Low-Level Image Properties of Visual Objects Predict Patterns of Neural Response across Category-Selective Regions of the Ventral Visual Pathway
- Department of Psychology and York Neuroimaging Centre, University of York, York YO10 5DD, United Kingdom
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Author contributions: G.E.R. and T.J.A. designed research; G.E.R. and T.J.A. performed research; D.M.W., T.H., and T.J.A. contributed unpublished reagents/analytic tools; G.E.R. and T.J.A. analyzed data; G.E.R., D.M.W., T.H., and T.J.A. wrote the paper.
Abstract
Neuroimaging studies have revealed strong selectivity for object categories in high-level regions of the human visual system. However, it is unknown whether this selectivity is truly based on object category, or whether it reflects tuning for low-level features that are common to images from a particular category. To address this issue, we measured the neural response to different object categories across the ventral visual pathway. Each object category elicited a distinct neural pattern of response. Next, we compared the patterns of neural response between object categories. We found a strong positive correlation between the neural patterns and the underlying low-level image properties. Importantly, this correlation was still evident when the within-category correlations were removed from the analysis. Next, we asked whether basic image properties could also explain variation in the pattern of response to different exemplars from one object category (faces). A significant correlation was also evident between the similarity of neural patterns of response and the low-level properties of different faces, particularly in regions associated with face processing. These results suggest that the appearance of category-selective regions at this coarse scale of representation may be explained by the systematic convergence of responses to low-level features that are characteristic of each category.
- Received December 17, 2013.
- Revision received March 18, 2014.
- Accepted April 13, 2014.
- Copyright © 2014 Rice et al.
This article is freely available online through the J Neurosci Author Open Choice option.





