences, University of Trento, Italy
| | - Marco Tettamanti
- CIMeC - Center for Mind/Brain Sciences, University of Trento, Italy.
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50
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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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