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Individual differences in non-adjacent statistical dependency learning in infants

Published online by Cambridge University Press:  13 June 2019

Department of Psychology, University of Notre Dame, USA
Department of Psychology, University of Notre Dame, USA
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There is considerable controversy over the factors that shape infants’ developing knowledge of grammar. Work with artificial languages suggests that infants’ ability to track statistical regularities within the speech they hear could, in principle, support grammatical development. However, little work has tested whether infants’ performance on laboratory tasks reflects factors that are relevant in real-world language learning. Here we tested whether the language that infants hear at home, and their receptive language skills, predict their performance on tasks assessing the ability to learn non-adjacent statistical dependencies (NADs) at 15 months, and whether that in turn predicts sensitivity to native-language NADs at 18 months. We found evidence for some (though not all) of these relations, and primarily for females. The results suggest that performance on the artificial language-learning task reveals something about the mechanisms of grammatical development, and that females and males may be learning NADs differently.

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Bates, E., Bretherton, I., & Snyder, L. S. (1991). From first words to grammar: individual differences and dissociable mechanisms (Vol. 20). Cambridge University Press.Google Scholar
Bayley, N. (2006). Bayley scales of infant and toddler development: administration manual (3rd ed.). Psychorp.Google Scholar
Beech, J. R., & Beauvois, M. W. (2006). Early experience of sex hormones as a predictor of reading, phonology, and auditory perception. Brain and Language, 96(1), 4958.CrossRefGoogle ScholarPubMed
Cartwright, T. A., & Brent, M. R. (1997). Syntactic categorization in early language acquisition: formalizing the role of distributional analysis. Cognition, 63, 121–70.CrossRefGoogle ScholarPubMed
Christiansen., M. H., Onnis, L., & Hockema, S. A. (2009). The secret is in the sound: from unsegmented speech to lexical categories. Developmental Science, 12, 388–95.CrossRefGoogle ScholarPubMed
Christophe, A., Millotte, S., Bernal, S., & Lidz, J. (2008). Bootstrapping lexical and syntactic acquisition. Language and Speech, 51 (1/2), 6175.CrossRefGoogle ScholarPubMed
Culbertson, J., Koulaguina, E., Gonzalez-Gómez, N., batesdre, G., & Nazzi, T. (2016). Developing knowledge of nonadjacent dependencies. Developmental Psychology, 52, 2174–83.CrossRefGoogle ScholarPubMed
Fisher, C., & Tokura, H. (1996). Acoustic cues to grammatical structure in infant-directed speech: cross-linguistic evidence. Child Development, 67, 3192–218.CrossRefGoogle ScholarPubMed
Friederici, A. D., Mueller, J. L., & Oberecker, R. (2011). Precursors to natural grammar learning: preliminary evidence from 4-month-old infants. PLoS One, 6 (3), e17920.CrossRefGoogle ScholarPubMed
Friederici, A. D., Pannekamp, A., Partsch, C., Ulmen, U., Oehler, K., Schmutzler, R., & Hesse, V. (2008). Sex hormone testosterone affects language organization in the infant brain. Cognitive Neuroscience and Neuropsychology, 19, 283–6.Google ScholarPubMed
Gómez, R. L. (2002). Variability and detection of invariant structure. Psychological Science, 13, 431–6.CrossRefGoogle ScholarPubMed
Gomez, R. L., & Gerken, L. (1999). Artificial grammar learning by 1-year-olds leads to specific and abstract knowledge. Cognition, 70 (2), 109–35.CrossRefGoogle ScholarPubMed
Gómez, R. L., & Lakusta, L. (2004). A first step in form-based category abstraction in 12-month-old infants. Developmental Science, 7, 567–80.CrossRefGoogle ScholarPubMed
Gómez, R. L., & Maye, J. (2005). The developmental trajectory of nonadjacent dependency learning. Infancy, 7, 183206.CrossRefGoogle Scholar
Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: P.H. Brookes.Google Scholar
Höhle, B., Schmitz, M., Santelmann, L. M., & Weissenborn, J. (2006). The recognition of discontinuous verbal dependencies by German 19-month-olds: evidence for lexical and structural influences on children's early processing capacities. Language Learning and Development, 2, 277300.CrossRefGoogle Scholar
Hunter, M. A., & Ames, E. W. (1988). A multifactor model of infant preferences for novel and familiar stimuli. Advances in Infancy Research, 5, 6995.Google Scholar
Huttenlocher, J., Waterfall, H., Vasilyeva, M., Vevea, J., & Hedges, L. V. (2010). Sources of variability in children's language growth. Cognitive Psychology, 61(4), 343–65.CrossRefGoogle ScholarPubMed
Jusczyk, P. W., Hirsh-Pasek, K., Nelson, D. G. K., Kennedy, L. J., Woodward, A., & Piwoz, J. (1992). Perception of acoustic correlates of major phrasal units by young infants. Cognitive Psychology, 24(2), 252–93.CrossRefGoogle ScholarPubMed
Kitamura, C., & Burnham, D. (2003). Pitch and communicative intent and mother's speech: adjustments for age and sex in the first year. Infancy, 4, 85110.CrossRefGoogle Scholar
Kitamura, C., Thanavishuth, C., Burnham, D., & Luksaneeyanawin, S. (2002). Universality and specificity in infant-directed speech: pitch modifications as a function of infant age and sex in a tonal and non-tonal language. Infant Behavior and Development, 24, 372–92.CrossRefGoogle Scholar
Kuhl, P. K., Williams, K. A., Lacerda, F., Stevens, K. N., & Lindblom, B. (1992). Linguistic experience alters phonetic perception in infants by 6 months of age. Science, 255, 606–8.CrossRefGoogle ScholarPubMed
Lany, J. (2014). Judging words by their covers and the company they keep: probabilistic cues support word learning. Child Development, 85, 1727–39.CrossRefGoogle ScholarPubMed
Lany, J., & Gómez, R. L. (2008). Twelve-month-old infants benefit from prior experience in statistical learning. Psychological Science, 19, 1247–52.CrossRefGoogle ScholarPubMed
Lany, J., & Saffran, J. R. (2010). From statistics to meaning: infant acquisition of lexical categories. Psychological Science, 21, 284–91.CrossRefGoogle ScholarPubMed
Lany, J., Shoaib, A., Thompson, A., & Estes, K. G. (2018). Infant statistical-learning ability is related to real-time language processing. Journal of Child Language, 45(2), 368–91.CrossRefGoogle ScholarPubMed
Legendre, G., Barrière, I., Goyet, L., & Nazzi, T. (2010). Comprehension of infrequent subject–verb agreement forms: evidence from French-learning children. Child Development, 81 (6), 1859–75.CrossRefGoogle ScholarPubMed
Lidz, J., & Gleitman, L. R. (2004). Argument structure and the child's contribution to language learning. Trends in Cognitive Sciences, 8(4), 157–61.CrossRefGoogle ScholarPubMed
Liu, H.-M., Kuhl, P. K., & Tsao, F. M. (2003). An association between mothers’ speech clarity and infants’ speech discrimination skills. Developmental Science, 6, F1F10.CrossRefGoogle Scholar
Maye, J., Werker, J. F., & Gerken, L. (2002). Infant sensitivity to distributional information can affect phonetic discrimination. Cognition, 82, B101B111.CrossRefGoogle ScholarPubMed
Mintz, T. H. (2003). Frequent frames as a cue for grammatical categories in child directed speech. Cognition, 90, 91117.CrossRefGoogle ScholarPubMed
Mintz, T. H., Newport, E. L., & Bever, T. G. (2002). The distributional structure of grammatical categories in speech to young children. Cognitive Science, 26, 393424.CrossRefGoogle Scholar
Monaghan, P., Christiansen, M. H., & Chater, N. (2007). The phonological-distributional coherence hypothesis: cross-linguistic evidence in language acquisition. Cognitive Psychology, 55, 259305.CrossRefGoogle ScholarPubMed
Mueller, J. L., Friederici, A. D., & Männel, C. (2012). Auditory perception at the root of language learning. Proceedings of the National Academy of Sciences, 109, 15953–8.CrossRefGoogle ScholarPubMed
Nazzi, T., Barrière, I., Goyet, L., Kresh, S., & Legendre, G. (2011). Tracking irregular morphophonological dependencies in natural language: evidence from the acquisition of subject–verb agreement in French. Cognition, 120(1), 119–35.CrossRefGoogle ScholarPubMed
Newport, E. L., & Aslin, R. N. (2004). Learning at a distance I: statistical learning of non-adjacent dependencies. Cognitive Psychology, 48(2), 127–62.CrossRefGoogle Scholar
Ngon, C., Martin, A., Dupoux, E., Cabrol, D., Dutat, M., & Peperkamp, S. (2013). (Non)words, (non)words, (non)words: evidence for a protolexicon during the first year of life. Developmental Science, 16(1), 2434.CrossRefGoogle ScholarPubMed
Pelucchi, B., Hay, J. F., & Saffran, J. R. (2009). Statistical learning in a natural language by 8-month-old infants. Child Development, 80, 674–85.CrossRefGoogle Scholar
Peña, M., Bonatti, L. L., Nespor, M., & Mehler, J. (2002). Signal-driven computations in speech processing. Science, 298, 604–7.CrossRefGoogle ScholarPubMed
Pinker, S. (1989). Learnability and cognition: the acquisition of argument structure. Cambridge, MA: MIT Press.Google Scholar
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–31.CrossRefGoogle ScholarPubMed
Ramírez-Esparza, N., García-Sierra, A., & Kuhl, P. K. (2014). Look who's talking: speech style and social context in language input to infants are linked to concurrent and future speech development. Developmental Science, 17 (6), 880–91.CrossRefGoogle ScholarPubMed
Ramirez-Esparza, N., Garcia-Sierra, A., & Kuhl, P. K. (2015). Look who's talking: speech style and social context in language input to infants are linked to concurrent and future speech development. Developmental Science, 17, 880–91.CrossRefGoogle Scholar
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–8.CrossRefGoogle ScholarPubMed
Saffran, J. R., & Wilson, D. P. (2003). From syllables to syntax: multilevel statistical learning by 12-month-old infants. Infancy, 4(2), 273–84.CrossRefGoogle Scholar
Santelmann, L. M., & Jusczyk, P. W. (1998). Sensitivity to discontinuous dependencies in language learners: evidence for limitations in processing space. Cognition, 69(2), 105–34.CrossRefGoogle ScholarPubMed
Schaadt, G., Hesse, V., & Friederici, A. D. (2015). Sex hormones in early infancy seem to predict aspects of later language development. Brain and Language, 141, 70–6.CrossRefGoogle ScholarPubMed
Shoaib, A., Wang, T., Hay, J. F., & Lany, J. (2018). Do infants learn words from statistics? Evidence from English-learning infants hearing Italian. Cognitive Science, 42, 3083–99.CrossRefGoogle ScholarPubMed
Thiessen, E. D., Hill, E. A., & Saffran, J. R. (2005). Infant-directed speech facilitates word segmentation. Infancy, 7(1), 5371.CrossRefGoogle Scholar
Van Heugten, M., & Johnson, E. K. (2010). Linking infants’ distributional learning abilities to natural language acquisition. Journal of Memory and Language, 63(2), 197209.CrossRefGoogle Scholar
Van Heugten, M., & Shi, R. (2010). Infants’ sensitivity to non-adjacent dependencies across phonological phrase boundaries. Journal of the Acoustical Society of America, 128 (5), EL223EL228.CrossRefGoogle ScholarPubMed
Wang, F. H., & Mintz, T. H. (2018). Learning nonadjacent dependencies embedded in sentences of an artificial language: when learning breaks down. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44(4), 604–14.Google ScholarPubMed
Weisleder, A., & Fernald, A. (2013). Talking to children matters: early language experience strengthens processing and builds vocabulary. Psychological Science, 24, 2143–52.CrossRefGoogle ScholarPubMed
Willits, J., Saffran, J., & Lany, J. (2017). Toddlers can use semantic cues to learn difficult nonadjacent dependencies. Scholar
Witte, A. V., Savli, M., Holik, A., Kasper, S., & Lanzenberger, R. (2010). Regional sex differences in grey matter volume are associated with sex hormones in the young adult human brain. Neuroimage, 49(2), 1205–12.CrossRefGoogle ScholarPubMed
Xu, D., Yapanel, U., & Gray, S. (2009). Reliability of the LENATM language environment analysis system in young children's natural home environment. Retrieved from <>..>Google Scholar
Yang, C. D. (2004). Universal Grammar, statistics or both? Trends in Cognitive Sciences, 8(10), 451–6.CrossRefGoogle ScholarPubMed

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