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  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.

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 Urheber:
Singer, Johannes J. D.1, 2, Autor
Cichy, Radoslaw M.2, Autor
Hebart, Martin N.1, 3, Autor                 
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              

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Schlagwörter: MEG; Decoding; fMRI; Line drawings; Object recognition; Representational similarity analysis
 Zusammenfassung: 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.

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Sprache(n): eng - English
 Datum: 2022-11-182022-08-042022-11-302022-12-192023-01-18
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1523/JNEUROSCI.1546-22.2022
Anderer: epub 2022
PMID: 36535769
PMC: PMC9864561
 Art des Abschluß: -

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Projektname : -
Grant ID : M.TN.A.NEPF0009
Förderprogramm : -
Förderorganisation : Max Planck Society
Projektname : -
Grant ID : ERC-StG-2021-101039712; ERC-StG-2018-803370
Förderprogramm : -
Förderorganisation : European Research Council (ERC)
Projektname : -
Grant ID : CI241/1-1; CI241/3-1; CI241/7-1
Förderprogramm : -
Förderorganisation : German Research Council (DFG)

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Titel: The Journal of Neuroscience
  Andere : The Journal of Neuroscience: the Official Journal of the Society for Neuroscience
  Kurztitel : J. Neurosci.
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: Washington, DC : Society of Neuroscience
Seiten: - Band / Heft: 43 (3) Artikelnummer: - Start- / Endseite: 484 - 500 Identifikator: ISSN: 0270-6474
CoNE: https://pure.mpg.de/cone/journals/resource/954925502187_1