Grey-Matter Thickness of the Left But Not the Right Primary Visual Area Correlates with Autism Traits in Typically Developing Adults

Journal of Autism and Developmental Disorders volume 51, pages405–417(2021)Cite this article

Abstract

We examined whether functional and structural variability in the primary visual area (V1) correlated with autism traits. Twenty-nine participants (16 males; MAge = 26.4 years, SDAge = 4.0 years) completed the autism-spectrum quotient (AQ) questionnaire prior to a magnetic resonance imaging session. The total AQ scores was used to assess the degree of self-reported autism traits. The average functional activation in V1 to visual stimulation and its average grey-matter thickness were calculated. There were no correlations between functional activation in V1 and autism traits. Conversely, grey-matter thickness of the left but not the right V1 correlated with autism traits. We conclude that structural changes in the left V1 could be a marker for the presence of autism traits.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

US$ 39.95

Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. American Psychiatric Association. (2013). DSM-V: Diagnostic and statistical manual of mental disorders, 5th edition. Washington: DC: American Psychiatric Publishing, Inc.

  2. Amunts, K., Malikovic, A., Mohlberg, H., Schormann, T., & Zilles, K. (2000). Brodmann's areas 17 and 18 brought into stereotaxic space-where and how variable? Neuroimage, 11(1), 66–84. https://doi.org/10.1006/nimg.1999.0516.

    Article  PubMed  Google Scholar 

  3. Ashwin, E., Ashwin, C., Rhydderch, D., Howells, J., & Baron-Cohen, S. (2009). Eagle-eyed visual acuity: An experimental investigation of enhanced perception in autism. Biological Psychiatry, 65(1), 17–21. https://doi.org/10.1016/j.biopsych.2008.06.012.

    Article  PubMed  Google Scholar 

  4. 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(10), 1052–1060. https://doi.org/10.1001/archgenpsychiatry.2010.123.

    Article  PubMed  Google Scholar 

  5. Baron-Cohen, S., Ring, H., Chitnis, X., Wheelwright, S., Gregory, L., Williams, S., et al. (2006). fMRI of parents of children with Asperger syndrome: A pilot study. Brain and Cognition, 61(1), 122–130. https://doi.org/10.1016/j.bandc.2005.12.011.

    Article  PubMed  Google Scholar 

  6. Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The autism-spectrum quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31(1), 5–17. https://doi.org/10.1023/a:1005653411471.

    Article  Google Scholar 

  7. Baum, S. H., Stevenson, R. A., & Wallace, M. T. (2015). Behavioral, perceptual, and neural alterations in sensory and multisensory function in autism spectrum disorder. Progress in Neurobiology, 134, 140–160. https://doi.org/10.1016/j.pneurobio.2015.09.007.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bertone, A., Mottron, L., Jelenic, P., & Faubert, J. (2005). Enhanced and diminished visuo-spatial information processing in autism depends on stimulus complexity. Brain, 128(Pt 10), 2430–2441. https://doi.org/10.1093/brain/awh561.

    Article  PubMed  Google Scholar 

  9. Bezgin, G., Lewis, J. D., & Evans, A. C. (2018). Developmental changes of cortical white-gray contrast as predictors of autism diagnosis and severity. Transl Psychiatry, 8(1), 249. https://doi.org/10.1038/s41398-018-0296-2.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Billeci, L., Calderoni, S., Conti, E., Gesi, C., Carmassi, C., Dell'Osso, L., et al. (2016). The broad autism (endo)phenotype: Neurostructural and neurofunctional correlates in parents of individuals with autism spectrum disorders. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2016.00346.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bourgeron, T. (2015). From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nature Reviews Neuroscience, 16(9), 551–563. https://doi.org/10.1038/nrn3992.

    Article  PubMed  Google Scholar 

  12. Brainard, D. H. (2011). The psychophysics toolbox. Spatial Vision, 10, 433–436.

    Article  Google Scholar 

  13. Cheung, C., Chua, S. E., Cheung, V., Khong, P. L., Tai, K. S., Wong, T. K. W., et al. (2009). White matter fractional anisotrophy differences and correlates of diagnostic symptoms in autism. Journal of Child Psychology and Psychiatry, 50(9), 1102–1112. https://doi.org/10.1111/j.1469-7610.2009.02086.x.

    Article  PubMed  Google Scholar 

  14. Chouinard, P. A., Royals, K. A., Landry, O., & Sperandio, I. (2018). The Shepard illusion is reduced in children with an autism spectrum disorder because of perceptual rather than attentional mechanisms. Frontiers in Psychology, 9, 2452. https://doi.org/10.3389/fpsyg.2018.02452.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Chouinard, P. A., Unwin, K. L., Landry, O., & Sperandio, I. (2016). Susceptibility to optical illusions varies as a function of the autism-spectrum quotient but not in ways predicted by local-global biases. Journal of Autism and Developmental Disorders, 46(6), 2224–2239. https://doi.org/10.1007/s10803-016-2753-1.

    Article  PubMed  Google Scholar 

  16. Dawson, G., Warrenburg, S., & Fuller, P. (1982). Cerebral lateralization in individuals diagnosed as autistic in early-childhood. Brain and Language, 15(2), 353–368. https://doi.org/10.1016/0093-934x(82)90065-7.

    Article  PubMed  Google Scholar 

  17. Dumoulin, S. O., Hoge, R. D., Baker, C. L., Jr., Hess, R. F., Achtman, R. L., & Evans, A. C. (2003). Automatic volumetric segmentation of human visual retinotopic cortex. Neuroimage, 18(3), 576–587. https://doi.org/10.1016/s1053-8119(02)00058-7.

    Article  PubMed  Google Scholar 

  18. Engel, S. A., Glover, G. H., & Wandell, B. A. (1997). Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cerebral Cortex, 7(2), 181–192. https://doi.org/10.1093/cercor/7.2.181.

    Article  PubMed  Google Scholar 

  19. Gebauer, L., Foster, N. E. V., Vuust, P., & Hyde, K. L. (2015). Is there a bit of autism in all of us? Autism spectrum traits are related to cortical thickness differences in both autism and typical development. Research in Autism Spectrum Disorders, 13–14, 8–14. https://doi.org/10.1016/j.rasd.2014.12.013.

    Article  Google Scholar 

  20. Greimel, E., Schulte-Ruther, M., Kircher, T., Kamp-Becker, I., Remschmidt, H., Fink, G. R., et al. (2010). Neural mechanisms of empathy in adolescents with autism spectrum disorder and their fathers. Neuroimage, 49(1), 1055–1065. https://doi.org/10.1016/j.neuroimage.2009.07.057.

    Article  PubMed  Google Scholar 

  21. Hadjikhani, N., Chabris, C. F., Joseph, R. M., Clark, J., McGrath, L., Aharon, I., et al. (2004). Early visual cortex organization in autism: An fMRI study. NeuroReport, 15(2), 267–270. https://doi.org/10.1097/01.wnr.0000107523.38715.fa.

    Article  PubMed  Google Scholar 

  22. Hier, D. B., Lemay, M., & Rosenberger, P. B. (1979). Autism and unfavorable left-right asymmetries of the brain. Journal of Autism and Developmental Disorders, 9(2), 153–159. https://doi.org/10.1007/Bf01531531.

    Article  PubMed  Google Scholar 

  23. Hyde, K. L., Samson, F., Evans, A. C., & Mottron, L. (2010). Neuroanatomical differences in brain areas implicated in perceptual and other core features of autism revealed by cortical thickness analysis and voxel-based morphometry. Human Brain Mapping, 31(4), 556–566. https://doi.org/10.1002/hbm.20887.

    Article  PubMed  Google Scholar 

  24. Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford: Oxford University Press.

    Google Scholar 

  25. Keehn, B., Brenner, L., Palmer, E., Lincoln, A. J., & Muller, R. A. (2008). Functional brain organization for visual search in ASD. Journal of the International Neuropsychological Society, 14(6), 990–1003. https://doi.org/10.1017/S1355617708081356.

    Article  PubMed  Google Scholar 

  26. Kemner, C., van Ewijk, L., van Engeland, H., & Hooge, I. (2008). Brief report: Eye movements during visual search tasks indicate enhanced stimulus discriminability in subjects with PDD. Journal of Autism and Developmental Disorders, 38(3), 553–557. https://doi.org/10.1007/s10803-007-0406-0.

    Article  PubMed  Google Scholar 

  27. Kennedy, K. M., Rodrigue, K. M., Bischof, G. N., Hebrank, A. C., Reuter-Lorenz, P. A., & Park, D. C. (2015). Age trajectories of functional activation under conditions of low and high processing demands: An adult lifespan fMRI study of the aging brain. Neuroimage, 104, 21–34. https://doi.org/10.1016/j.neuroimage.2014.09.056.

    Article  PubMed  Google Scholar 

  28. Koh, H. C., Milne, E., & Dobkins, K. (2010). Spatial contrast sensitivity in adolescents with autism spectrum disorders. Journal of Autism and Developmental Disorders, 40(8), 978–987. https://doi.org/10.1007/s10803-010-0953-7.

    Article  PubMed  Google Scholar 

  29. Lainhart, J. E. (2015). Brain imaging research in autism spectrum disorders: In search of neuropathology and health across the lifespan. Current Opinion in Psychiatry, 28(2), 76–82. https://doi.org/10.1097/Yco.0000000000000130.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Lainhart, J. E., & Lange, N. (2011). The biological broader autism phenotype. In G. D. D. G. Amaral & D. H. Geschwind (Eds.), Autism spectrum disorders. New York: Oxford University Press, Inc.

    Google Scholar 

  31. Landry, O., & Chouinard, P. A. (2016). Why we should study the broader autism phenotype in typically developing populations. Journal of Cognition and Development, 17(4), 584–595. https://doi.org/10.1080/15248372.2016.1200046.

    Article  Google Scholar 

  32. Loth, E., Garrido, L., Ahmad, J., Watson, E., Duff, A., & Duchaine, B. (2018). Facial expression recognition as a candidate marker for autism spectrum disorder: How frequent and severe are deficits? Molecular Autism. https://doi.org/10.1186/s13229-018-0187-7.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Macdonald, H., Rutter, M., Howlin, P., Rios, P., Leconteur, A., Evered, C., et al. (1989). Recognition and expression of emotional cues by autistic and normal adults. Journal of Child Psychology and Psychiatry and Allied Disciplines, 30(6), 865–877. https://doi.org/10.1111/j.1469-7610.1989.tb00288.x.

    Article  Google Scholar 

  34. Manjaly, Z. M., Bruning, N., Neufang, S., Stephan, K. E., Brieber, S., Marshall, J. C., et al. (2007). Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents. Neuroimage, 35(1), 283–291. https://doi.org/10.1016/j.neuroimage.2006.11.036.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Marco, E. J., Hinkley, L. B. N., Hill, S. S., & Nagarajan, S. S. (2011). Sensory processing in autism: A review of neurophysiologic findings. Pediatric Research, 69(5), 48r–54r. https://doi.org/10.1203/PDR.0b013e3182130c54.

    Article  PubMed  PubMed Central  Google Scholar 

  36. O'Riordan, M. A. (2004). Superior visual search in adults with autism. Autism, 8(3), 229–248. https://doi.org/10.1177/1362361304045219.

    Article  PubMed  Google Scholar 

  37. Ogawa, S., Tank, D. W., Menon, R., Ellermann, J. M., Kim, S. G., Merkle, H., et al. (1992). Intrinsic signal changes accompanying sensory stimulation—Functional brain mapping with magnetic-resonance-imaging. Proceedings of the National Academy of Sciences of the United States of America, 89(13), 5951–5955. https://doi.org/10.1073/pnas.89.13.5951.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442.

    Article  Google Scholar 

  39. Pellicano, E., & Burr, D. (2012). When the world becomes 'too real': A Bayesian explanation of autistic perception. Trends in Cognitive Sciences, 16(10), 504–510. https://doi.org/10.1016/j.tics.2012.08.009.

    Article  PubMed  Google Scholar 

  40. Peterson, D., Mahajan, R., Crocetti, D., Mejia, A., & Mostofsky, S. (2015). Left-hemispheric microstructural abnormalities in children with high-functioning autism spectrum disorder. Autism Research, 8(1), 61–72. https://doi.org/10.1002/aur.1413.

    Article  PubMed  Google Scholar 

  41. Peterson, E., Schmidt, G. L., Tregellas, J. R., Winterrowd, E., Kopelioff, L., Hepburn, S., et al. (2006). A voxel-based morphometry study of gray matter in parents of children with autism. NeuroReport, 17(12), 1289–1292. https://doi.org/10.1097/01.wnr.0000233087.15710.87.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Robertson, C. E., Thomas, C., Kravitz, D. J., Wallace, G. L., Baron-Cohen, S., Martin, A., et al. (2014). Global motion perception deficits in autism are reflected as early as primary visual cortex. Brain, 137(Pt 9), 2588–2599. https://doi.org/10.1093/brain/awu189.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Ruzich, E., Allison, C., Smith, P., Watson, P., Auyeung, B., Ring, H., et al. (2015). Measuring autistic traits in the general population: A systematic review of the Autism-Spectrum Quotient (AQ) in a nonclinical population sample of 6,900 typical adult males and females. Mol Autism, 6, 2. https://doi.org/10.1186/2040-2392-6-2.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Samson, F., Mottron, L., Soulieres, I., & Zeffiro, T. A. (2012). Enhanced visual functioning in autism: An ALE meta-analysis. Human Brain Mapping, 33(7), 1553–1581. https://doi.org/10.1002/hbm.21307.

    Article  PubMed  Google Scholar 

  45. Sawyer-Glover, A. M., & Shellock, F. G. (2000). Pre-MRI procedure screening: Recommendations and safety considerations for biomedical implants and devices. Journal of Magnetic Resonance Imaging, 12(1), 92–106.

    Article  Google Scholar 

  46. Saxe, R., Brett, M., & Kanwisher, N. (2006). Divide and conquer: A defense of functional localizers. Neuroimage, 30(4), 1088–1096. https://doi.org/10.1016/j.neuroimage.2005.12.062.

    Article  PubMed  Google Scholar 

  47. Schwarzkopf, D. S., Anderson, E. J., de Haas, B., White, S. J., & Rees, G. (2014). Larger extrastriate population receptive fields in autism spectrum disorders. Journal of Neuroscience, 34(7), 2713–2724. https://doi.org/10.1523/JNEUROSCI.4416-13.2014.

    Article  PubMed  Google Scholar 

  48. Sereno, M. I., Dale, A. M., Reppas, J. B., Kwong, K. K., Belliveau, J. W., Brady, T. J., et al. (1995). Borders of multiple visual areas in humans revealed by functional magnetic-resonance-imaging. Science, 268(5212), 889–893. https://doi.org/10.1126/science.7754376.

    Article  PubMed  Google Scholar 

  49. Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003). Mapping cortical change across the human life span. Nature Neuroscience, 6(3), 309–315. https://doi.org/10.1038/nn1008.

    Article  PubMed  Google Scholar 

  50. Sperandio, I., Chouinard, P. A., & Goodale, M. A. (2012). Retinotopic activity in V1 reflects the perceived and not the retinal size of an afterimage. Nature Neuroscience, 15(4), 540–542. https://doi.org/10.1038/nn.3069.

    Article  PubMed  Google Scholar 

  51. Sperandio, I., Unwin, K. L., Landry, O., & Chouinard, P. A. (2017). Size constancy is preserved but afterimages are prolonged in typical individuals with higher degrees of self-reported autistic traits. Journal of Autism and Developmental Disorders, 47(2), 447–459. https://doi.org/10.1007/s10803-016-2971-6.

    Article  PubMed  Google Scholar 

  52. Tsermentseli, S., O'Brien, J. M., & Spencer, J. V. (2008). Comparison of form and motion coherence processing in autistic spectrum disorders and dyslexia. Journal of Autism and Developmental Disorders, 38(7), 1201–1210. https://doi.org/10.1007/s10803-007-0500-3.

    Article  PubMed  Google Scholar 

  53. Vandenbroucke, M. W. G., Scholte, H. S., van Engeland, H., Lamme, V. A. F., & Kemner, C. (2008). A neural substrate for atypical low-level visual processing in autism spectrum disorder. Brain, 131, 1013–1024. https://doi.org/10.1093/brain/awm321.

    Article  PubMed  Google Scholar 

  54. Wandell, B. A., & Winawer, J. (2011). Imaging retinotopic maps in the human brain. Vision Research, 51(7), 718–737. https://doi.org/10.1016/j.visres.2010.08.004.

    Article  PubMed  Google Scholar 

  55. Yucel, G. H., Belger, A., Bizzell, J., Parlier, M., Adolphs, R., & Piven, J. (2015). Abnormal neural activation to faces in the parents of children with autism. Cerebral Cortex, 25(12), 4653–4666. https://doi.org/10.1093/cercor/bhu147.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by a grant from La Trobe University’s Understanding Disease Research Focus Area awarded to PAC and by a scholarship award from La Trobe University to GYY. We also acknowledge the facilities and scientific and technical assistance of Australia’s National Imaging Facility, a National Collaborative Research Infrastructure Strategy (NCRIS) capability, at the Swinburne Neuroimaging Facility (SNI), at the Swinburne University of Technology. We thank Alyse Brown for collecting the MRI data.

Author information

Affiliations

  1. Department of Psychology and Counselling, School of Psychology and Public Health, La Trobe University, Melbourne, VIC, Australia

    Gizem Y. Yildiz, Julian S. Vilsten, Amy Siobhan Millard & Philippe A. Chouinard

Authors
  1. Gizem Y. Yildiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julian S. Vilsten
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amy Siobhan Millard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Philippe A. Chouinard
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JSV and PAC contributed to the conceptualisation of the design. All authors contributed to the analyses and the writing of the manuscript.

Corresponding author

Correspondence to Philippe A. Chouinard.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 19 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yildiz, G.Y., Vilsten, J.S., Millard, A.S. et al. Grey-Matter Thickness of the Left But Not the Right Primary Visual Area Correlates with Autism Traits in Typically Developing Adults. J Autism Dev Disord 51, 405–417 (2021). https://doi.org/10.1007/s10803-020-04553-w

Download citation

Keywords

  • Autism-spectrum quotient (AQ)
  • Magnetic resonance imaging (MRI)
  • Primary visual area (V1)
  • Grey-matter thickness
  • Retinotopy