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Typical and Atypical Neurodevelopment for Face Specialization: An fMRI Study

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Abstract

Individuals with autism spectrum disorder (ASD) and their relatives process faces differently from typically developed (TD) individuals. In an fMRI face-viewing task, TD and undiagnosed sibling (SIB) children (5–18 years) showed face specialization in the right amygdala and ventromedial prefrontal cortex, with left fusiform and right amygdala face specialization increasing with age in TD subjects. SIBs showed extensive antero-medial temporal lobe activation for faces that was not present in any other group, suggesting a potential compensatory mechanism. In ASD, face specialization was minimal but increased with age in the right fusiform and decreased with age in the left amygdala, suggesting atypical development of a frontal–amygdala–fusiform system which is strongly linked to detecting salience and processing facial information.

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Acknowledgments

This research was sponsored by Autism Speaks and the National Institutes of Health (R01 HD052724, R01 HD042452). We thank Christine Corbly, Myra Huffman and Melissa Wheatley for assistance with data collection and Michelle DiBartolo for help with manuscript preparation.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics statement

All procedures were approved by the university’s Institutional Review Board and have been performed in accordance with the ethical standards established in the 1964 Declaration of Helsinki and its later amendments. All persons gave informed consent or assent prior to inclusion in the study.

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Authors and Affiliations

  1. Department of Neurosciences, Medical University of South Carolina, Clinical Sciences Building, Room 325E, MSC 616, Charleston, SC, 29425, USA

    Jane E. Joseph, Xun Zhu, Andrew Gundran & Faraday Davies

  2. Department of Anatomy and Neurobiology, University of Kentucky Chandler Medical Center, Lexington, KY, USA

    Jonathan D. Clark & Paul Glaser

  3. Department of Educational, School and Counseling Psychology, University of Kentucky, Lexington, KY, USA

    Lisa Ruble

  4. Department of Psychiatry, University of Kentucky, Lexington, KY, USA

    Paul Glaser

  5. Department of Psychology, University of Kentucky, Lexington, KY, USA

    Ramesh S. Bhatt

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  1. Jane E. Joseph
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Correspondence to Jane E. Joseph.

Appendix

Appendix

The Face > Texture contrast was used to isolate regions of interest (ROIs) in the present study, but this contrast may be biased to detect face preferential responses, thereby raising concerns about the independence of ROI definition and hypothesis testing. To address this concern, we also ran a (Face + Object)/2 > Texture contrast and applied the same uncorrected threshold (z > 2.81) that was used to create ROIs from the Face > Texture contrast. As shown in Fig. 5, this contrast yielded 2 large occipito-temporal clusters that survive an extent threshold of 43 voxels. Forty-three voxels was used as a minimal extent threshold given that spatial smoothing used a 7-mm FWHM Gaussian kernel. Therefore, the resolvable element size was 343 μL. During spatial normalization the data were resampled to 2 mm3 or 8 μL; therefore, 43 voxels in MNI space = 344 μL, which matches the minimum resolvable element.

Fig. 5
figure 5

Comparison of two approaches used to define ROIs. The approach on the left was used for the main analysis and the approach on the right is an alternative approach that was explored. a Face > Texture contrast at uncorrected, z > 2.81 (red–yellow). The right occipito-temporal activation was masked by the AAL atlas to yield the right FFA (blue). b (Face + Object)/2 > Texture contrast at uncorrected, z > 2.81. This activation map was further masked by the AAL atlas to yield FFA regions (yellow) and OFA regions (green) (Color figure online)

Full size image

These two large clusters were further broken down into FFA and OFA components using AAL atlas regions as masks (as we did for the ROIs from the Face > Texture contrast). The resulting ROIs are very similar, but not identical to, the FFA and OFA ROIs that we used in the paper. We then examined face-specialization index (FSI) and object-specialization index (OSI) in these 4 new ROIs to see if any of the results differed.

One difference was that SIBs showed a significant FSI (compared to 0) in the new right FFA which was marginally significant before. Another difference was that the comparison of ASD versus TD-A (via nonparametric Median Test) was not significant in the new right FFA. Also, the marginal correlation between age and FSI in the TD-combined group was not significant in the new left FFA. However, the correlation between FSI and age in the right remains significant in the new right FFA as well.

Taken together, different results with the new ROIs apply to those situations where the effects were marginal or not as strong as in some other ROIs. However, the fundamental findings of the present study were not drastically changed by the two approaches to defining ROIs.

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Joseph, J.E., Zhu, X., Gundran, A. et al. Typical and Atypical Neurodevelopment for Face Specialization: An fMRI Study. J Autism Dev Disord 45, 1725–1741 (2015). https://doi.org/10.1007/s10803-014-2330-4

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  • DOI: https://doi.org/10.1007/s10803-014-2330-4

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