Journal of Autism and Developmental Disorders

, Volume 45, Issue 2, pp 363–375 | Cite as

An Electrophysiological Investigation of Interhemispheric Transfer Time in Children and Adolescents with High-Functioning Autism Spectrum Disorders

  • Ann Clawson
  • Peter E. Clayson
  • Mikle South
  • Erin D. Bigler
  • Michael J. LarsonEmail author
Original Paper


Little is known about the functional impact of putative deficits in white-matter connectivity across the corpus callosum (CC) in individuals with autism spectrum disorders (ASDs). We utilized the temporal sensitivity of event-related potentials to examine the interhemispheric transfer time (IHTT) of basic visual information across the CC in youth with high-functioning ASD relative to healthy controls. We conducted two experiments: a visual letter matching experiment (n = 46) and a visual picture matching experiment, (n = 48) and utilized both electrophysiological (N1 and P1 amplitudes and latencies) and behavioral [response times (RTs), error rates] indices of IHTT. There were no significant group differences on either experiment for RTs, error rates, or N1 and P1 latencies, suggesting that on basic tasks the timing of information flow across the CC may not be altered in high functioning ASD.


Autism Interhemispheric transfer time N1 P1 Event-related potential Corpus callosum White matter 



We gratefully acknowledge the assistance of Kyle Jamison, Whitney Worsham, Whitney Ernst, and Tiffany Newton in data collection. This study was supported by funds from the Brigham Young University College of Family, Home, and Social Sciences, and the Poelman Foundation.

Conflict of interest

The authors report no conflicts of interest.


  1. Alexander, A. L., Lee, J. E., Lazar, M., Boudos, R., DuBray, M. B., Oakes, T. R., et al. (2007). Diffusion tensor imaging of the corpus callosum in Autism. Neuroimage, 34, 61–73. doi: 10.1016/j.neuroimage.2006.08.032.PubMedCrossRefGoogle Scholar
  2. Anderson, J. S., Druzgal, T. J., Froehlich, A., DuBray, M. B., Lange, N., Alexander, A. L., et al. (2011a). Decreased interhemispheric functional connectivity in autism. Cerebral Cortex, 21, 1134–1146. doi: 10.1093/cercor/bhq190.PubMedCentralPubMedCrossRefGoogle Scholar
  3. Anderson, J. S., Nielsen, J. A., Froehlich, A. L., DuBray, M. B., Druzgal, T. J., Cariello, A. N., et al. (2011b). Functional connectivity magnetic resonance imaging classification of autism. Brain, 134, 3742–3754. doi: 10.1093/brain/awr263.PubMedCrossRefGoogle Scholar
  4. Banich, M. T., & Brown, W. S. (2000). A life-span perspective on interaction between the cerebral hemispheres. Developmental Neuropsychology, 18, 1–10.PubMedCrossRefGoogle Scholar
  5. Banich, M. T., Passarotti, A. M., White, D. A., Nortz, M. J., & Steiner, R. D. (2000). Interhemispheric interaction during childhood: II. Children with early-treated phenylketonuria. Developmental Neuropsychology, 18, 53–71. doi: 10.1207/S15326942DN1801_4.PubMedCrossRefGoogle Scholar
  6. Barnea-Goraly, N., Lotspeich, L. J., & Reiss, A. L. (2010). Similar white matter aberrations in children with autism and their unaffected siblings: A diffusion tensor imaging study using tract-based spatial statistics. Archives of General Psychiatry, 67, 1052–1060. doi: 10.1001/archgenpsychiatry.2010.123.PubMedCrossRefGoogle Scholar
  7. Barnett, K. J., & Kirk, I. J. (2005). Lack of asymmetrical transfer for linguistic stimuli in schizophrenia: An ERP study. Clinical Neurophysiology, 116, 1019–1027. doi: 10.1016/j.clinph.2004.12.008.PubMedCrossRefGoogle Scholar
  8. Baruth, J. M., Casanova, M. F., Sears, L., & Sokhadze, E. (2010). Early-stage visual processing abnormalities in high-functioning autism spectrum disorder (ASD). Translational Neuroscience, 1, 177–187. doi: 10.2478/v10134-010-0024-9.PubMedCentralPubMedCrossRefGoogle Scholar
  9. Belmonte, M. K., Allen, G., Beckel-Mitchener, A., Boulanger, L. M., Carper, R. A., & Webb, S. J. (2004). Autism and abnormal development of brain connectivity. The Journal of Neuroscience, 24, 9228–9231. doi: 10.1523/JNEUROSCI.3340-04.2004.PubMedCrossRefGoogle Scholar
  10. Betancur, C. (2011). Etiological heterogenity in autism spectrum disorders: More than 100 genetic and genomic disorders and still counting. Brain Research, 1380, 42–77. doi: 10.1016/j.brainres.2010.11.078.PubMedCrossRefGoogle Scholar
  11. Birmaher, B., Brent, D. A., Chiappetta, L., Bridge, J., Monga, S., & Baugher, M. (1999). Psychometric properties of the screen for child anxiety related emotional disorders (SCARED): A replication study. Journal of the American Academy of Child and Adolescent Psychiatry, 38, 1230–1236.PubMedCrossRefGoogle Scholar
  12. Brown, W. S., Larson, E. B., & Jeeves, M. A. (1994). Directional asymmetries in interhemispheric transmission time: Evidence from visual evoked potentials. Neuropsychologia, 32, 439–448.PubMedCrossRefGoogle Scholar
  13. Clark, V. P., & Hillyard, S. A. (1996). Spatial selective attention affects early extrastriate but not striate components of the visual evoked potential. Journal of Cognitive Neuroscience, 8, 387–402. doi: 10.1162/jocn.1996.8.5.387.PubMedCrossRefGoogle Scholar
  14. Clayson, P. E., Baldwin, S. A., & Larson, M. J. (2013). How does noise affect amplitude and latency measurement of event-related potentials (ERPs)? A methodological critique and simulation study. Psychophysiology, 50, 174–186. doi: 10.1111/psyp.12001.PubMedCrossRefGoogle Scholar
  15. Courchesne, E., Pierce, K., Schumann, C. M., Redcay, E., Buckwalter, J. A., Kennedy, D. P., et al. (2007). Mapping early brain development in autism. Neuron, 56, 399–413. doi: 10.1016/j.neuron.2007.10.016.PubMedCrossRefGoogle Scholar
  16. Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134, 9–21. doi: 10.1016/j.jneumeth.2003.10.009.PubMedCrossRefGoogle Scholar
  17. Di Russo, F., Martinez, A., Sereno, M. I., Pitzalis, S., & Hillyard, S. A. (2002). Cortical sources of the early components of the visual evoked potential. Human Brain Mapping, 15, 95–111. doi: 10.1002/hbm.10010.PubMedCrossRefGoogle Scholar
  18. Dien, J., Franklin, M. S., & May, C. J. (2006). Is “Blank” a suitable neutral prime for event-related potential experiments? Brain and Language, 97, 91–101. doi: 10.1016/j.bandl.2005.08.002.PubMedCrossRefGoogle Scholar
  19. Dien, J., Michelson, C. A., & Franklin, M. S. (2010). Separating the visual sentence N400 effect from the P400 sequential expectancy effect: Cognitive and neuroanatomical implications. Brain Research, 1355, 126–140. doi: 10.1016/j.brainres.2010.07.099.PubMedCrossRefGoogle Scholar
  20. Dien, J., & Santuzzi, A. M. (2005). Principal components analysis of event-related potential datasets. In T. Handy (Ed.), Event-related potentials: A methods handbook. Cambridge: MIT Press.Google Scholar
  21. Eapen, V. (2011). Genetic basis of autism: Is there a way forward? Current Opinion in Psychiatry, 24, 226–236. doi: 10.1097/YCO.0b013e328345927e.PubMedCrossRefGoogle Scholar
  22. Eliassen, J. C., Baynes, K., & Gazzaniga, M. S. (2000). Anterior and posterior callosal contributions to simultaneous bimanual movements of the hands and fingers. Brain: A Journal of Neurology, 123, 2501–2511. doi: 10.1093/brain/123.12.2501.CrossRefGoogle Scholar
  23. Fabri, M., Polonara, G., Del Pesce, M., Quattrini, A., Salvolini, U., & Manzoni, T. (2001). Posterior corpus callosum and interhemispheric transfer of somatosensory information: An fMRI and neuropsychological study of a partially callosotomized patient. Journal of Cognitive Neuroscience, 13, 1071–1079. doi: 10.1162/089892901753294365.PubMedCrossRefGoogle Scholar
  24. Gorrie, C., Duflou, J., Brown, J., Gibson, T., & Waite, P. M. (2001). Extent and distribution of vascular brain injury in pediatric road fatalities. Journal of Neurotrauma, 18, 849–860. doi: 10.1089/089771501750451776.PubMedCrossRefGoogle Scholar
  25. Hagelthorn, K. M., Brown, W. S., Amano, S., & Asarnow, R. (2000). Normal development of bilateral field advantage and evoked potential interhemispheric transmission time. Developmental Neuropsychology, 18, 11–31. doi: 10.1207/S15326942DN1801_2.PubMedCrossRefGoogle Scholar
  26. Hong, S., Ke, X., Tang, T., Hang, Y., Chu, K., Huang, H., et al. (2011). Detecting abnormalities of corpus callosum connectivity in autism using magnetic resonance imaging and diffusion tensor tractography. Psychiatry Research: Neuroimaging, 194, 333–339. doi: 10.1016/j.pscychresns.2011.03.009.PubMedCrossRefGoogle Scholar
  27. Iwabuchi, S. J., & Kirk, I. J. (2009). Atypical interhemispheric communication in left-handed individuals. NeuroReport, 20, 166–169. doi: 10.1097/WNR.0b013e32831f1cbb.PubMedCrossRefGoogle Scholar
  28. Junghöfer, M., Elbert, T., Tucker, D. M., & Braun, C. (1999). The polar average reference effect: A bias in estimating the head surface integral in EEG recording. Clinical Neurophysiology, 110, 1149–1155.PubMedCrossRefGoogle Scholar
  29. Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew, N. J. (2007). Functional and anatomical cortical underconnectivity in autism: Evidence from an fMRI study of an executive function task and corpus callosum morphometry. Cerebral Cortex, 17, 951–961. doi: 10.1093/cercor/bhl006.PubMedCrossRefGoogle Scholar
  30. Kana, R. K., Keller, K., Minshew, N. J., & Just, M. A. (2007). Inhibitory control in high-functioning autism: Decreased activation and underconnectivity in inhibition networks. Biological Psychiatry, 62, 198–206. doi: 10.1016/j.biopsych.2006.08.004.PubMedCrossRefGoogle Scholar
  31. Kana, R. K., Libero, L. E., & Moore, M. S. (2011). Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders. Physics of Life Reviews, 8, 410–437. doi: 10.1016/j.plrev.2011.10.001.PubMedCrossRefGoogle Scholar
  32. Keller, T. A., Kana, R. K., & Just, M. A. (2007). A developmental study of the structural integrity of white matter in autism. Neuroreport, 18, 23–27.PubMedCrossRefGoogle Scholar
  33. Keselman, H. J., Wilcox, R. R., & Lix, L. M. (2003). A generally robust approach to hypothesis testing in independent and correlated groups designs. Psychophysiology, 40, 586–596. doi: 10.1037/1082-989X.13.2.110.PubMedCrossRefGoogle Scholar
  34. Kleinhans, N. M., Richards, T., Sterling, L., Stegbauer, K. C., Mahurin, R., Johnson, L. C., et al. (2008). Abnormal functional connectivity in autism spectrum disorders during face processing. Brain, 131, 1000–1012. doi: 10.1093/brain/awm334.PubMedCrossRefGoogle Scholar
  35. Kumar, A., Sundaram, S. K., Sivaswamy, L., Behen, M. E., Makki, M. I., & Ager, J. (2010). Alterations in frontal lobe tracts and corpus callosum in young children with autism spectrum disorder. Cerebral Cortex, 20, 2103–2113. doi: 10.1093/cercor/bhp278.PubMedCrossRefGoogle Scholar
  36. Larson, M. J., South, M., Clayson, P. E., & Clawson, A. (2012). Cognitive control and conflict adaptation in youth with high-functioning autism. Journal of Child Psychology and Psychiatry, 53, 440–448. doi: 10.1111/j.1469-7610.2011.02498.x.PubMedCrossRefGoogle Scholar
  37. Larson, M. J., South, M., Krauskopf, E., Clawson, A., & Crowley, M. J. (2010). Feedback and reward processing in high-functioning autism. Psychiatry Research, 187, 198–203. doi: 10.1016/j.psychres.2010.11.006.PubMedCrossRefGoogle Scholar
  38. Levin, H. S., Wilde, E. A., Chu, Z., Yallampalli, R., Hanten, G. R., & Li, X. (2008). Diffusion tensor imaging in relation to cognitive and functional outcome of traumatic brain injury in children. The Journal of Head Trauma Rehabilitation, 23, 197–208. doi: 10.1097/01.HTR.0000327252.54128.7c.PubMedCentralPubMedCrossRefGoogle Scholar
  39. Lo, Y., Soong, W., Gau, S. S., Wu, Y., Lai, M., Yeh, F., et al. (2011). The loss of asymmetry and reduced interhemispheric connectivity in adolescents with autism: A study using diffusion spectrum imaging tractography. Psychiatry Research: Neuroimaging, 192, 60–66. doi: 10.1016/j.pscychresns.2010.09.008.PubMedCrossRefGoogle Scholar
  40. Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavore, P. C., et al. (2000). The autism diagnostic observation schedule-generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223.PubMedCrossRefGoogle Scholar
  41. Martin, C. D., Thierry, G., Démonet, J.-F., Roberts, M., & Nazir, T. (2007). ERP evidence for the split fovea theory. Brain Research, 1185, 212–220. doi: 10.1016/j.brainres.2007.09.049.PubMedCrossRefGoogle Scholar
  42. McCaffery, P., & Deutsch, C. K. (2005). Macrocephaly and the control of brain growth in autistic disorders. Progress in Neurobiology, 77, 38–56. doi: 10.1016/j.pneurobio.2005.10.005.PubMedCrossRefGoogle Scholar
  43. Moes, P., Brown, W., & Minnema, M. (2007). Individual differences in interhemispheric transfer time (IHTT) as measured by event related potentials. Neuropsychologia, 45, 2626–2630. doi: 10.1016/j.neuropsychologia.2007.03.017.PubMedCrossRefGoogle Scholar
  44. Noriuchi, M., Kikuchi, Y., Yoshiura, T., Kira, R., Shigeto, H., & Hara, T. (2010). Altered white matter fractional anisotropy and social impairment in children with autism spectrum disorder. Brain Research, 1362, 141–149. doi: 10.1016/j.brainres.2010.09.051.PubMedCrossRefGoogle Scholar
  45. Orekhova, E. V., Stroganova, T. A., Nygren, G., Tsetlin, M. M., Posikera, I. N., Gillberg, C., et al. (2007). Excess of high frequency electroencephalogram oscillations in boys with autism. Biological Psychiatry, 62, 1022–1029. doi: 10.1016/j.biopsych.2006.12.029.PubMedCrossRefGoogle Scholar
  46. Patson, L. L., Kirk, I. J., Rolfe, M. H. S., Corballis, M. C., & Tippett, L. J. (2007). The unusual symmetry of musicians: Musicians have equilateral interhemispheric transfer for visual information. Neuropsychologia, 45, 2059–2065. doi: 10.1016/j.neuropsychologia.2007.02.001.CrossRefGoogle Scholar
  47. Pfefferbaum, A., Sullivan, E. V., Hedehus, M., Adalsteinsson, E., Lim, K. O., & Moseley, M. (2000). In vivo detection and functional correlates of white matter microstructural disruption in chronic alcoholism. Alcoholism, Clinical and Experimental Research, 24, 1214–1221. doi: 10.1111/j.1530-0277.2000.tb02086.x.PubMedCrossRefGoogle Scholar
  48. Rugg, M. D., Milner, A. D., & Lines, C. R. (1985). Visual evoked potentials to lateralised stimuli in two cases of callosal agenesis. Journal of Neurology, Neurosurgery and Psychiatry, 48, 367–373.PubMedCentralPubMedCrossRefGoogle Scholar
  49. Samson, F., Mottron, L., Soulieres, I., & Zeffiro, T. A. (2012). Enhanced visual functioning in autism: An ALE meta-analysis. Human Brain Mapping, 33, 1553–1581. doi: 10.1002/hbm.21307.PubMedCrossRefGoogle Scholar
  50. Schimmel, H. (1967). The (±) reference: Accuracy of estimated mean components in average response studies. Science, 157, 92–94.PubMedCrossRefGoogle Scholar
  51. Shukla, D. K., Keehn, B., Lincoln, A. J., & Müller, R. A. (2010). White matter compromise of callosal and subcortical fiber tracts in children with autism spectrum disorder: A diffusion tensor imaging study. Journal of the American Academy of Child and Adolescent Psychiatry, 49(1269–1278), e1262. doi: 10.1016/j.jaac.2010.08.018.Google Scholar
  52. South, M., Larson, M. J., Krauskopf, E., & Clawson, A. (2010). Error processing in high-functioning Autism Spectrum Disorders. Biological Psychology, 85, 242–251. doi: 10.1016/j.biopsycho.2010.07.009.PubMedCrossRefGoogle Scholar
  53. Steger, J., Imhof, K., Denoth, J., Pascual-Marqui, R. D., Steinhausen, H. C., & Brandeis, D. (2001). Brain mapping of bilateral visual interactions in children. Psychophysiology, 38, 243–253. doi: 10.1111/1469-8986.3820243.PubMedCrossRefGoogle Scholar
  54. Viding, E., & Blakemore, S. J. (2007). Endophenotype approach to developmental psychopathology: Implications for autism research. Behavioral Genetics, 37, 51–60. doi: 10.1007/s10519-006-9105-4.CrossRefGoogle Scholar
  55. Wass, S. (2011). Distortions and disconnections: Disrupted brain connectivity in autism. Brain and Cognition, 75, 18–28. doi: 10.1016/j.bandc.2010.10.005.PubMedCrossRefGoogle Scholar
  56. Westerhausen, R., Kreuder, F., Woerner, W., Huster, R. J., Smit, C. M., Schweiger, E., et al. (2006). Interhemispheric transfer time and structural properties of the corpus callosum. Neuroscience Letters, 409, 140–145. doi: 10.1016/j.neulet.2006.09.028.PubMedCrossRefGoogle Scholar
  57. Yamauchi, H., Fukuyama, H., Nagahama, Y., Katsumi, Y., Dong, Y., & Hayashi, T. (1998). Atrophy of the corpus callosum, cortical hypometabolism, and cognitive impairment in corticobasal degeneration. Archives of Neurology, 55, 609–614.PubMedCrossRefGoogle Scholar
  58. Yamauchi, H., Fukuyama, H., Nagahama, Y., Katsumi, Y., Dong, Y., Konishi, J., et al. (1996). Atrophy of the corpus callosum associated with cognitive impairment and widespread cortical hypometabolism in carotid artery occlusive disease. Archives of Neurology, 53, 1103–1109.PubMedCrossRefGoogle Scholar
  59. Yamauchi, H., Fukuyama, H., Nagahama, Y., Katsumi, Y., Dong, Y., Konishi, J., et al. (1997). Atrophy of the corpus callosum, cognitive impairment, and cortical hypometabolism in progressive supranuclear palsy. Annals of neurology, 41, 606–614. doi: 10.1002/ana.410410509.PubMedCrossRefGoogle Scholar
  60. Zikopoulos, B., & Barbas, H. (2010). Changes in prefrontal axons may disrupt the network in autism. Journal of Neuroscience, 30, 14595–14609. doi: 10.1523/JNEUROSCI.2257-10.2010.PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Ann Clawson
    • 1
    • 2
  • Peter E. Clayson
    • 3
  • Mikle South
    • 1
    • 2
  • Erin D. Bigler
    • 1
    • 4
  • Michael J. Larson
    • 1
    • 2
    Email author
  1. 1.Department of PsychologyBrigham Young UniversityProvoUSA
  2. 2.Neuroscience CenterBrigham Young UniversityProvoUSA
  3. 3.Department of PsychologyUniversity of California, Los AngelesLos AngelesUSA
  4. 4.Neuroscience CenterBrigham Young UniversityProvoUSA

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