Scene-selective regions in the brain play an important role in the way that we navigate through our visual environment. However, the principles that govern the organization of these regions are not fully understood. For example, it is not clear whether patterns of response in scene-selective regions are linked to high-level semantic category or to low-level spatial structure in scenes. To address this issue, we used multivariate pattern analysis with fMRI to compare patterns of response to different categories of scenes. Although we found distinct patterns of neural response to each category of scene, the magnitude of the within-category similarity varied across different scenes. To determine whether this variation in the categorical response to scenes could reflect variation in the low-level image properties, we measured the similarity of images from each category of scene. Although we found that the low-level properties of images from each category were more similar to each other than to other categories of scenes, we also found that the magnitude of the within-category similarity varied across different scenes. Finally, we compared variation in the neural response to different categories of scenes with corresponding variation in the low-level image properties. We found a strong positive correlation between the similarity in the patterns of neural response to different scenes and the similarity in the image properties. Together, these results suggest that categorical patterns of response to scenes are linked to the low-level properties of the images.
Keywords: MVPA; PPA; Scenes; fMRI.
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