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A model of comprehension in spina bifida meningomyelocele: Meaning activation, integration, and revision

Published online by Cambridge University Press:  14 August 2007

MARCIA A. BARNES ,
JOELENE HUBER ,
AMBER M. JOHNSTON  and
MAUREEN DENNIS
MARCIA A. BARNES
Affiliation:
Department of Psychology, University of Guelph, Guelph, Ontario Department of Pediatrics, University of Toronto, Toronto, Ontario Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Ontario
JOELENE HUBER
Affiliation:
Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Ontario
AMBER M. JOHNSTON
Affiliation:
Department of Psychology, University of Guelph, Guelph, Ontario
MAUREEN DENNIS
Affiliation:
Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Ontario Departments of Surgery and Psychology, University of Toronto, Toronto, Ontario
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Abstract

Spina bifida meningomyelocele (SBM) is a neurodevelopmental disorder associated with adequate development of word reading and single word comprehension, but deficient text and discourse comprehension. Studies of comprehension in children with SBM are reviewed in relation to a comprehension model in which meanings are either activated from the surface code or constructed through resource-intensive integration and revision processes to form representations of the text base and models of the situation described by the text. Two new studies probed the construction of situation models in SBM. Experiment 1 tested the ability to build spatial and affective situation models from single sentences in 86 children with SBM (8 to 18 years of age) and 37 control children (8 to 16 years of age). Experiment 2 tested the ability to integrate across sentences to build spatial situation models in 15 children with SBM and 15 age-matched controls. Compared to age peers, children with SBM did not construct situation models that required integration of information across sentences, even though they could construct such models from single sentences. The data bear on the distinctive SBM neurocognitive profile, and more generally, on the significance of integration processes for the constructive aspects of language comprehension. (JINS, 2007, 13, 854–864.)

Keywords

Neural tube defectsHydrocephalusComprehensionLanguageShort-term memory
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 13 , Issue 5 , September 2007 , pp. 854 - 864
Copyright
2007 The International Neuropsychological Society

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References

REFERENCES

Albrecht, J.E. & Myers, J.L. (1998). Accessing distant text information during reading: Effects of contextual cues. Discourse Processes, 26, 87–107.Google Scholar
Barnes, M.A. & Dennis, M. (1992). Reading in children and adolescents after early-onset hydrocephalus and in normally developing peers: Phonological analysis, word recognition, word comprehension, and passage comprehension skill. Journal of Pediatric Psychology, 17, 445–465.Google Scholar
Barnes, M.A. & Dennis, M. (1996). Reading comprehension deficits arise from diverse sources: Evidence from readers with and without developmental brain pathology. In C. Cornoldi & J. Oakhill (Eds.), Reading Comprehension Difficulties (pp. 251–278). Hillsdale, NJ: Lawrence Erlbaum Associates.
Barnes, M.A. & Dennis, M. (1998). Discourse after early-onset hydrocephalus: Core deficits in children of average intelligence. Brain and Language, 61, 309–334.Google Scholar
Barnes, M.A. & Dennis, M. (2001). Knowledge-based inferencing after childhood head injury. Brain and Language, 76, 253–265.Google Scholar
Barnes, M.A., Dennis, M., & Haefele-Kalvaitis, J. (1996). The effects of knowledge availability and knowledge accessibility on coherence and elaborative inferencing in children from six to fifteen years of age. Journal of Experimental Child Psychology, 61, 216–241.Google Scholar
Barnes, M.A., Faulkner, H., & Dennis, M. (2001). Poor reading comprehension despite fast word decoding in children with hydrocephalus. Brain and Language, 76, 35–44.Google Scholar
Barnes, M.A., Faulkner, H., Wilkinson, M., & Dennis, M. (2004). Meaning construction and integration in children with hydrocephalus. Brain and Language, 89, 47–56.Google Scholar
Barnes, M.A., Wilkinson, M., Boudousquie, A., Khemani, E., Dennis, M., & Fletcher, J.M. (2006). Arithmetic processing in chil-dren with spina bifida: Calculation accuracy, strategy use, and fact retrieval fluency. Journal of Learning Disabilities, 39, 174–187.Google Scholar
Bransford, J.D. & Franks, J.J. (1972). The abstraction of linguistic ideas: A review. Cognition, 1, 211–249.Google Scholar
Bunge, S.A., Ochsner, K.N., Desmond, J.E., Glover, G.H., & Gabrieli, J.D.E. (2001). Prefrontal regions involved in keeping information out of mind. Brain, 124, 2074–2086.Google Scholar
Cain, K., Oakhill, J.V., Barnes, M.A., & Bryant, P.E. (2001). Comprehension skill, inference making ability and their relation to knowledge. Memory and Cognition, 29, 850–859.Google Scholar
Cain, K., Oakhill, J., & Elbro, C. (2003). The ability to learn new word meanings from context by school-age children with and without language comprehension difficulties. Journal of Child Language, 30, 681–694.Google Scholar
Caplan, D. & Waters, G. (2006). Language disorders in aging. In E. Bialystok & F.I.M. Craik (Eds.), Life Span Cognition: Mechanisms of Change. Oxford, UK: Oxford University Press.
Clifton, C.Jr. & Duffy, S.A. (2001). Sentence and text comprehension: Roles of linguistic structure. Annual Review of Psychology, 52, 167–196.Google Scholar
Colvin, A.N., Yeates, O.K., Enrile, B.G., & Coury, D.L. (2003). Motor adaptation in children with myelomeningocele: Comparison to children with ADHD and healthy siblings. Journal of the International Neuropsychological Society, 9, 642–652.Google Scholar
Darby, D. (2000). MacStim (version 3.0) computer software. West Melbourne, VIC, Australia: WhiteAnt Occasional Publishing.
Dempster, F.N. (1993). Resistance to interference: Developmental changes in a basic processing mechanism. In M.L. Howe & R. Pasnak (Eds.), Emerging Themes in Cognitive Development, Volume I: Foundations (pp. 3–27). New York: Springer-Verlag.
Dennis, M. & Barnes, M.A. (2002). Math and numeracy skills in young adults with spina bifida and hydrocephalus. Developmental Neuropsychology, 21, 141–155.Google Scholar
Dennis, M., Fletcher, J.M., Rogers, S., Hetherington, R., & Francis, D. (2002). Object-based and action-based visual perception in children with spina bifida and hydrocephalus. Journal of the International Neuropsychological Society, 8, 95–106.Google Scholar
Dennis, M., Hendrick, E.B., Hoffman, H.J., & Humphreys, R.P. (1987). The language of hydrocephalic children and adolescents. Journal of Clinical and Experimental Neuropsychology, 9, 593–621.Google Scholar
Dennis, M., Jacennik, B., & Barnes, M.A. (1994). The content of narrative discourse in children and adolescents after early-onset hydrocephalus and in normally-developing age peers. Brain and Language, 46, 129–165.Google Scholar
Dennis, M., Jewell, D., Edelstein, K., Brandt, M., Hetherington, R., Blaser, S., & Fletcher, J. (2006a). Motor learning in children with spina bifida: Intact learning and performance on a ballistic task. Journal of the International Neuropsychological Society, 12, 598–608.Google Scholar
Dennis, M., Landry, S.H., Barnes, M.A., & Fletcher, J.M. (2006b). A model of neurocognitive function in spina bifida over the lifespan. Journal of the International Neuropsychological Society, 12, 285–296.Google Scholar
Edelstein, K., Dennis, M., Copeland, K., Francis, D., Frederick, J., Brandt, M., Hetherington, R., & Fletcher, J.M. (2004). Motor learning in children with spina bifida: Dissociation between performance level and acquisition rate. Journal of the International Neuropsychological Society, 10, 877–887.Google Scholar
Engle, R.W., Conway, A.R.A., Tuholski, S.W., & Shisler, R.J. (1995). A resource account of inhibition. Psychological Science, 6, 122–126.Google Scholar
Fletcher, J.M., Dennis, M., Northrup, H., Barnes, M.A., Hannay, H.J., Landry, S.H., Copeland, K., Blaser, S.E., Kramer, L.A., Brandt, M.E., & Francis, D.J. (2004). Spina bifida: Genes, brain, and development. In L.M. Glidden, (Ed.), Handbook of Research on Mental Retardation (Vol. 28). San Diego: Academic Press.
Fletcher, J.M., Copeland, K., Frederick, J., Blaser, S.E., Kramer, L.A., Northrup, H., Hannay, H.J., Brandt, M.E., Francis, D.J., Villarreal, G., Drake, J.M., Laurent, J., Townsend, I., Inwood, S., Boudousquie, A., & Dennis, M. (2005). Spinal lesion level in spina bifida meningomyelocele: A source of neural and cognitive heterogeneity. Journal of Neurosurgery, 102, 268–279.Google Scholar
Fox Tree, J.E. & Meijer, P.J.A. (1999). Building syntactic structure in speaking. Journal of Psycholinguistic Research, 28, 71–92.Google Scholar
Friederici, A.D. (2002). Towards a neural basis of auditory sentence processing. Trends in Cognitive Science, 6, 78–84.Google Scholar
Gazzaley, A., Cooney, J.W., McEvoy, K., Knight, R.T., & D'Esposito, D. (2005). Top down enhancement and suppression of the magnitude and speed of neural activity. Journal of Cognitive Neuroscience, 17, 507–517.Google Scholar
Gernsbacher, M.A. (1990). Language comprehension as structure building. Hillsdale. NJ: Lawrence Erlbaum.
Gernsbacher, M.A. & Faust, M.E. (1991). The mechanism of suppression: A component of general comprehension skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 245–262.Google Scholar
Graesser, A.C., Millis, K., & Zwaan, R.A. (1997). Discourse comprehension. Annual Review of Psychology, 48, 163–189.Google Scholar
Harnishfeger, K.K. & Bjorklund, D.F. (1994). A developmental perspective on individual differences in inhibition. Learning and Individual Differences, 6, 331–355.Google Scholar
Horn, D.G., Lorch, E.P., Lorch, R.F., & Culatta, B. (1985). Distractibility and vocabulary deficits in children with spina bifida and hydrocephalus. Developmental Medicine and Child Neurology, 27, 713–720.Google Scholar
Huber-Okrainec, J., Blaser, S.E., & Dennis, M. (2005). Idiom comprehension deficits in relation to corpus callosum agenesis and hypoplasia in children with spina bifida meningomyelocele. Brain and Language, 93, 349–368.Google Scholar
Johnston, A. & Barnes, M.A. (2007). The role of attentional control in reading comprehension. Poster presentation at the Society for Scientific Studies in Reading annual conference, Prague, The Czech Republic, July 12–14.
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction integration model. Psychological Review, 95, 163–182.Google Scholar
Kirkpatrick, T.L. & Northrup, H. (2003). Neural tube defects: Genetics. Encyclopedia of the Human Gemone. London: Macmillan Publishers Ltd., Nature Publishing Group.
Long, D.L., Oppy, B.J., & Seely, M.R. (1997). Individual differences in readers' sentence- and text-level representations, Journal of Memory and Language, 36, 129–145.Google Scholar
MacDonald, M.C., Pearlmutter, N.J., & Seidenberg, M.S. (1994). Lexical nature of syntactic ambiguity resolution. Psychological Review, 101, 676–703.Google Scholar
Mani, K. & Johnson-Laird, P.N. (1982). The mental representation of spatial descriptions. Memory & Cognition, 10, 181–187.Google Scholar
Miyake, A. & Shah, P. (1999). Models of working memory. Mechanisms of active maintenance and executive control. Cambridge, UK: Cambridge University Press.
Morrow, D.G., Bower, G.H., & Greenspan, S.L. (1989). Updating situation models during narrative comprehension. Journal of Memory and Language, 28, 292–312.Google Scholar
Parsons, J.G. (1969). An investigation into the verbal facility of hydrocephalic children with special reference to vocabulary, morphology, and fluency. Developmental Medicine and Childhood Neurology, 10, 109–110.Google Scholar
Phillips, C.E., Jarrold, C., Baddeley, A., Grant, J., & Karmiloff-Smith, A. (2004). Comprehension of spatial language terms in Williams syndrome: Evidence for an interaction between domains of strength and weakness. Cortex, 40, 85–101.Google Scholar
Purzner, J., Wilkinson, M., Boudousquie, A., Fletcher, J., & Barnes, M.A. (2004). Verbal and visual working memory in children with spina bifida. Journal of the International Neuropsychological Society, 10.Google Scholar
Salman, M.S., Sharpe, J.A., Eizenman, M., Lillakas, L., To, T., Westall, C., Steinbach, M., & Dennis, M. (2005). Saccades in children with spina bifida and Arnold-Chiari Type II malformation. Neurology, 64, 2098–2101.Google Scholar
Schmalhofer, F., McDaniel, M.A., & Keefe, D. (2002). A unified model for predictive and bridging inferences. Discourse Processes, 33, 105–132.Google Scholar
Seidenberg, M.S., Tanenhaus, M.K., Leiman, J.M., & Bienkowski, M. (1982). Automatic access of the meaning of ambiguous words in context: Some limitations of knowledge-based processing. Cognitive Psychology, 14, 489–537.Google Scholar
Snodgrass, J.G. & Vanderwart, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology. Human Learning and Memory, 6, 174–215.Google Scholar
Spooner, A.R.L., Gathercole, S.E., & Baddeley, D.E. (2006). Does weak reading comprehension reflect an integration deficit? Journal of Research in Reading, 29, 173–193.Google Scholar
Thorndike, R.L., Hagen, E.P., & Sattler, J.M. (1986). The Stanford-Biner Intelligence Scale: Fourth Edition. Chicago: Riverside.
Tompkins, C.A., Baumgaertner, A., Lehman, M.T., & Fassbinder, W. (2000). Mechanisms of discourse comprehension impairment after right hemisphere brain damage: Suppression in lexical ambiguity resolution. Journal of Speech, Language, and Hearing Research, 43, 62–78.Google Scholar
van den Broek, P., Young, M., Tzeng, Y., & Linderholm, T. (1999). The landscape model of reading: Inferences and the online construction of a memory representation. In H. van Oostendorp & S.R. Goldman (Eds.), The Construction of Mental Representations During Reading (pp. 71–98). Mahwah, New Jersey: Lawrence Erlbaum.
Van Lancker-Sidtis, D. (2004). When novel sentences spoken or heard for the first time in the history of the universe are not enough: Toward a dual-process model of language. International Journal of Language & Communication Disorders, 39, 1–44.Google Scholar
Vosse, T. & Kempen, G. (2000). Syntactic structure assembly in human parsing: A computational model based on competitive inhibition and a lexicalist grammar. Cognition, 75, 105–143.Google Scholar
Woodcock, R.W. & Johnson, M.B. (1989). Tests of Cognitive Ability and Tests of Achievement. Rolling Meadows, IL: Riverside Publishing.
Yeates, K.O. & Enrile, B.G. (2005). Implicit and explicit memory in children with congenital and acquired brain disorder. Neuropsychology, 19, 618–628.Google Scholar
Yeates, K.O., Enrile, B.G., Loss, N., Blumenstein, E., & Delis, D. (1995). Verbal learning and memory in children with myelomeningocele. Journal of Pediatric Psychology, 20, 801–815.Google Scholar
Zwann, R.A. & Radvansky, G.A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123, 162–185.Google Scholar