首页 | 本学科首页   官方微博 | 高级检索  
     


Implicit learning for probable changes in a visual change detection task
Authors:Beck Melissa R  Angelone Bonnie L  Levin Daniel T  Peterson Matthew S  Varakin D Alexander
Affiliation:Department of Psychology, Louisiana State University, 236 Audubon Hall, Baton Rouge, LA 70803, USA. mbeck@lsu.edu
Abstract:Previous research demonstrates that implicitly learned probability information can guide visual attention. We examined whether the probability of an object changing can be implicitly learned and then used to improve change detection performance. In a series of six experiments, participants completed 120–130 training change detection trials. In four of the experiments the object that changed color was the same shape (trained shape) on every trial. Participants were not explicitly aware of this change probability manipulation and change detection performance was not improved for the trained shape versus untrained shapes. In two of the experiments, the object that changed color was always in the same general location (trained location). Although participants were not explicitly aware of the change probability, implicit knowledge of it did improve change detection performance in the trained location. These results indicate that improved change detection performance through implicitly learned change probability occurs for location but not shape.
Keywords:Implicit learning   Change detection   Visual attention
本文献已被 ScienceDirect PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号