Abstract
How are complex visual entities such as scenes represented in the human brain? More concretely, along what visual and semantic dimensions are scenes encoded in memory? One hypothesis is that global spatial properties provide a basis for categorizing the neural response patterns arising from scenes. In contrast, non-spatial properties, such as single objects, also account for variance in neural responses. The list of critical scene dimensions has continued to grow—sometimes in a contradictory manner—coming to encompass properties such as geometric layout, big/small, crowded/sparse, and three-dimensionality. We demonstrate that these dimensions may be better understood within the more general framework of associative properties. That is, across both the perceptual and semantic domains, features of scene representations are related to one another through learned associations. Critically, the components of such associations are consistent with the dimensions that are typically invoked to account for scene understanding and its neural bases. Using fMRI, we show that non-scene stimuli displaying novel associations across identities or locations recruit putatively scene-selective regions of the human brain (the parahippocampal/lingual region, the retrosplenial complex, and the transverse occipital sulcus/occipital place area). Moreover, we find that the voxel-wise neural patterns arising from these associations are significantly correlated with the neural patterns arising from everyday scenes providing critical evidence whether the same encoding principals underlie both types of processing. These neuroimaging results provide evidence for the hypothesis that the neural representation of scenes is better understood within the broader theoretical framework of associative processing. In addition, the results demonstrate a division of labor that arises across scene-selective regions when processing associations and scenes providing better understanding of the functional roles of each region within the cortical network that mediates scene processing.
Highlights
Scenes are complex stimuli containing rich, statistically regular information about objects, background, context, semantics, and spatial layout at multiple scales
In particular, that associative processing is inherent in scene understanding, we explore whether the network of brain regions recruited in scene perception is recruited when processing non-scene-like stimuli that contain associative information
Given the reliable correlation between the patterns of activity elicited for associative processing and for scene processing, as a control, we examined whether other, non-associative, visual tasks would elicit similar patterns of activity in these Region of interest (ROI)
Summary
Scenes are complex stimuli containing rich, statistically regular information about objects, background, context, semantics, and spatial layout at multiple scales. Scene categories (e.g., kitchens) emerge as a consequence of these, and other, regular, co-occurring entities (e.g., oven and refrigerator; dishwasher located next to the sink)–something that is reflected in cortical representation [4] These associated regularities are useful in defining scene categories, and in predicting which other objects and relations are likely to occur within a scene [5]. What we mean by associative is that the features of any kind of mental representation, irrespective as to whether that representation is nominally visual, linguistic, etc., are related to one another via learned associations These associations are not necessarily modality-specific–for example, visual representations are likely to carry many semantic and affective associations not directly present in the image. We investigated, using fMRI, whether different types of relations, all falling under the heading of associative processing, reliably recruit specific components of the network of brain regions known to be scene selective
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