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Your place or mine? The neural dynamics of personally familiar scene recognition suggests category independent familiarity encoding.

Klink, H., Kaiser, D., Stecher, R., Ambrus, G. G and Kovács, G., 2023. Your place or mine? The neural dynamics of personally familiar scene recognition suggests category independent familiarity encoding. Cerebral Cortex, bhad397. (In Press)

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DOI: 10.1093/cercor/bhad397

Abstract

Recognizing a stimulus as familiar is an important capacity in our everyday life. Recent investigation of visual processes has led to important insights into the nature of the neural representations of familiarity for human faces. Still, little is known about how familiarity affects the neural dynamics of non-face stimulus processing. Here we report the results of an EEG study, examining the representational dynamics of personally familiar scenes. Participants viewed highly variable images of their own apartments and unfamiliar ones, as well as personally familiar and unfamiliar faces. Multivariate pattern analyses were used to examine the time course of differential processing of familiar and unfamiliar stimuli. Time-resolved classification revealed that familiarity is decodable from the EEG data similarly for scenes and faces. The temporal dynamics showed delayed onsets and peaks for scenes as compared to faces. Familiarity information, starting at 200 ms, generalized across stimulus categories and led to a robust familiarity effect. In addition, familiarity enhanced category representations in early (250-300 ms) and later (>400 ms) processing stages. Our results extend previous face familiarity results to another stimulus category and suggest that familiarity as a construct can be understood as a general, stimulus-independent processing step during recognition.

Item Type:Article
ISSN:1047-3211
Uncontrolled Keywords:EEG; familiarity; multivariate pattern analysis; recognition; scene perception
Group:Faculty of Science & Technology
ID Code:39167
Deposited By: Symplectic RT2
Deposited On:21 Nov 2023 11:23
Last Modified:21 Nov 2023 11:23

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