five

Dataset for: Detection versus Discrimination: The Limits of Binding Accounts in Action Control

收藏
PsychArchives2019-10-24 更新2026-04-25 收录
下载链接:
https://hdl.handle.net/20.500.12034/2249
下载链接
链接失效反馈
官方服务:
资源简介:
Dataset for: Schöpper, L., Hilchey, M.D., Lappe, M. et al. Detection versus discrimination: The limits of binding accounts in action control. Atten Percept Psychophys 82, 2085–2097 (2020). https://doi.org/10.3758/s13414-019-01911-4 Actions can be investigated by using sequential priming tasks, in which participants respond to prime and probe targets (sometimes accompanied by distractors). Facilitation and interference from prime to probe are measured by repeating, changing, or partially repeating features or responses between prime and probe. According to the action control literature, feature-feature or feature-response bindings are universal and apply for all actions. The attentional orienting literature, however, suggests that if the task is to detect stimuli, such binding effects may be absent. In two experiments, we compared performance in a discrimination task and a detection task with the exact same perceptual setup of prime-probe sequences. For the discrimination task, we replicated the typical feature-response binding pattern. Crucially, we did not observe any binding effects for the detection task, which can be explained by task-specific processes or fast response execution. These results reveal an important boundary of current binding models in action control. Dataset for the study "Detection versus Discrimination: The Limits of Binding Accounts in Action Control", to-be-published in Attention, Perception, & Psychophysics. For further information please refer to the aforementioned paper. The aggregated data files can be analyzed by using the respective SPSS-Syntax available under "Code for: Detection versus Discrimination: The Limits of Binding Accounts in Action Control" to perform the analysis reported in the paper.
提供机构:
PsychArchives
创建时间:
2019-10-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作