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Zhao Z, Shuai Y, Wu Y, Xu X, Li M, Wu D. Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study. Neuroimage 2024; 297:120669. [PMID: 38852805 DOI: 10.1016/j.neuroimage.2024.120669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/01/2024] [Accepted: 06/05/2024] [Indexed: 06/11/2024] Open
Abstract
The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.
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Affiliation(s)
- Zhiyong Zhao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yifan Shuai
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yihan Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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2
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Xu Y, Liao X, Lei T, Cao M, Zhao J, Zhang J, Zhao T, Li Q, Jeon T, Ouyang M, Chalak L, Rollins N, Huang H, He Y. Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2. Cereb Cortex 2024; 34:bhae204. [PMID: 38771241 DOI: 10.1093/cercor/bhae204] [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: 12/15/2023] [Revised: 04/23/2024] [Accepted: 05/01/2024] [Indexed: 05/22/2024] Open
Abstract
The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2 years of age. Our findings highlight network-level neural substrates underlying early cognitive development.
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Affiliation(s)
- Yuehua Xu
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Miao Cao
- Institution of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220 Handan Road, Shanghai 200433, China
| | - Jianlong Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tina Jeon
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Chinese Institute for Brain Research, No. 26 Kexueyuan Road, Beijing 102206, China
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3
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Song L, Peng Y, Ouyang M, Peng Q, Feng L, Sotardi S, Yu Q, Kang H, Sindabizera KL, Liu S, Huang H. Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels. Hum Brain Mapp 2024; 45:e26695. [PMID: 38727010 PMCID: PMC11083905 DOI: 10.1002/hbm.26695] [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: 10/15/2023] [Revised: 03/11/2024] [Accepted: 04/10/2024] [Indexed: 05/13/2024] Open
Abstract
Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.
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Affiliation(s)
- Limei Song
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- School of Medical ImagingWeifang Medical UniversityWeifangChina
| | - Yun Peng
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Minhui Ouyang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Qinmu Peng
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Lei Feng
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Susan Sotardi
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Qinlin Yu
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Huiying Kang
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Kay L. Sindabizera
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Shuwei Liu
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
| | - Hao Huang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Ouyang M, Detre JA, Hyland JL, Sindabizera KL, Kuschner ES, Edgar JC, Peng Y, Huang H. Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588784. [PMID: 38645183 PMCID: PMC11030426 DOI: 10.1101/2024.04.10.588784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.
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Affiliation(s)
- Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - John A Detre
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Jessica L Hyland
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
| | - Kay L Sindabizera
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
| | - Emily S Kuschner
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - J Christopher Edgar
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, Beijing, 100045, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
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5
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Kirschen MP, Ouyang M, Patel B, Berman JI, Burnett R, Berg RA, Diaz-Arrastia R, Topjian A, Huang H, Vossough A. Association between ASL MRI-derived cerebral blood flow and outcomes after pediatric cardiac arrest. Resuscitation 2024; 196:110128. [PMID: 38280508 PMCID: PMC10923119 DOI: 10.1016/j.resuscitation.2024.110128] [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: 10/05/2023] [Revised: 01/08/2024] [Accepted: 01/19/2024] [Indexed: 01/29/2024]
Abstract
AIM Cerebral blood flow (CBF) is dysregulated after cardiac arrest. It is unknown if post-arrest CBF is associated with outcome. We aimed to determine the association of CBF derived from arterial spin labelling (ASL) MRI with outcome after pediatric cardiac arrest. METHODS Retrospective observational study of patients ≤18 years who had a clinically obtained brain MRI within 7 days of cardiac arrest between June 2005 and December 2019. Primary outcome was unfavorable neurologic status: change in Pediatric Cerebral Performance Category (PCPC) ≥1 from pre-arrest that resulted in hospital discharge PCPC 3-6. We measured CBF in whole brain and regions of interest (ROIs) including frontal, parietal, and temporal cortex, caudate, putamen, thalamus, and brainstem using pulsed ASL. We compared CBF between outcome groups using Wilcoxon Rank-Sum and performed logistic regression to associate each region's CBF with outcome, accounting for age, sex, and time between arrest and MRI. RESULTS Forty-eight patients were analyzed (median age 2.8 [IQR 0.95, 8.8] years, 65% male). Sixty-nine percent had unfavorable outcome. Time from arrest to MRI was 4 [3,5] days and similar between outcome groups (p = 0.39). Whole brain median CBF was greater for unfavorable compared to favorable groups (28.3 [20.9,33.0] vs. 19.6 [15.3,23.1] ml/100 g/min, p = 0.007), as was CBF in individual ROIs. Greater CBF in the whole brain and individual ROIs was associated with higher odds of unfavorable outcome after controlling for age, sex, and days from arrest to MRI (aOR for whole brain 19.08 [95% CI 1.94, 187.41]). CONCLUSION CBF measured 3-5 days after pediatric cardiac arrest by ASL MRI was independently associated with unfavorable outcome.
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Affiliation(s)
- Matthew P Kirschen
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Minhui Ouyang
- Department of Radiology, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Bhavesh Patel
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey I Berman
- Department of Radiology, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Ryan Burnett
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Robert A Berg
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Alexis Topjian
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Hao Huang
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arastoo Vossough
- Department of Radiology, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Xia Y, Zhao J, Xu Y, Duan D, Xia M, Jeon T, Ouyang M, Chalak L, Rollins N, Huang H, He Y. Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age. iScience 2024; 27:108981. [PMID: 38327782 PMCID: PMC10847735 DOI: 10.1016/j.isci.2024.108981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 12/13/2023] [Accepted: 01/17/2024] [Indexed: 02/09/2024] Open
Abstract
Functional connectome gradients represent fundamental organizing principles of the brain. Here, we report the development of the connectome gradients in preterm and term babies aged 31-42 postmenstrual weeks using task-free functional MRI and its association with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present during the late preterm period and continuously evolves toward a term-like pattern. The global measurements of this gradient, characterized by explanation ratio, gradient range, and gradient variation, increased with age (p < 0.05, corrected). Focal gradient development mainly occurs in the sensorimotor, lateral, and medial parietal regions, and visual regions (p < 0.05, corrected). The connectome gradient at birth predicts cognitive and language outcomes at 2-year follow-up (p < 0.005). These results are replicated using an independent dataset from the Developing Human Connectome Project. Our findings highlight early emergent rules of the brain connectome gradient and their implications for later cognitive growth.
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Affiliation(s)
- Yunman Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Jianlong Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Tina Jeon
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Minhui Ouyang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Hao Huang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
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7
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Frohlich J, Bayne T, Crone JS, DallaVecchia A, Kirkeby-Hinrup A, Mediano PA, Moser J, Talar K, Gharabaghi A, Preissl H. Not with a “zap” but with a “beep”: measuring the origins of perinatal experience. Neuroimage 2023; 273:120057. [PMID: 37001834 DOI: 10.1016/j.neuroimage.2023.120057] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023] Open
Abstract
When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory ("beep-and-zip"), visual ("flash-and-zip"), or even olfactory ("sniff-and-zip") cortical perturbations in place of electromagnetic perturbations ("zap-and-zip") might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.
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