Brain Imaging and Behavior

, Volume 10, Issue 1, pp 238–251 | Cite as

White and grey matter relations to simple, choice, and cognitive reaction time in spina bifida

  • Maureen Dennis
  • Paul T. Cirino
  • Nevena Simic
  • Jenifer Juranek
  • W. Pat Taylor
  • Jack M. Fletcher
Original Research

Abstract

Elevated reaction time (RT) is common in brain disorders. We studied three forms of RT in a neurodevelopmental disorder, spina bifida myelomeningocele (SBM), characterized by regional alterations of both white and grey matter, and typically developing individuals aged 8 to 48 years, in order to establish the nature of the lifespan-relations of RT and brain variables. Cognitive accuracy and RT speed and variability were all impaired in SBM relative to the typically developing group, but the most important effects of SBM on RT are seen on tasks that require a cognitive decision rule. Individuals with SBM are impaired not only in speeded performance, but also in the consistency of their performance on tasks that extend over time, which may contribute to poor performance on a range of cognitive tasks. The group with SBM showed smaller corrected corpus callosum proportions, larger corrected cerebellar white matter proportions, and larger corrected proportions for grey matter in the Central Executive and Salience networks. There were clear negative relations between RT measures and corpus callosum, Central Executive, and Default Mode networks in the group with SBM; relations were not observed in typically developing age peers. Statistical mediation analyses indicated that corpus callosum and Central Executive Network were important mediators. While RT is known to rely heavily on white matter under conditions of typical development and in individuals with adult-onset brain injury, we add the new information that additional involvement of grey matter may be important for a key neuropsychological function in a common neurodevelopmental disorder.

Keywords

Spina bifida Hydrocephalus Reaction time Magnetic resonance imaging FreeSurfer 

Abbreviations

CEN

Central executive network

DMN

Default mode network

GM

Grey matter

IQ

Intelligence quotient

ms

Millisecond

ROI

Region of interest

RT

Reaction time

SBM

Spina bifida myelomeningocele

SES

Socioeconomic status

SN

Salience network

TD

Typically developing

WM

White matter

Notes

Acknowledgments

This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Grant (P01 HD35946-06, “Spina Bifida: Cognitive and Neurobiological Variability”). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development or the National Institutes of Health. We thank Caroline Roncadin for assistance with the adapting her RT paradigms for the study.

Supplementary material

11682_2015_9388_MOESM1_ESM.doc (106 kb)
ESM 1 (DOC 105 kb)

References

  1. Achiron, A., Doniger, G. M., Harel, Y., Appleboim-Gavish, N., Lavie, M., & Simon, E. S. (2007). Prolonged response times characterize cognitive performance in multiple sclerosis. [Comparative Study]. European Journal of Neurology, 14(10), 1102–1108. doi: 10.1111/j.1468-1331.2007.01909.x.CrossRefPubMedGoogle Scholar
  2. Adolphs, R. (2010). What does the amygdala contribute to social cognition? Annals of the New York Academy of Sciences, 1191, 42–61. doi: 10.1111/j.1749-6632.2010.05445.x.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Anderson, V., Catroppa, C., Morse, S., Haritou, F., & Rosenfeld, J. (2005). Attentional and processing skills following traumatic brain injury in early childhood. Brain Injury, 19(9), 699–710. doi: 10.1080/02699050400025281.CrossRefPubMedGoogle Scholar
  4. Anstey, K. J., Mack, H. A., Christensen, H., Li, S. C., Reglade-Meslin, C., Maller, J., et al. (2007). Corpus callosum size, reaction time speed and variability in mild cognitive disorders and in a normative sample. Neuropsychologia, 45(8), 1911–1920. doi: 10.1016/j.neuropsychologia.2006.11.020.CrossRefPubMedGoogle Scholar
  5. Benes, F. M., Turtle, M., Khan, Y., & Farol, P. (1994). Myelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Archives of General Psychiatry, 51(6), 477–484. doi: 10.1001/archpsyc.1994.03950060041004.CrossRefPubMedGoogle Scholar
  6. Bonnelle, V., Ham, T. E., Leech, R., Kinnunen, K. M., Mehta, M. A., Greenwood, R. J., et al. (2012). Salience network integrity predicts default mode network function after traumatic brain injury. Proceedings of the National Academy of Sciences of the United States of America, 109(12), 4690–4695. doi: 10.1073/pnas.1113455109.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 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(2), 185–198. doi: 10.1037/0894-4105.15.2.185.CrossRefPubMedGoogle Scholar
  8. Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38. doi: 10.1196/annals.1440.011.CrossRefPubMedGoogle Scholar
  9. Dennis, M., & Barnes, M. A. (2010). The cognitive phenotype of spina bifida meningomyelocele. Developmental Disabilities Research Reviews, 16(1), 31–39. doi: 10.1002/ddrr.89.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Dennis, M., Edelstein, K., Copeland, K., Frederick, J., Francis, D. J., Hetherington, R., et al. (2005a). Covert orienting to exogenous and endogenous cues in children with spina bifida. Neuropsychologia, 43(6), 976–987. doi: 10.1016/j.neuropsychologia.2004.08.012.CrossRefPubMedGoogle Scholar
  11. Dennis, M., Edelstein, K., Copeland, K., Frederick, J. A., Francis, D. J., Hetherington, R., et al. (2005b). Space-based inhibition of return in children with spina bifida. Neuropsychology, 19(4), 456–465. doi: 10.1037/0894-4105.19.4.456.CrossRefPubMedGoogle Scholar
  12. 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(2), 285–296. doi: 10.1017/S1355617706060371.CrossRefPubMedGoogle Scholar
  13. Dennis, M., Francis, D. J., Cirino, P. T., Schachar, R., Barnes, M. A., & Fletcher, J. M. (2009). Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders. Journal of the International Neuropsychological Society, 15(3), 331–343. doi: 10.1017/S1355617709090481.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Der, G., & Deary, I. J. (2006). Age and sex differences in reaction time in adulthood: results from the United Kingdom Health and Lifestyle Survey. Psychology and Aging, 21(1), 62–73. doi: 10.1037/0882-7974.21.1.62.CrossRefPubMedGoogle Scholar
  15. Fletcher, J. M., Copeland, K., Frederick, J. A., Blaser, S. E., Kramer, L. A., Northrup, H., et al. (2005). Spinal lesion level in spina bifida: a source of neural and cognitive heterogeneity. Journal of Neurosurgery, 102(3 Suppl), 268–279. doi: 10.3171/ped.2005.102.3.0268.PubMedGoogle Scholar
  16. Gorus, E., De Raedt, R., & Mets, T. (2006). Diversity, dispersion and inconsistency of reaction time measures: effects of age and task complexity. Aging Clinical and Experimental Research, 18(5), 407–417. doi: 10.1007/BF03324837.CrossRefPubMedGoogle Scholar
  17. Gu, X., Liu, X., Van Dam, N. T., Hof, P. R., & Fan, J. (2013). Cognition-emotion integration in the anterior insular cortex. Cerebral Cortex, 23(1), 20–27. doi: 10.1093/cercor/bhr367.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Han, X., Jovicich, J., Salat, D., van der Kouwe, A., Quinn, B., Czanner, S., et al. (2006). Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer. NeuroImage, 32(1), 180–194. doi: 10.1016/j.neuroimage.2006.02.051.CrossRefPubMedGoogle Scholar
  19. Hasan, K. M., Eluvathingal, T. J., Kramer, L. A., Ewing-Cobbs, L., Dennis, M., & Fletcher, J. M. (2008). White matter microstructural abnormalities in children with spina bifida myelomeningocele and hydrocephalus: a diffusion tensor tractography study of the association pathways. Journal of Magnetic Resonance Imaging, 27(4), 700–709. doi: 10.1002/jmri.21297.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Heath, M., Grierson, L., Binsted, G., & Elliott, D. (2007). Interhemispheric transmission time in persons with Down syndrome. Journal of Intellectual Disability Research, 51(Pt 12), 972–981. doi: 10.1111/j.1365-2788.2007.01009.x.CrossRefPubMedGoogle Scholar
  21. Hultsch, D. F., MacDonald, S. W., Hunter, M. A., Levy-Bencheton, J., & Strauss, E. (2000). Intraindividual variability in cognitive performance in older adults: comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology, 14(4), 588–598. doi: 10.1037/0894-4105.14.4.588.CrossRefPubMedGoogle Scholar
  22. Hultsch, D. F., MacDonald, S. W., & Dixon, R. A. (2002). Variability in reaction time performance of younger and older adults. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 57(2), 101–115. doi: 10.1093/geronb/57.2.P101.CrossRefGoogle Scholar
  23. Jovicich, J., Czanner, S., Han, X., Salat, D., van der Kouwe, A., Quinn, B., et al. (2009). MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. NeuroImage, 46(1), 177–192. doi: 10.1016/j.neuroimage.2009.02.010.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Juranek, J., & Salman, M. S. (2010). Anomalous development of brain structure and function in spina bifida myelomeningocele. Developmental Disabilities Research Reviews, 16(1), 23–30. doi: 10.1002/ddrr.88.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Juranek, J., Fletcher, J. M., Hasan, K. M., Breier, J. I., Cirino, P. T., Pazo-Alvarez, P., et al. (2008). Neocortical reorganization in spina bifida. NeuroImage, 40(4), 1516–1522. doi: 10.1016/j.neuroimage.2008.01.043.CrossRefPubMedPubMedCentralGoogle Scholar
  26. Kail, R. (1993). Processing time decreases globally at an exponential rate during childhood and adolescence. Journal of Experimental Child Psychology, 56(2), 254–265. doi: 10.1006/jecp.1993.1034.CrossRefPubMedGoogle Scholar
  27. Kourtidou, P., McCauley, S. R., Bigler, E. D., Traipe, E., Wu, T. C., Chu, Z. D., et al. (2013). Centrum semiovale and corpus callosum integrity in relation to information processing speed in patients with severe traumatic brain injury. The Journal of Head Trauma Rehabilitation, 28(6), 433–441. doi: 10.1097/HTR.0b013e3182585d06.CrossRefPubMedGoogle Scholar
  28. Lew, H. L., Thomander, D., Gray, M., & Poole, J. H. (2007). The effects of increasing stimulus complexity in event-related potentials and reaction time testing: clinical applications in evaluating patients with traumatic brain injury. Journal of Clinical Neurophysiology, 24(5), 398–404. doi: 10.1097/WNP.0b013e318150694b.CrossRefPubMedGoogle Scholar
  29. Luks, T. L., Oliveira, M., Possin, K. L., Bird, A., Miller, B. L., Weiner, M. W., et al. (2010). Atrophy in two attention networks is associated with performance on a Flanker task in neurodegenerative disease. Neuropsychologia, 48(1), 165–170. doi: 10.1016/j.neuropsychologia.2009.09.001.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Mabbott, D. J., Noseworthy, M. D., Bouffet, E., Rockel, C., & Laughlin, S. (2006). Diffusion tensor imaging of white matter after cranial radiation in children for medulloblastoma: correlation with IQ. Neuro-Oncology, 8(3), 244–252. doi: 10.1215/15228517-2006-002.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Menon, V. (2011). Large-scale brain networks and psychopathology: a unifying triple network model. Trends in Cognitive Science, 15(10), 483–506. doi: 10.1016/j.tics.2011.08.003.CrossRefGoogle Scholar
  32. Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain Structure and Function, 214(5–6), 655–667. doi: 10.1007/s00429-010-0262-0.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Menzies, L., Achard, S., Chamberlain, S. R., Fineberg, N., Chen, C. H., del Campo, N., et al. (2007). Neurocognitive endophenotypes of obsessive-compulsive disorder. Brain, 130(Pt 12), 3223–3236. doi: 10.1093/brain/awm205.CrossRefPubMedGoogle Scholar
  34. Niogi, S. N., Mukherjee, P., Ghajar, J., Johnson, C., Kolster, R. A., Sarkar, R., et al. (2008). Extent of microstructural white matter injury in postconcussive syndrome correlates with impaired cognitive reaction time: a 3T diffusion tensor imaging study of mild traumatic brain injury. AJNR - American Journal of Neuroradiology, 29(5), 967–973. doi: 10.3174/ajnr.A0970.CrossRefPubMedGoogle Scholar
  35. 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(4), 948–954. doi: 10.1016/j.neuroimage.2004.10.014.CrossRefPubMedGoogle Scholar
  36. Palmer, S. L., Armstrong, C., Onar-Thomas, A., Wu, S., Wallace, D., Bonner, M. J., et al. (2013). Processing speed, attention, and working memory after treatment for medulloblastoma: an international, prospective, and longitudinal study. Journal of Clinical Oncology, 31(28), 3494–3500. doi: 10.1200/JCO.2012.47.4775.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Perneczky, R., Ghosh, B. C., Hughes, L., Carpenter, R. H., Barker, R. A., & Rowe, J. B. (2011). Saccadic latency in Parkinson’s disease correlates with executive function and brain atrophy, but not motor severity. Neurobiology of Disease, 43(1), 79–85. doi: 10.1016/j.nbd.2011.01.032.CrossRefPubMedPubMedCentralGoogle Scholar
  38. Prigatano, G. P., Zeiner, H. K., Pollay, M., & Kaplan, R. J. (1983). Neuropsychological functioning in children with shunted uncomplicated hydrocephalus. Child’s Brain, 10(2), 112–120. doi: 10.1159/000120104.PubMedGoogle Scholar
  39. Ratcliff, R., Thapar, A., & McKoon, G. (2001). The effects of aging on reaction time in a signal detection task. Psychology and Aging, 16(2), 323–341. doi: 10.1037/0882-7974.16.2.323.CrossRefPubMedGoogle Scholar
  40. Schatz, J., Kramer, J. H., Ablin, A., & Matthay, K. K. (2000). Processing speed, working memory, and IQ: a developmental model of cognitive deficits following cranial radiation therapy. Neuropsychology, 14(2), 189–200. doi: 10.1037/0894-4105.14.2.189.CrossRefPubMedGoogle Scholar
  41. Singer, T., Seymour, B., O’Doherty, J. P., Stephan, K. E., Dolan, R. J., & Frith, C. D. (2006). Empathic neural responses are modulated by the perceived fairness of others. Nature, 439(7075), 466–469. doi: 10.1038/nature04271.CrossRefPubMedPubMedCentralGoogle Scholar
  42. Sridharan, D., Levitin, D. J., & Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences of the United States of America, 105(34), 12569–12574. doi: 10.1073/pnas.0800005105.CrossRefPubMedPubMedCentralGoogle Scholar
  43. Tew, B., Laurence, K., & Richards, A. (1980). Inattention among children with hydrocephalus and spina bifida. Zeitschrift für Kinderchirurgie, 31, 381–385. doi: 10.1055/s-2008-1066449.Google Scholar
  44. Treble, A., Juranek, J., Stuebing, K. K., Dennis, M., & Fletcher, J. M. (2013). Functional significance of atypical cortical organization in spina bifida myelomeningocele: relations of cortical thickness and gyrification with IQ and fine motor dexterity. Cerebral Cortex, 23(10), 2357–2369. doi: 10.1093/cercor/bhs226.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Turken, A., Whitfield-Gabrieli, S., Bammer, R., Baldo, J. V., Dronkers, N. F., & Gabrieli, J. D. (2008). Cognitive processing speed and the structure of white matter pathways: convergent evidence from normal variation and lesion studies. NeuroImage, 42(2), 1032–1044. doi: 10.1016/j.neuroimage.2008.03.057.CrossRefPubMedPubMedCentralGoogle Scholar
  46. Walhovd, K. B., & Fjell, A. M. (2007). White matter volume predicts reaction time instability. Neuropsychologia, 45(10), 2277–2284. doi: 10.1016/j.neuropsychologia.2007.02.022.CrossRefPubMedGoogle Scholar
  47. Ware, A. L., Juranek, J., Williams, V. J., Cirino, P. T., Dennis, M., & Fletcher, J. M. (2014). Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida. NeuroImage: Clinical. doi: 10.1016/j.nicl.2014.05.012.Google Scholar
  48. Wiedenbauer, G., & Jansen-Osmann, P. (2007). Mental rotation ability of children with spina bifida: what influence does manual rotation training have? Developmental Neuropsychology, 32(3), 809–824. doi: 10.1080/87565640701539626.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Maureen Dennis
    • 1
    • 2
    • 3
  • Paul T. Cirino
    • 4
  • Nevena Simic
    • 1
  • Jenifer Juranek
    • 5
  • W. Pat Taylor
    • 4
  • Jack M. Fletcher
    • 4
  1. 1.Program in Neurosciences and Mental HealthThe Hospital for Sick ChildrenTorontoCanada
  2. 2.Department of Surgery, Faculty of MedicineUniversity of TorontoTorontoCanada
  3. 3.Music and Health Research Collaboratory, Faculty of MusicUniversity of TorontoTorontoCanada
  4. 4.Department of Psychology, and Texas Institute for Measurement, Evaluation and Statistics (TIMES)University of HoustonHoustonUSA
  5. 5.Department of PediatricsUniversity of Texas Health Science CenterHoustonUSA

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