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Prenatal neural origins of infant motor development: Associations between fetal brain and infant motor development

Published online by Cambridge University Press:  02 August 2018

Moriah E. Thomason ,
Jasmine Hect ,
Rebecca Waller ,
Janessa H. Manning ,
Ann M. Stacks ,
Marjorie Beeghly ,
Jordan L. Boeve ,
Kristyn Wong ,
Marion I. van den Heuvel  and
Edgar Hernandez-Andrade
...Show all authors
Moriah E. Thomason*
Affiliation:
New York University School of Medicine Perinatology Research Branch of NICHD/NIH/DHHS
Jasmine Hect
Affiliation:
Wayne State University
Rebecca Waller
Affiliation:
University of Michigan University of Pennsylvania
Janessa H. Manning
Affiliation:
Perinatology Research Branch of NICHD/NIH/DHHS Wayne State University
Ann M. Stacks
Affiliation:
Wayne State University
Marjorie Beeghly
Affiliation:
Wayne State University
Jordan L. Boeve
Affiliation:
Wayne State University
Kristyn Wong
Affiliation:
Brown University’s Alpert Medical School Bradley/Hasbro Children’s Research Center
Marion I. van den Heuvel
Affiliation:
Tilburg University
Edgar Hernandez-Andrade
Affiliation:
Perinatology Research Branch of NICHD/NIH/DHHS Wayne State University
Sonia S. Hassan
Affiliation:
Perinatology Research Branch of NICHD/NIH/DHHS Wayne State University
Roberto Romero
Affiliation:
Perinatology Research Branch of NICHD/NIH/DHHS Wayne State University University of Michigan Michigan State University
*
Address correspondence and reprint requests to: Dr. Moriah E. Thomason, Merrill Palmer Skillman Institute, Wayne State University, 71 E. Ferry Street, Detroit, MI 48009; E-mail: [email protected].
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Abstract

Functional circuits of the human brain emerge and change dramatically over the second half of gestation. It is possible that variation in neural functional system connectivity in utero predicts individual differences in infant behavioral development, but this possibility has yet to be examined. The current study examines the association between fetal sensorimotor brain system functional connectivity and infant postnatal motor ability. Resting-state functional connectivity data was obtained in 96 healthy human fetuses during the second and third trimesters of pregnancy. Infant motor ability was measured 7 months after birth using the Bayley Scales of Infant Development. Increased connectivity between the emerging motor network and regions of the prefrontal cortex, temporal lobes, posterior cingulate, and supplementary motor regions was observed in infants that showed more mature motor functions. In addition, females demonstrated stronger fetal-brain to infant-behavior associations. These observations extend prior longitudinal research back into prenatal brain development and raise exciting new ideas about the advent of risk and the ontogeny of early sex differences.

Type
Special Issue Articles
Information
Development and Psychopathology , Volume 30 , Special Issue 3: Developmental Origins of Psychopathology: Mechanisms, Processes, and Pathways Linking the Prenatal Environment to Postnatal Outcomes , August 2018 , pp. 763 - 772
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

This project was supported by awards from the National Institutes of Health, MH110793 and ES026022 (to M.E.T.), and by a NARSAD Young Investigator Award. This research was also supported, in part, by the Perinatology Research Branch, Division of Obstetrics and Maternal–Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services (NICHD/NIH/DHHS), and, in part, with federal funds from NICHD/NIH/DHHS under Contract No. HHSN275201300006C. Support was also provided by NIAAA T32 Fellowship 2T32AA007477-24A1 in the Addiction Center, Department of Psychiatry, University of Michigan (to R.W.). The authors thank Pavan Jella, Sophia Neuenfeldt, Toni Lewis, Tamara Qawasmeh, Fatimah Alismail, and Nada Alrajhi for their assistance in data acquisition and analyses. The authors also thank participant families who generously shared their time.

References

Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., … Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in System Neuroscience, 5, 2. doi:10.3389/fnsys.2011.00002Google Scholar
Almli, C. R., Ball, R. H., & Wheeler, M. E. (2001). Human fetal and neonatal movement patterns: Gender differences and fetal-to-neonatal continuity. Developmental Psychobiology, 38, 252–273.Google Scholar
Arca-Diaz, G., Re, T. J., Drottar, M., Fortuno, C. R., De Macedo-Rodrigues, K., Im, K., … Grant, P. E. (2017). Can cerebellar and brainstem apparent diffusion coefficient (ADC) values predict neuromotor outcome in term neonates with hypoxic-ischemic encephalopathy (HIE) treated with hypothermia? PLOS ONE, 12, e0178510. doi:10.1371/journal.pone.0178510Google Scholar
Bale, T. L., & Epperson, C. N. (2015). Sex differences and stress across the lifespan. Nature Neuroscience, 18. doi:10.1038/nn.4112Google Scholar
Barnett, M. A., & Scaramella, L. V. (2013). Mothers’ parenting and child sex differences in behavior problems among African American preschoolers. Journal of Family Psychology, 27, 773–783. doi:10.1037/a0033792Google Scholar
Bayley, N. (1965). Comparisons of mental and motor test scores for ages 1–15 months by sex, birth-order, race, geographical location, and education of the parents. Child Development, 36, 379–411. doi:10.1111/j.1467-8624.1965.tb05304.xGoogle Scholar
Bayley, N. (1966). Learning in adulthood: The role of intelligence. New York: Academic Press.Google Scholar
Bayley, N. (1968). Behavioral correlates of mental growth—Birth to 36 years. American Psychologist, 23. doi:10.1037/h0037690Google Scholar
Bayley, N. (2006). Bayley Scales of Infant and Toddler Development: Administration manual (3rd ed.). San Antonio, TX: Harcourt.Google Scholar
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. (2011). The organization of the human cerebellum estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 2322–2345. doi:10.1152/jn.00339.2011Google Scholar
Calhoun, V. D., Adali, T., Pearlson, G. D., & Pekar, J. J. (2001). A method for making group inferences from functional MRI data using independent component analysis. Human Brain Mapping, 14, 140–151. doi:10.1002/hbm.1048Google Scholar
Caviness, V. S. Jr., Kennedy, D. N., Richelme, C., Rademacher, J., & Filipek, P. A. (1996). The human brain age 7–11 years: A volumetric analysis based on magnetic resonance images. Cerebral Cortex, 6, 726–736.Google Scholar
Choe, M. S., Ortiz-Mantilla, S., Makris, N., Gregas, M., Bacic, J., Haehn, D., … Grant, P. E. (2013). Regional infant brain development: An MRI-based morphometric analysis in 3 to 13 month olds. Cerebral Cortex, 23, 2100–2117. doi:10.1093/cercor/bhs197Google Scholar
Coe, C. L., & Lubach, G. R. (2005). Prenatal origins of individual variation in behavior and immunity. Neuroscience and Biobehavioral Reviews, 29, 39–49. doi:10.1016/j.neubiorev.2004.11.003Google Scholar
de Lacoste, M. C., Horvath, D. S., & Woodward, D. J. (1991). Possible sex differences in the developing human fetal brain. Journal of Clinical and Experimental Neuropsychology, 13, 831–846. doi:10.1080/01688639108405101Google Scholar
DiPietro, J. A., & Voegtline, K. M. (2017). The gestational foundation of sex differences in development and vulnerability. Neuroscience, 342, 4–20. doi:10.1016/j.neuroscience.2015.07.068Google Scholar
Drobyshevsky, A., Bregman, J., Storey, P., Meyer, J., Prasad, P. V., Derrick, M., … Tan, S. (2007). Serial diffusion tensor imaging detects white matter changes that correlate with motor outcome in premature infants. Developmental Neuroscience, 29, 289–301. doi:10.1159/000105470Google Scholar
Emerson, R. W., Gao, W., & Lin, W. (2016). Longitudinal study of the emerging functional connectivity asymmetry of primary language regions during infancy. Journal of Neuroscience, 36, 10883–10892. doi:10.1523/jneurosci.3980-15.2016Google Scholar
Fransson, P., Åden, U., Blennow, M., & Lagercrantz, H. (2011). The functional architecture of the infant brain as revealed by resting-state fMRI. Cerebral Cortex, 21, 145–154. doi:10.1093/cercor/bhq071Google Scholar
Gao, W., Alcauter, S., Elton, A., Hernandez-Castillo, C. R., Smith, J. K., Ramirez, J., & Lin, W. (2015). Functional network development during the first year: Relative sequence and socioeconomic correlations. Cerebral Cortex, 25, 2919–2928. doi:10.1093/cercor/bhu088Google Scholar
Gilmore, J. H., Lin, W., Prastawa, M. W., Looney, C. B., Vetsa, Y. S., Knickmeyer, R. C., … Gerig, G. (2007). Regional gray matter growth, sexual dimorphism, and cerebral asymmetry in the neonatal brain. Journal of Neuroscience, 27, 1255–1260.Google Scholar
Góes, F. V. d., Méio, M. D. B. B., Mello, R. R. d., & Morsch, D. (2015). Evaluation of neurodevelopment of preterm infants using Bayley III scale. Revista Brasileira de Saúde Materno Infantil, 15, 47–55.Google Scholar
Grayson, D. S., & Fair, D. A. (2017). Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature. Neuroimage. Advance online publication. doi:10.1016/j.neuroimage.2017.01.079Google Scholar
Griffanti, L., Douaud, G., Bijsterbosch, J., Evangelisti, S., Alfaro-Almagro, F., Glasser, M. F., … Smith, S. M. (2017). Hand classification of fMRI ICA noise components. Neuroimage, 154, 188–205. doi:10.1016/j.neuroimage.2016.12.036Google Scholar
Guell, X., Schmahmann, J. D., Gabrieli, J. D. E., & Ghosh, S. S. (2018). Functional gradients of the cerebellum: A fundamental movement-to-thought principle. Unpublished manuscript.Google Scholar
Hata, T., Hanaoka, U., Mostafa AboEllail, M. A., Uematsu, R., Noguchi, J., Kusaka, T., & Kurjak, A. (2016). Is there a sex difference in fetal behavior? A comparison of the KANET test between male and female fetuses. Journal of Perinatal Medicine, 44, 585–588. doi:10.1515/jpm-2015-0387Google Scholar
Hines, M. (2010). Sex-related variation in human behavior and the brain. Trends in Cognitive Sciences, 14, 448–456. doi:10.1016/j.tics.2010.07.005Google Scholar
Ingemarsson, I. (2003). Gender aspects of preterm birth. BJOG, 110, 34–38. doi:10.1046/j.1471-0528.2003.00022.xGoogle Scholar
Ispa, J. M., Claire Cook, J., Harmeyer, E., & Rudy, D. (2015). Mothers' physical interventions in toddler play in a low-income, African American sample. Infant Behavioral Development, 41, 88–101. doi:10.1016/j.infbeh.2015.08.006Google Scholar
Jakab, A., Schwartz, E., Kasprian, G., Gruber, G. M., Prayer, D., Schopf, V., & Langs, G. (2014). Fetal functional imaging portrays heterogeneous development of emerging human brain networks. Frontiers in Human Neuroscience, 8, 852. doi:10.3389/fnhum.2014.00852Google Scholar
Johnson, C. B., Jenkins, D. D., Bentzley, J. P., Lambert, D., Hope, K., Rollins, L. G., … Katikaneni, L. D. (2015). Proton magnetic resonance spectroscopy and outcome in term neonates with chorioamnionitis. Journal of Perinatology, 35, 1030–1036. doi:10.1038/jp.2015.121Google Scholar
Kendall, G. S., Melbourne, A., Johnson, S., Price, D., Bainbridge, A., Gunny, R., … Robertson, N. J. (2014). White matter NAA/Cho and Cho/Cr ratios at MR spectroscopy are predictive of motor outcome in preterm infants. Radiology, 271, 230–238. doi:10.1148/radiol.13122679Google Scholar
Keunen, K., Isgum, I., van Kooij, B. J., Anbeek, P., van Haastert, I. C., Koopman-Esseboom, C., … Benders, M. J. (2016). Brain volumes at term-equivalent age in preterm infants: Imaging biomarkers for neurodevelopmental outcome through early school age. Journal of Pediatrics, 172, 88–95. doi:10.1016/j.jpeds.2015.12.023Google Scholar
Knickmeyer, R. C., Wang, J., Zhu, H., Geng, X., Woolson, S., Hamer, R. M., … Gilmore, J. H. (2014). Impact of sex and gonadal steroids on neonatal brain structure. Cerebral Cortex, 24, 2721–2731. doi:10.1093/cercor/bht125Google Scholar
Koolschijn, P. C., & Crone, E. A. (2013). Sex differences and structural brain maturation from childhood to early adulthood. Developmental Cognitive Neuroscience, 5, 106–118. doi:10.1016/j.dcn.2013.02.003Google Scholar
Lewis, M. (1972). State as an infant-environment interaction—Analysis of mother-infant interaction as a function of sex. Merrill-Palmer Quarterly of Behavior and Development, 18, 95–121.Google Scholar
Massaro, A. N., Evangelou, I., Fatemi, A., Vezina, G., McCarter, R., Glass, P., & Limperopoulos, C. (2015). White matter tract integrity and developmental outcome in newborn infants with hypoxic-ischemic encephalopathy treated with hypothermia. Devopmental Medicine and Child Neurology, 57, 441–448. doi:10.1111/dmcn.12646Google Scholar
Mileva-Seitz, V. R., Ghassabian, A., Bakermans-Kranenburg, M. J., van den Brink, J. D., Linting, M., Jaddoe, V. W. V., … van Ijzendoorn, M. H. (2015). Are boys more sensitive to sensitivity? Parenting and executive function in preschoolers. Journal of Experimental Child Psychology, 130(Supplement C), 193–208. doi:10.1016/j.jecp.2014.08.008Google Scholar
Murray, G. K., Jones, P. B., Kuh, D., & Richards, M. (2007). Infant developmental milestones and subsequent cognitive function. Annals of Neurology, 62, 128–136. doi:10.1002/ana.21120Google Scholar
Muthén, L. K., & Muthén, B. O. (2014). Mplus user's guide (7th ed.). Los Angeles: Author.Google Scholar
Neligan, G., & Prudham, D. (1969). Norms for 4 standard developmental milestones by sex, social class, and place in a family. Devopmental Medicine and Child Neurology, 11.Google Scholar
Papenfuss, T., & Whitacre, C. (2009). Sex hormones, pregnancy, and immunef. In Hormones, brain and behavior (2nd ed., pp. 367–394). New York: Academic Press.Google Scholar
Piek, J. P., Gasson, N., Barrett, N., & Case, I. (2002). Limb and gender differences in the development of coordination in early infancy. Human Movement Science, 21, 621–639.Google Scholar
Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437–448.Google Scholar
Robinson, S., Basso, G., Soldati, N., Sailer, U., Jovicich, J., Bruzzone, L., … Moser, E. (2009). A resting state network in the motor control circuit of the basal ganglia. BMC Neuroscience, 10, 137. doi:10.1186/1471-2202-10-137Google Scholar
Robles de Medina, P. G., Visser, G. H., Huizink, A. C., Buitelaar, J. K., & Mulder, E. J. (2003). Fetal behaviour does not differ between boys and girls. Early Human Development, 73, 17–26.Google Scholar
Rollins, C. K., Asaro, L. A., Akhondi-Asl, A., Kussman, B. D., Rivkin, M. J., Bellinger, D. C., … Soul, J. S. (2017). White matter volume predicts language development in congenital heart disease. Journal of Pediatrics, 181, 42–48. doi:10.1016/j.jpeds.2016.09.070Google Scholar
Rose, J., Butler, E. E., Lamont, L. E., Barnes, P. D., Atlas, S. W., & Stevenson, D. K. (2009). Neonatal brain structure on MRI and diffusion tensor imaging, sex, and neurodevelopment in very-low-birthweight preterm children. Developmental Medicine and Child Neurology, 51, 526–535. doi:10.1111/j.1469-8749.2008.03231.xGoogle Scholar
Ruigrok, A. N. V., Salimi-Khorshidi, G., Lai, M.-C., Baron-Cohen, S., Lombardo, M. V., Tait, R. J., & Suckling, J. (2014). A meta-analysis of sex differences in human brain structure. Neuroscience and Biobehavioral Reviews, 39(Supplement C), 34–50. doi:10.1016/j.neubiorev.2013.12.004Google Scholar
Satterthwaite, T. D., Wolf, D. H., Roalf, D. R., Ruparel, K., Erus, G., Vandekar, S., … Gur, R. C. (2015). Linked sex differences in cognition and functional connectivity in youth. Cerebral Cortex, 25, 2383–2394. doi:10.1093/cercor/bhu036Google Scholar
Schumacher, E. M., Larsson, P. G., Sinding-Larsen, C., Aronsen, R., Lindeman, R., Skjeldal, O. H., & Stiris, T. A. (2013). Automated spectral EEG analyses of premature infants during the first three days of life correlated with developmental outcomes at 24 months. Neonatology, 103, 205–212. doi:10.1159/000345923Google Scholar
Serag, A., Aljabar, P., Ball, G., Counsell, S. J., Boardman, J. P., Rutherford, M. A., … Rueckert, D. (2012). Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression. Neuroimage, 59, 2255–2265. doi:10.1016/j.neuroimage.2011.09.062Google Scholar
Shattuck, D. W., & Leahy, R. M. (2002). BrainSuite: An automated cortical surface identification tool. Medical Image Analysis, 6, 129–142.Google Scholar
Shatz, C. J., & Kliot, M. (1982). Prenatal misrouting of the retinogeniculate pathway in Siamese cats. Nature, 300, 525–529.Google Scholar
Skiöld, B., Alexandrou, G., Padilla, N., Blennow, M., Vollmer, B., & Ådén, U. (2014). Sex differences in outcome and associations with neonatal brain morphology in extremely preterm children. Journal of Pediatrics, 164, 1012–1018. doi:10.1016/j.jpeds.2013.12.051Google Scholar
Spielberger, C. D. (1984). State-trait anxiety inventory: A comprehensive bibliography. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Stiles, J., & Jernigan, T. L. (2010). The basics of brain development. Neuropsychology Review, 20, 327–348. doi:10.1007/s11065-010-9148-4Google Scholar
Thalagala, N. (2015). Windows of achievement for development milestones of Sri Lankan infants and toddlers: Estimation through statistical modelling. Child Care Health and Development, 41, 1030–1039. doi:10.1111/cch.12258Google Scholar
Thomas, J. R., & French, K. E. (1985). Gender differences across age in motor performance: A meta-analysis. Psychological Bulletin, 98, 260–282.Google Scholar
Thomason, M. E., Brown, J. A., Dassanayake, M. T., Shastri, R., Marusak, H. A., Hernandez-Andrade, E., … Romero, R. (2014). Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus. PLOS ONE, 9, e94423.Google Scholar
Thomason, M. E., Dassanayake, M. T., Shen, S., Katkuri, Y., Alexis, M., Anderson, A. L., … Romero, R. (2013). Cross-hemispheric functional connectivity in the human fetal brain. Science Translational Medicine, 5. doi:10.1126/scitranslmed.3004978Google Scholar
Thomason, M. E., Scheinost, D., Manning, J. H., Grove, L. E., Hect, J., Marshall, N., … Romero, R. (2017). Weak functional connectivity in the human fetal brain prior to preterm birth. Scientific Reports, 7, 39286. doi:10.1038/srep39286Google Scholar
Thordstein, M., Lofgren, N., Flisberg, A., Lindecrantz, K., & Kjellmer, I. (2006). Sex differences in electrocortical activity in human neonates. Neuroreport, 17, 1165–1168. doi:10.1097/01.wnr.0000227978.98389.43Google Scholar
Tiemeier, H., Lenroot, R. K., Greenstein, D. K., Tran, L., Pierson, R., & Giedd, J. N. (2010). Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study. Neuroimage, 49, 63–70. doi:10.1016/j.neuroimage.2009.08.016Google Scholar
Tolner, E. A., Sheikh, A., Yukin, A. Y., Kaila, K., & Kanold, P. O. (2012). Subplate neurons promote spindle bursts and thalamocortical patterning in the neonatal rat somatosensory cortex. Journal of Neuroscience, 32, 692–702. doi:10.1523/jneurosci.1538-11.2012Google Scholar
Touwen, B. (1976). Neurological development in infancy. London: William Heinmann Medical Books.Google Scholar
van Batenburg-Eddes, T., Henrichs, J., Schenk, J. J., Sincer, I., de Groot, L., Hofman, A., … Tiemeier, H. (2013). Early infant neuromotor assessment is associated with language and nonverbal cognitive function in toddlers: The Generation R Study. Journal of Developmental and Behavioral Pediatrics, 34, 326–334.Google Scholar
van Kooij, B. J. M., de Vries, L. S., Ball, G., van Haastert, I. C., Benders, M. J. N. L., Groenendaal, F., & Counsell, S. J. (2012). Neonatal tract-based spatial statistics findings and outcome in preterm infants. American Journal of Neuroradiology, 33, 188.Google Scholar
Whitfield, M. F., Grunau, R. V., & Holsti, L. (1997). Extremely premature (< or = 800 g) schoolchildren: Multiple areas of hidden disability. Archives of Disease in Childhood Fetal–Neonatal Edition, 77, F85–F90.Google Scholar
Woodward, L. J., Anderson, P. J., Austin, N. C., Howard, K., & Inder, T. E. (2006). Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. New England Journal of Medicine, 355, 685–694. doi:10.1056/NEJMoa053792Google Scholar
Xu, H., Furman, M., Mineur, Y., Chen, H., King, S., Zenisek, D., … Crair, M. (2011). An instructive role for patterned spontaneous retinal activity in mouse visual map development. Neuron, 70, 1115–1127. doi:10.1016/j.neuron.2011.04.028Google Scholar