4.5 Article

A quantitative link between face discrimination deficits and neuronal selectivity for faces in autism

期刊

NEUROIMAGE-CLINICAL
卷 2, 期 -, 页码 320-331

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2013.02.002

关键词

Face; Autism; ASD; fMRI; fMRI-RA; Local correlation

资金

  1. Autism Speaks Foundation
  2. NIMH [R01MH076281]
  3. NSF [0449743]
  4. SNF [PPOOB-110741]
  5. NIH IDDRC [P30HD40677]
  6. NIH GCRC [M01-RR13297]

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Individuals with Autism Spectrum Disorder (ASD) appear to show a general face discrimination deficit across a range of tasks including social-emotional judgments as well as identification and discrimination. However, functional magnetic resonance imaging (fMRI) studies probing the neural bases of these behavioral differences have produced conflicting results: while some studies have reported reduced or no activity to faces in ASD in the Fusiform Face Area (FFA), a key region in human face processing, others have suggested more typical activation levels, possibly reflecting limitations of conventional fMRI techniques to characterize neuron-level processing. Here, we test the hypotheses that face discrimination abilities are highly heterogeneous in ASD and are mediated by FFA neurons, with differences in face discrimination abilities being quantitatively linked to variations in the estimated selectivity of face neurons in the FFA. Behavioral results revealed a wide distribution of face discrimination performance in ASD, ranging from typical performance to chance level performance. Despite this heterogeneity in perceptual abilities, individual face discrimination performance was well predicted by neural selectivity to faces in the FFA, estimated via both a novel analysis of local voxel-wise correlations, and the more commonly used fMRI rapid adaptation technique. Thus, face processing in ASD appears to rely on the FFA as in typical individuals, differing quantitatively but not qualitatively. These results for the first time mechanistically link variations in the ASD phenotype to specific differences in the typical face processing circuit, identifying promising targets for interventions. (C) 2013 The Authors. Published by Elsevier Inc.

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