Associative Processing Is Inherent in Scene Perception.

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....

Full description

Bibliographic Details
Main Authors: Elissa M Aminoff, Michael J Tarr
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4467091?pdf=render
id doaj-baab1d185e614a788dd7f0757f2767e1
record_format Article
spelling doaj-baab1d185e614a788dd7f0757f2767e12020-11-25T02:47:02ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01106e012884010.1371/journal.pone.0128840Associative Processing Is Inherent in Scene Perception.Elissa M AminoffMichael J TarrHow 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.http://europepmc.org/articles/PMC4467091?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Elissa M Aminoff
Michael J Tarr
spellingShingle Elissa M Aminoff
Michael J Tarr
Associative Processing Is Inherent in Scene Perception.
PLoS ONE
author_facet Elissa M Aminoff
Michael J Tarr
author_sort Elissa M Aminoff
title Associative Processing Is Inherent in Scene Perception.
title_short Associative Processing Is Inherent in Scene Perception.
title_full Associative Processing Is Inherent in Scene Perception.
title_fullStr Associative Processing Is Inherent in Scene Perception.
title_full_unstemmed Associative Processing Is Inherent in Scene Perception.
title_sort associative processing is inherent in scene perception.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description 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.
url http://europepmc.org/articles/PMC4467091?pdf=render
work_keys_str_mv AT elissamaminoff associativeprocessingisinherentinsceneperception
AT michaeljtarr associativeprocessingisinherentinsceneperception
_version_ 1724755186174394368