1
|
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 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.
Collapse
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
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
Blanchett R, Chen Y, Aguate F, Xia K, Cornea E, Burt SA, de Los Campos G, Gao W, Gilmore JH, Knickmeyer RC. Genetic and environmental factors influencing neonatal resting-state functional connectivity. Cereb Cortex 2023; 33:4829-4843. [PMID: 36190430 PMCID: PMC10110449 DOI: 10.1093/cercor/bhac383] [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: 06/01/2021] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 11/14/2022] Open
Abstract
Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.
Collapse
Affiliation(s)
- Reid Blanchett
- Genetics and Genome Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Yuanyuan Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Fernando Aguate
- Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Kai Xia
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - S Alexandra Burt
- Department of Psychology, Michigan State University, East Lansing, MI 48824, USA
| | - Gustavo de Los Campos
- Departments of Epidemiology and Biostatistics and Statistics and Probability, Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Rebecca C Knickmeyer
- Department of Pediatrics and Human Development, Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI 48824, USA
| |
Collapse
|
5
|
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.
Collapse
|
6
|
Kim P, Chen H, Dufford AJ, Tribble R, Gilmore J, Gao W. Intergenerational neuroimaging study: mother-infant functional connectivity similarity and the role of infant and maternal factors. Cereb Cortex 2022; 32:3175-3186. [PMID: 34849641 PMCID: PMC9618162 DOI: 10.1093/cercor/bhab408] [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: 07/30/2021] [Revised: 10/13/2021] [Accepted: 10/14/2021] [Indexed: 11/15/2022] Open
Abstract
Mother and infant neural and behavioral synchrony is important for infant development during the first years of life. Recent studies also suggest that neural risk markers associated with parental psychopathology may be transmitted across generations before symptoms emerge in offspring. There is limited understanding of how early similarity in brain functioning between 2 generations emerges. In the current study, using functional magnetic resonance imaging, we examined the functional connectivity (FC) similarity between mothers and newborns during the first 3 months after the infant's birth. We found that FC similarity between mothers and infants increased as infant age increased. Furthermore, we examined whether maternal factors such as maternal socioeconomic status and prenatal maternal depressive symptoms may influence individual differences in FC similarity. For the whole-brain level, lower maternal education levels were associated with greater FC similarity. In previous literature, lower maternal education levels were associated with suboptimal cognitive and socioemotional development. Greater FC similarity may reflect that the infants develop their FC similarity prematurely, which may suboptimally influence their developmental outcomes in later ages.
Collapse
Affiliation(s)
- Pilyoung Kim
- Department of Psychology, University of Denver, Denver, CO 80208-3500, USA
| | - Haitao Chen
- Department of Biomedical Sciences and Imaging, Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Alexander J Dufford
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Rebekah Tribble
- Department of Psychology, University of Denver, Denver, CO 80208-3500, USA
| | - John Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Wei Gao
- Department of Biomedical Sciences and Imaging, Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| |
Collapse
|
7
|
Molloy MF, Saygin ZM. Individual variability in functional organization of the neonatal brain. Neuroimage 2022; 253:119101. [PMID: 35304265 DOI: 10.1016/j.neuroimage.2022.119101] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 02/28/2022] [Accepted: 03/14/2022] [Indexed: 11/25/2022] Open
Abstract
The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? And what is the individual variability in this organization in neonates? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We quantified individual variability across neonates, and found the most individual variability in the ventral attention networks. Crucially, the variability of these networks was not driven by SNR differences or differences from adult networks (Yeo et al., 2011). Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks and identified potential genes of interest for future developmental and individual variability research. Overall, we found neonatal connectomes (even at the voxel-level) can reveal broad individual-specific information processing units. The presence of individual differences in neonates and the framework for personalized parcellations demonstrated here has the potential to improve prediction of behavior and future outcomes from neonatal and infant brain data.
Collapse
Affiliation(s)
- M Fiona Molloy
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, United States
| | - Zeynep M Saygin
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, United States.
| |
Collapse
|
8
|
Korom M, Camacho MC, Filippi CA, Licandro R, Moore LA, Dufford A, Zöllei L, Graham AM, Spann M, Howell B, Shultz S, Scheinost D. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Dev Cogn Neurosci 2021; 53:101055. [PMID: 34974250 PMCID: PMC8733260 DOI: 10.1016/j.dcn.2021.101055] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/28/2021] [Accepted: 12/26/2021] [Indexed: 01/07/2023] Open
Abstract
The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging. The field of infant MRI is young with evolving standards. We address 20 questions that researchers commonly receive reviewers. These come from research ethics boards, grant, and manuscript reviewers. This article reflects the cumulative knowledge of experts in the FIT’NG community.
Collapse
Affiliation(s)
- Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA.
| | - M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University School of Medicine, St. Louis, MO, USA.
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Roxane Licandro
- Institute of Visual Computing and Human-Centered Technology, Computer Vision Lab, TU Wien, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research, Medical University of Vienna, Vienna, Austria
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Alexander Dufford
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Department of Human Development and Family Science, Virginia Polytechnic Institute and State University, Roanoke, VA, USA
| | | | - Sarah Shultz
- Division of Autism & Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
| | - Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
| |
Collapse
|
9
|
Dufford AJ, Salzwedel AP, Gilmore JH, Gao W, Kim P. Maternal trait anxiety symptoms, frontolimbic resting-state functional connectivity, and cognitive development in infancy. Dev Psychobiol 2021; 63:e22166. [PMID: 34292595 PMCID: PMC10775911 DOI: 10.1002/dev.22166] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 06/13/2021] [Accepted: 06/22/2021] [Indexed: 11/07/2022]
Abstract
Exposure to maternal anxiety symptoms during infancy has been associated with difficulties in development and greater risk for developing anxiety later in life. Although previous studies have examined associations between prenatal maternal distress, infant brain development, and developmental outcomes, it is still largely unclear if there are associations between postnatal anxiety, infant brain development, and cognitive development in infancy. In this study, we used resting-state functional magnetic resonance imaging to examine the association between maternal anxiety symptoms and resting-state functional connectivity in the first year of life. We also examine the association between frontolimbic functional connectivity and infant cognitive development. The sample consisted of 21 infants (mean age = 24.15 months, SD = 4.17) that were scanned during their natural sleep using. We test the associations between maternal trait anxiety symptoms and amygdala-anterior cingulate cortex (ACC) functional connectivity, a neural circuit implicated in early life stress exposure. We also test the associations between amygdala-ACC connectivity and cognitive development. We found a significant negative association between maternal trait anxiety symptoms and left amygdala-right ACC functional connectivity (p < .05, false discovery rate corrected). We found a significant negative association between left amygdala-right ACC functional connectivity and infant cognitive development (p < .05). These findings have potential implications for understanding the role of postpartum maternal anxiety symptoms in functional brain and cognitive development in infancy.
Collapse
Affiliation(s)
| | - Andrew P. Salzwedel
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Gao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Pilyoung Kim
- Department of Psychology, University of Denver, Denver, Colorado, USA
| |
Collapse
|
10
|
Chen H, Liu J, Chen Y, Salzwedel A, Cornea E, Gilmore JH, Gao W. Developmental heatmaps of brain functional connectivity from newborns to 6-year-olds. Dev Cogn Neurosci 2021; 50:100976. [PMID: 34174513 PMCID: PMC8246150 DOI: 10.1016/j.dcn.2021.100976] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/07/2021] [Accepted: 06/14/2021] [Indexed: 12/17/2022] Open
Abstract
Heatmaps quantify degrees of developmental changes in functional connectivity. More changes are observed in the first than second postnatal year, driven by girls. Most change is observed from ages 2–4 compared with any other age span. Limbic and subcortical areas show more changes than primary sensory regions. Consistent trajectories of functional connectivity are found across validations.
Different functional networks exhibit distinct longitudinal trajectories throughout development, but the timeline of the dynamics of functional connectivity across the whole brain remains to be elucidated. Here we used resting-state fMRI to investigate the development of voxel-level changes in functional connectivity across the first six years of life. Globally, we found that developmental changes in functional connectivity are nonlinear with more changes during the first postnatal year than the second, followed by most significant changes from ages 2–4 and from ages 4–6. However, the overall global difference observed between the first and second year appears to have been driven by girls. Limbic and subcortical areas consistently demonstrated the most substantial changes, whereas primary sensory areas were the most stable. These patterns were consistent in full-term and preterm subgroups. Validation on randomly divided subsamples as well as in an independent cross-sectional sample revealed global patterns consistent with the main results. Overall, the derived developmental heatmaps reveal novel dynamics underlying functional circuit development during the first 6 years of life.
Collapse
Affiliation(s)
- Haitao Chen
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA; Department of Bioengineering, University of California at Los Angeles, Los Angeles, CA, 90095, USA
| | - Janelle Liu
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Yuanyuan Chen
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Andrew Salzwedel
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, 27599, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Wei Gao
- Biomedical Imaging Research Institute (BIRI), Department of Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA; Department of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
| |
Collapse
|
11
|
Liu J, Chen Y, Stephens R, Cornea E, Goldman B, Gilmore JH, Gao W. Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance. Cortex 2021; 138:165-177. [PMID: 33691225 PMCID: PMC8058274 DOI: 10.1016/j.cortex.2021.02.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/03/2020] [Accepted: 02/05/2021] [Indexed: 02/08/2023]
Abstract
The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.
Collapse
Affiliation(s)
- Janelle Liu
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Yuanyuan Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Rebecca Stephens
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Barbara Goldman
- FPG Child Development Institute and Department of Psychology & Neuroscience, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA; David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
| |
Collapse
|
12
|
Gao W, Chen Y, Cornea E, Goldman BD, Gilmore JH. Neonatal brain connectivity outliers identify over forty percent of IQ outliers at 4 years of age. Brain Behav 2020; 10:e01846. [PMID: 32945129 PMCID: PMC7749582 DOI: 10.1002/brb3.1846] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 09/01/2020] [Accepted: 09/03/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Defining reliable brain markers for the prediction of abnormal behavioral outcomes remains an urgent but extremely challenging task in neuroscience research. This is particularly important for infant studies given the most dramatic brain and behavioral growth during infancy. METHODS In this study, we proposed a novel prediction scheme through abstracting individual newborn's whole-brain functional connectivity pattern to three outlier measures (Triple O) and tested the hypothesis that neonates identified as "brain outliers" based on Triple O were more likely to develop as IQ outliers at 4 years of age. Without need for training with behavioral data, Triple O represents a novel proof-of-concept approach to predict later IQ outcomes based on neonatal brain data. RESULTS Triple O correctly identified 42.1% true IQ outliers among a mixed cohort of 175 newborns with different term, twin, and maternal disorder statuses. Triple O also reached a high level of specificity (96.2%) and overall accuracy (90.3%). Further incorporating a demographic information indicator, the enhanced Triple O+ could further differentiate between high and low 4YR IQ outliers. Validation tests against seven independent reference samples revealed highly consistent results and a minimum sample size of ~50 for robust performance. CONCLUSIONS Considering that postnatal brain growth and various environmental factors likely also contribute to 4YR IQ, the fact that Triple O, based purely on neonatal functional connectivity data, could identify >40% of 4YR IQ outliers is striking. Together with the very high level of specificity, each outlier predicted by Triple O represents a meaningful risk but future efforts are needed to explore ways to identify the rest of outliers. Overall, with no need for training, a high level of robustness, and a minimal requirement on sample size, the proposed Triple O approach demonstrates great potential to predict later outlying IQ performances using neonatal functional connectivity data.
Collapse
Affiliation(s)
- Wei Gao
- Department of Biomedical Sciences and Imaging, Biomedical Imaging Research Institute (BIRI), Cedars-Sinai Medical Center, Los Angeles, CA, USA.,Department of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Yuanyuan Chen
- Department of Biomedical Sciences and Imaging, Biomedical Imaging Research Institute (BIRI), Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA
| | - Barbara D Goldman
- Department of Psychology and Neuroscience FPG Child Development Institute, University of North Carolina Chapel Hill, Chapel Hill, NC, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|