Foundations

Part I - Foundations

Published online by Cambridge University Press: 26 September 2020

Edited by

Jeffrey J. Lockman and

Catherine S. Tamis-LeMonda

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Jeffrey J. Lockman: Affiliation:
Tulane University, Louisiana
Catherine S. Tamis-LeMonda: Affiliation:
New York University

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Type: Chapter
Information: The Cambridge Handbook of Infant Development
Brain, Behavior, and Cultural Context
, pp. 1 - 154

DOI: https://doi.org/10.1017/9781108351959 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2020

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References

Adolph, K. E., & Berger, S. E. (2006). Motor development. Handbook of Child Psychology, 2, 161–213.Google Scholar

Akerman, C. J., Smyth, D., & Thompson, I. D. (2002). Visual experience before eye-opening and the development of the retinogeniculate pathway. Neuron, 36(5), 869–879.Google Scholar

Allendoerfer, K. L., & Shatz, C. J. (1994). The subplate, a transient neocortical structure: Its role in the development of connections between thalamus and cortex. Annual Review of Neuroscience, 17(1), 185–218.CrossRef Google Scholar PubMed

Als, H., Lawhon, G., Brown, E., Gibes, R., Duffy, F. H., McAnulty, G., & Blickman, J. G. (1986). Individualized behavioral and environmental care for the very low birth weight preterm infant at high risk for bronchopulmonary dysplasia: Neonatal intensive care unit and developmental outcome. Pediatrics, 78(6), 1123–1132.Google Scholar

Asada, M., MacDorman, K. F., Ishiguro, H., & Kuniyoshi, Y. (2001). Cognitive developmental robotics as a new paradigm for the design of humanoid robots. Robotics and Autonomous Systems, 37(2–3), 185–193.Google Scholar

Ball, G., Srinivasan, L., Aljabar, P., Counsell, S. J., Durighel, G., Hajnal, J. V., … Edwards, A. D. (2013). Development of cortical microstructure in the preterm human brain. Proceedings of the National Academy of Sciences, 110(23), 9541–9546.Google Scholar

Banerjee, A., Meredith, R. M., Rodríguez-Moreno, A., Mierau, S. B., Auberson, Y. P., & Paulsen, O. (2009). Double dissociation of spike timing-dependent potentiation and depression by subunit-preferring NMDA receptor antagonists in mouse barrel cortex. Cerebral Cortex, 19(12), 2959–2969.CrossRef Google Scholar PubMed

Barbu-Roth, M., Anderson, D. I., Desprès, A., Streeter, R. J., Cabrol, D., Trujillo, M., … Provasi, J. (2014). Air stepping in response to optic flows that move toward and away from the neonate. Developmental Psychobiology, 56(5), 1142–1149.Google Scholar

Bayatti, N., Moss, J. A., Sun, L., Ambrose, P., Ward, J. F., Lindsay, S., & Clowry, G. J. (2007). A molecular neuroanatomical study of the developing human neocortex from 8 to 17 postconceptional weeks revealing the early differentiation of the subplate and subventricular zone. Cerebral Cortex, 18(7), 1536–1548.Google Scholar

Beccaria, E., Martino, M., Briatore, E., Podestà, B., Pomero, G., Micciolo, R., … Calzolari, S. (2012). Poor repertoire general movements predict some aspects of development outcome at 2 years in very preterm infants. Early Human Development, 88(6), 393–396.Google Scholar

Ben-Ari, Y., Gaiarsa, J. -L., Tyzio, R., & Khazipov, R. (2007). GABA: A pioneer transmitter that excites immature neurons and generates primitive oscillations. Physiological Reviews, 87(4), 1215–1284.Google Scholar

Blaesse, P., Airaksinen, M. S., Rivera, C., & Kaila, K. (2009). Cation-chloride cotransporters and neuronal function. Neuron, 61(6), 820–838.Google Scholar

Blankenship, A. G., & Feller, M. B. (2010). Mechanisms underlying spontaneous patterned activity in developing neural circuits. Nature Reviews Neuroscience, 11(1), 18.Google Scholar

Bobet, J., & Stein, R. B. (1998). A simple model of force generation by skeletal muscle during dynamic isometric contractions. IEEE Transactions on Biomedical Engineering, 45(8), 1010–1016.CrossRef Google Scholar PubMed

Boivin, M. J., Kakooza, A. M., Warf, B. C., Davidson, L. L., & Grigorenko, E. L. (2015). Reducing neurodevelopmental disorders and disability through research and interventions. Nature, 527(7578), S155.Google Scholar

Bosco, G., & Poppele, R. (2001). Proprioception from a spinocerebellar perspective. Physiological Reviews, 81(2), 539–568.Google Scholar

Bradley, R. M., & Mistretta, C. M. (1975). Fetal sensory receptors. Physiological Reviews, 55(3), 352–382.Google Scholar

Bremner, A. J., Lewkowicz, D. J., & Spence, C. (2012). Multisensory development. Oxford: Oxford University Press.Google Scholar

Brooks, R. A. (1991). Intelligence without representation. Artificial intelligence, 47(1–3), 139–159.Google Scholar

Brumley, M. R., & Robinson, S. R. (2013). Sensory feedback alters spontaneous limb movements in newborn rats: Effects of unilateral forelimb weighting. Developmental Psychobiology, 55(4), 323–333.Google Scholar

Butterworth, G., & Hopkins, B. (1988). Hand–mouth coordination in the new-born baby. British Journal of Developmental Psychology, 6(4), 303–314.Google Scholar

Byrge, L., Sporns, O., & Smith, L. B. (2014). Developmental process emerges from extended brain–body–behavior networks. Trends in Cognitive Sciences, 18(8), 395–403.Google Scholar

Caligiore, D., Parisi, D., & Baldassarre, G. (2014). Integrating reinforcement learning, equilibrium points, and minimum variance to understand the development of reaching: A computational model. Psychological Review, 121(3), 389.Google Scholar

Cascio, C. J. (2010). Somatosensory processing in neurodevelopmental disorders. Journal of Neurodevelopmental Disorders, 2(2), 62.Google Scholar

Cheng-Yu, T. L., Poo, M. -M., & Dan, Y. (2009). Burst spiking of a single cortical neuron modifies global brain state. Science, 324(5927), 643–646.Google Scholar

Clancy, B., Darlington, R., & Finlay, B. (2001). Translating developmental time across mammalian species. Neuroscience, 105(1), 7–17.Google Scholar

Clifton, R. K., Morrongiello, B. A., Kulig, J. W., & Dowd, J. M. (1981). Newborns’ orientation toward sound: Possible implications for cortical development. Child Development, 52(3), 833–838.Google Scholar

Crisp, S. J., Evers, J. F., & Bate, M. (2011). Endogenous patterns of activity are required for the maturation of a motor network. Journal of Neuroscience, 31(29), 10445–10450.Google Scholar

Cuajunco, F. (1940). Development of the neuromuscular spindle in human fetuses. Contributions to Embryology, 28, 97–128.Google Scholar

de Vries, J. I., Visser, G. H., & Prechtl, H. F. (1982). The emergence of fetal behaviour. I: Qualitative aspects. Early Human Development, 7(4), 301–322.Google Scholar

DeCasper, A. J., Lecanuet, J. -P., Busnel, M. -C., Granier-Deferre, C., & Maugeais, R. (1994). Fetal reactions to recurrent maternal speech. Infant Behavior and Development, 17(2), 159–164.Google Scholar

Demiris, J., Rougeaux, S., Hayes, G., Berthouze, L., & Kuniyoshi, Y. (1997). Deferred imitation of human head movements by an active stereo vision head. Paper presented at 6th IEEE International Workshop on Robot and Human Communication, RO-MAN’97 SENDAI, Sendai, Japan.Google Scholar

The Developing Human Connectome Project. Retrieved from www.developingconnectome.org.Google Scholar

Dubois, J., Hertz-Pannier, L., Dehaene-Lambertz, G., Cointepas, Y., & Le Bihan, D. (2006). Assessment of the early organization and maturation of infants’ cerebral white matter fiber bundles: A feasibility study using quantitative diffusion tensor imaging and tractography. Neuroimage, 30(4), 1121–1132.Google Scholar

Eyre, J., Miller, S., Clowry, G., Conway, E., & Watts, C. (2000). Functional corticospinal projections are established prenatally in the human foetus permitting involvement in the development of spinal motor centres. Brain, 123(1), 51–64.Google Scholar

Fombonne, E. (2009). Epidemiology of pervasive developmental disorders. Pediatric Research, 65(6), 591.CrossRef Google Scholar PubMed

Fuchino, Y., Naoi, N., Shibata, M., Niwa, F., Kawai, M., Konishi, Y., … Myowa-Yamakoshi, M. (2013). Effects of preterm birth on intrinsic fluctuations in neonatal cerebral activity examined using optical imaging. PloS one, 8(6), e67432.Google Scholar

Gallagher, S., & Zahavi, D. (2007). The phenomenological mind: An introduction to philosophy of mind and cognitive science. London: Routledge.Google Scholar

Gaugler, T., Klei, L., Sanders, S. J., Bodea, C. A., Goldberg, A. P., Lee, A. B., … Reichert, J. (2014). Most genetic risk for autism resides with common variation. Nature Genetics, 46(8), 881.Google Scholar

Gerhard, D. (2013). Neuroscience. 5th edition. Yale Journal of Biology and Medicine, 86(1), 113–114.Google Scholar

Ghosh, A., Antonini, A., McConnell, S. K., & Shatz, C. J. (1990). Requirement for subplate neurons in the formation of thalamocortical connections. Nature, 347(6289), 179.Google Scholar

Gibson, J. (1979). The theory of affordances. In Gibson, J. (Ed.), The ecological approach to visual perception (pp. 127–143). Boston, MA: Houghton Mifflin.Google Scholar

Gima, H., Ohgi, S., Morita, S., Karasuno, H., Fujiwara, T., & Abe, K. (2011). A dynamical system analysis of the development of spontaneous lower extremity movements in newborn and young infants. Journal of Physiological Anthropology, 30(5), 179–186.Google Scholar

Girvan, M., & Newman, M. E. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences, 99(12), 7821–7826.Google Scholar

Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., … Toga, A. W. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences, 101(21), 8174–8179.CrossRef Google Scholar PubMed

Goldman, A., & de Vignemont, F. (2009). Is social cognition embodied? Trends in Cognitive Sciences, 13(4), 154–159.Google Scholar

Gonzalez-Islas, C., & Wenner, P. (2006). Spontaneous network activity in the embryonic spinal cord regulates AMPAergic and GABAergic synaptic strength. Neuron, 49(4), 563–575.CrossRef Google Scholar PubMed

Granmo, M., Petersson, P., & Schouenborg, J. (2008). Action-based body maps in the spinal cord emerge from a transitory floating organization. Journal of Neuroscience, 28(21), 5494–5503.Google Scholar

Grillner, S. (2006). Biological pattern generation: The cellular and computational logic of networks in motion. Neuron, 52(5), 751–766.Google Scholar

Grillner, S., & Jessell, T. M. (2009). Measured motion: Searching for simplicity in spinal locomotor networks. Current Opinion in Neurobiology, 19(6), 572–586.Google Scholar

Groen, S. E., de Blécourt, A. C., Postema, K., & Hadders-Algra, M. (2005). General movements in early infancy predict neuromotor development at 9 to 12 years of age. Developmental Medicine and Child Neurology, 47(11), 731–738.Google Scholar

Hadders-Algra, M. (2004). General movements: A window for early identification of children at high risk for developmental disorders. Journal of Pediatrics, 145(2), S12–S18.Google Scholar

Hadders-Algra, M. (2007). Putative neural substrate of normal and abnormal general movements. Neuroscience & Biobehavioral Reviews, 31(8), 1181–1190.Google Scholar

Hadders-Algra, M., Mavinkurve-Groothuis, A. M., Groen, S. E., Stremmelaar, E. F., Martijn, A., & Butcher, P. R. (2004). Quality of general movements and the development of minor neurological dysfunction at toddler and school age. Clinical Rehabilitation, 18(3), 287–299.Google Scholar

Haider, B., Duque, A., Hasenstaub, A. R., & McCormick, D. A. (2006). Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. Journal of Neuroscience, 26(17), 4535–4545.Google Scholar

Hakamada, S., Hayakawa, F., Kuno, K., & Tanaka, R. (1988). Development of the monosynaptic reflex pathway in the human spinal cord. Developmental Brain Research, 42(2), 239–246.Google Scholar

Hamburger, V., Wenger, E., & Oppenheim, R. (1966). Motility in the chick embryo in the absence of sensory input. Journal of Experimental Zoology, 162(2), 133–159.Google Scholar

Hanson, M. G., Milner, L. D., & Landmesser, L. T. (2008). Spontaneous rhythmic activity in early chick spinal cord influences distinct motor axon pathfinding decisions. Brain Research Reviews, 57(1), 77–85.Google Scholar

Hashimoto, T., Bazmi, H. H., Mirnics, K., Wu, Q., Sampson, A. R., & Lewis, D. A. (2008). Conserved regional patterns of GABA-related transcript expression in the neocortex of subjects with schizophrenia. American Journal of Psychiatry, 165(4), 479–489.Google Scholar

He, J., Maltenfort, M. G., Wang, Q., & Hamm, T. M. (2001). Learning from biological systems: Modeling neural control. IEEE Control Systems, 21(4), 55–69.Google Scholar

Hepper, P. G. (1996). Fetal memory: Does it exist? What does it do? Acta Paediatrica, 85, 16–20.Google Scholar

Hoffmann, M., Marques, H., Arieta, A., Sumioka, H., Lungarella, M., & Pfeifer, R. (2010). Body schema in robotics: A review. IEEE Transactions on Autonomous Mental Development, 2(4), 304–324.Google Scholar

Honey, C. J., Kötter, R., Breakspear, M., & Sporns, O. (2007). Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proceedings of the National Academy of Sciences, 104(24), 10240–10245.Google Scholar

Hooker, D. (1952). The prenatal origin of behavior. Lawrence: University of Kansas Press.Google Scholar

Hromádka, T., DeWeese, M. R., & Zador, A. M. (2008). Sparse representation of sounds in the unanesthetized auditory cortex. PLoS biology, 6(1), e16.Google Scholar

Huffman, K. J., & Krubitzer, L. (2001). Area 3a: Topographic organization and cortical connections in marmoset monkeys. Cerebral Cortex, 11(9), 849–867.Google Scholar

James, D. K. (2010). Fetal learning: A critical review. Infant and Child Development: An International Journal of Research and Practice, 19(1), 45–54.Google Scholar

James, D. K., Spencer, C., & Stepsis, B. (2002). Fetal learning: A prospective randomized controlled study. Ultrasound in Obstetrics & Gynecology, 20(5), 431–438.Google Scholar

Kaas, J. H. (1983). What, if anything, is SI? Organization of first somatosensory area of cortex. Physiological Reviews, 63(1), 206–231.CrossRef Google Scholar PubMed

Kalaska, J., Cohen, D., Prud’Homme, M., & Hyde, M. (1990). Parietal area 5 neuronal activity encodes movement kinematics, not movement dynamics. Experimental Brain Research, 80(2), 351–364.Google Scholar

Kanazawa, H., Kawai, M., Kinai, T., Iwanaga, K., Mima, T., & Heike, T. (2014). Cortical muscle control of spontaneous movements in human neonates. European Journal of Neuroscience, 40(3), 2548–2553.Google Scholar

Kanold, P. O., & Luhmann, H. J. (2010). The subplate and early cortical circuits. Annual Review of Neuroscience, 33, 23–48.Google Scholar

Kanold, P. O., & Shatz, C. J. (2006). Subplate neurons regulate maturation of cortical inhibition and outcome of ocular dominance plasticity. Neuron, 51(5), 627–638.Google Scholar

Khazipov, R., Sirota, A., Leinekugel, X., Holmes, G. L., Ben-Ari, Y., & Buzsáki, G. (2004). Early motor activity drives spindle bursts in the developing somatosensory cortex. Nature, 432(7018), 758.Google Scholar

Kinney, H. C., Brody, B. A., Kloman, A. S., & Gilles, F. H. (1988). Sequence of central nervous system myelination in human infancy: II. Patterns of myelination in autopsied infants. Journal of Neuropathology & Experimental Neurology, 47(3), 217–234.Google Scholar

Kisilevsky, B. S., Hains, S. M., Lee, K., Xie, X., Huang, H., Ye, H. H., … Wang, Z. (2003). Effects of experience on fetal voice recognition. Psychological Science, 14(3), 220–224.Google Scholar

Kostović, I., & Judaš, M. (2010). The development of the subplate and thalamocortical connections in the human foetal brain. Acta Paediatrica, 99(8), 1119–1127.Google Scholar

Koyanagi, T., Horimoto, N., Maeda, H., Kukita, J., Minami, T., Ueda, K., & Nakano, H. (1993). Abnormal behavioral patterns in the human fetus at term: Correlation with lesion sites in the central nervous system after birth. Journal of child neurology, 8(1), 19–26.Google Scholar

Kuniyoshi, Y. (1994). The science of imitation-towards physically and socially grounded intelligence. Paper presented at the Special Issue TR-94001, Real World Computing Project Joint Symposium, Tsukuba-shi, Ibaraki-ken.Google Scholar

Kuniyoshi, Y., & Berthouze, L. (1998). Neural learning of embodied interaction dynamics. Neural Networks, 11(7–8), 1259–1276.Google Scholar

Kuniyoshi, Y., Cheng, G., & Nagakubo, A. (2003). Etl-humanoid: A research vehicle for open-ended action imitation. Robotics Research, 6, 67–82.CrossRef Google Scholar

Kuniyoshi, Y., Yorozu, Y., Inaba, M., & Inoue, H. (2003). From visuo-motor self-learning to early imitation: A neural architecture for humanoid learning. Paper presented at the 2003 IEEE International Conference on Robotics and Automation (Cat. No. 03CH37422), Taipei, Japan.Google Scholar

Kurjak, A., Azumendi, G., Veček, N., Kupešic, S., Solak, M., Varga, D., & Chervenak, F. (2003). Fetal hand movements and facial expression in normal pregnancy studied by four-dimensional sonography. Journal of Perinatal Medicine, 31(6), 496–508.Google Scholar

Larroque, B., Ancel, P. -Y., Marret, S., Marchand, L., André, M., Arnaud, C., … Thiriez, G. (2008). Neurodevelopmental disabilities and special care of 5-year-old children born before 33 weeks of gestation (the EPIPAGE study): A longitudinal cohort study. Lancet, 371(9615), 813–820.Google Scholar

Larsen, R. S., Rao, D., Manis, P. B., & Philpot, B. D. (2010). STDP in the developing sensory neocortex. Frontiers in Synaptic Neuroscience, 2, 9.Google Scholar

Lawn, J. E., Mwansa-Kambafwile, J., Horta, B. L., Barros, F. C., & Cousens, S. (2010). “Kangaroo mother care” to prevent neonatal deaths due to preterm birth complications. International Journal of Epidemiology, 39(suppl. 1), i144–i154.Google Scholar

Lüchinger, A. B., Hadders-Algra, M., van Kan, C. M., & de Vries, J. I. (2008). Fetal onset of general movements. Pediatric Research, 63(2), 191.Google Scholar

Ludington-Hoe, S. M. (2013). Kangaroo care as a neonatal therapy. Newborn and Infant Nursing Reviews, 13(2), 73–75.Google Scholar

Lungarella, M., Metta, G., Pfeifer, R., & Sandini, G. (2003). Developmental robotics: A survey. Connection Science, 15(4), 151–190.Google Scholar

McConnell, S. K., Ghosh, A., & Shatz, C. J. (1989). Subplate neurons pioneer the first axon pathway from the cerebral cortex. Science, 245(4921), 978–982.Google Scholar

McQuillen, P. S., Sheldon, R. A., Shatz, C. J., & Ferriero, D. M. (2003). Selective vulnerability of subplate neurons after early neonatal hypoxia-ischemia. Journal of Neuroscience, 23(8), 3308–3315.Google Scholar

Meliza, C. D., & Dan, Y. (2006). Receptive-field modification in rat visual cortex induced by paired visual stimulation and single-cell spiking. Neuron, 49(2), 183–189.Google Scholar

Meltzoff, A. N., & Moore, M. K. (1977). Imitation of facial and manual gestures by human neonates. Science, 198(4312), 75–78.Google Scholar

Merleau-Ponty, M., & Smith, C. (1996). Phenomenology of perception. Delhi: Motilal Banarsidass Publishers.Google Scholar

Milh, M., Kaminska, A., Huon, C., Lapillonne, A., Ben-Ari, Y., & Khazipov, R. (2006). Rapid cortical oscillations and early motor activity in premature human neonate. Cerebral Cortex, 17(7), 1582–1594.Google Scholar

Miller, J. A., Ding, S. -L., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., … Aiona, K. (2014). Transcriptional landscape of the prenatal human brain. Nature, 508(7495), 199.Google Scholar

Mullen, K. M., Vohr, B. R., Katz, K. H., Schneider, K. C., Lacadie, C., Hampson, M., … Ment, L. R. (2011). Preterm birth results in alterations in neural connectivity at age 16 years. Neuroimage, 54(4), 2563–2570.Google Scholar

Myowa-Yamakoshi, M., & Takeshita, H. (2006). Do human fetuses anticipate self-oriented actions? A study by four-dimensional (4D) ultrasonography. Infancy, 10(3), 289–301.Google Scholar

Nagai, Y., Hosoda, K., Morita, A., & Asada, M. (2003). A constructive model for the development of joint attention. Connection Science, 15(4), 211–229.Google Scholar

Narayanan, D. Z., & Ghazanfar, A. A. (2014). Developmental neuroscience: How twitches make sense. Current Biology, 24(19), R971–R972.Google Scholar

Nebel, M. B., Joel, S. E., Muschelli, J., Barber, A. D., Caffo, B. S., Pekar, J. J., & Mostofsky, S. H. (2014). Disruption of functional organization within the primary motor cortex in children with autism. Human Brain Mapping, 35(2), 567–580.Google Scholar

Newman, M. E. (2004). Fast algorithm for detecting community structure in networks. Physical review E, 69(6), 066133.Google Scholar

Ohgi, S., Morita, S., Loo, K. K., & Mizuike, C. (2007). A dynamical systems analysis of spontaneous movements in newborn infants. Journal of Motor Behavior, 39(3), 203–214.Google Scholar

Ohlsson, A., & Jacobs, S. E. (2013). NIDCAP: A systematic review and meta-analyses of randomized controlled trials. Pediatrics, 131(3), e881–e893.Google Scholar

Okado, N. (1984). Ontogeny of the central nervous system: Neurogenesis, fibre connection, synaptogenesis and myelination in the spinal cord. In Prechtl, H. F. R. (Ed.), Continuity of neural functions from prenatal to postnatal life (pp. 31–45). London: Spastics International Medical Publications.Google Scholar

Partridge, E. A., Davey, M. G., Hornick, M. A., McGovern, P. E., Mejaddam, A. Y., Vrecenak, J. D., … Weiland, T. R. (2017). An extra-uterine system to physiologically support the extreme premature lamb. Nature Communications, 8, 15112.Google Scholar

Penfield, W., & Boldrey, E. (1937). Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain, 60(4), 389–443.Google Scholar

Petersson, P., Granmo, M., & Schouenborg, J. (2004). Properties of an adult spinal sensorimotor circuit shaped through early postnatal experience. Journal of Neurophysiology, 92, 280–288.Google Scholar

Petersson, P., Waldenström, A., Fåhraeus, C., & Schouenborg, J. (2003). Spontaneous muscle twitches during sleep guide spinal self-organization. Nature, 424(6944), 72.CrossRef Google Scholar PubMed

Pfeifer, R., & Scheier, C. (2001). Understanding intelligence. Cambridge, MA: MIT Press.Google Scholar

Piaget, J. (1952). The origins of intelligence in children. Madison, CT: International Universities Press.Google Scholar

Pitcher, J. B., Schneider, L. A., Burns, N. R., Drysdale, J. L., Higgins, R. D., Ridding, M. C., … Robinson, J. S. (2012). Reduced corticomotor excitability and motor skills development in children born preterm. Journal of Physiology, 590(22), 5827–5844.Google Scholar

Pitti, A., Mori, H., Yamada, Y., & Kuniyoshi, Y. (2010). A model of spatial development from parieto-hippocampal learning of body-place associations. Paper presented at the 10th International Conference on Epigenetic Robotics, Sweden.Google Scholar

Prechtl, H. F. R. (1984). Continuity and change in early neural development. In Prechtl, H. F. R. (Ed.), Continuity of neural functions from prenatal to postnatal life (pp. 1–15). London: Spastics International Medical Publications.Google Scholar

Prechtl, H. F. R. (1990). Qualitative changes of spontaneous movements in fetus and preterm infant are a marker of neurological dysfunction. Early Human Development, 23(3), 151–158.Google Scholar

Prechtl, H. F. R. (2001). General movement assessment as a method of developmental neurology: New paradigms and their consequences. Developmental Medicine & Child Neurology, 43(12), 836–842.Google Scholar

Purves, D. (2012). Neuroscience: Oxford: Oxford University Press.Google Scholar

Rausell, E., Bickford, L., Manger, P. R., Woods, T. M., & Jones, E. G. (1998). Extensive divergence and convergence in the thalamocortical projection to monkey somatosensory cortex. Journal of Neuroscience, 18(11), 4216–4232.Google Scholar

Reid, V. M., Dunn, K., Young, R. J., Amu, J., Donovan, T., & Reissland, N. (2017). The human fetus preferentially engages with face-like visual stimuli. Current Biology, 27(12), 1825–1828. e1823.Google Scholar

Reissland, N., Francis, B., Aydin, E., Mason, J., & Schaal, B. (2014). The development of anticipation in the fetus: A longitudinal account of human fetal mouth movements in reaction to and anticipation of touch. Developmental Psychobiology, 56(5), 955–963.Google Scholar

Robinson, S. R., & Kleven, G. A. (2005). Learning to move before birth. In Hopkins, B. & Johnson, S. (Eds.), Prenatal development of postnatal functions (Advances in Infancy Research series) (Vol. 2, pp. 131–175). Westport, CT: Praeger.Google Scholar

Robinson, S. R., Kleven, G. A., & Brumley, M. R. (2008). Prenatal development of interlimb motor learning in the rat fetus. Infancy, 13(3), 204–228.Google Scholar

Rochat, P. (2009). The infant’s world. Cambridge, MA: Harvard University Press.Google Scholar

Rochat, P. (2011). The self as phenotype. Consciousness and Cognition, 20(1), 109–119.Google Scholar

Rochat, P., & Hespos, S. J. (1997). Differential rooting response by neonates: Evidence for an early sense of self. Infant and Child Development, 6(3–4), 105–112.Google Scholar

Rubenstein, J. L. (2010). Three hypotheses for developmental defects that may underlie some forms of autism spectrum disorder. Current Opinion in Neurology, 23(2), 118–123.Google Scholar

Rubenstein, J. L. & Merzenich, M. M. (2003). Model of autism: Increased ratio of excitation/inhibition in key neural systems. Genes, Brain and Behavior, 2(5), 255–267.Google Scholar

Sarnat, H. B. (2003). Functions of the corticospinal and corticobulbar tracts in the human newborn. Journal of Pediatric Neurology, 1(1), 3–8.Google Scholar

Sasaki, R., Yamada, Y., Tsukahara, Y., & Kuniyoshi, Y. (2013). Tactile stimuli from amniotic fluid guides the development of somatosensory cortex with hierarchical structure using human fetus simulation. Paper presented at the 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL), Osaka, Japan.Google Scholar

Schaal, B., Marlier, L., & Soussignan, R. (1998). Olfactory function in the human fetus: Evidence from selective neonatal responsiveness to the odor of amniotic fluid. Behavioral Neuroscience, 112(6), 1438.Google Scholar

Shirado, H., Konyo, M., & Maeno, T. (2007). Modeling of tactile texture recognition mechanism. Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 73(9), 2514–2522.Google Scholar

Sizun, J., & Westrup, B. (2004). Early developmental care for preterm neonates: A call for more research. Archives of Disease in Childhood: Fetal and Neonatal Edition, 89(5), F384–F388.Google Scholar

Smyser, C. D., Inder, T. E., Shimony, J. S., Hill, J. E., Degnan, A. J., Snyder, A. Z., & Neil, J. J. (2010). Longitudinal analysis of neural network development in preterm infants. Cerebral Cortex, 20(12), 2852–2862.Google Scholar

Softky, W. R., & Koch, C. (1993). The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. Journal of Neuroscience, 13(1), 334–350.Google Scholar

Spittle, A., Orton, J., Doyle, L. W., & Boyd, R. (2007). Early developmental intervention programs post hospital discharge to prevent motor and cognitive impairments in preterm infants. Cochrane Database of Systematic Reviews, 2, CD005495. doi: 005491-CD005495.005471.Google Scholar

Spitzer, N. C. (2006). Electrical activity in early neuronal development. Nature, 444(7120), 707.Google Scholar

Sporns, O. (2010). Networks of the brain. Cambridge, MA: MIT Press.Google Scholar

Sretavan, D. W., Shatz, C. J., & Stryker, M. P. (1988). Modification of retinal ganglion cell axon morphology by prenatal infusion of tetrodotoxin. Nature, 336(6198), 468.Google Scholar

Stephen, D. G., Hsu, W. -H., Young, D., Saltzman, E. L., Holt, K. G., Newman, D. J., … Goldfield, E. C. (2012). Multifractal fluctuations in joint angles during infant spontaneous kicking reveal multiplicativity-driven coordination. Chaos, Solitons & Fractals, 45(9–10), 1201–1219.Google Scholar

Suster, M. L., & Bate, M. (2002). Embryonic assembly of a central pattern generator without sensory input. Nature, 416(6877), 174.Google Scholar

Symington, A. J., & Pinelli, J. (2006). Developmental care for promoting development and preventing morbidity in preterm infants. Cochrane Database Systematic Review, 4, CD001814.Google Scholar

Takahashi, E., Folkerth, R. D., Galaburda, A. M., & Grant, P. E. (2011). Emerging cerebral connectivity in the human fetal brain: An MR tractography study. Cerebral Cortex, 22(2), 455–464.Google Scholar

Takahashi, E., Hayashi, E., Schmahmann, J. D., & Grant, P. E. (2014). Development of cerebellar connectivity in human fetal brains revealed by high angular resolution diffusion tractography. Neuroimage, 96, 326–333.Google Scholar

Tau, G. Z., & Peterson, B. S. (2010). Normal development of brain circuits. Neuropsychopharmacology, 35(1), 147.Google Scholar

Teramae, J. -N., Tsubo, Y., & Fukai, T. (2012). Optimal spike-based communication in excitable networks with strong-sparse and weak-dense links. Scientific Reports, 2, 485.Google Scholar

Thelen, E., & Smith, L. B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT Press.Google Scholar

Toga, A. W., Thompson, P. M., & Sowell, E. R. (2006). Mapping brain maturation. TRENDS in Neurosciences, 29(3), 148–159.Google Scholar

Tomasello, M. (2009). The cultural origins of human cognition: Cambridge, MA: Harvard University Press.Google Scholar

Tripodi, M., Stepien, A. E., & Arber, S. (2011). Motor antagonism exposed by spatial segregation and timing of neurogenesis. Nature, 479(7371), 61.Google Scholar

Vaal, J., van Soest, A., Hopkins, B., Sie, L., & van der Knaap, M. (2000). Development of spontaneous leg movements in infants with and without periventricular leukomalacia. Experimental Brain Research, 135(1), 94–105.Google Scholar

van den Heuvel, M. P., Kersbergen, K. J., de Reus, M. A., Keunen, K., Kahn, R. S., Groenendaal, F., … Benders, M. J. (2014). The neonatal connectome during preterm brain development. Cerebral Cortex, 25(9), 3000–3013.Google Scholar

van der Meer, A. L. (1997). Keeping the arm in the limelight: Advanced visual control of arm movements in neonates. European Journal of Paediatric Neurology, 1(4), 103–108.Google Scholar

Varela, F. J., Rosch, E., & Thompson, E. (1992). The embodied mind: Cognitive science and human experience. Cambridge, MA: MIT Press.Google Scholar

Vauclair, J. (2012). Developpment du jeune enfant, Motricite, Perception, Cognition. Paris: Belin.Google Scholar

von Hofsten, C. (1982). Eye–hand coordination in the newborn. Developmental Psychology, 18(3), 450.Google Scholar

von Hofsten, C. (2007). Action in development. Developmental Science, 10(1), 54–60.Google Scholar

Waldmeier, S., Grunt, S., Delgado-Eckert, E., Latzin, P., Steinlin, M., Fuhrer, K., & Frey, U. (2013). Correlation properties of spontaneous motor activity in healthy infants: A new computer-assisted method to evaluate neurological maturation. Experimental Brain Research, 227(4), 433–446.Google Scholar

Wallin, L., & Eriksson, M. (2009). Newborn individual development care and assessment program (NIDCAP): A systematic review of the literature. Worldviews on Evidence-Based Nursing, 6(2), 54–69.Google Scholar

Warp, E., Agarwal, G., Wyart, C., Friedmann, D., Oldfield, C. S., Conner, A., … Isacoff, E. Y. (2012). Emergence of patterned activity in the developing zebrafish spinal cord. Current Biology, 22(2), 93–102.Google Scholar

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of “small-world” networks. Nature, 393(6684), 440.Google Scholar

Weng, J., McClelland, J., Pentland, A., Sporns, O., Stockman, I., Sur, M., & Thelen, E. (2001). Autonomous mental development by robots and animals. Science, 291(5504), 599–600.Google Scholar

White, L. E., Coppola, D. M., & Fitzpatrick, D. (2001). The contribution of sensory experience to the maturation of orientation selectivity in ferret visual cortex. Nature, 411(6841), 1049.Google Scholar

Yamada, Y., Fujii, K., & Kuniyoshi, Y. (2013). Impacts of environment, nervous system and movements of preterms on body map development: Fetus simulation with spiking neural network. Paper presented at the Development and Learning and Epigenetic Robotics (ICDL), 2013 IEEE Third Joint International Conference, Osaka, Japan.Google Scholar

Yamada, Y., Kanazawa, H., Iwasaki, S., Tsukahara, Y., Iwata, O., Yamada, S., & Kuniyoshi, Y. (2016). An embodied brain model of the human foetus. Scientific Reports, 6, 27893.Google Scholar

Yamada, Y., & Kuniyoshi, Y. (2012a). Embodiment guides motor and spinal circuit development in vertebrate embryo and fetus. Paper presented at the Development and Learning and Epigenetic Robotics (ICDL), 2012 IEEE International Conference, San Diego, California.Google Scholar

Yamada, Y., & Kuniyoshi, Y. (2012b). Emergent spontaneous movements based on embodiment: Toward a general principle for early development. Paper presented at the Post-Graduate Conference on Robotics and Development of Cognition, Lausanne, Switzerland.Google Scholar

Yvert, B., Branchereau, P., & Meyrand, P. (2004). Multiple spontaneous rhythmic activity patterns generated by the embryonic mouse spinal cord occur within a specific developmental time window. Journal of Neurophysiology, 91(5), 2101–2109.Google Scholar

Zoia, S., Blason, L., D’Ottavio, G., Bulgheroni, M., Pezzetta, E., Scabar, A., & Castiello, U. (2007). Evidence of early development of action planning in the human foetus: a kinematic study. Experimental Brain Research, 176(2), 217–226.Google Scholar

References

Adair, L. S., Fall, C. H. D., Osmond, C., Stein, A. D., Martorell, R., Ramirez-Zea, M., … COHORTS Group (2013). Associations of linear growth and relative weight gain during early life with adult health and human capital in countries of low and middle income: Findings from five birth cohort studies. Lancet, 382(9891), 525–534.Google Scholar

Adolph, K. E., & Franchak, J. M. (2017). The development of motor behavior. Wiley Interdisciplinary Reviews. Cognitive Science, 8 (1–2).Google Scholar

Adolph, K. E., & Robinson, S. R. (2015). Motor development. In Liben, L. S. & Muller, U. (Eds.), Handbook of child psychology and developmental science (7th ed., Vol. 2: Cognitive processes pp. 114–157). New York, NY: Wiley.Google Scholar

Akaboshi, I., Kitano, A., Kan, H., Haraguchi, Y., & Mizumoto, Y. (2012). Chest circumference in infancy predicts obesity in 3-year-old children. Asia Pacific Journal of Clinical Nutrition, 21(4), 495–501.Google Scholar

American Academy of Pediatrics (2014). Study on helmet therapy suffers from several weaknesses. AAP News, 35(11), 5–5.Google Scholar

American Academy of Pediatrics (2016). Systematic review and evidence-based guidelines for the management of patients with positional plagiocephaly. Pediatrics, 138(5), e20162802.Google Scholar

Amiel-Tison, C., Gosselin, J., & Infante-Rivard, C. (2002). Head growth and cranial assessment at neurological examination in infancy. Developmental Medicine and Child Neurology, 44(9), 643–648.Google Scholar

Arner, P. (2018). Fat tissue growth and development in humans. Nestle Nutrition Institute Workshop Series, 89, 37–45.Google Scholar

Avan, B., Richter, L. M., Ramchandani, P. G., Norris, S. A., & Stein, A. (2010). Maternal postnatal depression and children’s growth and behaviour during the early years of life: exploring the interaction between physical and mental health. Archives of Disease in Childhood, 95(9), 690–695.Google Scholar

Barker, D. J. P. (1995). Fetal origins of coronary heart disease. British Medical Journal, 311(6998), 171–174.Google Scholar

Bartholomeusz, H. H., Courchesne, E., & Karns, C. M. (2002). Relationship between head circumference and brain volume in healthy normal toddlers, children, and adults. Neuropediatrics, 33(5), 239–241.Google Scholar

Bastir, M., García Martínez, D., Recheis, W., Barash, A., Coquerelle, M., Rios, L., … O’Higgins, P. (2013). Differential growth and development of the upper and lower human thorax. PLoS ONE, 8(9), e75128.Google Scholar

Bell, K. A., Wagner, C. L., Perng, W., Feldman, H. A., Shypailo, R. J., & Belfort, M. B. (2018). Validity of body mass index as a measure of adiposity in infancy. Journal of Pediatrics, 196, 168–174.Google Scholar

Bhardwaj, R. D., Curtis, M. A., Spalding, K. L., Buchholz, B. A., Fink, D., Björk-Eriksson, T., … Frisén, J. (2006). Neocortical neurogenesis in humans is restricted to development. Proceedings of the National Academy of Sciences, 103(33), 12564–12568.Google Scholar

Braude, P., Bolton, V., & Moore, S. (1988). Human gene expression first occurs between the four- and eight-cell stages of preimplantation development. Nature, 332(6163), 459–461.Google Scholar

Bray, P. F., Shields, W. D., Wolcott, G. J., & Madsen, J. A. (1969). Occipitofrontal head circumference: An accurate measure of intracranial volume. Journal of Pediatrics, 75(2), 303–305.Google Scholar

Brei, C., Much, D., Heimberg, E., Schulte, V., Brunner, S., Stecher, L., … Hauner, H. (2015). Sonographic assessment of abdominal fat distribution during the first year of infancy. Pediatric Research, 78(3), 342–350.Google Scholar

Breij, L. M., Abrahamse-Berkeveld, M., Acton, D., de Lucia Rolfe, E., Ong, K. K., & Hokken-Koelega, A. C. S. (2017). Impact of early infant growth, duration of breastfeeding and maternal factors on total body fat mass and visceral fat at 3 and 6 months of age. Annals of Nutrition & Metabolism, 71(3–4), 203–210.Google Scholar

Breij, L. M., Kerkhof, G. F., de Lucia Rolfe, E., Ong, K. K., Abrahamse-Berkeveld, M., Acton, D., … Hokken-Koelega, A. C. S. (2017). Longitudinal fat mass and visceral fat during the first 6months after birth in healthy infants: Support for a critical window for adiposity in early life. Pediatric Obesity, 12(4), 286–294.Google Scholar

Buschang, P. H. (1982). Differential long bone growth of children between two months and eleven years of age. American Journal of Physical Anthropology, 58(3), 291–295.Google Scholar

Butte, N. F., Hopkinson, J. M., Wong, W. W., Smith, E. O., & Ellis, K. J. (2000). Body composition during the first 2 years of life: An updated reference. Pediatric Research, 47(5), 578–585.Google Scholar

Cameron, N. (1984). The measurement of human growth. London: Routledge.Google Scholar

Cameron, N., Preece, M. A., & Cole, T. J. (2005). Catch-up growth or regression to the mean? Recovery from stunting revisited. American Journal of Human Biology, 17(4), 412–417.Google Scholar

Chen, H., Wang, J., Uddin, L. Q., Wang, X., Gui, X., Lu, F., … Wu, L. (2018). Aberrant functional connectivity of neural circuits associated with social and sensorimotor deficits in young children with autism spectrum disorder. Autism Research, 11(12), 1643–1652.Google Scholar

Chen, L., Wang, D., Wu, Z., Ma, L., & Daley, G. Q. (2010). Molecular basis of the first cell fate determination in mouse embryogenesis. Cell Research, 20(9), 982–993.Google Scholar

Chester, V. L., & Jensen, R. K. (2005). Changes in infant segment inertias during the first three months of independent walking. Dynamic Medicine, 4(1), 9.Google Scholar

Collett, B. R., Starr, J. R., Kartin, D., Heike, C. L., Berg, J., Cunningham, M. L., & Speltz, M. L. (2011). Development in toddlers with and without deformational plagiocephaly. Archives of Pediatrics & Adolescent Medicine, 165(7), 653–658.Google Scholar

Conkle, J., Suchdev, P. S., Alexander, E., Flores-Ayala, R., Ramakrishnan, U., & Martorell, R. (2018). Accuracy and reliability of a low-cost, handheld 3D imaging system for child anthropometry. PloS One, 13(10), e0205320.Google Scholar

Courchesne, E., Karns, C. M., Davis, H. R., Ziccardi, R., Carper, R. A., Tigue, Z. D., … Courchesne, R. Y. (2001). Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study. Neurology, 57(2), 245–254.Google Scholar

Courchesne, E., Pramparo, T., Gazestani, V. H., Lombardo, M. V., Pierce, K., & Lewis, N. E. (2018). The ASD living biology: From cell proliferation to clinical phenotype. Molecular Psychiatry, 24(1), 88–107.Google Scholar

Day, N. L., Richardson, G., Robles, N., Sambamoorthi, U., Taylor, P., Scher, M., … Cornelius, M. 1990). Effect of prenatal alcohol exposure on growth and morphology of offspring at 8 months of age. Pediatrics, 85(5), 748–752.Google Scholar

Davis, T. A., & Fiorotto, M. L. (2009). Regulation of muscle growth in neonates. Current Opinion in Clinical Nutrition and Metabolic Care, 12(1), 78–85.Google Scholar

de Araújo, T. V. B., Rodrigues, L. C., de Alencar Ximenes, R., de Barros Miranda-Filho, D., Ramos Montarroyos, U., Lopes de Melo, A. P., … Turchi Martelli, C. M. (2016). Association between Zika virus infection and microcephaly in Brazil, January to May, 2016: Preliminary report of a case-control study. Lancet: Infectious Diseases, 16(12), 1356–1363.Google Scholar

de Brito, M. L., Nunes, M., Bernardi, J. R., Bosa, V. L., Goldani, M. Z., & da Silva, C. H. (2017). Somatic growth in the first six months of life of infants exposed to maternal smoking in pregnancy. BMC Pediatrics, 17(1), 67.Google Scholar

de Cunto, A., Paviotti, G., Ronfani, L., Travan, L., Bua, J., Cont, G., & Demarini, S. (2014). Can body mass index accurately predict adiposity in newborns? Archives of Disease in Childhood: Fetal and Neonatal Edition, 99(3), F238–239.Google Scholar

de Onis, M., de, Onyango, A. W., Borghi, E., Garza, C., & Yang, H. (2006). Child growth standards and the National Center for Health Statistics/WHO international growth reference: Implications for child health programmes. Public Health Nutrition, 9(7), 942–947.Google Scholar

Demerath, E. W., Choh, A. C., Czerwinski, S. A., Lee, M., Sun, S. S., Chumlea, W. C., … Towne, B. (2007). Genetic and environmental influences on infant weight and weight changes: The Fels Longitudinal Study. American Journal of Human Biology, 19, 692–702.Google Scholar

Demerath, E. W., & Fields, D. A. (2014). Body composition assessment in the infant. American Journal of Human Biology, 26(3), 291–304.Google Scholar

Dingwall, E. J. (1931). Artificial cranial deformation: A contribution to the study of ethnic mutilations. London: J. Bale & Danielsson.Google Scholar

Dobrova-Krol, N. A., van IJzendoorn, M. H., Bakermans-Kranenburg, M. J., Cyr, C., & Juffer, F. (2008). Physical growth delays and stress dysregulation in stunted and non-stunted Ukrainian institution-reared children. Infant Behavior & Development, 31(3), 539–553.Google Scholar

Dupont, C., Castellanos-Ryan, N., Séguin, J. R., Muckle, G., Simard, M. -N., Shapiro, G. D., … Lippé, S. (2018). The predictive value of head circumference growth during the first year of life on early child traits. Scientific Reports, 8(1), 9828.Google Scholar

Eveleth, P. B., & Tanner, J. M. (1990). Worldwide variation in human growth. Cambridge, UK: Cambridge University Press.Google Scholar

Fabiansen, C., Yaméogo, C. W., Devi, S., Friis, H., Kurpad, A., & Wells, J. C. (2017). Deuterium dilution technique for body composition assessment: Resolving methodological issues in children with moderate acute malnutrition. Isotopes in Environmental and Health Studies, 53(4), 344–355.Google Scholar

Fields, D. A., Demerath, E. W., Pietrobelli, A., & Chandler-Laney, P. C. (2012). Body composition at 6 months of life: Comparison of air displacement plethysmography and dual-energy X-ray absorptiometry. Obesity, 20(11), 2302–2306.Google Scholar

Fiorotto, M. L., & Davis, T. A. (2018). Critical windows for the programming effects of early-life nutrition on skeletal muscle mass. Nestle Nutrition Institute Workshop Series, 89, 25–35.Google Scholar

Fleming, T. P., Kwong, W. Y., Porter, R., Ursell, E., Fesenko, I., Wilkins, A., … Eckert, J. J. (2004). The embryo and its future. Biology of Reproduction, 71(4), 1046–1054.Google Scholar

Fleming, T. P., Watkins, A. J., Velazquez, M. A., Mathers, J. C., Prentice, A. M., Stephenson, J., … Godfrey, K. M. (2018). Origins of lifetime health around the time of conception: Causes and consequences. Lancet, 391(10132), 1842–1852.Google Scholar

Goto, E. (2011). Meta-analysis: Identification of low birthweight by other anthropometric measurements at birth in developing countries. Journal of Epidemiology, 21(5), 354–362.Google Scholar

Hadush, M. Y., Berhe, A. H., & Medhanyie, A. A. (2017). Foot length, chest and head circumference measurements in detection of low birth weight neonates in Mekelle, Ethiopia: A hospital based cross sectional study. BMC Pediatrics, 17(1), 111.Google Scholar

Hamill, P. V., Drizd, T. A., Johnson, C. L., Reed, R. B., & Roche, A. F. (1977). NCHS growth curves for children birth–18 years: United States. Vital and Health Statistics Series 11: Data from the National Health Survey, 165(i–iv), 1–74.Google Scholar

Hazlett, H. C., Gu, H., Munsell, B. C., Kim, S. H., Styner, M., Wolff, J. J., … Piven, J. (2017). Early brain development in infants at high risk for autism spectrum disorder. Nature, 542(7641), 348–351.Google Scholar

Helgeland, O., Vaudel, M., Juliusson, P. B., Holmen, O. L., Juodakis, J., Bacelis, J., … Njølstad, R. (2018). Genome-wide association study reveals a dynamic role of common genetic variation in infant and early childhood growth. bioRxiv, November 25. http://dx.doi.org/0.110/478255.Google Scholar

Himes, J. H. (2006). Long-term longitudinal studies and implications for the development of an international growth reference for children and adolescents. Food and Nutrition Bulletin, 27(Suppl. 4), S199–211.Google Scholar

Holzhauer, S., Zwijsen, R. M. L., Jaddoe, V. W. V., Boehm, G., Moll, H. A., Mulder, P. G., … Witteman, J. C. M. (2009). Sonographic assessment of abdominal fat distribution in infancy. European Journal of Epidemiology, 24(9), 521–529.Google Scholar

Idriz, S., Patel, J. H., Renani, S. A., Allan, R. A., & Vlahos, I. (2015). CT of normal developmental and variant anatomy of the pediatric skull: Distinguishing trauma from normality. Radiographics, 35(5), 1585–1601.Google Scholar

Illingworth, R. S., & Lutz, W. (1965). Head circumference of infants related to body weight. Archives of Disease in Childhood, 40(214), 672–676.Google Scholar

Janssen, P. A., Thiessen, P., Klein, M. C., Whitfield, M. F., Macnab, Y. C., & Cullis-Kuhl, S. C. (2007). Standards for the measurement of birth weight, length and head circumference at term in neonates of European, Chinese and South Asian ancestry. Open Medicine, 1(2), e74–288.Google Scholar

Jensen, R. K. (1981). The effect of a 12-month growth period on the body moments of inertia of children. Medicine and Science in Sports and Exercise, 13(4), 238–242.Google Scholar

Johnson, L., Llewellyn, C. H., van Jaarsveld, C. H. M., Cole, T. J., & Wardle, J. (2011). Genetic and environmental influences on infant growth: Prospective analysis of the Gemini twin birth cohort. PloS One, 6(5), e19918.Google Scholar

Johnson, T. S., Engstrom, J. L., & Gelhar, D. K. (1997). Intra- and interexaminer reliability of anthropometric measurements of term infants. Journal of Pediatric Gastroenterology and Nutrition, 24(5), 497–505.Google Scholar

Jukic, A. M., Baird, D. D., Weinberg, C. R., McConnaughey, D. R., & Wilcox, A. J. (2013). Length of human pregnancy and contributors to its natural variation. Human Reproduction, 28(10), 2848–2855.Google Scholar

Kabir, N., & Forsum, E. (1993). Estimation of total body fat and subcutaneous adipose tissue in full-term infants less than 3 months old. Pediatric Research, 34(4), 448–454.Google Scholar

Karasik, L. B., Tamis-LeMonda, C. S., Ossmy, O., & Adolph, K. E. (2018). The ties that bind: Cradling in Tajikistan. PLOS ONE, 13(10), e0204428.Google Scholar

Karsenty, G. (2017). Update on the biology of osteocalcin. Endocrine Practice, 23(10), 1270–1274.Google Scholar

Kelly, K. M., Joganic, E. F., Beals, S. P., Riggs, J. A., McGuire, M. K., & Littlefield, T. R. (2018). Helmet treatment of infants with deformational brachycephaly. Global Pediatric Health, 5. https://doi.org/10.1177/2333794X18805618.Google Scholar

Kleijkers, S. H. M., van Montfoort, A. P. A., Smits, L. J. M., Viechtbauer, W., Roseboom, T. J., Nelissen, E. C., … Dumoulin, J. C. (2014). IVF culture medium affects post-natal weight in humans during the first 2 years of life. Human Reproduction, 29(4), 661–669.Google Scholar

Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., … Gilmore, J. H. (2008). A structural MRI study of human brain development from birth to 2 years. Journal of Neuroscience, 28(47), 12176–12182.CrossRef Google Scholar PubMed

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(10), 2721–2731.Google Scholar

Knittle, J. L., Timmers, K., Ginsberg-Fellner, F., Brown, R. E., & Katz, D. P. (1979). The growth of adipose tissue in children and adolescents: Cross-sectional and longitudinal studies of adipose cell number and size. Journal of Clinical Investigation, 63(2), 239–246.Google Scholar

Kuczmarski, R. J., Ogden, C. L., Guo, S. S., Grummer-Strawn, L. M., Flegal, K. M., Mei, Z., … Johnson, C. L. (2002). 2000 CDC growth charts for the United States: methods and development. Vital and Health Statistics Series 11: Data from the National Health Survey, 246, 1–190.Google Scholar

La Berge, A. F. (1991). Mothers and infants, nurses and nursing: Alfred Donné and the medicalization of child care in nineteenth-century France. Journal of the History of Medicine and Allied Sciences, 46(1), 20–43.Google Scholar

Lam, S., Luerssen, T. G., Hadley, C., Daniels, B., Strickland, B. A., Brookshire, J., & Pan, I. W. (2017). The health belief model and factors associated with adherence to treatment recommendations for positional plagiocephaly. Journal of Neurosurgery Pediatrics, 19(3), 282–288.Google Scholar

Lampl, M., & Johnson, M. L. (2011a). Infant growth in length follows prolonged sleep and increased naps. Sleep, 34(5), 641–650.Google Scholar

Lampl, M., (2011b). Infant head circumference growth is saltatory and coupled to length growth. Early Human Development, 87(5), 361–368.Google Scholar

Lampl, M., Mummert, A., & Schoen, M. (2016). Promoting healthy growth or feeding obesity? The need for evidence-based oversight of infant nutritional supplement claims. Healthcare, 4(4), 84. https://doi.org/10.3390/healthcare4040084 Google Scholar

Lampl, M., & Schoen, M. (2017). How long bones grow children: Mechanistic paths to variation in human height growth. American Journal of Human Biology, 29(2), e22983.Google Scholar

Lampl, M., & Thompson, A. L. (2007). Growth chart curves do not describe individual growth biology. American Journal of Human Biology, 19(5), 643–653.Google Scholar

Lampl, M., Veldhuis, J. D., & Johnson, M. L. (1992). Saltation and stasis: A model of human growth. Science, 258(5083), 801–803.Google Scholar

Laughlin, J., Luerssen, T. G., Dias, M. S., & American Academy of Pediatrics Committee on Practice and Ambulatory Medicine (2011). Prevention and management of positional skull deformities in infants. Pediatrics, 128(6), 1236–1241.Google Scholar

Lee, H. S., Kim, S. J., & Kwon, J. -Y. (2018). Parents’ perspectives and clinical effectiveness of cranial-molding orthoses in infants with plagiocephaly. Annals of Rehabilitation Medicine, 42 5), 737–747.Google Scholar

Lindley, A. A., Benson, J. E., Grimes, C., Cole, T. M., & Herman, A. A. (1999). The relationship in neonates between clinically measured head circumference and brain volume estimated from head CT-scans. Early Human Development, 56(1), 17–29.Google Scholar

Lipira, A. B., Gordon, S., Darvann, T. A., Hermann, N. V., van Pelt, A. E., Naidoo, S. D., … Kane, A. A. (2010). Helmet versus active repositioning for plagiocephaly: A three-dimensional analysis. Pediatrics, 126(4), e936–945.Google Scholar

Livshits, G., Peter, I., Vainder, M., & Hauspie, R. (2000) Genetic analysis of growth curve parameters of body weight, height and head circumference. Annals Human Biology, 27(3):299–312.Google Scholar

Martínez-Abadías, N., Esparza, M., Sjøvold, T., González-José, R., Santos, M., & Hernández, M. (2009). Heritability of human cranial dimensions: Comparing the evolvability of different cranial regions. Journal of Anatomy, 214(1), 19–35.Google Scholar

Martini, M., Klausing, A., Lüchters, G., Heim, N., & Messing-Jünger, M. (2018). Head circumference: A useful single parameter for skull volume development in cranial growth analysis? Head & Face Medicine, 14(1), 3.Google Scholar

Martorell, R. (2017). Improved nutrition in the first 1000 days and adult human capital and health. American Journal of Human Biology, 29(2). doi: 10.1002/ajhb.22952.Google Scholar

McCammon, R. W. (1970). Human growth and development. Oxford: Charles C. Thomas.Google Scholar

Mehta, A., & Hindmarsh, P. C. (2002). The use of somatropin (recombinant growth hormone). in children of short stature. Paediatric Drugs, 4(1), 37–47.Google Scholar

Mei, Z., Grummer-Strawn, L. M., Thompson, D., & Dietz, W. H. (2004). Shifts in percentiles of growth during early childhood: Analysis of longitudinal data from the California Child Health and Development Study. Pediatrics, 113(6), e617–627.Google Scholar

Montgomery, S., Bartley, M., & Wilkinson, R. (1997). Family conflict and slow growth. Archives of Disease in Childhood, 77(4), 326–330.Google Scholar

Natale, V., & Rajagopalan, A. (2014). Worldwide variation in human growth and the World Health Organization growth standards: A systematic review. British Medical Journal: Open, 4(1), e003735.Google Scholar

Newell, K. M., & Wade, M. G. (2018). Physical growth, body scale, and perceptual-motor development. Advances in Child Development and Behavior, 55, 205–243.Google Scholar

Obri, A., Khrimian, L., Karsenty, G., & Oury, F. (2018). Osteocalcin in the brain: From embryonic development to age-related decline in cognition. Nature Reviews. Endocrinology, 14(3), 174–182.Google Scholar

Oury, F., Khrimian, L., Denny, C. A., Gardin, A., Chaouni, A., Goedden, N., … Karsenty, G. (2013). Maternal and offspring pools of osteocalcin influence brain development and functions. Cell, 155(1), 228–241.Google Scholar

Persing, J., James, H., Swanson, J., Kattwinkel, J., & American Academy of Pediatrics Committee on Practice and Ambulatory Medicine (2003). Prevention and management of positional skull deformities in infants. Pediatrics, 112(1), 199–202.Google Scholar

Pindrik, J., Ye, X., Ji, B.G., Pendleton, C., & Ahn, E. S. (2014). Anterior fontanelle closure and size in full-term children based on head computed tomography. Clinical Pediatrics, 53(12), 1149–1157.Google Scholar

Piven, J., Elison, J. T., & Zylka, M. J. (2018). Toward a conceptual framework for early brain and behavior development in autism. Molecular Psychiatry, 23(1), 165.Google Scholar

Pomeroy, E., Stock, J. T., Cole, T. J., O’Callaghan, M., & Wells, J. C. K. (2014). Relationships between neonatal weight, limb lengths, skinfold thicknesses, body breadths and circumferences in an Australian cohort. PLOS One, 9(8), e105108.Google Scholar

Ramanathan, C., Xu, H., Khan, S. K., Shen, Y., Gitis, P. J., Welsh, D. K., … Liu, A. C. (2014) Cell type-specific functions of period genes revealed by novel adipocyte and hepatocyte circadian clock models. PLoS Genet, 10(4), e1004244. doi:10.1371/journal.pgen.1004244.Google Scholar

Raymond, G. V., & Holmes, L. B. (1994). Head circumference standards in neonates. Journal of Child Neurology, 9(1), 63–66.Google Scholar

Roche, A. F., & Guo, S. (1992). Development of reference data for increments in variables related to growth. American Journal of Human Biology, 4(3), 365–371.Google Scholar

Rose, C., Parker, A., Jefferson, B., & Cartmell, E. (2015). The characterization of feces and urine: A review of the literature to inform advanced treatment technology. Critical Reviews in Environmental Science and Technology, 45(17), 1827–1879.Google Scholar

Roy, S. M., Fields, D. A., Mitchell, J. A., Hawkes, C. P., Kelly, A., Wu, G. D., … McCormack, S. E. (2019). Body mass index is a better indicator of body composition than weight-for-length at age 1 month. Journal of Pediatrics, 204, 77–83.Google Scholar

Scerri, E. M. L., Thomas, M. G., Manica, A., Gunz, P., Stock, J. T., Stringer, C., … Chikhl, L. (2018). Did our species evolve in subdivided populations across Africa, and why does it matter? Trends in Ecology and Evolution, 33(8), 582–594.Google Scholar

Schneider, K., Zernicke, R. F., Ulrich, B. D., Jensen, J. L., & Thelen, E. (1990). Understanding movement control in infants through the analysis of limb intersegmental dynamics. Journal of Motor Behavior, 22(4), 493–520.Google Scholar

Smit, D. J. A., Luciano, M., Bartels, M., van Beijsterveldt, C. E. M., Wright, M. J., Hansell, N. K., … Boomsma, D. I. (2010). Heritability of head size in Dutch and Australian twin families at ages 0–50 years. Twin Research and Human Genetics, 13(4), 370–380.Google Scholar

Smith, D. W., Truog, W., Rogers, J. E., Greitzer, L. J., Skinner, A. L., McCann, J. J., & Harvey, M. A. (1976). Shifting linear growth during infancy: Illustration of genetic factors in growth from fetal life through infancy. Journal of Pediatrics, 89(2), 225–230.Google Scholar

Teager, S. J., Constantine, S., Lottering, N., & Anderson, P. J. (2018). Physiologic closure time of the metopic suture in South Australian infants from 3D CT scans. Child’s Nervous System, 35(2), 329–335.Google Scholar

Treit, S., Zhou, D., Chudley, A. E., Andrew, G., Rasmussen, C., Nikkel, S. M., … Beaulieu, C. (2016). Relationships between head circumference, brain volume and cognition in children with prenatal alcohol exposure. PloS One, 11(2), e0150370.Google Scholar

Tubbs, R. S., Salter, E. G., & Oakes, W.J. (2006). Artificial deformation of the human skull: A review. Clinical Anatomy, 19(4), 372–377.Google Scholar

Velazquez, M. A., Sheth, B., Smith, S. J., Eckert, J. J., Osmond, C., & Fleming, T. P. (2018). Insulin and branched-chain amino acid depletion during mouse preimplantation embryo culture programmes body weight gain and raised blood pressure during early postnatal life. Biochimica et Biophysica Acta. Molecular Basis of Disease, 1864(2), 590–600.Google Scholar

van der Linden, V. (2016). Description of 13 infants born during October 2015–January 2016 with congenital Zika virus infection without microcephaly at birth. Morbidity and Mortality Weekly Report, 65(47), 1343–1348.Google Scholar

van Dommelen, P., de Gunst, M. C., van der Vaart, A. W., & Boomsma, D. I. (2004). Genetic study of the height and weight process during infancy. Twin Research, 7(6), 607–616.Google Scholar

van Dyck, L. I., & Morrow, E. M. (2017). Genetic control of postnatal human brain growth. Current Opinion in Neurology, 30(1), 114–124.Google Scholar

van Vlimmeren, L. A., Engelbert, R. H., Pelsma, M., Groenewoud, H. M., Boere-Boonekamp, M. M., & van der Sanden, M. ( 2017). The course of skull deformation from birth to 5 years of age: A prospective cohort study. European Journal of Pediatrics, 176(1), 11–21.Google Scholar

van Wijk, R. M., van Vlimmeren, L. A., Groothuis-Oudshoorn, C. G. M., van der Ploeg, C. P. B., Ijzerman, M. J., & Boore-Boonekamp, M. M. (2014). Helmet therapy in infants with positional skull deformation: Randomised controlled trial. British Medical Journal, 348, g2741.Google Scholar

Wagner, D. R. (2013). Ultrasound as a tool to assess body fat. Journal of Obesity, 2013, 1–9.Google Scholar

Weaver, D. D., & Christian, J. C. (1980). Familial variation of head size and adjustment for parental head circumference. Journal of Pediatrics, 96(6), 990–994.Google Scholar

World Health Organization (2006). WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: WHO.Google Scholar

Wright, C. M., & Emond, A. (2015). Head growth and neurocognitive outcomes. Pediatrics, 135(6), e1393–1398.Google Scholar

References

Almas, A. N., Degnan, K. A., Radulescu, A., Nelson, C. A., Zeanah, C. H., & Fox, N. A. (2012). Effects of early intervention and the moderating effects of brain activity on institutionalized children’s social skills at age 8. Proceedings of the National Academy of Sciences of the United States of America, 109(Suppl. 2), 17228–17231. https://doi.org/10.1073/pnas.1121256109 Google Scholar

Baccarelli, A., & Bollati, V. (2009). Epigenetics and environmental chemicals. Current Opinion in Pediatrics, 21(2), 243–251.Google Scholar

Baedke, J. (2013). The epigenetic landscape in the course of time: Conrad Hal Waddington’s methodological impact on the life sciences. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 44(4, Part B), 756–773. https://doi.org/10.1016/j.shpsc.2013.06.001 Google Scholar

Ben Maamar, M., Sadler-Riggleman, I., Beck, D., McBirney, M., Nilsson, E., Klukovich, R., … Skinner, M. K. (2018). Alterations in sperm DNA methylation, non-coding RNA expression, and histone retention mediate vinclozolin-induced epigenetic transgenerational inheritance of disease. Environmental Epigenetics, 4(2), dvy010. https://doi.org/10.1093/eep/dvy010 Google Scholar

Bernard, K., Frost, A., Bennett, C. B., & Lindhiem, O. (2017). Maltreatment and diurnal cortisol regulation: A meta-analysis. Psychoneuroendocrinology, 78, 57–67. https://doi.org/10.1016/j.psyneuen.2017.01.005 Google Scholar

Bowers, M. E., & Yehuda, R. (2016). Intergenerational transmission of stress in humans. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 41(1), 232–244. https://doi.org/10.1038/npp.2015.247 Google Scholar

Bowlby, J., & World Health Organization. (1952). Maternal care and mental health : A report prepared on behalf of the World Health Organization as a contribution to the United Nations programme for the welfare of homeless children (2nd ed.). Geneva: World Health Organization.Google Scholar

Braithwaite, E. C., Kundakovic, M., Ramchandani, P. G., Murphy, S. E., & Champagne, F. A. (2015). Maternal prenatal depressive symptoms predict infant NR3C1 1F and BDNF IV DNA methylation. Epigenetics, 10(5), 408–417. https://doi.org/10.1080/15592294.2015.1039221 Google Scholar

Brody, G. H., Yu, T., Chen, E., Beach, S. R. H., & Miller, G. E. (2016). Family-centered prevention ameliorates the longitudinal association between risky family processes and epigenetic aging. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 57(5), 566–574. https://doi.org/10.1111/jcpp.12495 Google Scholar

Brown, A. S., Gyllenberg, D., Malm, H., McKeague, I. W., Hinkka-Yli-Salomäki, S., Artama, M., … Sourander, A. (2016). Association of selective serotonin reuptake inhibitor exposure during pregnancy with speech, scholastic, and motor disorders in offspring. JAMA Psychiatry, 73(11), 1163–1170. https://doi.org/10.1001/jamapsychiatry.2016.2594 Google Scholar

Bush, N. R., Edgar, R. D., Park, M., MacIsaac, J. L., McEwen, L. M., Adler, N. E., … Boyce, W. T. (2018). The biological embedding of early-life socioeconomic status and family adversity in children’s genome-wide DNA methylation. Epigenomics, 10(11), 1445–1461. https://doi.org/10.2217/epi-2018-0042 Google Scholar

Busso, D. S., McLaughlin, K. A., Brueck, S., Peverill, M., Gold, A. L., & Sheridan, M. A. (2017). Child abuse, neural structure, and adolescent psychopathology: A longitudinal study. Journal of the American Academy of Child & Adolescent Psychiatry, 56(4), 321–328.e1. https://doi.org/10.1016/j.jaac.2017.01.013 Google Scholar

Caldji, C., Tannenbaum, B., Sharma, S., Francis, D., Plotsky, P. M., & Meaney, M. J. (1998). Maternal care during infancy regulates the development of neural systems mediating the expression of fearfulness in the rat. Proceedings of the National Academy of Sciences of the United States of America, 95(9), 5335–5340.Google Scholar

Cecil, C. A. M., Walton, E., Smith, R. G., Viding, E., McCrory, E. J., Relton, C. L., … Barker, E. D. (2016). DNA methylation and substance-use risk: A prospective, genome-wide study spanning gestation to adolescence. Translational Psychiatry, 6(12), e976. https://doi.org/10.1038/tp.2016.247 Google Scholar

Champagne, F. A. (2008). Epigenetic mechanisms and the transgenerational effects of maternal care. Frontiers in Neuroendocrinology, 29(3), 386–397. https://doi.org/10.1016/j.yfrne.2008.03.003 Google Scholar

Champagne, F. A. (2016). Epigenetic legacy of parental experiences: Dynamic and interactive pathways to inheritance. Development and Psychopathology, 28(4 Pt. 2), 1219–1228. https://doi.org/10.1017/S0954579416000808 Google Scholar

Champagne, F. A., & Meaney, M. J. (2006). Stress during gestation alters postpartum maternal care and the development of the offspring in a rodent model. Biological Psychiatry, 59(12), 1227–1235. https://doi.org/10.1016/j.biopsych.2005.10.016 Google Scholar

Champagne, F. A., (2007). Transgenerational effects of social environment on variations in maternal care and behavioral response to novelty. Behavioral Neuroscience, 121(6), 1353–1363. https://doi.org/10.1037/0735-7044.121.6.1353 Google Scholar

Champagne, F. A., Weaver, I. C. G., Diorio, J., Dymov, S., Szyf, M., & Meaney, M. J. (2006). Maternal care associated with methylation of the estrogen receptor-alpha1b promoter and estrogen receptor-alpha expression in the medial preoptic area of female offspring. Endocrinology, 147(6), 2909–2915. https://doi.org/10.1210/en.2005-1119 Google Scholar

Cheung, P., Allis, C. D., & Sassone-Corsi, P. (2000). Signaling to chromatin through histone modifications. Cell, 103(2), 263–271.Google Scholar

Cicchetti, D., Hetzel, S., Rogosch, F. A., Handley, E. D., & Toth, S. L. (2016). Genome-wide DNA methylation in 1-year-old infants of mothers with major depressive disorder. Development and Psychopathology, 28(4 Pt. 2), 1413–1419. https://doi.org/10.1017/S0954579416000912 Google Scholar

Cortessis, V. K., Thomas, D. C., Levine, A. J., Breton, C. V., Mack, T. M., Siegmund, K. D., … Laird, P. W. (2012). Environmental epigenetics: prospects for studying epigenetic mediation of exposure–response relationships. Human Genetics, 131(10), 1565–1589. https://doi.org/10.1007/s00439-012-1189-8 Google Scholar

Curley, J. P., Mashoodh, R., & Champagne, F. A. (2011). Epigenetics and the origins of paternal effects. Hormones and Behavior, 59(3), 306–314. https://doi.org/10.1016/j.yhbeh.2010.06.018 Google Scholar

Danchin, É., Charmantier, A., Champagne, F. A., Mesoudi, A., Pujol, B., & Blanchet, S. (2011). Beyond DNA: Integrating inclusive inheritance into an extended theory of evolution. Nature Reviews. Genetics, 12(7), 475–486. https://doi.org/10.1038/nrg3028 Google Scholar

D’Elia, A. T. D., Matsuzaka, C. T., Neto, J. B. B., Mello, M. F., Juruena, M. F., & Mello, A. F. (2018). Childhood sexual abuse and indicators of immune activity: A systematic review. Frontiers in Psychiatry, 9, 354. https://doi.org/10.3389/fpsyt.2018.00354 Google Scholar

Dias, B. G., & Ressler, K. J. (2014). Parental olfactory experience influences behavior and neural structure in subsequent generations. Nature Neuroscience, 17(1), 89–96. https://doi.org/10.1038/nn.3594 Google Scholar

Dupont, C., Armant, D. R., & Brenner, C. A. (2009). Epigenetics: Definition, mechanisms and clinical perspective. Seminars in Reproductive Medicine, 27(5), 351–357. https://doi.org/10.1055/s-0029-1237423 Google Scholar

Eddy, S. R. (2001). Non–coding RNA genes and the modern RNA world. Nature Reviews Genetics, 2(12), 919–929. https://doi.org/10.1038/35103511 Google Scholar

Fan, Y., Tian, C., Liu, Q., Zhen, X., Zhang, H., Zhou, L., … Zhu, M. (2018). Preconception paternal bisphenol A exposure induces sex-specific anxiety and depression behaviors in adult rats. PloS One, 13(2), e0192434. https://doi.org/10.1371/journal.pone.0192434 Google Scholar

Fareri, D. S., Gabard-Durnam, L., Goff, B., Flannery, J., Gee, D. G., Lumian, D. S., … Tottenham, N. (2017). Altered ventral striatal-medial prefrontal cortex resting-state connectivity mediates adolescent social problems after early institutional care. Development and Psychopathology, 29(5), 1865–1876. https://doi.org/10.1017/S0954579417001456 Google Scholar

Farrell, C., Doolin, K., O’ Leary, N., Jairaj, C., Roddy, D., Tozzi, L., … O’Keane, V. (2018). DNA methylation differences at the glucocorticoid receptor gene in depression are related to functional alterations in hypothalamic-pituitary-adrenal axis activity and to early life emotional abuse. Psychiatry Research, 265, 341–348. https://doi.org/10.1016/j.psychres.2018.04.064 Google Scholar

Feil, R., & Fraga, M. F. (2012). Epigenetics and the environment: Emerging patterns and implications. Nature Reviews. Genetics, 13(2), 97–109. https://doi.org/10.1038/nrg3142 Google Scholar

Fiorito, G., Polidoro, S., Dugué, P. -A., Kivimaki, M., Ponzi, E., Matullo, G., … Vineis, P. (2017). Social adversity and epigenetic aging: A multi-cohort study on socioeconomic differences in peripheral blood DNA methylation. Scientific Reports, 7(1), 16266. https://doi.org/10.1038/s41598-017-16391-5 Google Scholar

Francis, D., Diorio, J., Liu, D., & Meaney, M. J. (1999). Nongenomic transmission across generations of maternal behavior and stress responses in the rat. Science, 286(5442), 1155–1158.Google Scholar

Franklin, T. B., Russig, H., Weiss, I. C., Gräff, J., Linder, N., Michalon, A., … Mansuy, I. M. (2010). Epigenetic transmission of the impact of early stress across generations. Biological Psychiatry, 68(5), 408–415. https://doi.org/10.1016/j.biopsych.2010.05.036 Google Scholar

Gapp, K., Jawaid, A., Sarkies, P., Bohacek, J., Pelczar, P., Prados, J., … Mansuy, I. M. (2014). Implication of sperm RNAs in transgenerational inheritance of the effects of early trauma in mice. Nature Neuroscience, 17(5), 667–669. https://doi.org/10.1038/nn.3695 Google Scholar

Garg, E., Chen, L., Nguyen, T. T. T., Pokhvisneva, I., Chen, L. M., Unternaehrer, E., … Mavan Study Team. (2018). The early care environment and DNA methylome variation in childhood. Development and Psychopathology, 30(3), 891–903. https://doi.org/10.1017/S0954579418000627 Google Scholar

Gould, K. L., Coventry, W. L., Olson, R. K., & Byrne, B. (2018). Gene–environment interactions in ADHD: The roles of SES and chaos. Journal of Abnormal Child Psychology, 46(2), 251–263. https://doi.org/10.1007/s10802-017-0268-7 Google Scholar

Guibert, S., & Weber, M. (2013). Functions of DNA methylation and hydroxymethylation in mammalian development. Current Topics in Developmental Biology, 104, 47–83. https://doi.org/10.1016/B978-0-12-416027-9.00002-4 Google Scholar

Gurnot, C., Martin-Subero, I., Mah, S. M., Weikum, W., Goodman, S. J., Brain, U., … Hensch, T. K. (2015). Prenatal antidepressant exposure associated with CYP2E1 DNA methylation change in neonates. Epigenetics, 10(5), 361–372. https://doi.org/10.1080/15592294.2015.1026031 Google Scholar

Hane, A. A., Henderson, H. A., Reeb-Sutherland, B. C., & Fox, N. A. (2010). Ordinary variations in human maternal caregiving in infancy and biobehavioral development in early childhood: A follow-up study. Developmental Psychobiology, 52(6), 558–567. https://doi.org/10.1002/dev.20461 Google Scholar

Heijmans, B. T., Tobi, E. W., Stein, A. D., Putter, H., Blauw, G. J., Susser, E. S., … Lumey, L. H. (2008). Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proceedings of the National Academy of Sciences of the United States of America, 105(44), 17046–17049. https://doi.org/10.1073/pnas.0806560105 Google Scholar

Hobel, C. J., Goldstein, A., & Barrett, E. S. (2008). Psychosocial stress and pregnancy outcome. Clinical Obstetrics and Gynecology, 51(2), 333–348. https://doi.org/10.1097/GRF.0b013e31816f2709 Google Scholar

Hodel, A. S., Hunt, R. H., Cowell, R. A., van den Heuvel, S. E., Gunnar, M. R., & Thomas, K. M. (2015). Duration of early adversity and structural brain development in post-institutionalized adolescents. NeuroImage, 105, 112–119. https://doi.org/10.1016/j.neuroimage.2014.10.020 Google Scholar

Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14(10), R115. https://doi.org/10.1186/gb-2013-14-10-r115 Google Scholar

Houtepen, L. C., Hardy, R., Maddock, J., Kuh, D., Anderson, E. L., Relton, C. L., … Howe, L. D. (2018). Childhood adversity and DNA methylation in two population-based cohorts. Translational Psychiatry, 8(1), 266. https://doi.org/10.1038/s41398-018-0307-3 Google Scholar

Hu, F. B., Persky, V., Flay, B. R., Zelli, A., Cooksey, J., & Richardson, J. (1997). Prevalence of asthma and wheezing in public schoolchildren: Association with maternal smoking during pregnancy. Annals of Allergy, Asthma & Immunology: Official Publication of the American College of Allergy, Asthma, & Immunology, 79(1), 80–84. https://doi.org/10.1016/S1081-1206(10)63090–6 Google Scholar

Jaffee, S. R., & Price, T. S. (2007). Gene–environment correlations: A review of the evidence and implications for prevention of mental illness. Molecular Psychiatry, 12(5), 432–442. https://doi.org/10.1038/sj.mp.4001950 Google Scholar

Jenuwein, T., & Allis, C. D. (2001). Translating the histone code. Science, 293(5532), 1074–1080. https://doi.org/10.1126/science.1063127 Google Scholar

Jones, P. A. (2012). Functions of DNA methylation: Islands, start sites, gene bodies and beyond. Nature Reviews Genetics, 13(7), 484–492.Google Scholar

Kertes, D. A., Bhatt, S. S., Kamin, H. S., Hughes, D. A., Rodney, N. C., & Mulligan, C. J. (2017). BNDF methylation in mothers and newborns is associated with maternal exposure to war trauma. Clinical Epigenetics, 9, 68. https://doi.org/10.1186/s13148-017-0367-x Google Scholar

Kundakovic, M., Gudsnuk, K., Herbstman, J. B., Tang, D., Perera, F. P., & Champagne, F. A. (2015). DNA methylation of BDNF as a biomarker of early-life adversity. Proceedings of the National Academy of Sciences of the United States of America, 112(22), 6807–6813. https://doi.org/10.1073/pnas.1408355111 Google Scholar

Labonté, B., Suderman, M., Maussion, G., Navaro, L., Yerko, V., Mahar, I., … Turecki, G. (2012). Genome-wide epigenetic regulation by early-life trauma. Archives of General Psychiatry, 69(7), 722–731. https://doi.org/10.1001/archgenpsychiatry.2011.2287 Google Scholar

Lawn, R. B., Anderson, E. L., Suderman, M., Simpkin, A. J., Gaunt, T. R., Teschendorff, A. E., … Howe, L. D. (2018). Psychosocial adversity and socioeconomic position during childhood and epigenetic age: Analysis of two prospective cohort studies. Human Molecular Genetics, 27(7), 1301–1308. https://doi.org/10.1093/hmg/ddy036 Google Scholar

Lester, B. M., Marsit, C. J., Giarraputo, J., Hawes, K., LaGasse, L. L., & Padbury, J. F. (2015). Neurobehavior related to epigenetic differences in preterm infants. Epigenomics, 7(7), 1123–1136. https://doi.org/10.2217/epi.15.63 Google Scholar

Liu, D., Diorio, J., Day, J. C., Francis, D. D., & Meaney, M. J. (2000). Maternal care, hippocampal synaptogenesis and cognitive development in rats. Nature Neuroscience, 3(8), 799–806. https://doi.org/10.1038/77702 Google Scholar

Liu, D., Diorio, J., Tannenbaum, B., Caldji, C., Francis, D., Freedman, A., … Meaney, M. J. (1997). Maternal care, hippocampal glucocorticoid receptors, and hypothalamic-pituitary-adrenal responses to stress. Science, 277(5332), 1659–1662.Google Scholar

Mashoodh, R., Habrylo, I. B., Gudsnuk, K. M., Pelle, G., & Champagne, F. A. (2018). Maternal modulation of paternal effects on offspring development. Proceedings. Biological Sciences, 285(1874). https://doi.org/10.1098/rspb.2018.0118 Google Scholar

McGowan, P. O., Sasaki, A., D’Alessio, A. C., Dymov, S., Labonté, B., Szyf, M., … Meaney, M. J. (2009). Epigenetic regulation of the glucocorticoid receptor in human brain associates with childhood abuse. Nature Neuroscience, 12(3), 342–348. https://doi.org/10.1038/nn.2270 Google Scholar

McGowan, P. O., Suderman, M., Sasaki, A., Huang, T. C. T., Hallett, M., Meaney, M. J., & Szyf, M. (2011). Broad epigenetic signature of maternal care in the brain of adult rats. PloS One, 6(2), e14739. https://doi.org/10.1371/journal.pone.0014739 Google Scholar

McLaughlin, K. A., & Lambert, H. K. (2017). Child trauma exposure and psychopathology: Mechanisms of risk and resilience. Current Opinion in Psychology, 14, 29–34. https://doi.org/10.1016/j.copsyc.2016.10.004 Google Scholar

Meaney, M. J. (2010). Epigenetics and the biological definition of gene x environment interactions. Child Development, 81(1), 41–79. https://doi.org/10.1111/j.1467-8624.2009.01381.x Google Scholar

Melchior, M., Hersi, R., van der Waerden, J., Larroque, B., Saurel-Cubizolles, M. -J., Chollet, A., … EDEN Mother–Child Cohort Study Group. (2015). Maternal tobacco smoking in pregnancy and children’s socio-emotional development at age 5: The EDEN mother–child birth cohort study. European Psychiatry: The Journal of the Association of European Psychiatrists, 30(5), 562–568. https://doi.org/10.1016/j.eurpsy.2015.03.005 Google Scholar

Milaniak, I., Cecil, C. A. M., Barker, E. D., Relton, C. L., Gaunt, T. R., McArdle, W., & Jaffee, S. R. (2017). Variation in DNA methylation of the oxytocin receptor gene predicts children’s resilience to prenatal stress. Development and Psychopathology, 29(5), 1663–1674. https://doi.org/10.1017/S0954579417001316 Google Scholar

Millard, S. J., Weston-Green, K., & Newell, K. A. (2017). The effects of maternal antidepressant use on offspring behaviour and brain development: Implications for risk of neurodevelopmental disorders. Neuroscience and Biobehavioral Reviews, 80, 743–765. https://doi.org/10.1016/j.neubiorev.2017.06.008 Google Scholar

Miller, G. E., Yu, T., Chen, E., & Brody, G. H. (2015). Self-control forecasts better psychosocial outcomes but faster epigenetic aging in low-SES youth. Proceedings of the National Academy of Sciences of the United States of America, 112(33), 10325–10330. https://doi.org/10.1073/pnas.1505063112 Google Scholar

Mitsuya, K., Parker, A. N., Liu, L., Ruan, J., Vissers, M. C. M., & Myatt, L. (2017). Alterations in the placental methylome with maternal obesity and evidence for metabolic regulation. PloS One, 12(10), e0186115. https://doi.org/10.1371/journal.pone.0186115 Google Scholar

Mohn, F., & Schübeler, D. (2009). Genetics and epigenetics: Stability and plasticity during cellular differentiation. Trends in Genetics: TIG, 25(3), 129–136. https://doi.org/10.1016/j.tig.2008.12.005 Google Scholar

Moisiadis, V. G., Constantinof, A., Kostaki, A., Szyf, M., & Matthews, S. G. (2017). Prenatal glucocorticoid exposure modifies endocrine function and behaviour for 3 generations following maternal and paternal transmission. Scientific Reports, 7(1), 11814. https://doi.org/10.1038/s41598-017-11635-w Google Scholar

Monk, C., Feng, T., Lee, S., Krupska, I., Champagne, F. A., & Tycko, B. (2016). Distress during pregnancy: Epigenetic regulation of placenta glucocorticoid-related genes and fetal neurobehavior. American Journal of Psychiatry, 173(7), 705–713. https://doi.org/10.1176/appi.ajp.2015.15091171 Google Scholar

Monk, C., Spicer, J., & Champagne, F. A. (2012). Linking prenatal maternal adversity to developmental outcomes in infants: The role of epigenetic pathways. Development and Psychopathology, 24(4), 1361–1376. https://doi.org/10.1017/S0954579412000764 Google Scholar

Naumova, O. Y., Lee, M., Koposov, R., Szyf, M., Dozier, M., & Grigorenko, E. L. (2012). Differential patterns of whole-genome DNA methylation in institutionalized children and children raised by their biological parents. Development and Psychopathology, 24(1), 143–155. https://doi.org/10.1017/S0954579411000605 Google Scholar

Ng, S. -F., Lin, R. C. Y., Laybutt, D. R., Barres, R., Owens, J. A., & Morris, M. J. (2010). Chronic high-fat diet in fathers programs β-cell dysfunction in female rat offspring. Nature, 467(7318), 963–966. https://doi.org/10.1038/nature09491 Google Scholar

Nigg, J., Nikolas, M., & Burt, S. A. (2010). Measured gene-by-environment interaction in relation to attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 49(9), 863–873. https://doi.org/10.1016/j.jaac.2010.01.025 Google Scholar

Nilsson, E. E., Sadler-Riggleman, I., & Skinner, M. K. (2018). Environmentally induced epigenetic transgenerational inheritance of disease. Environmental Epigenetics, 4(2), dvy016. https://doi.org/10.1093/eep/dvy016 Google Scholar

Noble, D. (2015). Conrad Waddington and the origin of epigenetics. Journal of Experimental Biology, 218(6), 816–818. https://doi.org/10.1242/jeb.120071 Google Scholar

Non, A. L., Binder, A. M., Kubzansky, L. D., & Michels, K. B. (2014). Genome-wide DNA methylation in neonates exposed to maternal depression, anxiety, or SSRI medication during pregnancy. Epigenetics, 9(7), 964–972. https://doi.org/10.4161/epi.28853 Google Scholar

Oberlander, T. F., Weinberg, J., Papsdorf, M., Grunau, R., Misri, S., & Devlin, A. M. (2008). Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses. Epigenetics, 3(2), 97–106.Google Scholar

Papale, L. A., Seltzer, L. J., Madrid, A., Pollak, S. D., & Alisch, R. S. (2018). Differentially methylated genes in saliva are linked to childhood stress. Scientific Reports, 8(1), 10785. https://doi.org/10.1038/s41598-018-29107-0 Google Scholar

Paquette, A. G., Houseman, E. A., Green, B. B., Lesseur, C., Armstrong, D. A., Lester, B., & Marsit, C. J. (2016). Regions of variable DNA methylation in human placenta associated with newborn neurobehavior. Epigenetics, 11(8), 603–613. https://doi.org/10.1080/15592294.2016.1195534 Google Scholar

Paquette, A. G., Lester, B. M., Koestler, D. C., Lesseur, C., Armstrong, D. A., & Marsit, C. J. (2014). Placental FKBP5 genetic and epigenetic variation is associated with infant neurobehavioral outcomes in the RICHS cohort. PloS One, 9(8), e104913. https://doi.org/10.1371/journal.pone.0104913 Google Scholar

Parade, S. H., Parent, J., Rabemananjara, K., Seifer, R., Marsit, C. J., Yang, B. -Z., … Tyrka, A. R. (2017). Change in FK506 binding protein 5 (FKBP5) methylation over time among preschoolers with adversity. Development and Psychopathology, 29(5), 1627–1634. https://doi.org/10.1017/S0954579417001286 Google Scholar

Parent, C. I., & Meaney, M. J. (2008). The influence of natural variations in maternal care on play fighting in the rat. Developmental Psychobiology, 50(8), 767–776. https://doi.org/10.1002/dev.20342 Google Scholar

Pauwels, S., Ghosh, M., Duca, R. C., Bekaert, B., Freson, K., Huybrechts, I., … Godderis, L. (2016). Dietary and supplemental maternal methyl-group donor intake and cord blood DNA methylation. Epigenetics, 12(1), 1–10. https://doi.org/10.1080/15592294.2016.1257450 Google Scholar

Peña, C. J., Neugut, Y. D., & Champagne, F. A. (2013). Developmental timing of the effects of maternal care on gene expression and epigenetic regulation of hormone receptor levels in female rats. Endocrinology, 154(11), 4340–4351. https://doi.org/10.1210/en.2013-1595 Google Scholar

Perera, F., Vishnevetsky, J., Herbstman, J. B., Calafat, A. M., Xiong, W., Rauh, V., & Wang, S. (2012). Prenatal bisphenol A exposure and child behavior in an inner-city cohort. Environmental Health Perspectives, 120(8), 1190–1194. https://doi.org/10.1289/ehp.1104492 Google Scholar

Razin, A. (1998). CpG methylation, chromatin structure and gene silencing-a three-way connection. EMBO Journal, 17(17), 4905–4908. https://doi.org/10.1093/emboj/17.17.4905 Google Scholar

Razin, A., & Riggs, A. D. (1980). DNA methylation and gene function. Science, 210(4470), 604–610.Google Scholar

Rodgers, A. B., Morgan, C. P., Bronson, S. L., Revello, S., & Bale, T. L. (2013). Paternal stress exposure alters sperm microRNA content and reprograms offspring HPA stress axis regulation. Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 33(21), 9003–9012. https://doi.org/10.1523/JNEUROSCI.0914-13.2013 Google Scholar

Rogers, C. E., Lean, R. E., Wheelock, M. D., & Smyser, C. D. (2018). Aberrant structural and functional connectivity and neurodevelopmental impairment in preterm children. Journal of Neurodevelopmental Disorders, 10(1), 38. https://doi.org/10.1186/s11689-018-9253-x Google Scholar

Schieve, L. A., Tian, L. H., Rankin, K., Kogan, M. D., Yeargin-Allsopp, M., Visser, S., & Rosenberg, D. (2016). Population impact of preterm birth and low birth weight on developmental disabilities in US children. Annals of Epidemiology, 26(4), 267–274. https://doi.org/10.1016/j.annepidem.2016.02.012 Google Scholar

Sharp, G. C., Salas, L. A., Monnereau, C., Allard, C., Yousefi, P., Everson, T. M., … Relton, C. L. (2017). Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: Findings from the pregnancy and childhood epigenetics (PACE) consortium. Human Molecular Genetics, 26(20), 4067–4085. https://doi.org/10.1093/hmg/ddx290 Google Scholar

Shorey-Kendrick, L. E., McEvoy, C. T., Ferguson, B., Burchard, J., Park, B. S., Gao, L., … Spindel, E. R. (2017). Vitamin C prevents offspring DNA methylation changes associated with maternal smoking in pregnancy. American Journal of Respiratory and Critical Care Medicine, 196(6), 745–755. https://doi.org/10.1164/rccm.201610-2141OC Google Scholar

Simpkin, A. J., Hemani, G., Suderman, M., Gaunt, T. R., Lyttleton, O., Mcardle, W. L., … Smith, G. D. (2016). Prenatal and early life influences on epigenetic age in children: A study of mother–offspring pairs from two cohort studies. Human Molecular Genetics, 25(1), 191–201. https://doi.org/10.1093/hmg/ddv456 Google Scholar

Sonuga-Barke, E. J. S., Kennedy, M., Kumsta, R., Knights, N., Golm, D., Rutter, M., … Kreppner, J. (2017). Child-to-adult neurodevelopmental and mental health trajectories after early life deprivation: The young adult follow-up of the longitudinal English and Romanian Adoptees study. Lancet, 389(10078), 1539–1548. https://doi.org/10.1016/S0140-6736(17)30045-4 Google Scholar

Stamoulis, C., Vanderwert, R. E., Zeanah, C. H., Fox, N. A., & Nelson, C. A. (2017). Neuronal networks in the developing brain are adversely modulated by early psychosocial neglect. Journal of Neurophysiology, 118(4), 2275–2288. https://doi.org/10.1152/jn.00014.2017 Google Scholar

Staneva, A., Bogossian, F., Pritchard, M., & Wittkowski, A. (2015). The effects of maternal depression, anxiety, and perceived stress during pregnancy on preterm birth: A systematic review. Women and Birth: Journal of the Australian College of Midwives, 28(3), 179–193. https://doi.org/10.1016/j.wombi.2015.02.003 Google Scholar

Susser, E. S., & Lin, S. P. (1992). Schizophrenia after prenatal exposure to the Dutch Hunger Winter of 1944–1945. Archives of General Psychiatry, 49(12), 983–988.Google Scholar

Talati, A., Wickramaratne, P. J., Wesselhoeft, R., & Weissman, M. M. (2017). Prenatal tobacco exposure, birthweight, and offspring psychopathology. Psychiatry Research, 252, 346–352. https://doi.org/10.1016/j.psychres.2017.03.016 Google Scholar

Torche, F., & Kleinhaus, K. (2012). Prenatal stress, gestational age and secondary sex ratio: The sex-specific effects of exposure to a natural disaster in early pregnancy. Human Reproduction, 27(2), 558–567. https://doi.org/10.1093/humrep/der390 Google Scholar

Troller-Renfree, S., McDermott, J. M., Nelson, C. A., Zeanah, C. H., & Fox, N. A. (2015). The effects of early foster care intervention on attention biases in previously institutionalized children in Romania. Developmental Science, 18(5), 713–722. https://doi.org/10.1111/desc.12261 Google Scholar

Tserga, A., Binder, A. M., & Michels, K. B. (2017). Impact of folic acid intake during pregnancy on genomic imprinting of IGF2/H19 and 1-carbon metabolism. FASEB Journal: Official Publication of the Federation of American Societies for Experimental Biology, 31(12), 5149–5158. https://doi.org/10.1096/fj.201601214RR Google Scholar

Vassoler, F. M., White, S. L., Schmidt, H. D., Sadri-Vakili, G., & Pierce, R. C. (2013). Epigenetic inheritance of a cocaine-resistance phenotype. Nature Neuroscience, 16(1), 42–47. https://doi.org/10.1038/nn.3280 Google Scholar

Waddington, C. H. (1940). Organisers & genes. Cambridge, UK: Cambridge University Press.Google Scholar

Wadhwa, P. D., Entringer, S., Buss, C., & Lu, M. C. (2011). The contribution of maternal stress to preterm birth: Issues and considerations. Clinics in Perinatology, 38(3), 351–384. https://doi.org/10.1016/j.clp.2011.06.007 Google Scholar

Weaver, I. C. G., Cervoni, N., Champagne, F. A., D’Alessio, A. C., Sharma, S., Seckl, J. R., … Meaney, M. J. (2004). Epigenetic programming by maternal behavior. Nature Neuroscience, 7(8), 847–854. https://doi.org/10.1038/nn1276 Google Scholar

Weinstock, M., Fride, E., & Hertzberg, R. (1988). Prenatal stress effects on functional development of the offspring. Progress in Brain Research, 73, 319–331. https://doi.org/10.1016/S0079-6123(08)60513-0 Google Scholar

Welch, M. G., Firestein, M. R., Austin, J., Hane, A. A., Stark, R. I., Hofer, M. A., … Myers, M. M. (2015). Family nurture intervention in the neonatal intensive care unit improves social-relatedness, attention, and neurodevelopment of preterm infants at 18 months in a randomized controlled trial. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 56(11), 1202–1211. https://doi.org/10.1111/jcpp.12405 Google Scholar

Welch, M. G., Stark, R. I., Grieve, P. G., Ludwig, R. J., Isler, J. R., Barone, J. L., & Myers, M. M. (2017). Family nurture intervention in preterm infants increases early development of cortical activity and independence of regional power trajectories. Acta Paediatrica, 106(12), 1952–1960. https://doi.org/10.1111/apa.14050 Google Scholar

Wilkinson, L. S., Davies, W., & Isles, A. R. (2007). Genomic imprinting effects on brain development and function. Nature Reviews. Neuroscience, 8(11), 832–843. https://doi.org/10.1038/nrn2235 Google Scholar

Wilson, R. D., Davies, G., Désilets, V., Reid, G. J., Summers, A., Wyatt, P., … Genetics Committee and Executive and Council of the Society of Obstetricians and Gynaecologists of Canada (2003). The use of folic acid for the prevention of neural tube defects and other congenital anomalies. Journal of Obstetrics and Gynaecology Canada, 25(11), 959–973.Google Scholar

Winther, G., Eskelund, A., Bay-Richter, C., Elfving, B., Müller, H. K., Lund, S., & Wegener, G. (2019). Grandmaternal high-fat diet primed anxiety-like behaviour in the second-generation female offspring. Behavioural Brain Research, 359, 47–55. https://doi.org/10.1016/j.bbr.2018.10.017 Google Scholar

References

Balas, B., Westerlund, A., Hung, K., & Nelson III, C. A. (2011). Shape, color and the other-race effect in the infant brain. Developmental Science, 14(4), 892–900. doi:10.1111/j.1467-7687.2011.01039.xGoogle Scholar

Baldauf, D., & Desimone, R. (2014). Neural mechanisms of object-based attention. Science, 344(6182), 424–427. doi:10.1126/science.1247003Google Scholar

Barry, R. J., Clarke, A. R., McCarthy, R., Selikowitz, M., Rushby, J. A., & Ploskova, E. (2004). EEG differences in children as a function of resting-state arousal level. Clinical Neurophysiology, 115, 402–408.Google Scholar

Bhatt, R., Bertin, E., Hayden, A., & Reed, A. (2005). Face processing in infancy: Developmental changes in the use of different kinds of relational information. Child Development, 76(1), 169–181.Google Scholar

Bick, J., & Nelson, C. A. (2017). Early experience and brain development. Wiley Interdisciplinary Reviews: Cognitive Science, 8(1–2), e1387. doi:10.1002/wcs.1387Google Scholar

Bick, J., Zeanah, C. H., Fox, N. A., & Nelson, C. A. (2018). Memory and executive functioning in 12-year-old children with a history of institutional rearing. Child Development, 89(2), 495–508. doi:10.1111/cdev.12952Google Scholar

Bourgeois, J. P. (1997). Synaptogenesis, heterochrony and epigenesis in the mammalian neocortex. Acta Paediatric Supplement, 422, 27–33.Google Scholar

Bourgeois, J. P., & Rakic, P. (1993). Changes of synaptic density in the primary visual cortex of the macaque monkey from fetal to adult stage. Journal of Neuroscience, 13(7), 2801–2820. doi:10.1523/JNEUROSCI.13-07-02801.1993Google Scholar

Cantlon, J. F., Pinel, P., Dehaene, S., & Pelphrey, K. A. (2011). Cortical representations of symbols, objects, and faces are pruned back during early childhood. Cerebal Cortex, 21(1), 191–199. doi:10.1093/cercor/bhq078Google Scholar

Cashon, C. H., & Holt, N. A. (2015). Developmental origins of the face inversion effect. In Janette, B. B. (Ed.), Advances in child development and behaviour (Vol. 48, pp. 117–150). Philadelphia, PA: Elsevier.Google Scholar

Cohen, L., Dehaene, S., Naccache, L., Lehéricy, S., Dehaene-Lambertz, G., Hénaff, M. -A., & Michel, F. (2000). The visual word form area: Spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients. Brain, 123(2), 291–307. doi:10.1093/brain/123.2.291Google Scholar

Conel, J. L. (1939–67). Postnatal development of the human cerebral cortex (Vols. 1–8). Cambridge, MA: Harvard University Press.Google Scholar

Conel, J. L. (1951). The postnatal development of the human cerebral cortex. Vol. 6: The cortex of the six-month infant. Cambridge, MA: Harvard University Press.Google Scholar

Conel, J. L. (1967). The postnatal development of the human cerebral cortex. Vol. 8: The cortex of the six-year-old child. Cambridge, MA: Harvard University Press.Google Scholar

Conte, S., & Richards, J. E. (2019). The development of face-sensitive cortical processing in early Infancy. Paper presented at the Society for Research in Child Development, Baltimore, MD.Google Scholar

Conte, S., Richards, J. E., Guy, M. W., Zieber, N., Xie, W., & Roberts, J.E. (2020). Face-sensitive brain responses in the first year of life. NeuroImage, 211, 116602. https://doi.org/10.1016/j.neuroimage.2020.116602 Google Scholar

de Haan, M., Pascalis, O., & Johnson, M. H. (2002). Specialization of neural mechanisms underlying face recognition in human infants. Journal of Cognitive Neuroscience, 14(2), 199–209. doi:10.1162/089892902317236849Google Scholar

Dean, D. C., III, O’Muircheartaigh, J., Dirks, H., Travers, B. G., Adluru, N., Alexander, A. L., & Deoni, S. C. L. (2016). Mapping an index of the myelin g-ratio in infants using magnetic resonance imaging. Neuroimage, 132, 225–237. doi:10.1016/j.neuroimage.2016.02.040Google Scholar

Dean, D. C., III, O’Muircheartaigh, J., Dirks, H., Waskiewicz, N., Lehman, K., Walker, L., … Deoni, S. C. L. (2014). Modeling healthy male white matter and myelin development: 3 through 60 months of age. Neuroimage, 84, 742–752. doi:10.1016/j.neuroimage.2013.09.058Google Scholar

Dean, D. C., III, O’Muircheartaigh, J., Dirks, H., Waskiewicz, N., Lehman, K., Walker, L., (2015). Estimating the age of healthy infants from quantitative myelin water fraction maps. Human Brain Mapping, 36(4), 1233–1244. doi:10.1002/hbm.22671Google Scholar

Dean, D. C., III, O’Muircheartaigh, J., Dirks, H., Waskiewicz, N., Walker, L., Doernberg, E., … Deoni, S. C. L. (2015). Characterizing longitudinal white matter development during early childhood. Brain Structure & Function, 220(4), 1921–1933. doi:10.1007/s00429-014-0763-3Google Scholar

Dehaene, S., Le Clec’H, G., Poline, J.-B., Le Bihan, D., & Cohen, L. (2002). The visual word form area: A prelexical representation of visual words in the fusiform gyrus. Neuroreport, 13(3), 321–325.Google Scholar

Dehaene, S., Pegado, F., Braga, L. W., Ventura, P., Nunes Filho, G., Jobert, A., … Cohen, L. (2010). How learning to read changes the cortical networks for vision and language. Supplemental Info. Science, 330(6009), 1359–1364. doi:10.1126/science.1194140Google Scholar

Deoni, S. C. L., Dean, D. C., III, O’Muircheartaigh, J., Dirks, H., & Jerskey, B. A. (2012). Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. Neuroimage, 63(3), 1038–1053. doi:10.1016/j.neuroimage.2012.07.037Google Scholar

Deoni, S. C. L., Dean, D. C., III, Remer, J., Dirks, H., & O’Muircheartaigh, J. (2015). Cortical maturation and myelination in healthy toddlers and young children. Neuroimage, 115, 147–161. doi:10.1016/j.neuroimage.2015.04.058Google Scholar

Deoni, S. C. L., Mercure, E., Blasi, A., Gasston, D., Thomson, A., Johnson, M., … Murphy, D. G. M. (2011). Mapping infant brain myelination with magnetic resonance imaging. Journal of Neuroscience, 31(2), 784–791. doi:10.1523/JNEUROSCI.2106–10.2011Google Scholar

Deoni, S. C. L., Peters, T. M., & Rutt, B. K. (2005). High-resolution T1 and T2 mapping of the brain in a clinically acceptable time with DESPOT1 and DESPOT2. Magnetic Resonance in Medicine, 53(1), 237–241. doi:10.1002/mrm.20314Google Scholar

Deoni, S. C. L., Rutt, B. K., Arun, T., Pierpaoli, C., & Jones, D. K. (2008). Gleaning multicomponent T1 and T2 information from steady-state imaging data. Magnetic Resonance in Medicine, 60(6), 1372–1387. doi:10.1002/mrm.21704Google Scholar

Deoni, S. C. L., Rutt, B. K., & Peters, T. M. (2003). Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state. Magnetic Resonance in Medicine, 49(3), 515–526. doi:10.1002/mrm.10407Google Scholar

Deoni, S. C. L., Rutt, B. K., (2006). Synthetic T1-weighted brain image generation with incorporated coil intensity correction using DESPOT1. Magnetic Resonance Imaging, 24(9), 1241–1248. doi:10.1016/j.mri.2006.03.015Google Scholar

DeSilva, J. M., & Lesnik, J. J. (2008). Brain size at birth throughout human evolution: A new method for estimating neonatal brain size in hominins. Journal of Human Evolution, 55(6), 1064–1074. https://doi.org/10.1016/j.jhevol.2008.07.008 Google Scholar

Eimer, M., Gosling, A., Nicholas, S., & Kiss, M. (2011). The N170 component and its links to configural face processing: A rapid neural adaptation study. Brain Research, 1376, 76–87. doi:10.1016/j.brainres.2010.12.046Google Scholar

Fox, S. E., Levitt, P., & Nelson, C. A. (2010). How the timing and quality of early experiences influence the development of brain architecture. Child Development, 81(1), 28–40. doi:10.1111/j.1467-8624.2009.01380.xGoogle Scholar

Gao, C., Conte, S., Richards, J.E., Xie, W., & Hanayik, T. (2019). The neural sources of N170: Understanding timing of activation in face-selective areas. Psychophysiology, 56(6), e1336.Google Scholar

Greenough, W. T., Black, J. E., & Wallace, C. S. (1987). Experience and brain development. Child Development, 58(3), 539–559.Google Scholar

Guy, M. W., Richards, J. E., Tonnsen, B. L., & Roberts, J. E. (2017). Neural correlates of face processing in etiologically-distinct 12-month-old infants at high risk of autism spectrum disorder. Developmental Cognitive Neuroscience, 29, 61–71. doi:10.1016/j.dcn.2017.03.002Google Scholar

Guy, M. W., Zieber, N., & Richards, J. E. (2016). The cortical development of specialized face processing in infancy. Child Development, 87(5), 1581–1600. doi:10.1111/cdev.12543Google Scholar

Hackman, D. A., & Farah, M. J. (2009). Socioeconomic status and the developing brain. Trends in Cognitive Sciences, 13(2), 65–73. https://doi.org/10.1016/j.tics.2008.11.003 Google Scholar

Hair, N. L., Hanson, J. L., Wolfe, B. L., & Pollak, S. D. (2015). Association of child poverty, brain development, and academic achievement. JAMA Pediatrics, 169(9), 822–829. doi:10.1001/jamapediatrics.2015.1475Google Scholar

Halit, H., de Haan, M., & Johnson, M. H. (2003). Cortical specialisation for face processing: Face-sensitive event-related potential components in 3- and 12-month-old infants. Neuroimage, 19(3), 1180–1193. doi:10.1016/S1053-8119(03)00076-4Google Scholar

Hanson, J. L., Chandra, A., Wolfe, B. L., & Pollak, S. D. (2011). Association between income and the hippocampus. PLoS One, 6(5), e18712. doi:10.1371/journal.pone.0018712Google Scholar

Hanson, J. L., Chung, M. K., Avants, B. B., Rudolph, K. D., Shirtcliff, E. A., Gee, J. C., … Pollak, S. D. (2012). Structural variations in prefrontal cortex mediate the relationship between early childhood stress and spatial working memory. Journal of Neuroscience, 32(23), 7917–7925. doi:10.1523/JNEUROSCI.0307-12.2012Google Scholar

Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D. (2013). Family poverty affects the rate of human infant brain growth. PLoS One, 8(12), e80954. doi:10.1371/journal.pone.0080954Google Scholar

Hayden, A., Bhatt, R. S., Reed, A., Corbly, C. R., & Joseph, J. E. (2007). The development of expert face processing: are infants sensitive to normal differences in second-order relational information? Journal of Experimental Child Psychology, 97(2), 85–98. doi:10.1016/j.jecp.2007.01.004Google Scholar

Hoehl, S., & Peykarjou, S. (2012). The early development of face processing: What makes faces special? Neuroscience Bulletin, 28(6), 765–788. doi:10.1007/s12264-012-1280-0Google Scholar

Huttenlocher, P. R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28(6), 517–527.Google Scholar

Huttenlocher, P. R. (1994). Synaptogenesis, synapse elimination, and neural plasticity in human cerebral cortex. In Nelson, C. A. (Ed.), Threats to optimal development, the Minnesota symposia on child psychology (Vol. 27, pp. 35–54). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

Huttenlocher, P. R., & Dabholkar, A. S. (1997). Regional differences in synaptogenesis in human cerebral cortex. Journal of Comparative Neurology, 387(2), 167–178. doi:10.1002/(SICI)1096–9861(19971020)387:2<167::AID-CNE1>3.0.CO;2-ZGoogle Scholar

Jensen, S. K. G., Berens, A. E., & Nelson, C. A., III (2017). Effects of poverty on interacting biological systems underlying child development. Lancet Child & Adolescent Health, 1(3), 225–239. doi:10.1016/S2352-4642(17)30024-XGoogle Scholar

Johnson, M. H., Griffin, R., Csibra, G., Halit, H., Farroni, T., de Haan, M., … Richards, J. (2005). The emergence of the social brain network: Evidence from typical and atypical development. Development and Psychopathology, 17(3), 599–619. doi:10.1017/S0954579405050297Google Scholar

Johnson, M. H., & Morton, J. (1991). Biology and cognitive development: The case of face recognition. Oxford: Basil Blackwell.Google Scholar

Johnson, M. H., Senju, A., & Tomalski, P. (2014). The two-process theory of face processing: Modifications based on two decades of data from infants and adults. Neuroscience Biobehaviour Review. doi:10.1016/j.neubiorev.2014.10.009Google Scholar

Johnson, S. B., Riis, J. L., & Noble, K. G. (2016). State of the art review: Poverty and the developing brain. Pediatrics, 137(4). doi:10.1542/peds.2015–3075Google Scholar

Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17(11), 4302–4311.Google Scholar

Kanwisher, N., & Yovel, G. (2006). The fusiform face area: A cortical region specialized for the perception of faces. Philosophical Transactions of the Royal Society B: Biological Sciences, 361(1476), 2109–2128. doi:10.1098/rstb.2006.1934Google Scholar

Klingberg, T. (2008). White matter maturation and cognitive development during childhood. In Nelson, C. A. & Luciana, M. (Eds.), Handbook of developmental cognitive neuroscience (2nd ed., pp. 237–244). Cambridge, MA: MIT Press.Google Scholar

Klingberg, T. (2010). Training and plasticity of working memory. Trends in Cognitive Science, 14(7), 317–324. doi:10.1016/j.tics.2010.05.002Google Scholar

Kolb, B., & Fantie, B. (1989). Development of the child's brain and behavior. In Reynolds, C. R. & Fletcher-Janzen, E. (Eds.), Handbook of clinical child neuropsychology (pp. 17–39). New York, NY: Plenum Press.Google Scholar

Kral, A. (2007). Unimodal and cross-modal plasticity in the “deaf” auditory cortex. International Journal of Audiology, 46(9), 479–493.Google Scholar

Lebel, C., & Deoni, S. (2018). The development of brain white matter microstructure. Neuroimage, 182, 207–218. https://doi.org/10.1016/j.neuroimage.2017.12.097 Google Scholar

Leijser, L. M., Siddiqi, A., & Miller, S. P. (2018). Imaging evidence of the effect of socio-economic status on brain structure and development. Seminars in Pediatric Neurology, 27, 26–34. doi: https://doi.org/10.1016/j.spen.2018.03.004 Google Scholar

Luby, J., Belden, A., Botteron, K., Marrus, N., Harms, M. P., Bapp, C., … Barch, D. (2013). The effects of poverty on childhood brain development: The mediating effect of caregiving and stressful life events. JAMA Pediatrics, 167(12), 1135–1142. doi:10.1001/jamapediatrics.2013.3139Google Scholar

Lyall, A. E., Savadjiev, P., Shenton, M. E., & Kubicki, M. (2016). Insights into the brain: Neuroimaging of brain development and maturation. Journal of Neuroimaging in Psychiatry & Neurology, 1(1), 10–19. doi:10.17756/jnpn.2016-003Google Scholar

Marshall, P. J., Bar-Haim, Y., & Fox, N. A. (2002). Development of the EEG from 5 months to 4 years of age. Clinical Neurophysiology, 113(8), 1199–1208.Google Scholar

Marshall, P. J., Fox, N. A., & CoreGroup, T. B. (2004). A comparison of the electroencephalogram between institutionalized and community children in Romania. Journal of Cognitive Neuroscience, 16(8), 1327–1338. doi:10.1162/0898929042304723Google Scholar

Marshall, P. J., Reeb, B. C., Fox, N. A., Nelson, C. A., III, & Zeanah, C. H. (2008). Effects of early intervention on EEG power and coherence in previously institutionalized children in Romania. Development and Psychopathology, 20(3), 861–880. doi:10.1017/S0954579408000412Google Scholar

Maurer, D., Le Grand, R., & Mondloch, C. J. (2002). The many faces of configural processing. Trends in Cognitive Sciences, 6(5), 6.Google Scholar

McEwen, B. S., & Gianaros, P. J. (2010). Central role of the brain in stress and adaptation: Links to socioeconomic status, health, and disease. Annals of the New York Academy of Sciences, 1186(1), 190–222. doi:10.1111/j.1749-6632.2009.05331.xGoogle Scholar

McLaughlin, K. A., Sheridan, M. A., & Nelson, C. A. (2017). Neglect as a violation of species-expectant experience: Neurodevelopmental consequences. Biological Psychiatry, 82(7), 462–471. doi:10.1016/j.biopsych.2017.02.1096Google Scholar

Morton, J., & Johnson, M. H. (1991). CONSPEC and CONLERN: A two-process theory of infant face recognition. Psychological Review, 63, 1743–1753.Google Scholar

Moulson, M. C., Westerlund, A., Fox, N. A., Zeanah, C. H., & Nelson, C. A. (2009). The effects of early experience on face recognition: An event-related potential study of institutionalized children in Romania. Child Development, 80(4), 1039–1056.Google Scholar

Nagy, Z., Westerberg, H., & Klingberg, T. (2004). Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of Cognitive Neuroscience, 16(7), 1227–1233. doi:10.1162/0898929041920441Google Scholar

O’Hare, E. D., & Sowell, E. R. (2008). Imaging developmental changes in gray and white matter in the human brain. In Nelson, C. A. & Luciana, M. (Eds.), Handbook of developmental cognitive neuroscience (2nd ed., pp. 23–38). Cambridge, MA: MIT Press.Google Scholar

O’Muircheartaigh, J., Dean, D. C., III, Ginestet, C. E., Walker, L., Waskiewicz, N., Lehman, K., … Deoni, S. C. L. (2014). White matter development and early cognition in babies and toddlers. Human Brain Mapping, 35(9), 4475–4487. doi:10.1002/hbm.22488Google Scholar

Parker, S. W., Nelson, C. A., & Group, T. B. E. I. P. C. (2005a). An event-related potential study of the impact of institutional rearing on face recognition. Development and Psychopathology, 17, 621–639.Google Scholar

Parker, S. W., Nelson, C. A., (2005b). The impact of early institutional rearing on the ability to discriminate facial expressions of emotion: An event-related potential study. Child Development, 76(1), 54–72. doi:10.1111/j.1467-8624.2005.00829.xGoogle Scholar

Pavlakis, A. E., Noble, K., Pavlakis, S. G., Ali, N., & Frank, Y. (2015). Brain imaging and electrophysiology biomarkers: Is there a role in poverty and education outcome research? Pediatric Neurology, 52(4), 383–388. https://doi.org/10.1016/j.pediatrneurol.2014.11.005 Google Scholar

Pollak, S. D., Nelson, C. A., Schlaak, M. F., Roeber, B. J., Wewerka, S. S., Wiik, K. L., … Gunnar, M. R. (2010). Neurodevelopmental effects of early deprivation in postinstitutionalized children. Child Development, 81(1), 224–236. doi:10.1111/j.1467-8624.2009.01391.xGoogle Scholar

Pujol, J., Soriano-Mas, C., Ortiz, H., Sebastián-Gallés, N., Losilla, J. M., & Deus, J. (2006). Myelination of language-related areas in the developing brain. Neurology, 66(3), 339–343. doi:https://doi.org/10.1212/01.wnl.0000201049.66073.8d Google Scholar

Reinholz, J., & Pollmann, S. (2005). Differential activation of object-selective visual areas by passive viewing of pictures and words. Brain Research: Cognitive Brain Research, 24(3), 702–714. doi:10.1016/j.cogbrainres.2005.04.009Google Scholar

Remer, J., Croteau-Chonka, E., Dean, D. C., III, D’Arpino, S., Dirks, H., Whiley, D., & Deoni, S. C. L. (2017). Quantifying cortical development in typically developing toddlers and young children, 1–6 years of age. Neuroimage, 153, 246–261. https://doi.org/10.1016/j.neuroimage.2017.04.010 Google Scholar

Richards, J. E., Guy, M., Zieber, N., Xie, W., & Roberts, J. E. (2016). Brain changes in response to faces in the first year. Poster presented at the International Conference on Infant Studies, New Orleans, LA.Google Scholar

Richards, J. E., Guy, M., Zieber, N., Xie, W., (2017). Brain changes in response to faces in the first year. Paper presented at the Society for Research in Child Development, Austin, TX.Google Scholar

Richards, J. E., Sanchez, C., Phillips-Meek, M., & Xie, W. (2016). A database of age-appropriate average MRI templates. Neuroimage, 124(Pt. B), 1254–1259. doi:10.1016/j.neuroimage.2015.04.055Google Scholar

Richards, J. E., & Xie, W. (2015). Brains for all the ages: Structural neurodevelopment in infants and children from a life-span perspective. In Benson, J. (Ed.), Advances in Child Development and Behaviour (Vol. 48, pp. 1–52). Philadelphia, PA: Elsevier.Google Scholar

Rosenberg, K., & Trevathan, W. (2002). Birth, obstetrics and human evolution. BJOG: An International Journal of Obstetrics and Gynaecology, 109(11), 1199–1206. https://doi.org/10.1016/S1470-0328(02)00410-X Google Scholar

Scott, L. S., & Monesson, A. (2009). The origin of biases in face perception. Psychological Science, 20(6), 676–680. doi:10.1111/j.1467-9280.2009.02348.xGoogle Scholar

Scott, L. S., (2010). Experience-dependent neural specialization during infancy. Neuropsychologia, 48(6), 1857–1861. doi:10.1016/j.neuropsychologia.2010.02.008Google Scholar

Scott, L. S., & Nelson, C. A. (2006). Featural and configural face processing in adults and infants: A behavioral and electrophysiological investigation. Perception, 35(8), 1107–1128. doi:10.1068/p5493Google Scholar

Shankle, W. R., Romney, A. K., Landing, B. H., & Hara, J. (1998). Developmental patterns in the cytoarchitecture of the human cerebral cortex from birth to 6 years examined by correspondence analysis. Proceedings of the National Academy of Sciences of the United States of America, 95(7), 4023–4028.Google Scholar

Sheridan, M. A., Fox, N. A., Zeanah, C. H., McLaughlin, K. A., & Nelson, C. A. (2012). Variation in neural development as a result of exposure to institutionalization early in childhood. Proceedings of the National Academy of Sciences of the United States of America, 109(32), 12927–12932. doi:10.1073/pnas.1200041109Google Scholar

Simion, F., & Giorgio, E. D. (2015). Face perception and processing in early infancy: inborn predispositions and developmental changes. Frontiers in Psychology, 6, 969. doi:10.3389/fpsyg.2015.00969Google Scholar

Simion, F., Leo, I., Turati, C., Valenza, E., & Dalla Barba, B. (2007). How face specialization emerges in the first months of life. Progressive Brain Research, 164, 169–185. doi:10.1016/S0079-6123(07)64009-6Google Scholar

Smyke, A. T., Zeanah, C. H., Fox, N. A., Nelson, C. A., & Guthrie, D. (2010). Placement in foster care enhances quality of attachment among young institutionalized children. Child Development, 81(1), 212–223. doi:10.1111/j.1467-8624.2009.01390.xGoogle Scholar

Sowell, E. R., Thompson, P. M., & Toga, A. W. (2004). Mapping changes in the human cortex throughout the span of life. Neuroscientist, 10(4), 372–392. doi:10.1177/1073858404263960Google Scholar

Spader, H. S., Ellermeier, A., O’Muircheartaigh, J., Dean, D. C., III, Dirks, H., Boxerman, J. L., … Deoni, S. C. L. (2013). Advances in myelin imaging with potential clinical application to pediatric imaging. Neurosurgical Focus, 34(4), e9. doi:10.3171/2013.1.FOCUS12426Google Scholar

Stiles, J. (2017). Principles of brain development. Wiley Interdisciplinary Reviews: Cognitive Science, 8(1–2). doi:10.1002/wcs.1402Google Scholar

Stiles, J., & Jernigan, T. L. (2010). The basics of brain development. Neuropsychology Review, 20(4), 327–348. doi:10.1007/s11065-010-9148-4Google Scholar

Symms, M., Jager, H. R., Schmierer, K., & Yousry, T. A. (2004). A review of structural magnetic resonance neuroimaging. Journal of Neurology, Neurosurgery, and Psychiatry, 75(9), 1235–1244. doi:10.1136/jnnp.2003.032714Google Scholar

Toga, A. W., Thompson, P. M., & Sowell, E. R. (2006). Mapping brain maturation. Trends in Neurosciences, 29(3), 148–159. doi:10.1016/j.tins.2006.01.007Google Scholar

Uda, S., Matsui, M., Tanaka, C., Uematsu, A., Miura, K., Kawana, I., & Noguchi, K. (2015). Normal development of human brain white matter from infancy to early adulthood: A diffusion tensor imaging study. Journal of Developmental Neuroscience, 37(2), 182–194. doi:10.1159/000373885Google Scholar

Valentine, T. (1988). Upside-down faces: A review of the effect of inversion upon face recognition. British Journal of Psychology, 79(Pt. 4), 471–491.Google Scholar

Vanderwert, R. E., Marshall, P. J., Nelson, C. A., Zeanah, C. H., & Fox, N. A. (2010). Timing of intervention affects brain electrical activity in children exposed to severe psychosocial neglect. PLoS One, 5(7), e11415. doi:10.1371/journal.pone.0011415Google Scholar

Vanderwert, R. E., Zeanah, C. H., Fox, N. A., & Nelson, C. A. (2016). Normalization of EEG activity among previously institutionalized children placed into foster care: A 12-year follow-up of the Bucharest Early Intervention Project. Developmental Cognitive Neuroscience, 17, 68–75. https://doi.org/10.1016/j.dcn.2015.12.004 Google Scholar

Vogel, M., Monesson, A., & Scott, L. S. (2012). Building biases in infancy: The influence of race on face and voice emotion matching. Developmental Science, 15(3), 359–372. doi:10.1111/j.1467-7687.2012.01138.xGoogle Scholar

Xie, W., & Richards, J. E. (2016). Effects of interstimulus intervals on behavioral, heart rate, and event-related potential indices of infant engagement and sustained attention. Psychophysiology, 53(8), 1128–1142. doi:10.1111/psyp.12670Google Scholar

Zeanah, C. H., Nelson, C. A., Fox, N. A., Smyke, A. T., Marshall, P., Parker, S. W., & Koga, S. (2003). Designing research to study the effects of institutionalization on brain and behavioral development: The Bucharest Early Intervention Project. Development and Psychopathology, 15(4), 885–907.Google Scholar

References

Asperger, H. (1944). Die “Autistischen Psychopathen” im Kindesalter. Archiv für Psychiatrie und Nervenkrankheiten, 117, 76–136.Google Scholar

Baranek, G. T. (1999). Autism during infancy: A retrospective video analysis of sensory-motor and social behaviors at 9–12 months of age. Journal of Autism and Developmental Disorders, 29(3), 213–224.Google Scholar

Bedford, R., Elsabbagh, M., Gliga, T., Pickles, A., Senju, A., Charman, T., & Johnson, M. (2012). Precursors to social and communication difficulties in infants at-risk for autism: Gaze following and attentional engagement. Journal of Autism and Developmental Disorders, 42(10), 2208–2218. doi:10.1007/s10803-012-1450-yGoogle Scholar

Bedford, R., Jones, E. J., Johnson, M. H., Pickles, A., Charman, T., & Gliga, T. (2016). Sex differences in the association between infant markers and later autistic traits. Molecular Autism, 7(1), 21.Google Scholar

Blasi, A., Lloyd-Fox, S., Sethna, V., Brammer, M. J., Mercure, E., Murray, L., … Johnson, M. H. (2015). Atypical processing of voice sounds in infants at risk for autism spectrum disorder. Cortex, 71, 122–133.Google Scholar

Bölte, S., Tomalski, P., Marschik, P. B., Berggren, S., Norberg, J., Falck-Ytter, T., … Roeyers, H. (2016). Challenges and inequalities of opportunities in european psychiatry research. European Journal of Psychological Assessment, 34(4), 270–277.Google Scholar

Braukmann, R., Lloyd-Fox, S., Blasi, A., Johnson, M. H., Bekkering, H., Buitelaar, J. K., & Hunnius, S. (2018). Diminished socially selective neural processing in 5-month-old infants at high familial risk of autism. European Journal of Neuroscience, 47(6), 720–728.Google Scholar

Brian, J., Bryson, S. E., Garon, N., Roberts, W., Smith, I. M., Szatmari, P., & Zwaigenbaum, L. (2008). Clinical assessment of autism in high-risk 18-month-olds. Autism, 12(5), 433–456. doi:10.1177/1362361308094500Google Scholar

Brisson, J., Warreyn, P., Serres, J., Foussier, S., & Adrien-Louis, J. (2012). Motor anticipation failure in infants with autism: A retrospective analysis of feeding situations. Autism, 16(4), 420–429.Google Scholar

Bryson, S. E., Zwaigenbaum, L., Brian, J., Roberts, W., Szatmari, P., Rombough, V., & McDermott, C. (2007). A prospective case series of high-risk infants who developed autism. Journal of Autism and Developmental Disorders, 37(1), 12–24. doi:10.1007/s10803-006-0328-2Google Scholar

Bussu, G., Jones, E. J., Charman, T., Johnson, M. H., Buitelaar, J., & Team, B. (2018). Prediction of autism at 3 years from behavioural and developmental measures in high-risk infants: A longitudinal cross-domain classifier analysis. Journal of Autism and Developmental Disorders, 48, 2418–2433.Google Scholar

Chawarska, K., Macari, S., & Shic, F. (2013). Decreased spontaneous attention to social scenes in 6-month-old infants later diagnosed with autism spectrum disorders. Biological Psychiatry, 74(3), 195–203. doi:10.1016/j.biopsych.2012.11.022Google Scholar

Chawarska, K., Shic, F., Macari, S., Campbell, D. J., Brian, J., Landa, R., … Bryson, S. (2014). 18-month predictors of later outcomes in younger siblings of children with autism spectrum disorder: A baby siblings research consortium study. Journal of the American Academy of Child and Adolescent Psychiatry, 53(12), 1317–1327. doi:10.1016/j.jaac.2014.09.015Google Scholar

Clifford, S. M., Hudry, K., Elsabbagh, M., Charman, T., Johnson, M. H., & Team, B. (2013). Temperament in the first 2 years of life in infants at high-risk for autism spectrum disorders. Journal of Autism and Developmental Disorders, 43(3), 673–686.Google Scholar

Daluwatte, C., Miles, J., Sun, J., & Yao, G. (2015). Association between pupillary light reflex and sensory behaviors in children with autism spectrum disorders. Research in Developmental Disabilities, 37, 209–215.Google Scholar

Dawson, G., Osterling, J., Meltzoff, A. N., & Kuhl, P. (2000). Case study of the development of an infant with autism from birth to two years of age. Journal of Applied Developmental Psychology, 21(3), 299–313.Google Scholar

Ekberg, T. L., Falck-Ytter, T., Bölte, S., & Gredebäck, G. (2015). Reduced prospective motor control in 10-month-olds at risk for autism spectrum disorder. Clinical Psychological Science, 4(1), 129–135. https://doi.org/10.1177/2167702615576697 Google Scholar

Elison, J. T., Paterson, S. J., Wolff, J. J., Reznick, J. S., Sasson, N. J., Gu, H. B., … Network, I. (2013). White matter microstructure and atypical visual orienting in 7-month-olds at risk for autism. American Journal of Psychiatry, 170(8), 899–908. doi:10.1176/appi.ajp.2012.12091150Google Scholar

Elsabbagh, M., Fernandes, J., Webb, S. J., Dawson, G., Charman, T., Johnson, M. H., & British Autism Study of Infant Siblings Team (2013). Disengagement of visual attention in infancy is associated with emerging autism in toddlerhood. Biological Psychiatry, 74(3), 189–194. doi:10.1016/j.biopsych.2012.11.030Google Scholar

Elsabbagh, M., Gliga, T., Pickles, A., Hudry, K., Charman, T., Johnson, M. H., & Team, B. (2013). The development of face orienting mechanisms in infants at-risk for autism. Behavioural Brain Research, 251, 147–154. doi:10.1016/j.bbr.2012.07.030Google Scholar

Elsabbagh, M., Mercure, E., Hudry, K., Chandler, S., Pasco, G., Charman, T., … Team, B. (2012). Infant neural sensitivity to dynamic eye gaze is associated with later emerging autism. Current Biology, 22(4), 338–342. doi:10.1016/j.cub.2011.12.056Google Scholar

Estes, A., Zwaigenbaum, L., Gu, H., John, T. S., Paterson, S., Elison, J. T., … Schultz, R. T. (2015). Behavioral, cognitive, and adaptive development in infants with autism spectrum disorder in the first 2 years of life. Journal of Neurodevelopmental Disorders, 7(1), 24.Google Scholar

Falck-Ytter, T., Nyström, P., Gredebäck, G., Gliga, T., Bölte, S., & Team E (2018). Reduced orienting to audiovisual synchrony in infancy predicts autism diagnosis at 3 years of age. Journal of Child Psychology and Psychiatry, 59(8), 872–880. doi:10.1111/jcpp.12863Google Scholar

Falck-Ytter, T., Rehnberg, E., & Bölte, S. (2013). Lack of visual orienting to biological motion and audiovisual synchrony in 3-year-olds with autism. Plos One, 8(7). doi:e6881610.1371/journal.pone.0068816Google Scholar

Flanagan, J. E., Landa, R., Bhat, A., & Bauman, M. (2012). Head lag in infants at risk for autism: A preliminary study. American Journal of Occupational Therapy, 66(5), 577–585.Google Scholar

Gammer, I., Bedford, R., Elsabbagh, M., Garwood, H., Pasco, G., Tucker, L., … Team, B. (2015). Behavioural markers for autism in infancy: Scores on the Autism Observational Scale for infants in a prospective study of at-risk siblings. Infant Behavior and Development, 38, 107–115.Google Scholar

Green, J., Pickles, A., Pasco, G., Bedford, R., Wan, M. W., Elsabbagh, M., … Cheung, C. (2017). Randomised trial of a parent-mediated intervention for infants at high risk for autism: Longitudinal outcomes to age 3 years. Journal of Child Psychology and Psychiatry, 58(12), 1330–1340.Google Scholar

Hallett, V., Ronald, A., Rijsdijk, F., & Happé, F. (2012). Disentangling the associations between autistic-like and internalizing traits: A community based twin study. Journal of Abnormal Child Psychology, 40(5), 815–827.Google Scholar

Haartsen, R., Jones, E. J. H., Orekhova, E., Charman, T., & Johnson, M. H. (2019), Functional EEG connectivity in infants associates with later circumscribed interests in autism: A replication study. Translational Psychiatry, 9(1), 1–14.Google Scholar

Hazlett, H. C., Gu, H., Munsell, B. C., Kim, S. H., Styner, M., Wolff, J. J., … Botteron, K. N. (2017). Early brain development in infants at high risk for autism spectrum disorder. Nature, 542(7641), 348–351.Google Scholar

Hendry, A., Jones, E. J., Bedford, R., Gliga, T., Charman, T., & Johnson, M. H. (2018). Developmental change in look durations predicts later effortful control in toddlers at familial risk for ASD. Journal of Neurodevelopmental Disorders, 10(1), 3.Google Scholar

Hogan, A. L., Caravella, K. E., Ezell, J., Rague, L., Hills, K., & Roberts, J. E. (2017). Autism spectrum disorder symptoms in infants with fragile X syndrome: A prospective case series. Journal of Autism and Developmental Disorders, 47(6), 1628–1644.Google Scholar

Hoshino, Y., Kumashiro, H., Yashima, Y., Tachibana, R., Watanabe, M., & Furukawa, H. (1982). Early symptoms of autistic children and its diagnostic significance. Psychiatry and Clinical Neurosciences, 36(4), 367–374.Google Scholar

Hudry, K., Chandler, S., Bedford, R., Pasco, G., Gliga, T., Elsabbagh, M., … Charman, T. (2014). Early language profiles in infants at high-risk for autism spectrum disorders. Journal of Autism and Developmental Disorders, 44(1), 154–167.Google Scholar

Ibanez, L. V., Grantz, C. J., & Messinger, D. S. (2013). The development of referential communication and autism symptomatology in high-risk infants. Infancy, 18(5), 687–707. doi:10.1111/j.1532-7078.2012.00142.xGoogle Scholar

Jeste, S. S., & Geschwind, D. H. (2014). Disentangling the heterogeneity of autism spectrum disorder through genetic findings. Nature Reviews Neurology, 10(2), 74.Google Scholar

Johnson, M. H. (2005). Subcortical face processing. Nature Reviews Neuroscience, 6(10), 766–774.Google Scholar

Johnson, M. H., Gliga, T., Jones, E., & Charman, T. (2014). Annual research review: Infant development, autism, and ADHD – early pathways to emerging disorders. Journal of Child Psychology and Psychiatry, 56(3), 228–247. https://doi.org/10.1111/jcpp.12328 Google Scholar

Johnson, M. H., Jones, E. J., & Gliga, T. (2015). Brain adaptation and alternative developmental trajectories. Development and Psychopathology, 27(2), 425–442.Google Scholar

Jones, E. J. H., Dawson, G., Kelly, J., Estes, A., & Jane Webb, S. (2017). Parent-delivered early intervention in infants at risk for ASD: Effects on electrophysiological and habituation measures of social attention. Autism Research, 10(5), 961–972.Google Scholar

Jones, E. J. H., Dawson, G., & Webb, S. (2017). Sensory hypersensitivity predicts enhanced attention capture by faces in the early development of ASD. Developmental Cognitive Neuroscience, 29, 11–20.Google Scholar

Jones, E. J. H., Gliga, T., Bedford, R., Charman, T., & Johnson, M. H. (2014). Developmental pathways to autism: A review of prospective studies of infants at risk. Neuroscience and Biobehavioral Reviews, 39, 1–33. doi:10.1016/j.neubiorev.2013.12.001Google Scholar

Jones, W., & Klin, A. (2013). Attention to eyes is present but in decline in 2–6-month-old infants later diagnosed with autism. Nature, 504(7480), 427. doi:10.1038/nature12715Google Scholar

Kanner, L. (1943). Autistic disturbances of affective contact. Nervous Child, 2, 217–250.Google Scholar

Kas, M. J., Glennon, J. C., Buitelaar, J., Ey, E., Biemans, B., Crawley, J., … Talpos, J. (2014). Assessing behavioural and cognitive domains of autism spectrum disorders in rodents: Current status and future perspectives. Psychopharmacology, 231(6), 1125–1146.Google Scholar

Keehn, B., Mueller, R. -A., & Townsend, J. (2013). Atypical attentional networks and the emergence of autism. Neuroscience and Biobehavioral Reviews, 37(2), 164–183. doi:10.1016/j.neubiorev.2012.11.014Google Scholar

Kennedy, D. P., D’Onofrio, B. M., Quinn, P. D., Bölte, S., Lichtenstein, P., & Falck-Ytter, T. (2017). Genetic influence on eye movements to complex scenes at short timescales. Current Biology, 27(22), 3554–3560.Google Scholar

Klin, A., Lin, D. J., Gorrindo, P., Ramsay, G., & Jones, W. (2009). Two-year-olds with autism orient to non-social contingencies rather than biological motion. Nature, 459(7244), 257–261.Google Scholar

Kolesnik, A. M., Jones, E. J. H., Garg, S., Green, J., Charman, T., & Johnson, M. H. (2017). Early development of infants with neurofibromatosis type 1: A case series. Molecular Autism, 8(1), 62.Google Scholar

Landa, R., & Garrett-Mayer, E. (2006). Development in infants with autism spectrum disorders: A prospective study. Journal of Child Psychology and Psychiatry, 47(6), 629–638.Google Scholar

Landa, R. J., Holman, K. C., & Garrett-Mayer, E. (2007). Social and communication development in toddlers with early and later diagnosis of autism spectrum disorders. Archives of General Psychiatry, 64(7), 853–864.Google Scholar

Lazenby, D. C., Sideridis, G. D., Huntington, N., Prante, M., Dale, P. S., Curtin, S., … Dobkins, K. (2016). Language differences at 12 months in infants who develop autism spectrum disorder. Journal of Autism and Developmental Disorders, 46(3), 899–909.Google Scholar

Leppa, V. M., Kravitz, S. N., Martin, C. L., Andrieux, J., Le Caignec, C., Martin-Coignard, D., … Cantor, R. M. (2016). Rare inherited and de novo CNVs reveal complex contributions to ASD risk in multiplex families. American Journal of Human Genetics, 99(3), 540–554.Google Scholar

Lloyd-Fox, S., Begus, K., Halliday, D., Pirazzoli, L., Blasi, A., Papademetriou, M., … Moore, S. (2017). Cortical specialisation to social stimuli from the first days to the second year of life: A rural Gambian cohort. Developmental Cognitive Neuroscience, 25, 92–104.Google Scholar

Lloyd-Fox, S., Blasi, A., Elwell, C. E., Charman, T., Murphy, D., & Johnson, M. H. (2013). Reduced neural sensitivity to social stimuli in infants at risk for autism. Proceedings of the Royal Society B: Biological Sciences, 280(1758), 9. doi:10.1098/rspb.2012.3026Google Scholar

Lloyd-Fox, S., Blasi, A., Pasco, G., Gliga, T., Jones, E., Murphy, D., … Johnson, M. (2017). Cortical responses before 6 months of life associate with later autism. European Journal of Neuroscience, 47(6), 736–749.Google Scholar

Macari, S. L., Campbell, D., Gengoux, G. W., Saulnier, C. A., Klin, A. J., & Chawarska, K. (2012). Predicting developmental status from 12 to 24 months in infants at risk for autism spectrum disorder: A preliminary report. Journal of Autism and Developmental Disorders, 42(12), 2636–2647. doi:10.1007/s10803-012-1521-0Google Scholar

Mitchell, S., Brian, J., Zwaigenbaum, L., Roberts, W., Szatmari, P., Smith, I., & Bryson, S. (2006). Early language and communication development of infants later diagnosed with autism spectrum disorder. Journal of Developmental and Behavioral Pediatrics, 27(2), S69–S78.Google Scholar

Molenhuis, R. T., de Visser, L., Bruining, H., & Kas, M. J. (2014). Enhancing the value of psychiatric mouse models: Differential expression of developmental behavioral and cognitive profiles in four inbred strains of mice. European Neuropsychopharmacology, 24(6), 945–954.Google Scholar

Nyström, P., Gliga, T., Nilsson Jobs, E., Gredebäck, G., Charman, T., Johnson, M., … Falck-Ytter, T. (2018). Enhanced pupillary light reflex in infancy is associated with autism diagnosis in toddlerhood. Nature Communications, 9(1). doi:10.1038/s41467-018-03985-4Google Scholar

Orekhova, E. V., Elsabbagh, M., Jones, E. J., Dawson, G., Charman, T., & Johnson, M. H. (2014). EEG hyper-connectivity in high-risk infants is associated with later autism. Journal of Neurodevelopmental Disorders, 6(1), 40.Google Scholar

Ornitz, E. M., Guthrie, D., & Farley, A. H. (1977). The early development of autistic children. Journal of Autism and Childhood Schizophrenia, 7(3), 207–229.Google Scholar

Ozonoff, S., Iosif, A. M., Baguio, F., Cook, I. C., Hill, M. M., Hutman, T., … Young, G. S. (2010). A prospective study of the emergence of early behavioral signs of autism. Journal of the American Academy of Child and Adolescent Psychiatry, 49(3), 256–266. doi:10.1016/j.jaac.2009.11.009Google Scholar

Paul, R., Fuerst, Y., Ramsay, G., Chawarska, K., & Klin, A. (2011). Out of the mouths of babes: Vocal production in infant siblings of children with ASD. Journal of Child Psychology and Psychiatry, 52(5), 588–598.Google Scholar

Ronald, A., Edelson, L. R., Asherson, P., & Saudino, K. J. (2010). Exploring the relationship between autistic-like traits and ADHD behaviors in early childhood: Findings from a community twin study of 2-year-olds. Journal of Abnormal Child Psychology, 38(2), 185–196. doi:10.1007/s10802-009-9366-5Google Scholar

Ross, R. G., Hunter, S. K., Hoffman, M. C., McCarthy, L., Chambers, B. M., Law, A. J., … Freedman, R. (2016). Perinatal phosphatidylcholine supplementation and early childhood behavior problems: Evidence for CHRNA7 moderation. American Journal of Psychiatry, 173(5), 509–516.Google Scholar

Rozga, A., Hutman, T., Young, G. S., Rogers, S. J., Ozonoff, S., Dapretto, M., & Sigman, M. (2011). Behavioral profiles of affected and unaffected siblings of children with autism: Contribution of measures of mother–infant interaction and nonverbal communication. Journal of Autism and Developmental Disorders, 41(3), 287–301.Google Scholar

Sacrey, L. -A. R., Zwaigenbaum, L., Bryson, S., Brian, J., Smith, I. M., Roberts, W., … Novak, C. (2015). Can parents’ concerns predict autism spectrum disorder? A prospective study of high-risk siblings from 6 to 36 months of age. Journal of the American Academy of Child and Adolescent Psychiatry, 54(6), 470–478.Google Scholar

Shen, M. D., Kim, S. H., McKinstry, R. C., Gu, H., Hazlett, H. C., Nordahl, C. W., … Swanson, M. R. (2017). Increased extra-axial cerebrospinal fluid in high-risk infants who later develop autism. Biological Psychiatry, 82(3), 186–193.Google Scholar

Shen, M. D., Nordahl, C. W., Young, G. S., Wootton-Gorges, S. L., Lee, A., Liston, S. E., … Amaral, D. G. (2013). Early brain enlargement and elevated extra-axial fluid in infants who develop autism spectrum disorder. Brain, 136(9), 2825–2835.Google Scholar

Shephard, E., Bedford, R., Milosavljevic, B., Gliga, T., Jones, E. J. H., Pickles, A., … Bolton, P. (2019). Early developmental pathways to childhood symptoms of attention-deficit hyperactivity disorder, anxiety and autism spectrum disorder. Journal of Child Psychology and Psychiatry, 60(9), 963–974.Google Scholar

St. John, T., Estes, A. M., Dager, S. R., Kostopoulos, P., Wolff, J. J., Pandey, J., … Botteron, K. (2016). Emerging executive functioning and motor development in infants at high and low risk for autism spectrum disorder. Frontiers in Psychology, 7, 1016.Google Scholar

Sullivan, M., Finelli, J., Marvin, A., Garrett-Mayer, E., Bauman, M., & Landa, R. (2007). Response to joint attention in toddlers at risk for autism spectrum disorder: A prospective study. Journal of Autism And Developmental Disorders, 37(1), 37.Google Scholar

Swanson, M. R., Shen, M. D., Wolff, J. J., Elison, J. T., Emerson, R. W., Styner, M. A., … Paterson, S. (2017). Subcortical brain and behavior phenotypes differentiate infants with autism versus language delay. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2(8), 664–672.Google Scholar

Thorup, E., Nystrom, P., Gredeback, G., Bölte, S., Falck-Ytter, T., & EASE Team (2018). Reduced alternating gaze during social interaction in infancy is associated with elevated symptoms of autism in toddlerhood. Journal of Abnormal Child Psychology, 46(7), 1547–1561.Google Scholar

Varcin, K. J., & Jeste, S. S. (2017). The emergence of autism spectrum disorder: Insights gained from studies of brain and behaviour in high-risk infants. Current Opinion in Psychiatry, 30(2), 85–91.Google Scholar

Wan, M. W., Green, J., Elsabbagh, M., Johnson, M., Charman, T., & Plummer, F. (2013). Quality of interaction between at-risk infants and caregiver at 12–15 months is associated with 3-year autism outcome. Journal of Child Psychology and Psychiatry, 54(7), 763–771.Google Scholar

Wass, S. V., Jones, E. J. H., Gliga, T., Smith, T. J., Charman, T., & Johnson, M. H. (2015). Shorter spontaneous fixation durations in infants with later emerging autism. Scientific Reports, 5, 8284. doi:10.1038/srep08284Google Scholar

Webb, S. J., Nalty, T., Munson, J., Brock, C., Abbott, R., & Dawson, G. (2007). Rate of head circumference growth as a function of autism diagnosis and history of autistic regression. Journal of Child Neurology, 22(10), 1182–1190.Google Scholar

West, K. L., Leezenbaum, N. B., Northrup, J. B., & Iverson, J. M. (2019). The relation between walking and language in infant siblings of children with autism spectrum disorder. Child Development, 90(3), e356–e372.Google Scholar

Wolff, J. J., Jacob, S., & Elison, J. T. (2018). The journey to autism: Insights from neuroimaging studies of infants and toddlers. Development And Psychopathology, 30(2), 479–495.Google Scholar

Wolff, J. J., Swanson, M. R., Elison, J. T., Gerig, G., Pruett, J. R., Styner, M. A., … Estes, A. M. (2017). Neural circuitry at age 6 months associated with later repetitive behavior and sensory responsiveness in autism. Molecular Autism, 8(1), 8.Google Scholar

Yoder, P., Stone, W. L., Walden, T., & Malesa, E. (2009). Predicting social impairment and ASD diagnosis in younger siblings of children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 39(10), 1381–1391. doi:10.1007/s10803-009-0753-0Google Scholar

Zwaigenbaum, L., Bryson, S., Rogers, T., Roberts, W., Brian, J., & Szatmari, P. (2005). Behavioral manifestations of autism in the first year of life. International Journal Of Developmental Neuroscience, 23(2–3), 143–152.Google Scholar

Zwaigenbaum, L., Thurm, A., Stone, W., Baranek, G., Bryson, S., Iverson, J., … Sigman, M. (2007). Studying the emergence of autism spectrum disorders in high-risk infants: Methodological and practical issues. Journal of Autism and Developmental Disorders, 37(3), 466–480.Google Scholar

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Part I - Foundations

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