Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-28T02:11:19.013Z Has data issue: false hasContentIssue false
  • English
  • Français

Artificial grammar learning in Williams syndrome and in typical development: The role of rules, familiarity, and prosodic cues

Published online by Cambridge University Press:  17 July 2017

VESNA STOJANOVIK ,
VITOR ZIMMERER ,
JANE SETTER ,
KERRY HUDSON ,
ISIL POYRAZ-BILGIN  and
DOUG SADDY
VESNA STOJANOVIK*
Affiliation:
University of Reading
VITOR ZIMMERER
Affiliation:
University College London
JANE SETTER
Affiliation:
University of Reading
KERRY HUDSON
Affiliation:
University of Reading
ISIL POYRAZ-BILGIN
Affiliation:
University of Reading
DOUG SADDY
Affiliation:
University of Reading
*
ADDRESS FOR CORRESPONDENCE Vesna Stojanovik, School of Psychology and Clinical Language Sciences, University of Reading, Earley Gate, Reading RG6 6AL, UK. E-mail: v.stojanovik@reading.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

Artificial grammar learning is an empirical paradigm that investigates basic pattern and structural processing in different populations. It can inform how higher cognitive functions, such as language use, take place. Our study used artificial grammar learning to assess how children with Williams syndrome (WS; n = 16) extract patterns in structured sequences of synthetic speech, how they compare to typically developing (TD) children (n = 60), and how prosodic cues affect learning. The TD group was divided into a group whose nonverbal abilities were within the range of the WS group, and a group whose chronological age was within the range of the WS group. TD children relied mainly on rule-based generalization when making judgments about sequence acceptability, whereas children with WS relied on familiarity with specific stimulus combinations. The TD participants whose nonverbal abilities were similar to the WS group showed less evidence of relying on grammaticality than TD participants whose chronological age was similar to the WS group. In absence of prosodic cues, the children with WS did not demonstrate evidence of learning. Results suggest that, in WS children, the transition to rule-based processing in language does not keep pace with TD children and may be an indication of differences in neurocognitive mechanisms.

Keywords

artificial grammar learningprosodic cuesrulestypical developmentWilliams syndrome
Type
Original Article
Information
Applied Psycholinguistics , Volume 39 , Issue 2 , March 2018 , pp. 327 - 353
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abrams, R. A., & Christ, S. E. (2003). Motion onset captures attention. Psychological Science, 14, 427–432. doi:10.1111/1467-9280.01458 CrossRefGoogle ScholarPubMed
Beach, C. M., Katz, W. F., & Skowronski, A. (1996). Children's processing of prosodic cues for phrasal interpretation. Journal of the Acoustical Society of America, 99, 1148–1160.CrossRefGoogle ScholarPubMed
Bellugi, U., Bihrle, A., Neville, H., Jernigan, T., & Doherty, S. (1992). Language, cognition, and brain organization in a neurodevelopmental disorder. In Gunnar, M. & Nelson, C. (Eds.), Developmental behavioural neuroscience (pp. 201–232). Hillside, NJ: Erlbaum.Google Scholar
Bellugi, U., Lichtenberger, L., Jones, W., Lai, Z., & George, M. St. (2000). I. The neurocognitive profile of Williams Syndrome: A complex pattern of strengths and weaknesses. Journal of Cognitive Neuroscience, 12 (Suppl. 1), 7–29. doi:10.1162/089892900561959 CrossRefGoogle ScholarPubMed
Bellugi, U., Lichtenberger, L., Mills, D., Galaburda, A., & Korenberg, J. R. (1999). Bridging cognition, the brain and molecular genetics: Evidence from Williams syndrome. Trends in Neurosciences, 22, 197–207. doi:10.1016/S0166-2236(99)01397-1 CrossRefGoogle ScholarPubMed
Bellugi, U., Sabo, H., & Vaid, J. (1988). Spatial deficits in children with Williams syndrome. In Stiles-Davis, J., Kritchevshy, U., & Bellugi, U. (Eds.), Spatial cognition: Brain bases and development (pp. 273–297). Hillsdale, NJ: Erlbaum.Google Scholar
Bellugi, U., Wang, P. P., & Jernigan, T. L. (1994). Williams syndrome: An unusual neuropsychological profile. In Broman, S. & Grafman, J. (Eds.), Atypical cognitive deficits in developmental disorders: Implications for brain function (pp. 23–56). Hillsdale, NJ: Erlbaum.Google Scholar
Bihrle, A. M., Bellugi, U., Delis, D., & Marks, S. (1989). Seeing either the forest or the trees: Dissociation in visuospatial processing. Brain and Cognition, 11, 37–49. doi:10.1016/0278-2626(89)90003-1 Google Scholar
Boersma, P., & Weenink, D. (2005). Praat: Doing phonetics by computer (Version 4.3.01) [Computer software]. Retrieved from http://www.praat.org Google Scholar
Brock, J. (2007). Language abilities in Williams syndrome: A critical review. Development and Psychopathology, 19, 97–127. doi:10.1017/S095457940707006X Google Scholar
Brooks, L. R., & Vokey, J. R. (1991). Abstract analogies and abstracted grammars: Comments on Reber (1989) and Mathews et al. (1989). Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 316–323. doi:10.1037/0096-3445.120.3.316 Google Scholar
Brown, R. (1973). A first language: The early stages. London: Allen & Unwin.CrossRefGoogle Scholar
Catterall, C., Howard, S., Stojanovik, V., Szczerbinski, M., & Wells, B. (2006). Investigating prosodic ability in Williams Syndrome. Clinical Linguistics and Phonetics, 20, 7–8, 531–538.Google Scholar
Christiansen, M. H., Kelly, L. M., Shillock, R., & Greenfield, K. (2010). Impaired artificial grammar learning in agrammatism. Cognition, 116, 382–393. doi:10.1016/j.cognition.2010.05.015 Google Scholar
Conway, C. M., Bauernschmidt, A., Huang, S. S., & Pisoni, D. B. (2010). Implicit statistical learning in language processing: Word predictability is the key. Cognition, 114, 356–371. doi:10.1016/j.cognition.2009.10.009 Google Scholar
Deruelle, C., Mancini, J., Livet, M. O., Cassé Perrot, C., & de Schonen, S. (1999). Configural and local processing of faces in children with Williams syndrome. Brain and Cognition, 41, 276–298. doi:10.1006/brcg.1999.1127 Google Scholar
Deruelle, C., Schon, D., Rondan, C., & Mancini, J. (2005). Global and local music perception in children with Williams syndrome. NeuroReport, 16, 631–634.Google Scholar
Dominey, P. F., Hoen, M., Blanc, J.-M., & Lelekov-Boissard, T. (2003). Neurological basis of language and sequential cognition: Evidence from simulation, aphasia, and ERP studies. Brain and Language, 86, 207–225. doi:10.1016/S0093-934X(02)00529-1 Google Scholar
Don, A. J., Schellenberg, E. G., Reber, A. S., Di Girolamo, K. M., & Wang, P. P. (2003). Implicit learning in children and adults with Williams syndrome. Developmental Neuropsychology, 23, 201–225. doi:10.1207/S15326942DN231&2_9 Google Scholar
D'Souza, D., Booth, R., Connolly, M., Happé, F., & Karmiloff-Smith, A. (2015). Rethinking the con- cepts of “local or global processors”: Evidence from Williams syndrome, Down syndrome, and autism spectrum disorders. Developmental Science. Advance online publication. doi:10.1111/desc.12312 Google Scholar
D'Souza, D. H., Moretti-Ferreira, D., & Rugolo, L. M. S. S. (2007). Fluorescent in situ hybridization (FISH) as a diagnostic tool for Williams-Beuren syndrome. Genetics and Molecular Biology, 30, 17–20. doi:10.1590/S1415-47572007000100005 CrossRefGoogle Scholar
Elsabbagh, M., Cohen, H., & Karmiloff-Smith, A. (2010). Discovering structure in auditory input: Evidence from Williams syndrome. American Journal on Intellectual and Developmental Disabilities, 115, 128–139. doi:10.1352/1944-7558-115.2.128 CrossRefGoogle ScholarPubMed
Farran, E. K., Jarrold, C., & Gathercole, S. E. (2003). Divided attention, selective attention and drawing: Processing preferences in Williams syndrome are dependent on the task administered. Neuropsychologia, 41, 676–687. doi:10.1016/S0028-3932(02)00219-1 Google Scholar
Fisher, C. L. (1991). Prosodic cues to phrase structure in infant directed speech. Papers and Reports on Child Language Development, 30, [n.p.].Google Scholar
Fletcher, J., Maybery, M. T., & Bennett, S. (2000). Implicit learning differences: A question of developmental level? Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 246–252. doi:10.1037/0278-7393.26.1.246 Google ScholarPubMed
Gebauer, G. F., & Mackintosh, N. J. (2007). Psychometric intelligence dissociates implicit and explicit learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 34–54. doi:10.1037/0278-7393.33.1.34 Google ScholarPubMed
Gleitman, L. R., Gleitman, H., Landau, B., & Wanner, E. (1988). Where learning begins: Initial representations for language learning. In Newmeyer, F. J. (Ed.), Linguistics: The Cambridge survey: Vol. 3. Language: Psychological and biological aspects (pp. 150–193). New York: Cambridge University Press.Google Scholar
Goharpey, N., Tsoutsoulis, K., & Crewther, S. G. (2012). Raven's Coloured Progressive Matrices performance as a valid predictor of cognitive and motor delay in intellectual disability regardless of etiology. Abstract ACNS-2012 presented at the Australasian Cognitive Neuroscience Conference.Google Scholar
Grant, J., Valian, V., & Karmiloff-Smith, A. (2002). A study of relative clauses in Williams syndrome. Journal of Child Language, 29, 403–416. doi:10.1017/S030500090200510X CrossRefGoogle ScholarPubMed
Greenberg, E. (1990). Introduction to special issue on Williams syndrome. American Journal of Medical Genetics (Suppl.), 6, 85–88.Google Scholar
Grice, S. J., de Haan, M., Halit, H., Johnson, M., Csibra, G., Grant, J., & Karmiloff-Smith, A. (2003). ERP abnormalities of illusory contour perception in Williams syndrome. NeuroReport, 14, 1773–1777. doi:10.1097/01.wnr.0000094161.86963.c5 Google Scholar
Hirsh-Pasek, K., Kemler-Nelson, D. G., Jusczyk, P. W., Cassidy, K. W., Druss, B., & Kennedy, L. (1987). Clauses are perceptual units for young infants. Cognition, 26, 269–286. doi:10.1016/S0010-0277(87)80002-1 Google Scholar
Ingram, D., & Pye, C. (1993). The acquisition of miniature languages: The search for a new paradigm. International Journal of Psycholinguistics, 9, 147–158.Google Scholar
Joffe, V., & Varlokosta, S. (2007). Patterns of syntactic development in children with Williams syndrome and Down's syndrome: Evidence from passives and wh-questions. Clinical Linguistics & Phonetics, 21, 705–727. doi:10.1080/02699200701541375 Google Scholar
Jusczyk, P. W., Cutler, A., & Redanz, N. J. (1993). Infants' preference for the predominant stress patterns of English words. Child Development, 64, 675–687.Google Scholar
Jusczyk, P. W., Hirsch-Pasek, K., Kemler Nelson, D. G., Kennedy, L. J., Woodward, A., & Piwoz, J. (1992). Perception of acoustic correlates of major phrasal units by young infants. Cognitive Psychology, 24, 252–293. doi:10.1016/0010-0285(92)90009-Q Google Scholar
Karmiloff-Smith, A. (2012). Perspectives on the dynamic development of cognitive capacities: In- sights from Williams syndrome. Current Opinion in Neurology, 25, 106–111. doi:10.1097/WCO.0b013e3283518130 Google Scholar
Karmiloff-Smith, A., & Farran, E. (2012). Williams syndrome: A model for the neuroconstructivist approach. In Farran, E. & Karmiloff-Smith, A. (Eds.), Neurodevelopmental disorders across the lifespan: A neuroconstructivist approach (pp. 1–10). Oxford: Oxford University Press.Google Scholar
Karmiloff-Smith, A., Thomas, M., Annaz, D., Humphreys, K., Ewing, S., Brace, N., . . . Campbell, R. (2004). Exploring the Williams syndrome face-processing debate: The importance of building developmental trajectories. Journal of Child Psychology and Psychiatry, 45, 1258–1274. doi:10.1111/j.1469-7610.2004.00322.x Google Scholar
Key, A. P., & Dykens, E. M. (2011). Electrophysiological study of local/global processing in Williams syndrome. Journal of Neurodevelopmental Disorders, 3, 28–38. doi:10.1007/s11689-010-9064-1 Google Scholar
Knowlton, B. J., & Squire, L. R. (1994). The information acquired during artificial grammar learning. Journal of Experimental Psychology. Learning, Memory, and Cognition, 20, 79–91. doi:10.1037/0278-7393.20.1.79 Google Scholar
Lenhoff, H. (1998). Insights into the musical potential of cognitively impaired people diagnosed with Williams syndrome. Music Therapy, 16, 333–336.Google Scholar
Levitin, D. J., & Bellugi, U. (1998). Musical abilities in people with Williams syndrome. Music Perception, 15, 357–389.Google Scholar
Levitin, D. J., Cole, K., Chiles, M., Lai, Z., Lincoln, A., & Bellugi, U. (2004). Characterizing the musical phenotype in individuals with Williams syndrome. Child Neuropsychology, 10, 223–247.Google Scholar
Maratsos, M. P., & Chakley, M. (1980). The internal langauge of children's syntax: The ontogenesis and representtaion of syntactic categories. In Nelson, K. (Ed.), Children's language (Vol. 2, pp. 127–214). New York: Gardner.Google Scholar
Marcus, G. F., Vijayan, S., Rao, S. B., & Vishton, P. M. (1999). Rule learning by seven-month-old infants. Science, 283, 77–80.Google Scholar
Martinez-Castilla, P., Stojanovik, V., Setter, J., & Sotillo, M. (2012). Prosodic abilities in Spanish and English children with Williams syndrome: A cross-linguistic study. Applied Psycholinguistics, 33, 1–12.Google Scholar
Mattys, S. L., White, L., & Melhorn, J. F. (2005). Integration of multiple speech segmentation cues: A hierarchical framework. Journal of Experimental Psychology: General, 134, 477–500. doi:10.1037/0096-3445.134.4.477 CrossRefGoogle ScholarPubMed
Maybery, M. T., Taylor, M., & O'Brien-Malone, A. (1995). Implicit learning: Sensitive to age but not IQ. Australian Journal of Psychology, 47, 8–17. doi:10.1080/00049539508258763 Google Scholar
McMullen, E., & Saffran, J. (2004). Music and language: A developmental comparison. Music Perception, 21, 289–311.Google Scholar
Mervis, C. B., & John, A. E. (2008). Vocabulary abilities of children with Williams syndrome: Strengths, weaknesses, and relation to visuospatial construction ability. Journal of Speech, Language, and Hearing Research, 51, 967–982. doi:10.1044/1092-4388(2008/071) Google Scholar
Mervis, C. B., & John, A. E. (2012). Precursors to language and early language. In Farran, E. & Karmiloff-Smith, A. (Eds.), Neurodevelopmental disorders across the lifespan: A neuroconstructivist approach (pp. 187–204). Oxford: Oxford University Press.Google Scholar
Mervis, C. B., & Klein-Tasman, B. P. (2000). Williams syndrome: Cognition, personality, and adaptive behaviour. Mental Retardation and Developmental Disabilities Research Reviews, 6, 148–158.3.0.CO;2-T>CrossRefGoogle Scholar
Mervis, C. B., Robinson, B. F., Rowe, M. L., Becerra, A. M., & Klein-Tasman, B. P. (2004). Relations between language and cognition in Williams syndrome. In Bartke, S. & Siegmüller, J. (Eds.), Williams syndrome across languages (pp. 63–92). Amsterdam: Benjamins.Google Scholar
Mobbs, D., Eckert, M. A., Menon, V., Mills, D., Korenberg, J., Galaburda, A. M., & Reiss, A. L. (2007). Reduced parietal and visual cortical activation during global processing in Williams syndrome. Developmental Medicine & Child Neurology, 49, 433–438. doi:10.1111/j.1469-8749.2007.00433.x Google Scholar
Mondloch, C. J., Le Grand, R., & Maurer, D. (2002). Configural face-processing develops more slowly than featural face-processing. Perception, 31, 553–566. doi:10.1068/p3339 Google Scholar
Morgan, J. L., Meier, R. P., & Newport, E. L. (1987). Structural packaging in the input to language learning: Contributions of prosodic and morphological marking of phrases to the acquisition of language. Cognitive Psychology, 19, 498–550. doi:10.1016/0010-0285(87)90017-X Google Scholar
Nazzi, T., Paterson, S. J., & Karmiloff-Smith, A. (2003). Word segmentation by infants with Williams syndrome. Infancy, 4, 251–271. doi:10.1207/S15327078IN0402_06 Google Scholar
Pani, J. R., Mervis, C. B., & Robinson, B. F. (1999). Global spatial organization by individuals with Williams syndrome. Psychological Science, 10, 453–458.Google Scholar
Patel, A. (2003). Language, music, and the brain. Nature Neuroscience, 6, 674–681.Google Scholar
Pavlidou, E. V., Williams, J. M., & Kelly, L. M. (2009). Artificial grammar learning in primary school children with and without developmental dyslexia. Annals of Dyslexia, 59, 55–77. doi:10.1007/s11881-009-0023-z Google Scholar
Perruchet, P. (1994). Defining the knowledge units of a synthetic language: Comment on Vokey & Brooks (1992). Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 223–228.Google Scholar
Perruchet, P., & Pacteau, C. (1990). Synthetic grammar learning: Implicit rule abstraction or explicit fragmentary knowledge? Journal of Experimental Psychology: General, 119, 264–275. doi:10.1037/0096-3445.119.3.264 Google Scholar
Petersson, K. M., Folia, V., & Hagoort, P. (2012). What artificial grammar learning reveals about the neurobiology of syntax. Brain and Language, 120, 83–95. doi:10.1016/j.bandl.2010.08.003 Google Scholar
Petersson, K. M., Forkstam, C., & Ingvar, M. (2004). Artificial syntactic violations activate Broca's region. Cognitive Science, 28, 383–407. doi:10.1207/s15516709cog2803_4 Google Scholar
Pinker, S. (1984). Language learnability and language development. Cambridge, MA: Harvard University Press.Google Scholar
Poirel, N., Mellet, E., Houdé, O., & Pineau, A. (2008). First came the trees, then the forest: Developmental changes during childhood in the processing of visual local–global patterns according to the meaningfulness of the stimuli. Developmental Psychology, 44, 245–253. doi:10.1037/0012-1649.44.1.245 Google Scholar
Pothos, E. M. (2007). Theories of artificial grammar learning. Psychological Bulletin, 133, 227–244. doi:10.1037/0033-2909.133.2.227 Google Scholar
Pothos, E. M., & Bailey, T. M. (2000). The importance of similarity in artificial grammar learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 847–862. doi:10.1037/0278-7393.26.4.847 Google Scholar
Raven, J. (2007). Coloured Progressive Matrices. London: Harcourt.Google Scholar
Reber, A. S. (1967). Implicit learning of artificial grammars. Verbal Learning and Verbal Behavior, 5, 855–863. doi:10.1016/s0022-5371(67)80149-x Google Scholar
Redington, M., & Chater, N. (1996). Transfer in artificial grammar learning: A reevaluation. Jour- nal of Experimental Psychology: General, 125, 123–138. doi:10.1037/0096-3445.125.2.123 Google Scholar
Reilly, J., Klima, E. S., & Bellugi, U. (1990). Once more with feeling: Affect and language in atypical populations. Development and Psychopathology, 2, 367–391.Google Scholar
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274, 1926–1928.Google Scholar
Semel, E., Wiig, E. H., & Secord, W. A. (2004). Clinical Evaluation of Language Fundamentals—4 (CELF-4). Toronto: Psychological Corporation.Google Scholar
Semel, E., Wiig, E. H., & Secord, W. A. (2006). Pre-School Clinical Evaluation of Language Fundamentals—2 (Pre-School CELF-2). Toronto: Psychological Corporation.Google Scholar
Setter, J., Stojanovik, V., van Ewijk, L., & Moreland, M. (2007). Affective prosody in children with Williams syndrome. Clinical Linguistics and Phonetics, 9, 659–672.Google Scholar
Snedeker, J., & Trueswell, J. C. (2001). Unheeded cues: Prosody and syntactic ambiguity in mother-child communication. Paper presented at the 26th Boston University Conference on Language Development, Boston.Google Scholar
Stevens, T., & Karmiloff-Smith, A. (1997). Word learning in a special population: Do individuals with Williams syndrome obey lexical constraints? Journal of Child Language, 24, 737–765.Google Scholar
Stojanovik, V. (2010). Understanding and production of prosody in children with Williams syndrome: A developmental trajectory approach. Journal of Neurolinguistics, 23, 112–126. doi:10.1016/j.jneuroling.2009.11.001 Google Scholar
Stojanovik, V. (2012). Later language. In Farran, E. & Karmiloff-Smith, A. (Eds.), Neurodevelopmental disorders across the lifespan: A neuroconstructivist approach (pp. 205–223). Oxford: Oxford University Press.Google Scholar
Stojanovik, V., Perkins, M., & Howard, S. (2004). Williams syndrome and specific language impairment do not support claims for developmental double dissociations and innate modularity. Journal of Neurolinguistics, 17, 403–424. doi:10.1016/j.jneuroling.2004.01.002 Google Scholar
Stojanovik, V., Setter, J., & van Ewijk, L. (2007). Intonation abilities in children with Williams syndrome: A preliminary investigation. Journal of Speech, Language, and Hearing Research, 50, 1610–1617.Google Scholar
Strømme, P., Bjømstad, P. G., & Ramstad, K. (2002). Prevalence estimation of Williams syndrome. Journal of Child Neurology, 17, 269–271. doi:10.1177/088307380201700406 Google Scholar
Tassabehji, M., Metcalfe, K., Karmiloff-Smith, A., Carette, M. J., Grant, J., Dennis, N., . . . Donnai, D. (1999). Williams syndrome: Use of chromosomal micro-deletions as a tool to dissect cognitive and physical phenotypes. American Journal of Human Genetics, 64, 118–125.Google Scholar
Tauroza, S., & Allison, D. (1990). Speech rates in British English. Applied Linguistics, 11, 90–105. doi:10.1093/applin/11.1.90 Google Scholar
Thomas, K. M., & Nelson, C. A. (2001). Serial reaction time learning in preschool- and school-age children. Journal of Experimental Child Psychology, 79, 364–387. doi:10.1006/jecp.2000.2613 Google Scholar
Thomas, S. C. M., Grant, J., Barham, Z., Dsodl, M., Laing, E., Lakusta, L., . . . Karmloff-Smith, A. (2001). Past tense formation in Williams syndrome. Language and Cognitive Processes, 16, 143–176. doi:10.1080/01690960042000021 Google Scholar
Thomas, S. C. M., Purser, H. R., & Van Herwegen, J. (2012). Cognition: The developmental trajectory approach. In Farran, E. K. & Karmiloff-Smith, A. (Eds.), Neurodevelopmental diosrders across the lifespan: A neuroconstructivist approach (pp. 13–35). Oxford: Oxford University Press.Google Scholar
Trehub, S. E. (2003). The developmental origins of music. Nature Neuroscience, 6, 669–673.Google Scholar
Vinter, A., & Perruchet, P. (2000). Implicit learning in children is not related to age: Evidence from drawing behavior. Child Development, 71, 1223–1240. doi:10.1111/1467-8624.00225 Google Scholar
Visser, I., Raijmakers, M. E. J., & Pothos, E. M. (2009). Individual strategies in artificial grammar learning. American Journal of Psychology, 122, 293–307. doi:27784404 Google Scholar
Wang, L., Mottron, L., Peng, D., Berthiaume, C., & Dawson, M. (2007). Local bias and local-to-global interference without global deficit: A robust finding in autism under various conditions of attention, exposure time, and visual angle. Cognitive Neuropsychology, 24, 550–574. doi:10.1080/13546800701417096 Google Scholar
Wang, P. P., Doherty, S., Rourke, S. B., & Bellugi, U. (1995). Unique profile of visuo-perceptual skills in a genetic syndrome. Brain and Cognition, 29, 54–65. doi:10.1006/brcg.1995.1267 Google Scholar
Wexler, K., & Culicover, P. W. (1980). Formal principles of language acquisition. Cambridge, MA: MIT Press.Google Scholar
Young, A. W., Hellawell, D., & Hay, D. C. (1987). Configurational information in face perception. Perception, 16, 747–759. doi:10.1068/p160747 Google Scholar
Ypsilanti, A., Grouios, G., Alevriadou, A., & Tsapkini, K. (2005). Expressive and receptive vocabulary in children with Williams and Down syndromes. Journal of Intellectual Disability Research, 49, 353–364. doi:10.1111/j.1365-2788.2005.00654.x Google Scholar
Zimmerer, V. C., Cowell, P. E., & Varley, R. A. (2011). Individual behavior in learning of an artificial grammar. Memory & Cognition, 39, 491–501. doi:10.3758/s13421-010-0039-y CrossRefGoogle ScholarPubMed
Zimmerer, V. C., Cowell, P. E., & Varley, R. A. (2014). Artificial grammar learning in individuals with severe aphasia. Neuropsychologia, 53, 25–38. doi:10.1016/j.neuropsychologia.2013.10.014 Google Scholar
Zimmerer, V. C., & Varley, R. A. (2015). A case of “order insensitivity”? Natural and artificial language processing in a man with primary progressive aphasia. Cortex, 69, 212–219. doi:10.1016/j.cortex.2015.05.006 Google Scholar