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Tract-Based Spatial Statistics Reveal Altered Relationship Between Non-verbal Reasoning Abilities and White Matter Integrity in Autism Spectrum Disorder

Published online by Cambridge University Press:  08 April 2013

Timothy M. Ellmore*
Affiliation:
Department of Psychology and Program in Behavioral and Cognitive Neuroscience, The City College and Graduate Center of the City University of New York, New York, New York
Hai Li
Affiliation:
Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, Texas
Zhong Xue
Affiliation:
Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, Texas
Stephen T.C. Wong
Affiliation:
Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, Texas
Richard E. Frye
Affiliation:
Arkansas Children's Hospital Research Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas
*
Correspondence and reprint requests to: Timothy M. Ellmore, Department of Psychology, NAC 7/120, 160 Convent Avenue, New York, New York 10031. E-mail: [email protected]

Abstract

Altered brain connectivity accompanies autism spectrum disorders (ASD), but the relationship between connectivity and intellectual abilities, which often differs within ASD, and between ASD and typically developing (TD) children, is not understood. Here, diffusion tensor imaging (DTI) was used to explore the relationship between white matter integrity and non-verbal intelligence quotients (IQ) in children with ASD and in age- and gender-matched TD children. Tract-based spatial statistical analyses (TBSS) of DTI fractional anisotropy (FA) revealed altered relationships between white matter and IQ. Different relationships were found using within-group analyses, where regions of significant (p < .05, corrected) correlations in ASD overlapped minimally with regions of FA-IQ correlations in TD subjects. An additional between-groups analysis revealed significant correlation differences in widespread cortical and subcortical areas. These preliminary findings suggest altered brain connectivity may underlie some differences in intellectual abilities of ASD, and should be investigated further in larger samples as a function of development. (JINS, 2013, 19, 1–6)

Type
Brief Communication
Copyright
Copyright © The International Neuropsychological Society 2013 

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References

Ameis, S.H., Fan, J., Rockel, C., Voineskos, A.N., Lobaugh, N.J., Soorya, L., Anagnostou, E. (2011). Impaired structural connectivity of socio-emotional circuits in autism spectrum disorders: A diffusion tensor imaging study. PLoS One, 6(11), e28044.CrossRefGoogle ScholarPubMed
Anderson, J.S., Lange, N., Froehlich, A., DuBray, M.B., Druzgal, T.J., Froimowitz, M.P., Lainhart, J.E. (2011). Decreased left posterior insular activity during auditory language in autism. American Journal of Neuroradiology, 31(1), 131139.CrossRefGoogle Scholar
Bode, M.K., Mattila, M.L., Kiviniemi, V., Rahko, J., Moilanen, I., Ebeling, H., Nikkinen, J. (2011). White matter in autism spectrum disorders – Evidence of impaired fiber formation. Acta Radiologica, 52(10), 11691174.CrossRefGoogle ScholarPubMed
Casanova, M.F. (2007). The neuropathology of autism. Brain Pathology, 17(4), 422433.CrossRefGoogle ScholarPubMed
Charman, T., Pickles, A., Simonoff, E., Chandler, S., Loucas, T., Baird, G. (2011). IQ in children with autism spectrum disorders: Data from the Special Needs and Autism Project (SNAP). Psychological Medicine, 41(3), 619627.CrossRefGoogle ScholarPubMed
Cheng, Y., Chou, K.H., Chen, I.Y., Fan, Y.T., Decety, J., Lin, C.P. (2010). Atypical development of white matter microstructure in adolescents with autism spectrum disorders. Neuroimage, 50(3), 873882.CrossRefGoogle ScholarPubMed
Cheung, C., Chua, S.E., Cheung, V., Khong, P.L., Tai, K.S., Wong, T.K., McAlonan, G.M. (2009). White matter fractional anisotrophy differences and correlates of diagnostic symptoms in autism. Journal of Child Psychology and Psychiatry, 50(9), 11021112.CrossRefGoogle ScholarPubMed
Courchesne, E., Pierce, K. (2005). Brain overgrowth in autism during a critical time in development: Implications for frontal pyramidal neuron and interneuron development and connectivity. International Journal of Developmental Neuroscience, 23(2-3), 153170.CrossRefGoogle ScholarPubMed
Fletcher, P.T., Whitaker, R.T., Tao, R., DuBray, M.B., Froehlich, A., Ravichandran, C., Lainhart, J.E. (2011). Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism. Neuroimage, 51(3), 11171125.CrossRefGoogle Scholar
Frye, R.E., Beauchamp, M.S. (2009). Receptive language organization in high-functioning autism. Journal of Child Neurology, 24(2), 231236.CrossRefGoogle ScholarPubMed
Fugard, A.J., Stewart, M.E., Stenning, K. (2011). Visual/verbal-analytic reasoning bias as a function of self-reported autistic-like traits: A study of typically developing individuals solving Raven's Advanced Progressive Matrices. Autism, 15(3), 327340.CrossRefGoogle ScholarPubMed
Geschwind, D.H. (2009). Advances in autism. Annual Review of Medicine, 60, 367380.CrossRefGoogle ScholarPubMed
Hammill, D., Pearson, N., Wiederholt, J. (1997). Comprehensive test of nonverbal intelligence. Austin, TX: Pro-Ed.Google Scholar
Jou, R.J., Mateljevic, N., Kaiser, M.D., Sugrue, D.R., Volkmar, F.R., Pelphrey, K.A. (2011). Structural neural phenotype of autism: Preliminary evidence from a diffusion tensor imaging study using tract-based spatial statistics. AJNR American Journal of Neuroradiology, 32(9), 16071613.CrossRefGoogle ScholarPubMed
Kamphaus, R.W. (2005). Clinical assessment of child and adolescent intelligence (2nd ed). New York: Springer.CrossRefGoogle Scholar
Kleinhans, N.M., Pauley, G., Richards, T., Neuhaus, E., Martin, N., Corrigan, N.M., Dager, S.R. (2012). Age-related abnormalities in white matter microstructure in autism spectrum disorders. Brain Research, 1479, 116.CrossRefGoogle ScholarPubMed
Morgan, J.T., Chana, G., Pardo, C.A., Achim, C., Semendeferi, K., Buckwalter, J., Everall, I.P. (2010). Microglial activation and increased microglial density observed in the dorsolateral prefrontal cortex in autism. Biological Psychiatry, 68(4), 368376. doi:10.1016/j.biopsych.2010.05.024.CrossRefGoogle ScholarPubMed
Perrin, J.S., Leonard, G., Perron, M., Pike, G.B., Pitiot, A., Richer, L., Paus, T. (2009). Sex differences in the growth of white matter during adolescence. Neuroimage, 45(4), 10551066.CrossRefGoogle ScholarPubMed
Smith, S.M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T.E., Mackay, C.E., Behrens, T.E. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4), 14871505.CrossRefGoogle ScholarPubMed
Tamnes, C.K., Ostby, Y., Walhovd, K.B., Westlye, L.T., Due-Tonnessen, P., Fjell, A.M. (2010). Intellectual abilities and white matter microstructure in development: A diffusion tensor imaging study. Human Brain Mapping, 31(10), 16091625. doi:10.1002/hbm.20962.CrossRefGoogle ScholarPubMed
Vissers, M.E., Cohen, M.X., Geurts, H.M. (2012). Brain connectivity and high functioning autism: A promising path of research that needs refined models, methodological convergence, and stronger behavioral links. Neuroscience and Biobehavioral Reviews, 36(1), 604625. doi:10.1016/j.neubiorev.2011.09.003.CrossRefGoogle ScholarPubMed