Skip to main content
Log in

Multimodal Imaging in Autism: an Early Review of Comprehensive Neural Circuit Characterization

  • Autism Spectrum Disorders (ES Brodkin, Section Editor)
  • Published:
Current Psychiatry Reports Aims and scope Submit manuscript

Abstract

There is accumulating evidence that the neurobiology of autism spectrum disorders (ASD) is linked to atypical neural communication and connectivity. This body of work emphasizes the need to characterize the function of multiple regions that comprise neural circuits rather than focusing on singular regions as contributing to deficits in ASD. Multimodal neuroimaging — the formal combination of multiple functional and structural measures of the brain — is extremely promising as an approach to understanding neural deficits in ASD. This review provides an overview of the multimodal imaging approach, and then provides a snapshot of how multimodal imaging has been applied in the study of ASD to date. This body of work is separated into two categories: one concerning whole brain connectomics and the other focused on characterizing neural circuits implicated as altered in ASD. We end this review by highlighting emerging themes from the existing body of literature, and new resources that will likely influence future multimodal imaging studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. Casanova MF, van Kooten IAJ, Switala AE, van Engeland H, Heinsen H, Steinbusch HWM, et al. Minicolumnar abnormalities in autism. Acta Neuropathol (Berl). 2006;112:287–303.

    Article  Google Scholar 

  2. Casanova MF, Buxhoeveden DP, Switala AE, Roy E. Minicolumnar pathology in autism. Neurology. 2002;58:428–32.

    Article  PubMed  Google Scholar 

  3. Belmonte MK, Allen G, Beckel-Mitchener A, Boulanger LM, Carper RA, Webb SJ. Autism and abnormal development of brain connectivity. J Neurosci. 2004;24:9228–31.

    Article  PubMed  CAS  Google Scholar 

  4. Müller R-A. The study of autism as a distributed disorder. Ment Retard Dev Disabil Res Rev. 2007;13:85–95.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Müller R-A. From loci to networks and back again: anomalies in the study of autism. Ann N Y Acad Sci. 2008;1145:300–15.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Mueller S, Keeser D, Samson AC, Kirsch V, Blautzik J, Grothe M, et al. Convergent findings of altered functional and structural brain connectivity in individuals with high functioning autism: a multimodal MRI study. PLoS ONE. 2013;8:e67329.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  7. Nair A, Treiber JM, Shukla DK, Shih P, Müller R-A. Impaired thalamocortical connectivity in autism spectrum disorder: a study of functional and anatomical connectivity. Brain. 2013;136:1942–55. This multimodal imaging study combined resting state and DTI data to characterize thalamocortical networks in children with and without ASD. Prefrontal, motor, and sensorimotor thalamocortical networks had reduced functional and structural connectivity in ASD compared to controls, but the temporal thalamocortical network was hyperconnected in ASD.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Rudie JD, Brown JA, Beck-Pancer D, Hernandez LM, Dennis EL, Thompson PM, et al. Altered functional and structural brain network organization in autism. NeuroImage Clin. 2013;2:79–94.

    Article  PubMed Central  Google Scholar 

  9. Brown JA, Rudie JD, Bandrowski A, Van Horn JD, Bookheimer SY. The UCLA multimodal connectivity database: a web-based platform for brain connectivity matrix sharing and analysis. Front Neuroinformatics. 2012;6:28.

    Article  Google Scholar 

  10. Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. NeuroImage. 2012;62:782–90.

    Article  PubMed  Google Scholar 

  11. Biessmann F, Plis S, Meinecke FC, Eichele T, Muller K-R. Analysis of multimodal neuroimaging data. IEEE Rev Biomed Eng. 2011;4:26–58.

    Article  PubMed  Google Scholar 

  12. Ameis SH, Fan J, Rockel C, Voineskos AN, Lobaugh NJ, Soorya L, et al. Impaired structural connectivity of socio-emotional circuits in autism spectrum disorders: a diffusion tensor imaging study. PLoS ONE. 2011;6:e28044.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  13. Bloy L, Ingalhalikar M, Eavani H, Roberts TPL, Schultz RT, Verma R. HARDI based pattern classifiers for the identification of white matter pathologies. Med Image Comput Comput Assist Interv MICCAI Int Conf Med Image Comput Comput Assist Interv. 2011;14:234–41.

    Google Scholar 

  14. Ecker C, Rocha-Rego V, Johnston P, Mourao-Miranda J, Marquand A, Daly EM, et al. Investigating the predictive value of whole-brain structural MR scans in autism: a pattern classification approach. NeuroImage. 2010;49:44–56.

    Article  PubMed  Google Scholar 

  15. Ecker C, Ginestet C, Feng Y, Johnston P, Lombardo MV, Lai M-C, et al. Brain surface anatomy in adults with autism: the relationship between surface area, cortical thickness, and autistic symptoms. JAMA Psychiatry. 2013;70:59–70.

    Article  PubMed  Google Scholar 

  16. Hazlett HC, Poe MD, Gerig G, Styner M, Chappell C, Smith RG, et al. Early brain overgrowth in autism associated with an increase in cortical surface area before age 2 years. Arch Gen Psychiatry. 2011;68:467–76.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Hazlett HC, Poe MD, Gerig G, Smith RG, Piven J. Cortical gray and white brain tissue volume in adolescents and adults with autism. Biol Psychiatry. 2006;59:1–6.

    Article  PubMed  Google Scholar 

  18. Langen M, Leemans A, Johnston P, Ecker C, Daly E, Murphy CM, et al. Fronto-striatal circuitry and inhibitory control in autism: findings from diffusion tensor imaging tractography. Cortex. 2012;48:183–93.

    Article  PubMed  Google Scholar 

  19. Misaki M, Wallace GL, Dankner N, Martin A, Bandettini PA. Characteristic cortical thickness patterns in adolescents with autism spectrum disorders: interactions with age and intellectual ability revealed by canonical correlation analysis. NeuroImage. 2012;60:1890–901.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Shukla DK, Keehn B, Lincoln AJ, Müller R-A. White matter compromise of callosal and subcortical fiber tracts in children with autism spectrum disorder: a diffusion tensor imaging study. J Am Acad Child Adolesc Psychiatry. 2010;49:1269–1278.e2.

  21. Shukla DK, Keehn B, Müller R-A. Tract-specific analyses of diffusion tensor imaging show widespread white matter compromise in autism spectrum disorder. J Child Psychol Psychiatry [Internet]. 2010 [cited 2010 Nov 29]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/21073464.

  22. Thakkar KN, Polli FE, Joseph RM, Tuch DS, Hadjikhani N, Barton JJS, et al. Response monitoring, repetitive behaviour and anterior cingulate abnormalities in autism spectrum disorders (ASD). Brain. 2008;131:2464–78.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Wallace GL, Robustelli B, Dankner N, Kenworthy L, Giedd JN, Martin A. Increased gyrification, but comparable surface area in adolescents with autism spectrum disorders. Brain. 2013. doi:10.1093/brain/awt106.

    PubMed  PubMed Central  Google Scholar 

  24. Wallace GL, Dankner N, Kenworthy L, Giedd JN, Martin A. Age-related temporal and parietal cortical thinning in autism spectrum disorders. Brain [Internet]. 2010 [cited 2010 Oct 27]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/20926367.

  25. Wolff JJ, Gu H, Gerig G, Elison JT, Styner M, Gouttard S, et al. Differences in white matter fiber tract development present from 6 to 24 months in infants with autism. Am J Psychiatry [Internet]. 2012 [cited 2012 Feb 27]; Available from: http://proxy.library.upenn.edu:2309/article.aspx?articleid=668180.

  26. Gaonkar B, Davatzikos C. Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification. NeuroImage. 2013;78C:270–83.

    Article  Google Scholar 

  27. Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. NeuroImage. 2010;52:1059–69.

    Article  PubMed  Google Scholar 

  28. Barttfeld P, Wicker B, Cukier S, Navarta S, Lew S, Sigman M. A big-world network in ASD: dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections. Neuropsychologia. 2011;49:254–63.

    Article  PubMed  Google Scholar 

  29. Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, et al. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci U S A. 2009;106:2035–40.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  30. Poldrack RA, Fletcher PC, Henson RN, Worsley KJ, Brett M, Nichols TE. Guidelines for reporting an fMRI study. NeuroImage. 2008;40:409–14.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ. Functional and anatomical cortical underconnectivity in autism: evidence from an FMRI study of an executive function task and corpus callosum morphometry. Cereb Cortex. 2007;17:951–61.

    Article  PubMed  Google Scholar 

  32. Herrington JD, Schultz RT. Neuroimaging of developmental disorders. In: Shenton M, Turetsky BI, editors. Underst. Neuropsychiatr. Disord. Insights Neuroimaging. Cambridge: Cambridge University Press; 2010.

    Google Scholar 

  33. Rudie JD, Hernandez LM, Brown JA, Beck-Pancer D, Colich NL, Gorrindo P, et al. Autism-associated promoter variant in MET impacts functional and structural brain networks. Neuron. 2012;75:904–15. This innovative multimodal imaging study combined fMRI, DTI, and resting state data to elucidate atypical function and connectivity of the default mode network in a large sample of children with and without ASD. This study also stratified children by an autism risk gene – Met Receptor Tyrosine (MET) Kinase gene – and found enhanced group differences in children with at least one MET risk allele.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  34. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008;1124:1–38.

    Article  PubMed  Google Scholar 

  35. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci U S A. 2001;98:676–82.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  36. Castelli F, Frith C, Happé F, Frith U. Autism, Asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes. Brain. 2002;125:1839–49.

    Article  PubMed  Google Scholar 

  37. Heilman KM, Gilmore RL. Cortical influences in emotion. J Clin Neurophysiol. 1998;15:409–23.

    Article  PubMed  CAS  Google Scholar 

  38. Pelphrey KA, Carter EJ. Brain mechanisms for social perception: lessons from autism and typical development. Ann N Y Acad Sci. 2008;1145:283–99.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Völlm BA, Taylor ANW, Richardson P, Corcoran R, Stirling J, McKie S, et al. Neuronal correlates of theory of mind and empathy: a functional magnetic resonance imaging study in a nonverbal task. NeuroImage. 2006;29:90–8.

    Article  PubMed  Google Scholar 

  40. Baron-Cohen S, Ring HA, Wheelwright S, Bullmore ET, Brammer MJ, Simmons A, et al. Social intelligence in the normal and autistic brain: an fMRI study. Eur J Neurosci. 1999;11:1891–8.

    Article  PubMed  CAS  Google Scholar 

  41. Mundy P. Annotation: the neural basis of social impairments in autism: the role of the dorsal medial-frontal cortex and anterior cingulate system. J Child Psychol Psychiatry. 2003;44:793–809.

    Article  PubMed  Google Scholar 

  42. Allison T, Puce A, McCarthy G. Social perception from visual cues: role of the STS region. Trends Cogn Sci. 2000;4:267–78.

    Article  PubMed  Google Scholar 

  43. Adolphs R. Cognitive neuroscience of human social behavior. Nat Rev Neurosci. 2003;4:165–78.

    Article  PubMed  CAS  Google Scholar 

  44. Hasan KM, Walimuni IS, Frye RE. Global cerebral and regional multimodal neuroimaging markers of the neurobiology of autism development and cognition. J Child Neurol. 2013;28:874–85.

    Article  PubMed  Google Scholar 

  45. Ke X, Tang T, Hong S, Hang Y, Zou B, Li H, et al. White matter impairments in autism, evidence from voxel-based morphometry and diffusion tensor imaging. Brain Res. 2009;1265:171–7.

    Article  PubMed  CAS  Google Scholar 

  46. Poustka L, Jennen-Steinmetz C, Henze R, Vomstein K, Haffner J, Sieltjes B. Fronto-temporal disconnectivity and symptom severity in children with autism spectrum disorder. World J Biol Psychiatry. 2011;13:269–80.

    Article  PubMed  Google Scholar 

  47. Schaer M, Ottet M-C, Scariati E, Dukes D, Franchini M, Eliez S, et al. Decreased frontal gyrification correlates with altered connectivity in children with autism. Front Hum Neurosci. 2013;7:750.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Beacher FD, Minati L, Baron-Cohen S, Lombardo MV, Lai M-C, Gray MA, et al. Autism attenuates sex differences in brain structure: a combined voxel-based morphometry and diffusion tensor imaging study. Am J Neuroradiol. 2012;33:83–9.

    Article  PubMed  CAS  Google Scholar 

  49. Lord C, Rutter M, DiLavore PC, Risi S, Gotham K, Bishop S. Autism diagnostic observation schedule, second edition (ADOS-2) manual (part I): modules 1–4. Torrance: Westerm Psychological Services; 2012.

    Google Scholar 

  50. Corbett BA, Carmean V, Ravizza S, Wendelken C, Henry ML, Carter C, et al. A functional and structural study of emotion and face processing in children with autism. Psychiatry Res Neuroimaging. 2009;173:196–205.

    Article  Google Scholar 

  51. Sahyoun CP, Belliveau JW, Soulières I, Schwartz S, Mody M. Neuroimaging of the functional and structural networks underlying visuospatial vs. linguistic reasoning in high-functioning autism. Neuropsychologia. 2010;48:86–95.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Courchesne E, Pierce K. Why the frontal cortex in autism might be talking only to itself: local over-connectivity but long-distance disconnection. Curr Opin Neurobiol. 2005;15:225–30.

    Article  PubMed  CAS  Google Scholar 

  53. Roberts TPL, Lanza MR, Dell J, Qasmieh S, Hines K, Blaskey L, et al. Maturational differences in thalamocortical white matter microstructure and auditory evoked response latencies in autism spectrum disorders. Brain Res. 2013;1537:79–85.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  54. Kenworthy L, Yerys BE, Anthony LG, Wallace GL. Understanding executive control in autism spectrum disorders in the lab and in the real world. Neuropsychol Rev. 2008;18:320–38.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Delmonte S, Gallagher L, O’Hanlon E, Mc Grath J, Balsters JH. Functional and structural connectivity of frontostriatal circuitry in autism spectrum disorder. Front Hum Neurosci. 2013;7:430.

    Article  PubMed  PubMed Central  Google Scholar 

  56. McGrath J, Johnson K, O’Hanlon E, Garavan H, Leemans A, Gallagher L. Abnormal functional connectivity during visuospatial processing is associated with disrupted organisation of white matter in autism. Front Hum Neurosci. 2013;7:434.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Schmitz N, Rubia K, Daly E, Smith A, Williams S, Murphy DGM. Neural correlates of executive function in autistic spectrum disorders. Biol Psychiatry. 2006;59:7–16.

    Article  PubMed  Google Scholar 

  58. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey C, Wedeen V, et al. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6:1479–93.

    Article  CAS  Google Scholar 

  59. Setsompop K, Cohen-Adad J, Gagoski BA, Raij T, Yendiki A, Keil B, et al. Improving diffusion MRI using simultaneous multi-slice echo planar imaging. NeuroImage. 2012;63:569–80.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  60. Wedeen VJ, Wang RP, Schmahmann JD, Benner T, Tseng WYI, Dai G, et al. Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. NeuroImage. 2008;41:1267–77.

    Article  PubMed  CAS  Google Scholar 

  61. Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci. 2013;14:365–76.

    Article  PubMed  CAS  Google Scholar 

  62. Van Essen DC, Smith SM, Barch DM, Behrens TEJ, Yacoub E, Ugurbil K, et al. The WU-Minn Human Connectome Project: an overview. NeuroImage. 2013;80:62–79.

    Article  PubMed  Google Scholar 

  63. Di Martino A, Yan C-G, Li Q, Denio E, Castellanos FX, Alaerts K, et al. The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry. 2013. doi:10.1038/mp.2013.78.

    PubMed  Google Scholar 

  64. Hanke M, Halchenko YO, Sederberg PB, Olivetti E, Fründ I, Rieger JW, et al. PyMVPA: a unifying approach to the analysis of neuroscientific data. Front Neuroinformatics. 2009;3:3.

    Article  PubMed Central  Google Scholar 

Download references

Acknowledgments

Benjamin E. Yerys is supported by two grants from the National Institutes of Health (K23MH086111, R21MH092615) and an internal “New Program Development Award” from the Intellectual and Developmental Disabilities Research Center at the Children’s Hospital of Philadelphia (P30 HD02679), and the Philadelphia Foundation. John D. Herrington is supported by a grant from Shire Pharmaceuticals. We thank Gregory L. Wallace for feedback on a draft of this manuscript.

Compliance with Ethics Guidelines

Conflict of Interest

Benjamin E. Yerys and John D. Herrington declare that they have no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Benjamin E. Yerys or John D. Herrington.

Additional information

This article is part of the Topical Collection on Autism Spectrum Disorders

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yerys, B.E., Herrington, J.D. Multimodal Imaging in Autism: an Early Review of Comprehensive Neural Circuit Characterization. Curr Psychiatry Rep 16, 496 (2014). https://doi.org/10.1007/s11920-014-0496-2

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s11920-014-0496-2

Keywords

Navigation