Dynamics of low-pass-filtered object categories: A decoding approach to ERP recordings. (March 2023)

• Record Type: Journal Article
• Authors: Wamain, Yannick; Garric, Clémentine; Lenoble, Quentin
• Is Part Of: Vision research. Volume 204(2023)
• Publication Date: 2023-03
• Subjects: Living object -- Manufactured object -- Coarse-to-fine -- Decoding; Vision -- Periodicals; 573.88
• DOI: 10.1016/j.visres.2022.108165
• Languages: English
• ISSNs: 0042-6989

Abstract

Highlights: Behavioral performances decrease for furniture in low spatial frequency (LSF) only. Classifier based on brain response is able to disentangle item's category. Living/non-living item classification is possible as early as 130 ms. Filtering delays by 30 ms the living/non-living item classification. Classification for living items is based on LSF information. Abstract: 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.