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Motor learning in children with spina bifida: Dissociation between performance level and acquisition rate

Published online by Cambridge University Press:  01 October 2004

KIM EDELSTEIN ,
MAUREEN DENNIS ,
KIM COPELAND ,
JON FREDERICK ,
DAVID FRANCIS ,
ROSS HETHERINGTON ,
MICHAEL E. BRANDT  and
JACK M. FLETCHER
KIM EDELSTEIN
Affiliation:
Brain and Behaviour Program, The Hospital for Sick Children, Toronto, Canada Department of Psychology, The Hospital for Sick Children, Toronto, Canada
MAUREEN DENNIS
Affiliation:
Brain and Behaviour Program, The Hospital for Sick Children, Toronto, Canada Department of Psychology, The Hospital for Sick Children, Toronto, Canada Department of Surgery, University of Toronto, Toronto, Canada Department of Psychology, University of Toronto, Toronto, Canada
KIM COPELAND
Affiliation:
Department of Psychology, University of Houston, Houston, Texas
JON FREDERICK
Affiliation:
Center for Computational Biomedicine, University of Texas Health Science Center at Houston
DAVID FRANCIS
Affiliation:
Department of Psychology, University of Houston, Houston, Texas
ROSS HETHERINGTON
Affiliation:
Community Health and Knowledge Transfer, The Hospital for Sick Children, Toronto, Canada Department of Psychology, University of Toronto, Toronto, Canada
MICHAEL E. BRANDT
Affiliation:
Department of Psychology, University of Houston, Houston, Texas Center for Computational Biomedicine, University of Texas Health Science Center at Houston
JACK M. FLETCHER
Affiliation:
Department of Pediatrics, University of Texas Health Science Center at Houston
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Abstract

The cerebellum is part of a neural circuit involved in procedural motor learning. We examined how congenital cerebellar malformations affect mirror drawing performance, a procedural learning task that involves learning to trace the outline of a star while looking at the reflection of the star in a mirror. Participants were 88 children with spina bifida myelomeningocele, a neural tube defect that results in lesions of the spinal cord, dysmorphology of the cerebellum, and requires shunt treatment for hydrocephalus, and 35 typically developing controls. Participants completed 10 trials in the morning and 10 trials following a 3-hr delay. Although children with spina bifida myelomeningocele were initially slower at tracing and made more errors than controls, all participants improved their performance of the task, as demonstrated by increased speed and accuracy across trials. Moreover, degree of cerebellar dysmorphology was not correlated with level of performance, rate of acquisition, or retention of mirror drawing. The results suggest that congenital cerebellar dysmorphology in spina bifida does not impair motor skill learning as measured by acquisition and retention of the mirror drawing task. (JINS, 2004, 10, 877–887.)

Keywords

CerebellumHydrocephalusMirror drawingMagnetic resonance imaging
Type
Research Article
Information
Journal of the International Neuropsychological Society , Volume 10 , Issue 6 , October 2004 , pp. 877 - 887
Copyright
© 2004 The International Neuropsychological Society

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References

REFERENCES

Anderson, E.M. & Plewis, I. (1977). Impairment of a motor skill in children with spina bifida cystica and hydrocephalus: An exploratory study. British Journal of Psychology, 68, 61–70.CrossRefGoogle Scholar
Barkovich, A.J. (1995). Pediatric neuroimaging (2nd ed.). New York: Raven Press.
Brandt, M.E., Bohan, T.P., Kramer, L.A., & Fletcher, J.M. (1994). Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images. Computerized Medical Imaging Graphics, 18, 25–34.CrossRefGoogle Scholar
Brandt, M.E., Bohan, T.P., Thorstad, K., Beaver, S.R., Davidson, K.C., Francis, D.J., Kramer, L.A., & Fletcher, J.M. (1996). Reliability of brain structure morphometry in hydrocephalic children using MR images. Magnetic Resonance Imaging, 14, 649–655.CrossRefGoogle Scholar
Brandt, M.E., Fletcher, J.M., & Bohan, T.P. (1992). Estimation of CSF, white, and gray matter volumes from MRIs of hydrocephalic and HIV-positive subjects. Proceedings of SimTec/WNN, 643–650.
Clark, R.E., Manns, J.R., & Squire, L.R. (2002). Classical conditioning, awareness, and brain systems. Trends in Cognitive Sciences, 6, 524–531.CrossRefGoogle 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, 642–652.CrossRefGoogle Scholar
del Bigio, M. (1993) Neuropathological changes caused by hydrocephalus. Acta Neuropathologica, 18, 573–585.CrossRefGoogle Scholar
Dennis, M., Edelstein, K., Hetherington, R., Copeland, K., Frederick, J., Blaser, S.E., Kramer, L.A., Drake, J.M., Brandt, M., & Fletcher, J.M. (2004) Neurobiology of perceptual and motor timing in children with spina bifida in relation to cerebellar volume. Brain, 127, 1292–1301.CrossRefGoogle Scholar
Dennis, M., Hetherington, C.R., Spiegler, B.J., & Barnes, M.A. (1999). Functional consequences of congenital cerebellar dysmorphologies and acquired cerebellar lesions of childhood. In S.H. Broman & J.M. Fletcher (Eds.), The changing nervous system: Neurobehavioral consequences of early brain disorders (pp. 172–198). New York: Oxford University Press.
Desmond, J.E. & Fiez, J.A. (1998). Neuroimaging studies of the cerebellum: language, learning, and memory. Trends in Cognitive Sciences, 2, 355–362.CrossRefGoogle Scholar
Doyon, J., Penhune, V., & Ungerleider, L.G. (2003). Distinct contribution of the cortico–striatal and cortico–cerebellar systems to motor skill learning. Neuropsychologia, 41, 252–262.CrossRefGoogle Scholar
Fletcher, J.M., Bohan, T.P., Brandt, M.E., Kramer, L.A., Brookshire, B.L., Thorstad, K., Davidson, K.C., Francis, D.J., McCauley, S.R., & Baumgartner, J.E. (1996) Morphometric evaluation of the hydrocephalic brain: Relationships with cognitive development. Child's Nervous System, 12, 192–199.CrossRefGoogle Scholar
Fletcher, J.M., Copeland, K., Frederick, J., Blaser, S.E., Kramer, L.A., Hannay, H.J., Brandt, M.E., Francis, D.J., Villarreal, G., Drake, J.M., Laurent, J., Townsend, I., Inwood, S., Boudousquie, A., & Dennis, M. (under review). Spinal lesion level in spina bifida meningomyelocele: A source of neural and cognitive heterogeneity. Neurosurgery.
Fletcher, J.M., Dennis, M., & Northrup, H. (2000) Hydrocephalus. In K.O. Yeates, M.D. Ris, & H.G. Taylor (Eds.), Pediatric neuropsychology: Research, theory and practice (pp. 25–46). New York: Guilford Press.
Fletcher, J.M., Francis, J., Thompson, N.M., Davidson, K.C., & Miner, M.E. (1992). Verbal and nonverbal skill discrepancies in hydrocephalic children. Journal of Clinical and Experimental Neuropsychology, 14, 593–609.CrossRefGoogle Scholar
Gabrieli, J.D.E., Corkin, S., Mickel, S.F., & Growdon, J.H. (1993). Intact acquisition and long-term retention of mirror-tracing skill in Alzheimer's disease and in global amnesia. Behavioral Neuroscience, 107, 899–910.CrossRefGoogle Scholar
Gerig, G., Kubler, O., Kikinis, R., & Jolesz, F.A. (1992). Nonlinear anisotropic filtering of MRI data. IEEE Transactions Medical Imaging, 11, 221–232.CrossRefGoogle Scholar
Harris, I.M., Fulham, M.J., & Miller, L.A. (2001). The effects of mesial temporal and cerebellar hypometabolism on learning and memory. Journal of the International Neurosychological Society, 7, 353–362.CrossRefGoogle Scholar
Hetherington, R., Dennis, M., Spiegler, B. (2000). Perception and estimation of time in long-term survivors of childhood posterior fossa tumors. Journal of the International Neuropsychological Society, 6, 682–692.CrossRefGoogle Scholar
Jueptner, M. & Weiller, C. (1998). A review of differences between basal ganglia and cerebellar control of movements as revealed by functional imaging studies. Brain, 121, 1437–1449.CrossRefGoogle Scholar
Laforce, R. & Doyon, J. (2002). Differential roles for the striatum and cerebellum in response to novel movements using a motor learning paradigm. Neuropsychologia, 40, 512–517.CrossRefGoogle Scholar
Laforce, R. & Doyon, J. (2001). Distinct contribution of the striatum and cerebellum to motor learning. Brain and Cognition, 45, 189–211.CrossRefGoogle Scholar
Miall, R.C. & Reckess, G.Z. (2002). The cerebellum and the timing of coordinated eye and hand tracking. Brain and Cognition, 48, 212–226.CrossRefGoogle Scholar
Milner, B., Squire, L.R., & Kandel, E.R. (1998). Cognitive neuroscience and the study of memory. Neuron, 20, 445–468.CrossRefGoogle Scholar
Mostofsky, S.H., Green, J.T., Meginley, M., Christensen, J.R., & Woodruff-Pak, D.S. (1999). Conditioning in identical twins with ataxia-telangiectasia. Neurocase, 5, 425–433.CrossRefGoogle Scholar
Ohyama, T., Nores, W.L., Murphy, M., & Mauk, M.D. (2003). What the cerebellum computes. Trends in Neurosciences, 26, 222–227.CrossRefGoogle Scholar
Pao, Y.H. (1989). Adaptive pattern recognition and neural networks. Reading, MA: Addison Wesley.
Park, C.H., Stewart, W., Khoury, M.J., & Mulinare, J. (1992). Is there etiologic heterogeneity between upper and lower neural tube defects? American Journal of Epidemiology, 136, 1491–1493.Google Scholar
Pascual-Leone, A., Grafman, J., Clark, K., Stewart, M., Massaquoi, S., Lou, J.S., & Hallett, M. (1993). Procedural learning in Parkinson's disease and cerebellar degeneration. Annals of Neurology, 34, 594–602.CrossRefGoogle Scholar
Sanes, J.N., Dimitrov, B., & Hallett, M. (1990). Motor learning in patients with cerebellar dysfunction. Brain, 113, 103–120.CrossRefGoogle Scholar
Seidler, R.D., Purushotham, A., Kim, S.-G., Ugurbul, K., Willingham, D., & Ashe, J. (2002). Cerebellum activation associated with performance change but not motor learning. Science, 296, 2043–2046.CrossRefGoogle Scholar
Singer, J.D. (1998). Using SAS PROC MIXED to fit multilevel models, hierarchical models, and individual growth models. Journal of Educational and Behavioral Statistics, 24, 323–355.CrossRefGoogle Scholar
Swanson, J.M. (1992). School-based assessments and interventions for ADD students. Irvine, CA: KC Publishing.
Thach, W.T. (1998). What is the role of the cerebellum in motor learning and cognition? Trends in Cognitive Sciences, 2, 331–337.Google Scholar
Thorndike, R.L., Hagen, E.P., & Sattler, J.M. (1986). The Stanford-Binet Intelligence Scale (4th ed.). Itasca, IL: Riverside.
Timmann, D., Shimansky, Y., Larson, P.S., Wunderlich, D.A., Stelmach, G.E., & Bloedel, J.R. (1996). Visuomotor learning in cerebellar patients. Behavioral Brain Research, 81, 99–113.CrossRefGoogle Scholar
Van der Put, N.M., van Straaten, H.W., Trijbels, F.J., & Blom, H.J. (2001). Folate, homocysteine and neural tube defects: An overview. Experimental Biological Medicine, 226, 243–270CrossRefGoogle Scholar
Volcik, K.A., Blanton, S.H., & Northrup, H. (2001). Examinations of methylenetetrahydrofolate reductase C677T and A1298C mutations and in utero viability. American Journal of Human Genetics, 69, 1150–1153.CrossRefGoogle Scholar
Weiner, M.J., Hallett, M., & Funkenstein, H.H. (1983). Adaptation to lateral displacement of vision in patients with lesions of the central nervous system. Neurology, 33, 766–772.CrossRefGoogle Scholar
Wills, K.E. (1993). Neuropsychological functioning in children with spina bifida and/or hydrocephalus. Journal of Clinical Child Psychology, 22, 247–265.CrossRefGoogle Scholar