Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Abe K, Watanabe D. 2011. Songbirds possess the spontaneous ability to discriminate syntactic rules. Nat. Neurosci. 14:81067–74 [Google Scholar]
  2. Addyman C, Mareschal D. 2013. Local redundancy governs infants' spontaneous orienting to visual‐temporal sequences. Child Dev 84:41137–44 [Google Scholar]
  3. Antovich DM, Graf Estes K. 2017. Learning across languages: Bilingual experience supports dual language statistical word segmentation. Dev. Sci. In press [Google Scholar]
  4. Aslin RN, Saffran JR, Newport EL. 1998. Computation of conditional probability statistics by 8-month-old infants. Psychol. Sci. 9:4321–24 [Google Scholar]
  5. Aslin RN, Slemmer JA, Kirkham NZ, Johnson SP. 2001. Statistical learning of visual shape sequences Presented at Biennial Meet. Soc. Res. Child Dev., Apr 19–22 Minneapolis, MN: [Google Scholar]
  6. Baldwin D, Andersson A, Saffran J, Meyer M. 2008. Segmenting dynamic human action via statistical structure. Cognition 106:31382–407 [Google Scholar]
  7. Bulf H, Brenna V, Valenza E, Johnson SP, Turati C. 2015. Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning. Front. Psychol. 6:1595 [Google Scholar]
  8. Bulf H, Johnson SP, Valenza E. 2011. Visual statistical learning in the newborn infant. Cognition 121:1127–32 [Google Scholar]
  9. Byers‐Heinlein K, Fennell CT. 2014. Perceptual narrowing in the context of increased variation: insights from bilingual infants. Dev. Psychobiol. 56:2274–91 [Google Scholar]
  10. Canfield RL, Haith MM. 1991. Young infants’ visual expectations for symmetric and asymmetric stimulus sequences. Dev. Psychol. 27:198–208 [Google Scholar]
  11. Cashon CH, Ha OR, Estes KG, Saffran JR, Mervis CB. 2016. Infants with Williams syndrome detect statistical regularities in continuous speech. Cognition 154:165–68 [Google Scholar]
  12. Chomsky N. 1965. Aspects of the Theory of Syntax Cambridge, MA: MIT Press [Google Scholar]
  13. Christiansen MH, Chater N. 2008. Language as shaped by the brain. Behav. Brain Sci. 31:05489–509 [Google Scholar]
  14. Conway CM, Christiansen MH. 2005. Modality-constrained statistical learning of tactile, visual, and auditory sequences. J. Exp. Psychol. Learn. Mem. Cogn. 31:124–39 [Google Scholar]
  15. Costa A, Sebastián-Gallés N. 2014. How does the bilingual experience sculpt the brain. Nat. Rev. Neurosci. 15:5336–45 [Google Scholar]
  16. Dawson C, Gerken L. 2009. From domain-generality to domain-sensitivity: 4-month-olds learn an abstract repetition rule in music that 7-month-olds do not. Cognition 111:3378–82 [Google Scholar]
  17. Dougherty M, Thomas R, Lange N. 2010. Toward an integrative theory of hypothesis generation, probability judgment, and hypothesis testing. Psychol. Learn. Motiv. 52:299–342 [Google Scholar]
  18. Edelman S, Intrator N, Jacobson JS. 2002. Unsupervised learning of visual structure. Proc. Int. Workshop Biol. Motiv. Comp. Vis., 2nd, Tübingen, Ger629–42 Berlin: Springer [Google Scholar]
  19. Ellis EM, Gonzalez MR, Deák GO. 2014. Visual prediction in infancy: What is the association with later vocabulary. Lang. Learn. Dev. 10:136–50 [Google Scholar]
  20. Emberson LL, Conway CM, Christiansen MH. 2011. Timing is everything: Changes in presentation rate have opposite effects on auditory and visual implicit statistical learning. Q. J. Exp. Psychol. 64:51021–40 [Google Scholar]
  21. Erickson L, Thiessen ET, Graf Estes K. 2014. Statistically coherent labels facilitate categorization in 8-month-olds. J. Mem. Lang. 72:49–58 [Google Scholar]
  22. Evans JL, Saffran JR, Robe-Torres K. 2009. Statistical learning in children with specific language impairment. J. Speech Lang. Hear. Res. 52:2321–35 [Google Scholar]
  23. Ferguson B, Lew-Williams C. 2016. Communicative signals support abstract rule learning by 7-month-old infants. Sci. Rep. 6:25434 [Google Scholar]
  24. Field DJ. 1987. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 4:122379–94 [Google Scholar]
  25. Fiser J, Aslin RN. 2001. Unsupervised statistical learning of higher-order spatial structures from visual scenes. Psychol. Sci. 12:6499–504 [Google Scholar]
  26. Fiser J, Aslin RN. 2002. Statistical learning of new visual feature combinations by infants. PNAS 99:2415822–26 [Google Scholar]
  27. Fiser J, Aslin RN. 2005. Encoding multielement scenes: statistical learning of visual feature hierarchies. J. Exp. Psychol. Gene. 134:4521–37 [Google Scholar]
  28. Fiser J, Scholl BJ, Aslin RN. 2007. Perceived object trajectories during occlusion constrain visual statistical learning. Psychon. Bull. Rev. 14:1173–78 [Google Scholar]
  29. French RM, Addyman C, Mareschal D. 2011. TRACX: a recognition-based connectionist framework for sequence segmentation and chunk extraction. Psychol. Rev. 118:4614–36 [Google Scholar]
  30. Frost R, Armstrong BC, Siegelman N, Christiansen MH. 2015. Domain generality versus modality specificity: the paradox of statistical learning. Trends Cogn. Sci. 19:3117–25 [Google Scholar]
  31. Frost R, Siegelman N, Narkiss A, Afek L. 2013. What predicts successful literacy acquisition in a second language. Psychol. Sci. 24:71243–52 [Google Scholar]
  32. Gabay Y, Thiessen ED, Holt LL. 2015. Impaired statistical learning in developmental dyslexia. J. Speech Lang. Hear. Res. 58:3934–45 [Google Scholar]
  33. Gauthier B, Shi R, Xu Y. 2007. Learning phonetic categories by tracking movements. Cognition 103:180–106 [Google Scholar]
  34. Gerken L. 2006. Decisions, decisions: infant language learning when multiple generalizations are possible. Cognition 98:3B67–74 [Google Scholar]
  35. Gerken L. 2010. Infants use rational decision criteria for choosing among models of their input. Cognition 115:2362–66 [Google Scholar]
  36. Gibson JJ. 1966. The Perception of the Visual World Boston: Houghton Mifflin [Google Scholar]
  37. Gómez RL. 2002. Variability and detection of invariant structure. Psychol. Sci. 13:5431–36 [Google Scholar]
  38. Goodsitt JV, Morgan JL, Kuhl PK. 1993. Perceptual strategies in prelingual speech segmentation. J. Child Lang. 20:2229–52 [Google Scholar]
  39. Graf Estes K, Evans JL, Alibali MW, Saffran JR. 2007. Can infants map meaning to newly segmented words? Statistical segmentation and word learning. Psychol. Sci. 18:3254–60 [Google Scholar]
  40. Graf Estes K, Lew-Williams C. 2015. Listening through voices: infant statistical word segmentation across multiple speakers. Dev. Psychol. 51:111517–28 [Google Scholar]
  41. Gweon H, Tenenbaum JB, Schulz LE. 2010. Infants consider both the sample and the sampling process in inductive generalization. PNAS 107:209066–71 [Google Scholar]
  42. Haith MM. 1993. Future-oriented processes in infancy: the case of visual expectations. Visual Perception and Cognition in Infancy CE Granrud 235–64 Hillsdale, NJ: Erlbaum [Google Scholar]
  43. Han CH, Musolino J, Lidz J. 2016. Endogenous sources of variation in language acquisition. PNAS 113:4942–47 [Google Scholar]
  44. Hasson U. 2017. The neurobiology of uncertainty: implications for statistical learning. Phil. Trans. R. Soc. B 372:171120160048 [Google Scholar]
  45. Hay JF, Pelucchi B, Estes KG, Saffran JR. 2011. Linking sounds to meanings: infant statistical learning in a natural language. Cogn. Psychol. 63:293–106 [Google Scholar]
  46. Hoff E, Core C, Place S, Rumiche R, Senor M, Parra M. 2012. Dual language exposure and early bilingual development. J. Child Lang. 39:1–27 [Google Scholar]
  47. James W. 1890. The Principles of Psychology Cambridge, MA: Harvard Univ. Press [Google Scholar]
  48. Jeste SS, Kirkham N, Senturk D, Hasenstab K, Sugar C. et al. 2015. Electrophysiological evidence of heterogeneity in visual statistical learning in young children with ASD. Dev. Sci. 18:190–105 [Google Scholar]
  49. Johnson EK, Tyler MD. 2010. Testing the limits of statistical learning for word segmentation. Dev. Sci. 13:2339–45 [Google Scholar]
  50. Jones J, Pashler H. 2007. Is the mind inherently forward looking? Comparing prediction and retrodiction. Psychon. Bull. Rev. 14:2295–300 [Google Scholar]
  51. Jusczyk PW, Aslin RN. 1995. Infants’ detection of the sound patterns of words in fluent speech. Cogn. Psychol. 29:11–23 [Google Scholar]
  52. Kidd E, Arciuli J. 2016. Individual differences in statistical learning predict children's comprehension of syntax. Child Dev 87:1184–93 [Google Scholar]
  53. Kidd C, Piantadosi ST, Aslin RN. 2012. The Goldilocks effect: Human infants allocate attention to visual sequences that are neither too simple nor too complex. PLOS ONE 7:5e36399 [Google Scholar]
  54. Kidd C, Piantadosi ST, Aslin RN. 2014. The Goldilocks effect in infant auditory attention. Child Dev 85:51795–804 [Google Scholar]
  55. Kirkham NZ, Richardson DC, Wu R, Johnson SP. 2012. The importance of “what”: Infants use featural information to index events. J. Exp. Child Psychol. 113:3430–39 [Google Scholar]
  56. Kirkham NZ, Slemmer JA, Johnson SP. 2002. Visual statistical learning in infancy: evidence for a domain general learning mechanism. Cognition 83:2B35–42 [Google Scholar]
  57. Kirkham NZ, Slemmer JA, Richardson DC, Johnson SP. 2007. Location, location, location: development of spatiotemporal sequence learning in infancy. Child Dev 78:51559–71 [Google Scholar]
  58. Krogh L, Vlach HA, Johnson SP. 2013. Statistical learning across development: flexible yet constrained. Front. Psychol. 3:598 [Google Scholar]
  59. Kuhl PK, Williams KA, Lacerda F, Stevens KN, Lindblom B. 1992. Linguistic experience alters phonetic perception in infants by 6 months of age. Science 255:606–8 [Google Scholar]
  60. Lany J, Gómez RL. 2008. Twelve-month-old infants benefit from prior experience in statistical learning. Psychol. Sci. 19:121247–52 [Google Scholar]
  61. Lew-Williams C, Saffran JR. 2012. All words are not created equal: Expectations about word length guide infant statistical learning. Cognition 122:2241–46 [Google Scholar]
  62. Lidz J, Gagliardi A. 2015. How nature meets nurture: universal grammar and statistical learning. Annu. Rev. Linguistics 1:333–53 [Google Scholar]
  63. Lum JA, Ullman MT, Conti-Ramsden G. 2013. Procedural learning is impaired in dyslexia: evidence from a meta-analysis of serial reaction time studies. Res. Dev. Disabil. 34:3460–76 [Google Scholar]
  64. Marcovitch S, Lewkowicz DJ. 2009. Sequence learning in infancy: the independent contributions of conditional probability and pair frequency information. Dev. Sci. 12:61020–25 [Google Scholar]
  65. Marcus GF, Fernandes KJ, Johnson SP. 2007. Infant rule learning facilitated by speech. Psychol. Sci. 18:5387–91 [Google Scholar]
  66. Marcus GF, Vijayan S, Rao SB, Vishton PM. 1999. Rule learning by seven-month-old infants. Science 283:539877–80 [Google Scholar]
  67. Mareschal D, French RM. 2017. TRACX2: a connectionist autoencoder using graded chunks to model infant visual statistical learning. Phil. Trans. R. Soc. B 372:171120160057 [Google Scholar]
  68. Marr D. 1982. Vision San Francisco: WH Freeman & Co. [Google Scholar]
  69. Mayo J, Eigsti IM. 2012. Brief report: a comparison of statistical learning in school-aged children with high functioning autism and typically developing peers. J. Autism Dev. Disord 42:(112476–85 [Google Scholar]
  70. Miller GA. 1956. The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63:281–97 [Google Scholar]
  71. Monroy CD, Gerson SA, Hunnius S. 2017. Toddlers’ action prediction: statistical learning of continuous action sequences. J. Exp. Child Psychol. 157:14–28 [Google Scholar]
  72. Nazzi T, Paterson S, Karmiloff-Smith A. 2003. Early word segmentation by infants and toddlers with Williams syndrome. Infancy 4:2251–71 [Google Scholar]
  73. Newport EL, Aslin RN. 2004. Learning at a distance: 1. Statistical learning of non-adjacent dependencies. Cogn. Psychol. 48:127–62 [Google Scholar]
  74. Obeid R, Brooks PJ, Powers KL, Gillespie-Lynch K, Lum JA. 2016. Statistical learning in specific language impairment and autism spectrum disorder: a meta-analysis. Front. Psychol. 7:1245 [Google Scholar]
  75. Papageorgiou KA, Smith TJ, Wu R, Johnson MH, Kirkham NZ, Ronald A. 2014. Individual differences in infant fixation duration relate to attention and behavioral control in childhood. Psychol. Sci. 25:71371–79 [Google Scholar]
  76. Pelucchi B, Hay JF, Saffran JR. 2009a. Learning in reverse: Eight-month-old infants track backward transitional probabilities. Cognition 113:2244–47 [Google Scholar]
  77. Pelucchi B, Hay JF, Saffran JR. 2009b. Statistical learning in a natural language by 8‐month‐old infants. Child Dev 80:3674–85 [Google Scholar]
  78. Perruchet P, Desaulty S. 2008. A role for backward transitional probabilities in word segmentation. Mem. Cogn. 36:1299–305 [Google Scholar]
  79. Perruchet P, Pacton S. 2006. Implicit learning and statistical learning: one phenomenon, two approaches. Trends Cogn. Sci. 10:233–38 [Google Scholar]
  80. Perruchet P, Peereman R. 2004. The exploitation of distributional information in syllable processing. J. Neurolinguist. 17:97–119 [Google Scholar]
  81. Perruchet P, Vintner A. 1998. PARSER: a model for word segmentation. J. Mem. Lang. 39:246–63 [Google Scholar]
  82. Piantadosi ST, Kidd C. 2016. Endogenous or exogenous? The data don't say. PNAS 113:20E2764 [Google Scholar]
  83. Potter C, Wang T, Saffran JR. 2016. Second language experience facilitates statistical learning of novel linguistic materials. Cogn. Sci. 41:S4913–27 [Google Scholar]
  84. Rescorla RA. 1968. Probability of shock in the presence and absence of CS in fear conditioning. J. Comp. Physiol. Psychol. 66:11–5 [Google Scholar]
  85. Romberg AR, Saffran JR. 2013a. All together now: concurrent learning of multiple structures in an artificial language. Cogn. Sci. 37:71290–320 [Google Scholar]
  86. Romberg AR, Saffran JR. 2013b. Expectancy learning from probabilistic input by infants. Front. Psychol. 3:610 [Google Scholar]
  87. Saffran JR. 2001a. The use of predictive dependencies in language learning. J. Mem. Lang. 44:493–515 [Google Scholar]
  88. Saffran JR. 2001b. Words in a sea of sounds: the output of statistical learning. Cognition 81:149–69 [Google Scholar]
  89. Saffran JR. 2002. Constraints on statistical language learning. J. Mem. Lang. 47:1172–96 [Google Scholar]
  90. Saffran JR. 2003. Absolute pitch in infancy and adulthood: the role of tonal structure. Dev. Sci. 6:135–43 [Google Scholar]
  91. Saffran JR. 2008. What can statistical learning tell us about infant learning?. Learning and the Infant Mind A Needham, A Woodward 29–46 Oxford, UK: Oxford Univ. Press [Google Scholar]
  92. Saffran JR, Aslin RN, Newport EL. 1996. Statistical learning by 8-month-old infants. Science 274:1926–28 [Google Scholar]
  93. Saffran JR, Griepentrog GJ. 2001. Absolute pitch in infant auditory learning: evidence for developmental reorganization. Dev. Psychol. 37:174–85 [Google Scholar]
  94. Saffran JR, Hauser M, Seibel R, Kapfhamer J, Tsao F, Cushman F. 2008. Grammatical pattern learning by human infants and cotton-top tamarin monkeys. Cognition 107:2479–500 [Google Scholar]
  95. Saffran JR, Johnson EK, Aslin RN, Newport EL. 1999. Statistical learning of tone sequences by human infants and adults. Cognition 70:127–52 [Google Scholar]
  96. Saffran JR, Pollak SD, Seibel RL, Shkolnik A. 2007. Dog is a dog is a dog: Infant rule learning is not specific to language. Cognition 105:3669–80 [Google Scholar]
  97. Saffran JR, Reeck K, Niebuhr A, Wilson D. 2005. Changing the tune: The structure of the input affects infants’ use of absolute and relative pitch. Dev. Sci. 8:11–7 [Google Scholar]
  98. Saffran JR, Thiessen ED. 2003. Pattern induction by infant language learners. Dev. Psychol. 39:3484–94 [Google Scholar]
  99. Saffran JR, Wilson DP. 2003. From syllables to syntax: multilevel statistical learning by 12‐month‐old infants. Infancy 4:2273–84 [Google Scholar]
  100. Sahni SD, Seidenberg MS, Saffran JR. 2010. Connecting cues: Overlapping regularities support cue discovery in infancy. Child Dev 81:3727–36 [Google Scholar]
  101. Santolin C, Rosa-Salva O, Vallortigara G, Regolin L. 2016. Unsupervised statistical learning in newly hatched chicks. Curr. Biol. 26:23R1218–20 [Google Scholar]
  102. Seidl A, Johnson EK. 2006. Infant word segmentation revisited: Edge alignment facilitates target extraction. Dev. Sci. 9:6565–73 [Google Scholar]
  103. Shafto CL, Conway CM, Field SL, Houston DM. 2012. Visual sequence learning in infancy: domain‐general and domain‐specific associations with language. Infancy 17:3247–71 [Google Scholar]
  104. Shukla M, Nespor M, Mehler J. 2007. An interaction between prosody and statistics in the segmentation of fluent speech. Cogn. Psychol. 54:11–32 [Google Scholar]
  105. Shukla M, White KS, Aslin RN. 2011. Prosody guides the rapid mapping of auditory word forms onto visual objects in 6-mo-old infants. PNAS 108:156038–43 [Google Scholar]
  106. Siegelman N, Bogaerts L, Christiansen MH, Frost R. 2017. Towards a theory of individual differences in statistical learning. Phil. Trans. R. Soc. B 372:171120160059 [Google Scholar]
  107. Siegelman N, Frost R. 2015. Statistical learning as an individual ability: theoretical perspectives and empirical evidence. J. Mem. Lang. 81:105–20 [Google Scholar]
  108. Smith K, Perfors A, Fehér O, Samara A, Swoboda K, Wonnacott E. 2017. Language learning, language use and the evolution of linguistic variation. Phil. Trans. R. Soc. B 372:171120160051 [Google Scholar]
  109. Sobel DM, Kirkham NZ. 2006. Blickets and babies: the development of causal reasoning in toddlers and infants. Dev. Psychol. 42:1103–15 [Google Scholar]
  110. Stahl AE, Romberg AR, Roseberry S, Golinkoff RM, Hirsh‐Pasek K. 2014. Infants segment continuous events using transitional probabilities. Child Dev 85:51821–26 [Google Scholar]
  111. Téglás E, Vul E, Girotto V, Gonzalez M, Tenenbaum JB, Bonatti LL. 2011. Pure reasoning in 12-month-old infants as probabilistic inference. Science 332:60331054–59 [Google Scholar]
  112. Thiessen ED. 2010. Effects of visual information on adults’ and infants’ auditory statistical learning. Cogn. Sci. 34:61093–106 [Google Scholar]
  113. Thiessen ED. 2011. Domain general constraints on statistical learning. Child Dev 82:2462–70 [Google Scholar]
  114. Thiessen ED. 2017. What's statistical about learning? Insights from modelling statistical learning as a set of memory processes. Phil. Trans. R. Soc. B 372:171120160056 [Google Scholar]
  115. Thiessen ED, Pavlik PI. 2013. iMinerva: a mathematical model of distributional statistical learning. Cogn. Sci. 37:2310–43 [Google Scholar]
  116. Thiessen ED, Saffran JR. 2007. Learning to learn: infants’ acquisition of stress-based strategies for word segmentation. Lang. Learn. Dev. 3:173–100 [Google Scholar]
  117. Thomas MS, Annaz D, Ansari D, Scerif G, Jarrold C, Karmiloff-Smith A. 2009. Using developmental trajectories to understand developmental disorders. J. Speech Lang. Hear. Res. 52:2336–58 [Google Scholar]
  118. Tomblin JB, Mainela-Arnold E, Zhang X. 2007. Procedural learning in adolescents with and without specific language impairment. Lang. Learn. Dev. 3:4269–93 [Google Scholar]
  119. Toro JM, Trobalón JB. 2005. Statistical computations over a speech stream in a rodent. Atten. Percept. Psychophys. 67:5867–75 [Google Scholar]
  120. Tummeltshammer K, Amso D, French RM, Kirkham NZ. 2017. Across space and time: Infants learn from backward and forward visual statistics. Dev. Sci. In press [Google Scholar]
  121. Tummeltshammer KS, Kirkham NZ. 2013. Learning to look: Probabilistic variation and noise guide infants' eye movements. Dev. Sci. 16:5760–71 [Google Scholar]
  122. Tummeltshammer KS, Mareschal D, Kirkham NZ. 2014a. Infants' selective attention to reliable visual cues in the presence of salient distractors. Child Dev 85:51981–94 [Google Scholar]
  123. Tummeltshammer KS, Wu R, Sobel DM, Kirkham NZ. 2014b. Infants track the reliability of potential informants. Psychol. Sci. 25:91730–38 [Google Scholar]
  124. Turk-Browne NB, Isola PJ, Scholl BJ, Treat TA. 2008. Multidimensional visual statistical learning. J. Exp. Psychol. Learn. Mem. Cogn. 34:2399–407 [Google Scholar]
  125. Vasuki PRM, Sharma M, Demuth K, Arciuli J. 2016. Musicians' edge: a comparison of auditory processing, cognitive abilities and statistical learning. Hear. Res. 342:112–23 [Google Scholar]
  126. Vogel EK, Luck SJ. 2000. The visual N1 component as an index of a discrimination process. Psychophysiology 37:2190–203 [Google Scholar]
  127. Wang T, Saffran JR. 2014. Statistical learning of a tonal language: the influence of bilingualism and previous linguistic experience. Front. Psychol. 5:953 [Google Scholar]
  128. Weiss DJ, Gerfen C, Mitchel AD. 2009. Speech segmentation in a simulated bilingual environment: a challenge for statistical learning. Lang. Learn. Dev. 5:130–49 [Google Scholar]
  129. Werker J, Tees RC. 1984. Cross-language speech perception: evidence for perceptual reorganization during the first year of life. Infant Behav. Dev. 7:49–63 [Google Scholar]
  130. Wu R, Gopnik A, Richardson DC, Kirkham NZ. 2011. Infants learn about objects from statistics and people. Dev. Psychol. 47:51220–29 [Google Scholar]
  131. Younger BA. 1985. The segregation of items into categories by ten-month-old infants. Child Dev 54:858–67 [Google Scholar]
  132. Younger BA, Cohen LB. 1986. Developmental change in infants' perception of correlations among attributes. Child Dev 57:803–15 [Google Scholar]
  133. Yu C, Smith LB, Klein KA, Shiffrin RM. 2007. Hypothesis testing and associative learning in cross-situational word learning: Are they one and the same?. Proc. Annu. Meet. Cogn. Sci. Soc., 29th, Nashville, TN737–42 Austin, TX: Cogn. Sci. Soc. [Google Scholar]
  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error