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Wu M, Liu H, Zhao X, Lu L, Wang Y, Wei C, Liu Y, Zhang YX. Speech-Processing Network Formation of Cochlear-Implanted Toddlers With Early Hearing Experiences. Dev Sci 2025; 28:e13568. [PMID: 39412370 DOI: 10.1111/desc.13568] [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: 09/22/2023] [Revised: 07/04/2024] [Accepted: 09/05/2024] [Indexed: 11/10/2024]
Abstract
To reveal the formation process of speech processing with early hearing experiences, we tracked the development of functional connectivity in the auditory and language-related cortical areas of 84 (36 female) congenitally deafened toddlers using repeated functional near-infrared spectroscopy for up to 36 months post cochlear implantation (CI). Upon hearing restoration, the CI children lacked the modular organization of the mature speech-processing network and demonstrated a higher degree of immaturity in temporo-parietal than temporo-frontal connections. The speech-processing network appeared to form rapidly with early CI experiences, with two-thirds of the developing connections following nonlinear trajectories reflecting possibly more than one synaptogenesis-pruning cycle. A few key features of the mature speech-processing network emerged within the first year of CI hearing, including left-hemispheric advantage, differentiation of the dorsal and ventral processing streams, and functional state (speech listening vs. resting) specific patterns of connectivity development. The developmental changes were predictable of future auditory and verbal communication skills of the CI children, with prominent contribution from temporo-parietal connections in the dorsal stream, suggesting a mediating role of speech-processing network formation with early hearing experiences in speech acquisition.
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Affiliation(s)
- Meiyun Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, 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, Peking University First Hospital, Beijing, China
| | - Xue Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Li Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuyang Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Chaogang Wei
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, 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, Beijing Normal University, Beijing, China
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2
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Huang Y, Glasier CM, Na X, Ou X. White matter functional networks in the developing brain. Front Neurosci 2024; 18:1467446. [PMID: 39507802 PMCID: PMC11538026 DOI: 10.3389/fnins.2024.1467446] [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: 07/19/2024] [Accepted: 10/14/2024] [Indexed: 11/08/2024] Open
Abstract
Background Functional magnetic resonance imaging (fMRI) is widely used to depict neural activity and understand human brain function. Studies show that functional networks in gray matter undergo complex transformations from neonatal age to childhood, supporting rapid cognitive development. However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear. Purpose Aims to examine and compare white matter functional networks in neonates and 8-year-old children. Methods We acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks' characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter. Results White matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (p < 0.05). Inter-network FC between cerebral peduncle (CP) and anterior corona radiation (ACR) was higher in 8-year-olds (p < 0.05). Additionally, 8-year-olds showed a greater distribution of brain activity energy in the high-frequency range of 0.01-0.15 Hz. Significant developmental differences in brain white matter functional networks exist between the two group, characterized by increased inter-network FC, decreased intra-network FC, and higher high-frequency energy distribution. Similar findings were also observed in gray matter functional networks. Conclusion White matter functional networks can be reliably measured in the developing brain, and the differences in these networks reflect functional differentiation and integration in brain development.
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Affiliation(s)
- Yali Huang
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Charles M. Glasier
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Xiaoxu Na
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Xiawei Ou
- Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- Arkansas Children’s Research Institute, Little Rock, AR, United States
- Arkansas Children’s Nutrition Center, Little Rock, AR, United States
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3
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Blanchett R, Chen H, Vlasova RM, Cornea E, Maza M, Davenport M, Reinhartsen D, DeRamus M, Edmondson Pretzel R, Gilmore JH, Hooper SR, Styner MA, Gao W, Knickmeyer RC. White matter microstructure and functional connectivity in the brains of infants with Turner syndrome. Cereb Cortex 2024; 34:bhae351. [PMID: 39256896 PMCID: PMC11387115 DOI: 10.1093/cercor/bhae351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/01/2024] [Accepted: 08/13/2024] [Indexed: 09/12/2024] Open
Abstract
Turner syndrome, caused by complete or partial loss of an X-chromosome, is often accompanied by specific cognitive challenges. Magnetic resonance imaging studies of adults and children with Turner syndrome suggest these deficits reflect differences in anatomical and functional connectivity. However, no imaging studies have explored connectivity in infants with Turner syndrome. Consequently, it is unclear when in development connectivity differences emerge. To address this gap, we compared functional connectivity and white matter microstructure of 1-year-old infants with Turner syndrome to typically developing 1-year-old boys and girls. We examined functional connectivity between the right precentral gyrus and five regions that show reduced volume in 1-year old infants with Turner syndrome compared to controls and found no differences. However, exploratory analyses suggested infants with Turner syndrome have altered connectivity between right supramarginal gyrus and left insula and right putamen. To assess anatomical connectivity, we examined diffusivity indices along the superior longitudinal fasciculus and found no differences. However, an exploratory analysis of 46 additional white matter tracts revealed significant group differences in nine tracts. Results suggest that the first year of life is a window in which interventions might prevent connectivity differences observed at later ages, and by extension, some of the cognitive challenges associated with Turner syndrome.
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Affiliation(s)
- Reid Blanchett
- Genetics and Genome Sciences, Michigan State University, Biomedical & Physical Sciences, Room 2165, East Lansing, MI 48824, United States
- Department of Epigenetics, Van Andel Research Institute, 33 Bostwick Ave NE, Grand Rapids, MI 49503, United States
| | - Haitao Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Roza M Vlasova
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Emil Cornea
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Maria Maza
- Department of Psychology and Neuroscience, Campus Box #3270, 235 E. Cameron Avenue, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Marsha Davenport
- Department of Pediatrics, 333 South Columbia Street, Suite 260 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Debra Reinhartsen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Margaret DeRamus
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - Rebecca Edmondson Pretzel
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, 101 Renee Lynn Ct, Carrboro, NC 27510, United States
| | - John H Gilmore
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
| | - Stephen R Hooper
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Health Sciences, Bondurant Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Martin A Styner
- Department of Psychiatry, 333 S. Columbia Street, Suite 304 MacNider Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States
- Department of Computer Science, Campus Box 3175, Brooks Computer Science Building, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, 8700 Beverly Blvd, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States
| | - Rebecca C Knickmeyer
- Department of Pediatrics and Human Development, Life Sciences Bldg. 1355 Bogue, #B240B, Michigan State University, East Lansing, MI 48824, United States
- Institute for Quantitative Health Sciences and Engineering, Room 2114, 775 Woodlot Dr., East Lansing, MI 48824, United States
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4
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Wan C, Cai H, Li F. Age Three: Milestone in the Development of Cognitive Flexibility. Behav Sci (Basel) 2024; 14:578. [PMID: 39062401 PMCID: PMC11274188 DOI: 10.3390/bs14070578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 06/29/2024] [Accepted: 07/02/2024] [Indexed: 07/28/2024] Open
Abstract
Although the cognitive flexibility (CF) of preschool children has been extensively studied, the development of CF in children around three years old is unclear. This study aimed to investigate the CF of three-year-olds in a stepwise rule-induction task (sRIT) comprising nine steps in which children are encouraged to switch attention to a new rule and then implicitly inhibit the old one. A pair of boxes was displayed at each step, and children aged 2.5 to 3.5 years were asked to select the target. When children learned a rule (e.g., the shape rule), they were encouraged to switch rules through negative feedback. The results showed that most children (81.10%) passed at least one of the two sets of the sRIT, and children over the age of three years performed better than those under three years. Additionally, a positive correlation existed between rule switching and rule generalization, whereby the old rule was implicitly inhibited. These findings indicate that age three might be a milestone in the development of CF, and inhibitory control might play a vital role in rule switching.
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Affiliation(s)
| | | | - Fuhong Li
- School of Psychology, Jiangxi Normal University, Nanchang 330022, China; (C.W.); (H.C.)
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Fenske SJ, Liu J, Chen H, Diniz MA, Stephens RL, Cornea E, Gilmore JH, Gao W. Sex differences in brain-behavior relationships in the first two years of life. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578147. [PMID: 38352542 PMCID: PMC10862872 DOI: 10.1101/2024.01.31.578147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Background Evidence for sex differences in cognition in childhood is established, but less is known about the underlying neural mechanisms for these differences. Recent findings suggest the existence of brain-behavior relationship heterogeneities during infancy; however, it remains unclear whether sex underlies these heterogeneities during this critical period when sex-related behavioral differences arise. Methods A sample of 316 infants was included with resting-state functional magnetic resonance imaging scans at neonate (3 weeks), 1, and 2 years of age. We used multiple linear regression to test interactions between sex and resting-state functional connectivity on behavioral scores of working memory, inhibitory self-control, intelligence, and anxiety collected at 4 years of age. Results We found six age-specific, intra-hemispheric connections showing significant and robust sex differences in functional connectivity-behavior relationships. All connections are either with the prefrontal cortex or the temporal pole, which has direct anatomical pathways to the prefrontal cortex. Sex differences in functional connectivity only emerge when associated with behavior, and not in functional connectivity alone. Furthermore, at neonate and 2 years of age, these age-specific connections displayed greater connectivity in males and lower connectivity in females in association with better behavioral scores. Conclusions Taken together, we critically capture robust and conserved brain mechanisms that are distinct to sex and are defined by their relationship to behavioral outcomes. Our results establish brain-behavior mechanisms as an important feature in the search for sex differences during development.
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Affiliation(s)
- Sonja J Fenske
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Janelle Liu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Haitao Chen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- David Geffen School of Medicine, University of California, Los Angeles, CA 90025
| | - Marcio A Diniz
- The Biostatistics and Bioinformatics Research Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Rebecca L Stephens
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, 27599
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, 27599
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, 27599
| | - Wei Gao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- David Geffen School of Medicine, University of California, Los Angeles, CA 90025
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Bagonis M, Cornea E, Girault JB, Stephens RL, Kim S, Prieto JC, Styner M, Gilmore JH. Early Childhood Development of Node Centrality in the White Matter Connectome and Its Relationship to IQ at Age 6 Years. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1024-1032. [PMID: 36162754 PMCID: PMC10033460 DOI: 10.1016/j.bpsc.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND The white matter (WM) connectome is important for cognitive development and intelligence and is altered in neuropsychiatric illnesses. Little is known about how the WM connectome develops or its relationship to IQ in early childhood. METHODS The development of node centrality in the WM connectome was studied in a longitudinal cohort of 226 (123 female) children from the University of North Carolina Early Brain Development Study. Structural and diffusion-weighted images were acquired after birth and at 1, 2, 4, and 6 years, and IQ was assessed at 6 years. Eigenvector centrality, betweenness centrality, and the global graph metrics of global efficiency, small worldness, and modularity were determined at each age. RESULTS The greatest developmental change in eigenvector centrality and betweenness centrality occurred during the first year of life, with relative stability between ages 1 and 6 years. Most of the high-centrality hubs at age 6 were also high-centrality hubs at 1 year, and many were already high-centrality hubs at birth. There were generally small but significant changes in global efficiency and modularity from birth to 6 years, while small worldness increased between 2 and 4 years. Individual node centrality was not significantly correlated with IQ at 6 years. CONCLUSIONS Node centrality in the WM connectome is established very early in childhood and is relatively stable from age 1 to 6 years. Many high-centrality hubs are established before birth, and most are present by age 1.
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Affiliation(s)
- Maria Bagonis
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Rebecca L Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - SunHyung Kim
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Juan Carlos Prieto
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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7
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Liu J, Chen H, Cornea E, Gilmore JH, Gao W. Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy. Cereb Cortex 2023; 33:10367-10379. [PMID: 37585708 PMCID: PMC10545442 DOI: 10.1093/cercor/bhad288] [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: 12/05/2022] [Revised: 07/13/2023] [Indexed: 08/18/2023] Open
Abstract
Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.
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Affiliation(s)
- Janelle Liu
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
| | - Haitao Chen
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - Wei Gao
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, United States
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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: 5] [Impact Index Per Article: 5.0] [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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9
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Banihashemi L, Schmithorst VJ, Bertocci MA, Samolyk A, Zhang Y, Lima Santos JP, Versace A, Taylor M, English G, Northrup JB, Lee VK, Stiffler R, Aslam H, Panigrahy A, Hipwell AE, Phillips ML. Neural Network Functional Interactions Mediate or Suppress White Matter-Emotional Behavior Relationships in Infants. Biol Psychiatry 2023; 94:57-67. [PMID: 36918062 PMCID: PMC10365319 DOI: 10.1016/j.biopsych.2023.03.004] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/28/2023] [Accepted: 03/02/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND Elucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural-emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural-emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures. METHODS The analytic sample comprised primary caregiver-infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality. RESULTS After significant WM-emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = -0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = -0.296, p = .022); however, lower orbitofrontal cortex-amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex-central executive network rsFC mediated this relationship. CONCLUSIONS Functional interactions among neural networks have an important influence on WM microstructural-emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.
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Affiliation(s)
- Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
| | - Vanessa J Schmithorst
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michele A Bertocci
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Alyssa Samolyk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Yicheng Zhang
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - João Paulo Lima Santos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Megan Taylor
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gabrielle English
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Jessie B Northrup
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Vincent K Lee
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Richelle Stiffler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Haris Aslam
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Ashok Panigrahy
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alison E Hipwell
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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10
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Truzzi A, Cusack R. The development of intrinsic timescales: A comparison between the neonate and adult brain. Neuroimage 2023; 275:120155. [PMID: 37169116 DOI: 10.1016/j.neuroimage.2023.120155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/13/2023] Open
Abstract
In human adults and other mammals, different brain regions have distinct intrinsic timescales over which they integrate information, from shorter in unimodal sensory-motor regions to longer in transmodal higher-order regions. These have been related to cognitive performance and clinical symptoms, but it remains unclear how they develop. We asked if there are regional differences in timescales at birth that could shape learning by acting as an inductive bias, or if they develop later as the temporal statistics of the environment are learned. We used resting-state fMRI to characterise timescales in human neonates and adults. They were highly consistent across two independent neonatal groups, but in both sensory-motor and higher order areas, timescales were longer in infants compared to adults, as might be expected from their less developed myelination, and recent evidence of longer neural segments in infants watching naturalistic stimuli. In adults, we replicated the finding that transmodal areas have longer timescales than sensory-motor areas, but in infants the opposite pattern was found, driven by long infant timescales in the somotomotor network. Across regions within single brain networks, both positive (limbic) and negative (visual) correlations were found between neonates and adults. In conclusion, neonatal timescales were found to be highly structured, but distinct from adults, suggesting they act as an inductive bias that favours learning on longer timescales, particularly in unimodal regions and then develop with experience or maturation. This "take it slow" initial approach might help human infants to create more regularised, holistic representations of the input less bound to fleeting details, which would favour the development of abstract and contextual representations.
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Affiliation(s)
- Anna Truzzi
- School of Psychology, Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
| | - Rhodri Cusack
- School of Psychology, Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
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Fenske SJ, Liu J, Chen H, Diniz MA, Stephens RL, Cornea E, Gilmore JH, Gao W. Sex differences in resting state functional connectivity across the first two years of life. Dev Cogn Neurosci 2023; 60:101235. [PMID: 36966646 PMCID: PMC10066534 DOI: 10.1016/j.dcn.2023.101235] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 02/17/2023] [Accepted: 03/19/2023] [Indexed: 03/29/2023] Open
Abstract
Sex differences in behavior have been reported from infancy through adulthood, but little is known about sex effects on functional circuitry in early infancy. Moreover, the relationship between early sex effects on the functional architecture of the brain and later behavioral performance remains to be elucidated. In this study, we used resting-state fMRI and a novel heatmap analysis to examine sex differences in functional connectivity with cross-sectional and longitudinal mixed models in a large cohort of infants (n = 319 neonates, 1-, and 2-year-olds). An adult dataset (n = 92) was also included for comparison. We investigated the relationship between sex differences in functional circuitry and later measures of language (collected in 1- and 2-year-olds) as well as indices of anxiety, executive function, and intelligence (collected in 4-year-olds). Brain areas showing the most significant sex differences were age-specific across infancy, with two temporal regions demonstrating consistent differences. Measures of functional connectivity showing sex differences in infancy were significantly associated with subsequent behavioral scores of language, executive function, and intelligence. Our findings provide insights into the effects of sex on dynamic neurodevelopmental trajectories during infancy and lay an important foundation for understanding the mechanisms underlying sex differences in health and disease.
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Liu T, Shi Z, Zhang J, Wang K, Li Y, Pei G, Wang L, Wu J, Yan T. Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing. Hum Brain Mapp 2022; 44:744-761. [PMID: 36214186 PMCID: PMC9842897 DOI: 10.1002/hbm.26096] [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: 06/28/2022] [Revised: 09/01/2022] [Accepted: 09/19/2022] [Indexed: 01/25/2023] Open
Abstract
Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.
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Affiliation(s)
- Tiantian Liu
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Zhongyan Shi
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Jian Zhang
- Intelligent Robotics Institute, School of Mechatronical EngineeringBeijing Institute of TechnologyBeijingChina
| | - Kexin Wang
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Yuanhao Li
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Guangying Pei
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Li Wang
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Jinglong Wu
- School of Medical TechnologyBeijing Institute of TechnologyBeijingChina
| | - Tianyi Yan
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
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