Impacts of cue reliability and explicit instruction on visual attention

Kanji Tanaka, Katsumi Watanabe

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

It has been known that effects of visual attention are modulated by cue validity (i.e., proportion of valid and invalid condition in a certain block). The present study aimed at examining whether the benefits (i.e., the differences of reaction times in the valid and invalid condition) were linear as a function of cue reliability. We also examined effects of explicit instruction of information regarding cue reliability on visual attention. In the experiment, we adopted a cueing paradigm in which cue reliability varied in each block (0, 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100%). We also classified all participants into two groups: Instruction and Non-instruction groups. The results showed that the benefit was linear as a function of cue reliability regardless of instruction, which indicates that cue validity has a strong influence on visual attention compared to a cued location. We also found that reaction time in the valid condition became shorter with increased cue reliability compared to the invalid condition with decreased cue reliability, albeit only in the Instruction group. This result indicates that participants with instruction focus more on the cued location (i.e., valid condition) and not the dominant proportion of cue validity.

本文言語英語
ホスト出版物のタイトル2017 9th International Conference on Knowledge and Smart Technology
ホスト出版物のサブタイトルCrunching Information of Everything, KST 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ270-273
ページ数4
ISBN(電子版)9781467390774
DOI
出版ステータス出版済み - 3月 23 2017
外部発表はい
イベント9th International Conference on Knowledge and Smart Technology, KST 2017 - Chonburi, タイ
継続期間: 2月 1 20172月 4 2017

出版物シリーズ

名前2017 9th International Conference on Knowledge and Smart Technology: Crunching Information of Everything, KST 2017

会議

会議9th International Conference on Knowledge and Smart Technology, KST 2017
国/地域タイ
CityChonburi
Period2/1/172/4/17

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学
  • 人工知能
  • コンピュータ サイエンスの応用

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