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Article Dans Une Revue Vision Research Année : 2023

Dynamics of low-pass-filtered object categories: A decoding approach to ERP recordings

Résumé

Rapid analysis of low spatial frequencies (LSFs) in the brain conveys the global shape of the object and allows for rapid expectations about the visual input. Evidence has suggested that LSF processing differs as a function of the semantic category to identify. The present study sought to specify the neural dynamics of the LSF contribution to the rapid object representation of living versus non-living objects. In this EEG experiment, participants had to categorize an object displayed at different spatial frequencies (LSF or non-filtered). Behavioral results showed an advantage for living versus non-living objects and a decrease in performance with LSF pictures of pieces of furniture only. Moreover, despite a difference in classification performance between LSF and non-filtered pictures for living items, the behavioral performance was maintained, which suggests that classification under our specific condition can be based on LSF information, in particular for living items.
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Dates et versions

hal-04353959 , version 1 (19-12-2023)

Identifiants

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Yannick Wamain, Clementine Garric, Quentin Lenoble. Dynamics of low-pass-filtered object categories: A decoding approach to ERP recordings. Vision Research, 2023, Vision Research, 204, p. 108165. ⟨10.1016/j.visres.2022.108165⟩. ⟨hal-04353959⟩
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