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The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings

Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for dr...

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Autores principales: Singer, Johannes J.D., Cichy, Radoslaw M., Hebart, Martin N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864561/
https://www.ncbi.nlm.nih.gov/pubmed/36535769
http://dx.doi.org/10.1523/JNEUROSCI.1546-22.2022
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author Singer, Johannes J.D.
Cichy, Radoslaw M.
Hebart, Martin N.
author_facet Singer, Johannes J.D.
Cichy, Radoslaw M.
Hebart, Martin N.
author_sort Singer, Johannes J.D.
collection PubMed
description Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for drawings and natural images, which suggests that similar mechanisms underlie the recognition of both. However, other work has proposed that representations of drawings and natural images become similar only after substantial processing has taken place, suggesting distinct mechanisms. To arbitrate between those alternatives, we measured brain responses resolved in space and time using fMRI and MEG, respectively, while human participants (female and male) viewed images of objects depicted as photographs, line drawings, or sketch-like drawings. Using multivariate decoding, we demonstrate that object category information emerged similarly fast and across overlapping regions in occipital, ventral-temporal, and posterior parietal cortex for all types of depiction, yet with smaller effects at higher levels of visual abstraction. In addition, cross-decoding between depiction types revealed strong generalization of object category information from early processing stages on. Finally, by combining fMRI and MEG data using representational similarity analysis, we found that visual information traversed similar processing stages for all types of depiction, yet with an overall stronger representation for photographs. Together, our results demonstrate broad commonalities in the neural dynamics of object recognition across types of depiction, thus providing clear evidence for shared neural mechanisms underlying recognition of natural object images and abstract drawings. SIGNIFICANCE STATEMENT When we see a line drawing, we effortlessly recognize it as an object in the world despite its simple and abstract style. Here we asked to what extent this correspondence in perception is reflected in the brain. To answer this question, we measured how neural processing of objects depicted as photographs and line drawings with varying levels of detail (from natural images to abstract line drawings) evolves over space and time. We find broad commonalities in the spatiotemporal dynamics and the neural representations underlying the perception of photographs and even abstract drawings. These results indicate a shared basic mechanism supporting recognition of drawings and natural images.
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spelling pubmed-98645612023-01-23 The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings Singer, Johannes J.D. Cichy, Radoslaw M. Hebart, Martin N. J Neurosci Research Articles Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for drawings and natural images, which suggests that similar mechanisms underlie the recognition of both. However, other work has proposed that representations of drawings and natural images become similar only after substantial processing has taken place, suggesting distinct mechanisms. To arbitrate between those alternatives, we measured brain responses resolved in space and time using fMRI and MEG, respectively, while human participants (female and male) viewed images of objects depicted as photographs, line drawings, or sketch-like drawings. Using multivariate decoding, we demonstrate that object category information emerged similarly fast and across overlapping regions in occipital, ventral-temporal, and posterior parietal cortex for all types of depiction, yet with smaller effects at higher levels of visual abstraction. In addition, cross-decoding between depiction types revealed strong generalization of object category information from early processing stages on. Finally, by combining fMRI and MEG data using representational similarity analysis, we found that visual information traversed similar processing stages for all types of depiction, yet with an overall stronger representation for photographs. Together, our results demonstrate broad commonalities in the neural dynamics of object recognition across types of depiction, thus providing clear evidence for shared neural mechanisms underlying recognition of natural object images and abstract drawings. SIGNIFICANCE STATEMENT When we see a line drawing, we effortlessly recognize it as an object in the world despite its simple and abstract style. Here we asked to what extent this correspondence in perception is reflected in the brain. To answer this question, we measured how neural processing of objects depicted as photographs and line drawings with varying levels of detail (from natural images to abstract line drawings) evolves over space and time. We find broad commonalities in the spatiotemporal dynamics and the neural representations underlying the perception of photographs and even abstract drawings. These results indicate a shared basic mechanism supporting recognition of drawings and natural images. Society for Neuroscience 2023-01-18 /pmc/articles/PMC9864561/ /pubmed/36535769 http://dx.doi.org/10.1523/JNEUROSCI.1546-22.2022 Text en Copyright © 2023 Singer et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Research Articles
Singer, Johannes J.D.
Cichy, Radoslaw M.
Hebart, Martin N.
The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title_full The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title_fullStr The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title_full_unstemmed The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title_short The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings
title_sort spatiotemporal neural dynamics of object recognition for natural images and line drawings
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864561/
https://www.ncbi.nlm.nih.gov/pubmed/36535769
http://dx.doi.org/10.1523/JNEUROSCI.1546-22.2022
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