September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Decoding objects’ roughness held in visual working memory
Author Affiliations & Notes
  • Munendo Fujimichi
    Graduate School of Human and Environmental Studies, Kyoto University
  • Hiroyuki Tsuda
    Graduate School of Human and Environmental Studies, Kyoto University
  • Hiroki Yamamoto
    Graduate School of Human and Environmental Studies, Kyoto University
  • Jun Saiki
    Graduate School of Human and Environmental Studies, Kyoto University
Journal of Vision September 2019, Vol.19, 248. doi:https://doi.org/10.1167/19.10.248
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      Munendo Fujimichi, Hiroyuki Tsuda, Hiroki Yamamoto, Jun Saiki; Decoding objects’ roughness held in visual working memory. Journal of Vision 2019;19(10):248. doi: https://doi.org/10.1167/19.10.248.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Previous studies on visual working memory revealed that both visual and parietal cortex play important roles for the memory of color and shapes. In contrast, prior studies on perception of objects’ material properties have shown that the ventral visual pathway supports the material perception. Which regions are responsible for visual working memory for objects’ material properties? To test this question, we conducted an fMRI experiment where participants performed a delayed roughness discrimination task (main task) in a 3T scanner. In each trial, two sample objects were sequentially presented. These objects consisted of rough object and smooth object. After these objects were presented, a numerical cue was presented. The cue indicated which sample to memorize. After an 11s delay, a probe object was presented and the participants indicated which one of the probe object and the memorized one had lower roughness. The imaging runs of the main task were followed by two kinds of imaging: localizer runs to identify brain regions processing objects, color, faces, and scenes, and phase-encoded retinotopy measurements to define retinotopic visual areas. We applied multivoxel pattern analysis (MVPA) to predict the memorized sample’s roughness, rough or smooth. The results of MVPA showed above-chance accuracies in the early visual areas, intraparietal sulcus, and ventral object vision pathway. These results suggest that not only the early visual cortex and intraparietal sulcus, but also ventral vision pathway can hold objects’ roughness in visual working memory.

Acknowledgement: Japan Society for the Promotion of Science (JSPS), Tokyo 
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