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3 - Development in spina bifida: Neurobiological and environmental factors

Published online by Cambridge University Press:  04 August 2010

By
Marcia A. Barnes ,
Heather B. Taylor ,
Susan B. Landry  and
Lianne H. English
Edited by
Marcia A. Barnes
Marcia A. Barnes
Affiliation:
University of Texas Health Science Center, Houston
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Summary

Introduction

Spina bifida myelomeningocele (SBM) is one of the world's most common disabling birth defects, yet, until recently, its genetic, neural, and cognitive phenotypes have been less systematically investigated than those of other neurogenetic disorders, including several of those featured in this volume. This chapter describes the findings from a large-scale multi-site study of more than 260 children with SBM between the ages of 7 and 16 years and over 160 children with SBM and their typically developing peers followed from infancy into school age that involves collaboration between the University of Texas Health Science Center at Houston, the University of Houston, and the Toronto Hospital for Sick Children.

The material is organized as follows: (1) What is SBM?; (2) The SBM genotype; (3) Relations between genotype and physical and neural phenotypes; (4) The SBM behavioral phenotype in relation to lesion level and environmental factors: intelligence, academic skills, and adaptive function; (5) Theoretical questions about typical and atypical development generated from studies of the SBM phenotype; (6) Longitudinal development in SBM from infancy through childhood and into adult life; and (7) Clinical care and intervention issues.

What is SBM?

SBM, a neural tube defect that affects the development of both spine and brain, arises in the third to fourth week of embryogenesis, and results in a failure of neural tube closure. The physical phenotype includes paraplegia of the lower limbs and neurogenic bladder and bowel function (Charney, 1992).

Type
Chapter
Information
Genes, Brain and Development
The Neurocognition of Genetic Disorders
 , pp. 53 - 82
Publisher: Cambridge University Press
Print publication year: 2010

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References

Albrecht, J. E. & O'Brien, E. J. (1993). Updating a mental model: Maintaining both local and global coherence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 1061–70.Google Scholar
Ayr, L. K., Yeates, K. O., & Enrile, B. G. (2005). Arithmetic skills and their cognitive correlates in children with acquired and congenital brain disorder. Journal of the International Neuropsychological Society, 11, 249–62.CrossRefGoogle ScholarPubMed
Barkovich, A. J. (2000).Congenital malformations of the brain and skull / Congenital anomalies of the spine. In: Barkovich, A J, editor. Pediatric Neuroimaging (pp. 330–7). Philadelphia: Lippincott Williams & Wilkins.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, 445–65.CrossRefGoogle ScholarPubMed
Barnes, M. A. & Dennis, M. (1998). Discourse after early-onset hydrocephalus: Core deficits in children of average intelligence. Brain and Language, 61, 309–34.CrossRefGoogle ScholarPubMed
Barnes, M. A., Dennis, M., & Hetherington, R. (2004a). Reading and writing skills in young adults with spina bifida and hydrocephalus. Journal of the International Neuropsychological Society, 10, 655–63.CrossRefGoogle ScholarPubMed
Barnes, M. A., Faulkner, H. J., & Dennis, M. (2001). Poor reading comprehension despite fast word decoding in children with hydrocephalus. Brain and Language, 76, 35–44.CrossRefGoogle ScholarPubMed
Barnes, M. A., Faulkner, H., Wilkinson, M., & Dennis, M. (2004b). Meaning construction and integration in children with hydrocephalus. Brain and Language, 89, 47–56.CrossRefGoogle ScholarPubMed
Barnes, M. A., Huber, J., Johnston, A. M., & Dennis, M. (2007a). A model of comprehension in spina bifida meningomyelocele: Meaning activation, integration, and revision. Journal of the International Neuropsychological Society. Special Issue: Reviews, 13, 854–64.Google ScholarPubMed
Barnes, M. A., Johnston, A. M., & Dennis, M. (2007b). Comprehension in a neurodevelopmental disorder, spina bifida myelomeningocele. In Cain, K. & Oakhill, J. (Eds.), Children's Comprehension Problems in Oral and Written Language: A Cognitive Perspective. Challenges in Language and Literacy (pp. 193–217). New York: Guilford Press.Google Scholar
Barnes, M. A., Pengelly, S., Dennis, M., Wilkinson, M., Rogers, T., & Faulkner, H. (2002). Mathematics skills in good readers with hydrocephalus. Journal of the International Neuropsychological Society, 8, 72–82.CrossRefGoogle ScholarPubMed
Barnes, M. A., Smith-Chant, B., & Landry, S. H. (2005). Number processing in neurodevelopmental disorders: Spina bifida. In Campbell, J. I. D. (Ed.), Handbook of Mathematical Cognition (pp. 299–313). New York: Psychology Press.Google Scholar
Barnes, M. A., Wilkinson, M., Khemani, E., Boudesquie, A., Dennis, M., & Fletcher, J. M. (2006). Arithmetic processing in children with spina bifida: Calculation accuracy, strategy use, and fact retrieval fluency. Journal of Learning Disabilities, 39, 174–87.CrossRefGoogle ScholarPubMed
Bentley, T. G., Willett, W. C., Weinstein, M. C., & Kuntz, K. M. (2006). Population-level changes in folate intake by age, gender, and race/ethnicity after folic acid fortification. American Journal of Public Health, 96(11), 2040–7.CrossRefGoogle Scholar
Berch, D. B. (2008). Working memory and mathematical cognitive development: Limitations of limited-capacity resource models. Developmental Neuropsychology, 33, 427–46.CrossRefGoogle ScholarPubMed
Bisanz, J., Sherman, J. L., Rasmussen, C., & Ho, E. (2005). Development of arithmetic skills and knowledge in preschool children. In Campbell, J. I. D. (Ed.), Handbook of Mathematical Cognition (pp. 143–162). New York: Psychology Press.Google Scholar
Bowman, R. M., McLone, D. G., Grant, J. A., Tomita, T., & Ito, J. A. (2001). Spina bifida outcome: A 25-year prospective. Pediatric Neurosurgery, 34, 114–20.CrossRefGoogle ScholarPubMed
Bransford, J. D. & Franks, J. J. (1972). The abstraction of linguistic ideas: A review. Cognition, 1, 211–49.CrossRefGoogle Scholar
Brewer, V. R., Fletcher, J. M., Hiscock, M., & Davidson, K. C. (2001). Attention processes in children with shunted hydrocephalus versus attention deficit-hyperactivity disorder. Neuropsychology, 15, 185–98.CrossRefGoogle ScholarPubMed
Bull, R., Espy, K. A., & Wiebe, S. A. (2008). Short-term memory, working memory, and executive functioning in preschoolers: Longitudinal predictors of mathematical achievement at 7 years. Developmental Neuropsychology, 33, 205–28.CrossRefGoogle ScholarPubMed
Burmeister, R., Hannay, H. J., Copeland, K., Fletcher, J. M., Boudousquie, A., & Dennis, M. (2005). Attention problems and executive functions in children with spina bifida and hydrocephalus. Child Neuropsychology, 11, 265–83.CrossRefGoogle ScholarPubMed
Butterworth, B. & Reigosa, V. (2007). Information processing deficits in dyscalculia. In Berch, D. B. & Mazzocco, M. M. M. (Eds.), Why Is Math so Hard for Some Children? The Nature and Origins of Mathematical Learning Difficulties and Disabilities (pp. 107–20). Baltimore: Paul H. Brookes Publishing Co.Google Scholar
Cain, K. & Oakhill, J. (2007). Reading comprehension difficulties: Correlates, causes, and consequences. In Cain, K. & Oakhill, J. (Eds.), Children's Comprehension Problems in Oral and Written Language: A Cognitive Perspective. Challenges in language and literacy (pp. 41–75). New York: Guilford Press.Google Scholar
Cain, K., Oakhill, J., Barnes, M. A., & Bryant, P. E. (2001). Comprehension skill, inference making ability and their relation to knowledge. Memory & Cognition, 29, 850–9.CrossRefGoogle Scholar
Cain, K., Oakhill, J., & Lemmon, K. (2004). Individual differences in the inference of word meanings from context: The influence of reading comprehension, vocabulary knowledge, and memory capacity. Journal of Educational Psychology, 96, 671–81.CrossRefGoogle Scholar
Caplan, D. & Waters, G. (2006). Language disorders in aging. In Bialystok, E. & Craik, F. I. M. (Eds.), Life Span Cognition: Mechanisms of Change. Oxford, UK: Oxford University Press.Google Scholar
Charney, E. (1992). Neural tube defects: Spina bifida and meningomyelocele. In Batshaw, M. & Perret, Y. (Eds.), Children with Disabilities: A Medical Primer 3rd edn. (pp. 471–88). Baltimore: Paul H. Brookes.Google Scholar
Clifton, C., Jr. & Duffy, S. A. (2001). Sentence and text comprehension: Roles of linguistic structure. Annual Review of Psychology, 52, 167–96.CrossRefGoogle ScholarPubMed
Coakley, R. M., Holmbeck, G. N., & Bryant, F. B. (2006). Constructing a prospective model of psychosocial adaptation in young adolescents with spina bifida: An application of optimal data analysis. Journal of Pediatric Psychology, 31, 1084–99.CrossRefGoogle ScholarPubMed
Collins, W. A., Maccoby, E. E., Steinberg, L., Hetherington, E. M., & Bornstein, M. H. (2003). Contemporary research on parenting: The case for nature and nurture. In Hertzig, M. E. & Farber, E. A. (Eds.), Annual Progress in Child Psychiatry and Child Development (pp. 125–54). New York: Routledge.Google Scholar
Colvin, A. N., Yeates, K. O., 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, 642–52.CrossRefGoogle ScholarPubMed
Cornoldi, C., Beni, R., & Pazzaglia, F. (1996). Profiles of Reading Comprehension Difficulties: An Analysis of Single Cases. Mahwah, NJ: Erlbaum.Google Scholar
Davidson, C. M., Northrup, H., King, T. M., et al. (2008). Genes in glucose metabolism and association with spina bifida. Reproductive Sciences, 15, 51–8.CrossRefGoogle ScholarPubMed
Dennis, M. & Barnes, M. A. (2002). Numeracy skills in adults with spina bifida. Developmental Neuropsychology, 21, 141–56.CrossRefGoogle Scholar
Dennis, M., Edelstein, K., Copeland, K., et al. (2004). Neurobiology of timing in children with spina bifida in relation to cerebellar volume. Brain, 127, 1292–301.CrossRefGoogle ScholarPubMed
Dennis, M., Edelstein, K., Copeland, K., et al. (2005a). Covert orienting to exogenous and endogenous cues in children with spina bifida. Neuropsychologia, 43, 976–87.CrossRefGoogle ScholarPubMed
Dennis, M., Edelstein, K., Copeland, K., et al. (2005b). Space-based inhibition of return in children with spina bifida. Neuropsychology, 19, 456–65.CrossRefGoogle ScholarPubMed
Dennis, M., Fletcher, J. M., Rogers, T., Hetherington, R., & Francis, D. J. (2002). Object-based and action-based visual perception in children with spina bifida and hydrocephalus. Journal of the International Neuropsychological Society, 8, 95–106.CrossRefGoogle ScholarPubMed
Dennis, M., Fritz, C. R., Netley, C. T., et al. (1981). The intelligence of hydrocephalic children. Archives of Neurology, 38, 607–15.CrossRefGoogle ScholarPubMed
Dennis, M., Hendrick, E. B., Hoffman, H. J., & Humphreys, R. P. (1987). Language of hydrocephalic children and adolescents. Journal of Clinical and Experimental Neuropsychology, 9, 593–621.CrossRefGoogle ScholarPubMed
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, 129–65.CrossRefGoogle ScholarPubMed
Dennis, M., Jewell, D., Drake, J., et al. (2007). Prospective, declarative, and non-declarative memory in young adults with spina bifida. Journal of the International Neuropsychological Society, 13, 312–23.CrossRefGoogle Scholar
Dennis, M., Landry, S. H., Barnes, M., & Fletcher, J. M. (2006). A model of neurocognitive function in spina bifida over the life span. Journal of the International Neuropsychological Society, 12, 285–96.CrossRefGoogle ScholarPubMed
Dennis, M., Nelson, R., & Fletcher, J. M. (2009). Prospective memory in younger and older adults with spina bifida. Poster presentation, Rotman Research Institute 14th Annual Conference “Cognitive Aging,” Toronto ON 8–9 March 2009, Toronto Ontario.
Dennis, M., Sinopoli, K. J., Fletcher, J. M., & Schachar, R. (2008). Puppets, robots, critics, and actors within a taxonomy of attention for developmental disorders. Journal of the International Neuropsychological Society, 14, 673–90.CrossRefGoogle ScholarPubMed
Dennis, M., Spiegler, B. J., & Hetherington, R. (2000). New survivors for the new millennium: Cognitive risk and reserve in adults with childhood brain insults. Brain and Cognition, 42, 102–5.CrossRefGoogle ScholarPubMed
Diamond, A. & Doar, B. (1989). The performance of human infants on a measure of frontal cortex function, the delayed response task. Developmental Psychobiology, 22, 271–94.CrossRefGoogle ScholarPubMed
Donders, J., Canady, A. I., & Rourke, B. P. (1990). Psychometric intelligence after infantile hydrocephalus: A critical review and reinterpretation. Child's Nervous System, 6, 148–54.CrossRefGoogle ScholarPubMed
Edelstein, K., Dennis, M., Copeland, K., et al. (2004). Motor learning in children with spina bifida: Dissociation between performance level and acquisition rate. Journal of the International Neuropsychological Society, 10, 877–87.CrossRefGoogle ScholarPubMed
English, L. H., Barnes, M. A., Taylor, H. B., & Landry, S. H., (2009). Mathematical development in spina bifida. Developmental Disabilities Research Reviews, 15, 28–34.CrossRefGoogle ScholarPubMed
Fletcher, J. M., Bohan, T. P., Brandt, M. E., et al. (1992). Cerebral white matter and cognition in hydrocephalic children. Archives of Neurology, 49, 818–24.CrossRefGoogle ScholarPubMed
Fletcher, J. M., Brookshire, B. L., Bohan, T. P., Brandt, M. E., & Davidson, K. C. (1995). Early hydrocephalus. In Rourke, B. P. (Ed.), Syndrome of Nonverbal Learning Disabilities: Neurodevelopmental Manifestations (pp. 206–238). New York: Guilford.Google Scholar
Fletcher, J. M., Copeland, K., Frederick, J., et al. (2005). Spinal lesion level in spina bifida meningomyelocele: A source of neural and cognitive heterogeneity. Journal of Neurosurgery, 102, 268–79.Google ScholarPubMed
Fletcher, J. M., Dennis, M., Northup, H., et al. (2004). Spina bifida: Genes, brain, and development. In Glidden, L. M., (Ed.), Handbook of Research on Mental Retardation (Vol. 28, pp. 63–117). San Diego: Academic Press.Google Scholar
Fletcher, J. M., Lyon, G. R., Fuchs, L. S., & Barnes, M. A. (2007). Learning Disabilities: From Identification to Intervention. New York: The Guilford Press.Google Scholar
Fletcher, J. M., Ostermaier, K. K., Cirino, P. T., & Dennis, M. (2008). Neurobehavioral outcomes in spina bifida: Processes versus outcomes. Journal of Pediatric Rehabilitation Medicine: An Interdisciplinary Approach, 1, 311–24.Google ScholarPubMed
Friedrich, W. N., Lovejoy, M. C., Shaffer, J., Shurtleff, D. B., & Beilke, R. L. (1991). Cognitive abilities and achievement status of children with myelomeningocele: A contemporary sample. Journal of Pediatric Psychology, 16, 423–8.CrossRefGoogle ScholarPubMed
Geary, D. C. (1993). Mathematical disabilities: Cognitive, neuropsychological, and genetic components. Psychological Bulletin, 114, 345–62.CrossRefGoogle ScholarPubMed
Geary, D. C., Hamson, C. O., & Hoard, M. K. (2000). Numerical and arithmetical cognition: A longitudinal study of process and concept deficits in children with learning disability. Journal of Experimental Child Psychology, 77, 236–63.CrossRefGoogle ScholarPubMed
Geary, D. C., Hoard, M. K., Byrd-Craven, J., Nugent, L., & Numtee, C. (2007). Cognitive mechanisms underlying achievement deficits in children with mathematical learning disability. Child Development, 78, 1343–59.CrossRefGoogle ScholarPubMed
Gernsbacher, M. A. (1990). Language Comprehension as Structure Building. Hillsdale, NJ: Lawrence Erlbaum.CrossRefGoogle Scholar
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, 245–62.Google ScholarPubMed
Gersten, R., Jordan, N. C., & Flojo, J. R. (2005). Early identification and interventions for students with mathematics difficulties. Journal of Learning Disabilities, 38, 293–304.CrossRefGoogle ScholarPubMed
Gibbs, R. W. (1986). Skating on thin ice: Literal meaning and understanding idioms in conversation. Discourse Processes, 9, 17–30.CrossRefGoogle Scholar
Goldberg, S. (1978). Prematurity: Effects on parent-infant interaction. Journal of Pediatric Psychology, 3, 137–44.CrossRefGoogle Scholar
Hartje, W. (1987). The effect of spatial disorders on arithmetical skills. In Deloche, G. & Seron, X. (Eds.), Mathematical Disabilities: A Cognitive Neuropsychological Perspective (pp. 121–35). Hillsdale, NJ: Erlbaum.Google Scholar
Haxby, J. V., Grady, C. L., Horwitz, B., et al. (1991). Dissociation of object and spatial visual processing pathways in human extrastriate cortex. Proceedings of the National Academy of Sciences of the United States of America, 88(5), 1621–5.CrossRefGoogle ScholarPubMed
Hess, R. D. & Shipman, V. C. (1965). Early experience and the socialization of cognitive modes in children. Child Development, 36, 869–86.CrossRefGoogle ScholarPubMed
Hetherington, R., Dennis, M., Barnes, M., Drake, J., & Gentilli, F. (2006). Functional outcome in young adults with spina bifida and hydrocephalus. Child's Nervous System, 22, 117–24.CrossRefGoogle ScholarPubMed
Holmbeck, G. N., Greenley, R. N., Coakley, R. M., Greco, J., & Hagstrom, J. (2006). Family functioning in children and adolescents with spina bifida: An evidence-based review of research and interventions. Journal of Developmental and Behavioral Pediatrics, 27(3), 249–77.CrossRefGoogle ScholarPubMed
Holmbeck, G. N., Westhoven, V. C., Phillips, W. S., et al. (2003). A multimethod, multi-informant, and multi-dimensional perspective on psychosocial adjustment in preadolescents with spina bifida. Journal of Consulting and Clinical Psychology, 71, 782–96.CrossRefGoogle Scholar
Holmes, J. & Adams, J. W. (2006). Working memory and children's mathematical skills: Implications for mathematical development and mathematical curricula. Educational Psychology, 26, 339–66.CrossRefGoogle 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, 713–20.CrossRefGoogle ScholarPubMed
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, 349–68.CrossRefGoogle ScholarPubMed
Johnston, A. M., Barnes, M. A., & Desrochers, A. (2008). Reading comprehension: Developmental processes, individual differences, and interventions. Canadian Psychology, 49, 125–32.CrossRefGoogle Scholar
Jordan, N. C., Hanich, L. B., & Kaplan, D. (2003). A longitudinal study of mathematical competencies in children with specific mathematics and reading difficulties. Child Development, 74, 834–50.CrossRefGoogle ScholarPubMed
Juranek, J., Fletcher, J. M., Hasan, K. M., et al. (2008). Neurocortical reorganization in spina bifida. Neuroimage, 40, 1516–22.CrossRefGoogle Scholar
Kalaman, D. A. & LeFevre, J. (2007). Working memory demands of exact and approximate addition. European Journal of Cognitive Psychology, 19, 187–212.CrossRefGoogle Scholar
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction- integration model. Psychological Review, 95, 163–82.CrossRefGoogle ScholarPubMed
Klein, R. M. (2000). Inhibition of return. Trends in Cognitive Sciences, 4, 138–47.CrossRefGoogle ScholarPubMed
Kogan, K. L. (1980). Interaction systems between preschool handicapped or developmentally delayed children and their parents. In Field, T., Goldberg, S., Stern, D., & Sostek, A. M. (Eds.), High-risk Infants and Children: Adult and Peer Interactions (pp. 227–47). New York: Academic Press, Inc.Google Scholar
Landry, S. H., Denson, S. E., & Swank, P. R. (1997). Effects of medical risk and socioeconomic status on the rate of change in cognitive and social development for low birth weight children. Journal of Clinical and Experimental Neuropsychology, 19, 261–74.CrossRefGoogle ScholarPubMed
Landry, S. H., Smith, K. E., & Swank, P. R. (2006). Responsive parenting: Establishing early foundations for social, communication, and independent problem-solving skills. Developmental Psychology, 42, 627–42.CrossRefGoogle ScholarPubMed
Landry, S. H., Smith, K. E., Swank, P. R., & Guttentag, C. (2008b). A responsive parenting intervention: The optimal timing across early childhood for impacting maternal behaviors and child outcomes. Developmental Psychology, 44, 1335–53.CrossRefGoogle ScholarPubMed
Landry, S. H., Taylor, H. B., Guttentag, C., & Smith, K. E. (2008a). Responsive parenting: Closing the learning gap for at-risk children. In Glidden, L. (Ed.), International Review of Research in Mental Retardation (Vol. 36 pp. 27–60). Burlington: Academic Press.Google Scholar
Leach, J. M., Scarborough, H. S., & Rescorla, L. (2003). Late-emerging reading disabilities. Journal of Educational Psychology, 95, 211–24.CrossRefGoogle Scholar
LeFevre, J., DeStefano, D., Coleman, B., & Shanahan, T. (2005). Mathematical cognition and working memory. In Campbell, J. I. D. (Ed.), The Handbook of Mathematical Cognition (pp. 361–78). New York: Psychology Press.Google Scholar
Lemelle, J. L., Guillemin, F., Aubert, D., Guys, J. M., Lottmann, H., Lortat-Jacob, S., Mouriquand, P., Ruffion, A., Moscovici, J., & Schmitt, M. (2006). Quality of life and continence in patients with spina bifida. Quality of Life Research, 15, 1481–92.CrossRefGoogle ScholarPubMed
Lomax-Bream, L. E., Barnes, M., Copeland, K., Taylor, H. B., & Landry, S. H. (2007a). The impact of spina bifida on development across the first 3 years. Developmental Neuropsychology, 31, 1–20.CrossRefGoogle ScholarPubMed
Lomax-Bream, L. E., Taylor, H. B., Landry, S. H., Barnes, M. A., Fletcher, J. M., & Swank, P. (2007b). Role of early parenting and motor skills on development in children with spina bifida. Journal of Applied Developmental Psychology, 28, 250–63.CrossRefGoogle Scholar
Loss, N., Yeates, K. O., & Enrile, B. G. (1998). Attention in children with myelomeningocele. Child Neuropsychology, 4, 7–20.CrossRefGoogle Scholar
MacDonald, M. C., Pearlmutter, N. J., & Seidenberg, M. S. (1994). Lexical nature of syntactic ambiguity resolution. Psychological Review, 101, 676–703.CrossRefGoogle ScholarPubMed
,March of Dimes (2006). Global Report on Birth Defects: The Hidden Toll of Dying and Disabled Children. White Plains, NY: March of Dimes.Google Scholar
Mayes, S. D. & Calhoun, S. L. (2006). Frequency of reading, math, and writing disabilities in children with clinical disorders. Learning and Individual Differences, 16, 145–57.CrossRefGoogle Scholar
McDonnell, G. V. & McCann, J. P. (2000). Issues of medical management in adults with spina bifida. Child's Nervous System, 16, 222–7.CrossRefGoogle ScholarPubMed
Muter, V., Hulme, C., Snowling, M. J., & Stevenson, J. (2004). Phonemes, rimes, vocabulary, and grammatical skills as foundations of early reading development: Evidence from a longitudinal study. Developmental Psychology, 40, 665–81.CrossRefGoogle ScholarPubMed
Northrup, H. & Volcik, K. A. (2000). Spina bifida and other neural tube defects. Current Problems in Pediatrics, 30, 317–32.CrossRefGoogle ScholarPubMed
Oakhill, J. V., Cain, K., & Bryant, P. E. (2003). Dissociation of single-word reading and text comprehension skills. Language and Cognitive Processes, 18, 443–68.CrossRefGoogle Scholar
Oddson, B. E., Clancy, C. A., & McGrath, P. J. (2006). The role of pain in reduced quality of life and depressive symptomology in children with spina bifida. Clinical Journal of Pain, 22, 784–9.CrossRefGoogle ScholarPubMed
O'Donnell, S., Noseworthy, M. D., Levine, B., & Dennis, M. (2005). Cortical thickness of the frontopolar area in typically developing children and adolescents. Neuroimage, 24, 948–54.CrossRefGoogle ScholarPubMed
Posner, M. I., Walker, J. A., Friedrich, F. J., & Rafal, R. D. (1984). Effects of parietal injury on covert orienting of attention. Journal of Neuroscience, 4, 1863–74.CrossRefGoogle ScholarPubMed
Raghubar, K. P., Cirino, P. T., Barnes, M. A., Ewing-Cobbs, L., Fletcher, J. M., & Fuchs, L. (2009). Errors in multi-digit arithmetic and behavioral inattention in children with math difficulties. Journal of Learning Disabilities 42, 356–71.CrossRefGoogle ScholarPubMed
Rendeli, C., Salvaggio, E., Cannizzaro, G. S., Bianchi, E., Caldarelli, M., & Guzzetta, F. (2002). Does locomotion improve the cognitive profile of children with meningomyelocele?Child's Nervous System, 18, 231–4.Google ScholarPubMed
Rose, B. M. & Holmbeck, G. N. (2007). Attention and executive functions in adolescents with spina bifida. Journal of Pediatric Psychology, 32, 983–94.CrossRefGoogle ScholarPubMed
Roselli, M. & Ardila, A. (1989). Calculation deficits in patients with right and left hemisphere damage. Neuropsychologia, 27, 607–17.CrossRefGoogle Scholar
Salman, M. S., Blaser, S., Sharpe, J. A., & Dennis, M. (2006). Cerebellar vermis morphology in children with spina bifida and Arnold Chiari Type II malformation. Child's Nervous System, 22, 385–93.CrossRefGoogle Scholar
Schmalhofer, F., McDaniel, M. A., & Keefe, D. (2002). A unified model for predictive and bridging inferences. Discourse Processes, 33, 105–32.CrossRefGoogle Scholar
Shalev, R. S., Auerbach, J., Manor, O., & Gross-Tsur, V. (2000). Developmental dyscalculia: Prevalence and prognosis. European Child and Adolescent Psychiatry, 9, II58–II64.CrossRefGoogle ScholarPubMed
Shaywitz, S. E., Fletcher, J. M., Holahan, J. M., et al. (1999). Persistence of dyslexia: The Connecticut Longitudinal Study at adolescence. Pediatrics, 104, 1351–9.CrossRefGoogle ScholarPubMed
Sutton, L. N. (2008). Fetal surgery for neural tube defects. Best Practice & Research Clinical Obstetrics and Gynaecology, 22, 175–88.CrossRefGoogle ScholarPubMed
Swanson, H. L. (2007). Commentary on Part I, Section II: Cognitive aspects of math disabilities. In Berch, D. B. & Mazzocco, M. M. M. (Eds.), Why Is Math so Hard for Some Children? The Nature and Origins of Mathematical Learning Difficulties and disabilities (pp. 133–44). Baltimore: Paul H. Brookes Publishing Co.Google Scholar
Swanson, H. L. & Jerman, O. (2006). Math disabilities: A selective meta-analysis of the literature. Review of Educational Research, 76, 249–74.CrossRefGoogle Scholar
Taylor, H. B., Landry, S. H., Barnes, M., Cohen, L., Swank, P., & Fletcher, J. (submitted). Early information processing among infants with and without spina bifida. Infant Behavior and Development.
Thelen, E. & Smith, L. B. (1994). A Dynamic Systems Approach to the Development of Cognition and Action. Cambridge, MA: MIT Press.Google Scholar
Allen, M. I., Kalousek, D. K., Chernoff, G. F., et al. (1993). Evidence for multi-site closure of the neural tube in humans. American Journal of Medical Genetics, 47, 723–43.CrossRefGoogle ScholarPubMed
Volcik, K. A., Blanton, S. H., Tyerman, G. H., et al. (2000). Methylenetetrahydrofolate reductase and spina bifida: Evaluation of level of defect and maternal genotypic risk in Hispanics. American Journal of Medical Genetics, 95, 21–7.3.0.CO;2-M>CrossRefGoogle ScholarPubMed
Wiig, E. H. & Secord, W. (1989). Test of Language Competence – Expanded Edition (TLC-E). San Antonio, TX: The Psychological Corporation.Google Scholar
Williams, L. J., Rasmussen, S. A., Flores, R. S., Kirby, R. S., & Edmunds, L. D. (2005). Decline in the prevalence of spina bifida and anencephaly by race/ethnicity: 1995–2002. Pediatrics, 116, 580–6.CrossRefGoogle Scholar
Wills, K. E. (1993). Neuropsychological functioning in children with spina bifida and/or hydrocephalus. Journal of Clinical Child Psychology, 22, 247–65.CrossRefGoogle Scholar
Wills, K. E., Holmbeck, G. N., Dillon, K., & McClone, D. G. (1990). Intelligence and achievement in children with myelomeningocele. Journal of Pediatric Psychology, 15, 161–76.CrossRefGoogle ScholarPubMed
Yeates, K. O. & Enrile, B. G. (2005). Implicit and explicit memory in children with congenital and acquired brain disorder. Neuropsychology, 19, 618–28.CrossRefGoogle ScholarPubMed
Yuill, N. & Oakhill, J. (1991). Children's problems in text comprehension: An experimental investigation. Cambridge Monographs and Texts in Applied Psycholinguistics. New York: Cambridge University Press.Google Scholar
Zwaan, R. A. & Radvansky, G. A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123, 162–85.CrossRefGoogle ScholarPubMed

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