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Meredith Weiss S, Aydin E, Lloyd-Fox S, Johnson MH. Trajectories of brain and behaviour development in the womb, at birth and through infancy. Nat Hum Behav 2024; 8:1251-1262. [PMID: 38886534 DOI: 10.1038/s41562-024-01896-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 04/04/2024] [Indexed: 06/20/2024]
Abstract
Birth is often seen as the starting point for studying effects of the environment on human development, with much research focused on the capacities of young infants. However, recent imaging advances have revealed that the complex behaviours of the fetus and the uterine environment exert influence. Birth is now viewed as a punctuate event along a developmental pathway of increasing autonomy of the child from their mother. Here we highlight (1) increasing physiological autonomy and perceptual sensitivity in the fetus, (2) physiological and neurochemical processes associated with birth that influence future behaviour, (3) the recalibration of motor and sensory systems in the newborn to adapt to the world outside the womb and (4) the effect of the prenatal environment on later infant behaviours and brain function. Taken together, these lines of evidence move us beyond nature-nurture issues to a developmental human lifespan view beginning within the womb.
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Affiliation(s)
- Staci Meredith Weiss
- University of Cambridge, Department of Psychology, Cambridge, UK.
- University of Roehampton, School of Psychology, London, UK.
| | - Ezra Aydin
- University of Cambridge, Department of Psychology, Cambridge, UK
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Sarah Lloyd-Fox
- University of Cambridge, Department of Psychology, Cambridge, UK
| | - Mark H Johnson
- University of Cambridge, Department of Psychology, Cambridge, UK
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
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2
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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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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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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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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. ADVANCES IN NEUROBIOLOGY 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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Thill B. The fetal pain paradox. FRONTIERS IN PAIN RESEARCH 2023; 4:1128530. [PMID: 37025166 PMCID: PMC10072285 DOI: 10.3389/fpain.2023.1128530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 02/21/2023] [Indexed: 04/08/2023] Open
Abstract
Controversy exists as to when conscious pain perception in the fetus may begin. According to the hypothesis of cortical necessity, thalamocortical connections, which do not form until after 24-28 weeks gestation, are necessary for conscious pain perception. However, anesthesiologists and neonatologists treat age-matched neonates as both conscious and pain-capable due to observable and measurable behavioral, hormonal, and physiologic indicators of pain. In preterm infants, these multimodal indicators of pain are uncontroversial, and their presence, despite occurring prior to functional thalamocortical connections, has guided the use of analgesics in neonatology and fetal surgery for decades. However, some medical groups state that below 24 weeks gestation, there is no pain capacity. Thus, a paradox exists in the disparate acknowledgment of pain capability in overlapping patient populations. Brain networks vary by age. During the first and second trimesters, the cortical subplate, a unique structure that is present only during fetal and early neonatal development, forms the first cortical network. In the third trimester, the cortical plate assumes this function. According to the subplate modulation hypothesis, a network of connections to the subplate and subcortical structures is sufficient to facilitate conscious pain perception in the fetus and the preterm neonate prior to 24 weeks gestation. Therefore, similar to other fetal and neonatal systems that have a transitional phase (i.e., circulatory system), there is now strong evidence for transitional developmental phases of fetal and neonatal pain circuitry.
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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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Ursino M, Magosso E, Petti M. Neural Networks and Connectivity among Brain Regions. Brain Sci 2022; 12:brainsci12030346. [PMID: 35326302 PMCID: PMC8946799 DOI: 10.3390/brainsci12030346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 03/01/2022] [Indexed: 02/01/2023] Open
Affiliation(s)
- Mauro Ursino
- Department of Electrical, Electronic and Information Engineering Guglielmo Marconi, Campus of Cesena, University of Bologna, Via Dell’Università 50, 47521 Cesena, Italy;
- Correspondence:
| | - Elisa Magosso
- Department of Electrical, Electronic and Information Engineering Guglielmo Marconi, Campus of Cesena, University of Bologna, Via Dell’Università 50, 47521 Cesena, Italy;
| | - Manuela Petti
- Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto, 25, 00185 Roma, Italy;
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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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