English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  The spatiotemporal neural dynamics of object recognition for natural images and line drawings

Singer, J. J. D., Cichy, R. M., & Hebart, M. N. (2023). The spatiotemporal neural dynamics of object recognition for natural images and line drawings. The Journal of Neuroscience, 43(3), 484-500. doi:10.1523/JNEUROSCI.1546-22.2022.

Item is

Files

show Files
hide Files
:
Singer_2023.pdf (Publisher version), 4MB
Name:
Singer_2023.pdf
Description:
-
OA-Status:
Hybrid
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
:
Singer_pre.pdf (Preprint), 5MB
Name:
Singer_pre.pdf
Description:
-
OA-Status:
Green
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show
hide
Description:
-
OA-Status:
Green

Creators

show
hide
 Creators:
Singer, Johannes J. D.1, 2, Author
Cichy, Radoslaw M.2, Author
Hebart, Martin N.1, 3, Author                 
Affiliations:
1Max Planck Research Group Vision and Computational Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3158378              
2Department of Education and Psychology, FU Berlin, Germany, ou_persistent22              
3Department of Medicine, Justus Liebig University, Giessen, Germany, ou_persistent22              

Content

show
hide
Free keywords: MEG; Decoding; fMRI; Line drawings; Object recognition; Representational similarity analysis
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 2022-11-182022-08-042022-11-302022-12-192023-01-18
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1523/JNEUROSCI.1546-22.2022
Other: epub 2022
PMID: 36535769
PMC: PMC9864561
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : -
Grant ID : M.TN.A.NEPF0009
Funding program : -
Funding organization : Max Planck Society
Project name : -
Grant ID : ERC-StG-2021-101039712; ERC-StG-2018-803370
Funding program : -
Funding organization : European Research Council (ERC)
Project name : -
Grant ID : CI241/1-1; CI241/3-1; CI241/7-1
Funding program : -
Funding organization : German Research Council (DFG)

Source 1

show
hide
Title: The Journal of Neuroscience
  Other : The Journal of Neuroscience: the Official Journal of the Society for Neuroscience
  Abbreviation : J. Neurosci.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Washington, DC : Society of Neuroscience
Pages: - Volume / Issue: 43 (3) Sequence Number: - Start / End Page: 484 - 500 Identifier: ISSN: 0270-6474
CoNE: https://pure.mpg.de/cone/journals/resource/954925502187_1