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Action-based selection across feature dimensions: Multidimensional vector models of stimulus-response compatibility.

机译:跨特征维的基于动作的选择:刺激-响应兼容性的多维矢量模型。

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摘要

From a functional point of view, cognition is a mechanism by which human uses information in their environments in order to actualize adaptive behavior to sustain their existence. The capacity of the system is limited, so only a subset of environmental information can be processed at a time. Thus, selection of information must occur. This selection mechanism is named selective attention.;The first chapter of the thesis reviews studies on selective attention across feature dimensions. Two types of the selection mechanisms are commonly distinguished; controlled processes that are intentionally initiated and monitored, and automatic processes that operate without the actor's intention. Although automatic processes are thought to be independent of the actor's intention, the review revealed that automatic processes are conditioned by the actor's intention. More specifically, selection across feature dimensions is implemented in accordance to what actions are prepared. This action-based selection plays a central role in psychological phenomena such as Stroop interference and stimulus-response (S-R) compatibility.;On the other hand, it is believed that controlled processes become automatized only if the operations are extensively practiced for a long period. However, recent studies provide evidence that certain controlled processes can be automatized without extensive training. The second chapter reports a series of experiments that investigated this issue. It is demonstrated that arbitrary S-R mappings can be implemented automatically without one's intention. Consequently, stimulus features that are irrelevant to performing the current task activate associated responses and facilitate or interfere with responding to the task-relevant features, resulting in the cross-dimensional response congruity effect. The experiments indicated that active maintenance of S-R mappings is not necessary for automatic implementation of task-defined S-R mappings. Instead, retrieval of episodic memory contributes to the automatic implementation of task-defined S-R mappings.;Finally, in the third chapter, a modeling framework for selection across feature dimensions is developed, named the multidimensional vector (MDV) model. The framework realizes the idea of action-based selective attention by specifying how response properties determine weights of feature dimensions in processing stimuli. Five experiments tested assumptions underlying the framework. The MDV models provided excellent accounts of the experimental data, validating the MDV framework.
机译:从功能的角度来看,认知是一种机制,人类可以通过这种机制在其环境中使用信息,以实现适应性行为以维持其生存。系统的容量有限,因此一次只能处理一部分环境信息。因此,必须进行信息选择。这种选择机制被称为选择性注意。;论文的第一章回顾了跨特征维度的选择性注意的研究。通常区分两种选择机制:有意识地启动和监视的受控过程,以及没有参与者意图的自动过程。尽管自动过程被认为与演员的意图无关,但该评论显示,自动过程取决于演员的意图。更具体地,根据准备的动作来实现跨特征尺寸的选择。这种基于动作的选择在诸如Stroop干扰和刺激响应(SR)兼容性等心理现象中起着核心作用;另一方面,据信只有长时间长时间广泛地进行操作,受控过程才能实现自动化。但是,最近的研究提供了证据,表明某些受控过程无需大量培训即可自动化。第二章报告了一系列研究此问题的实验。证明了任意S-R映射都可以自动实现,而无需任何人的意图。因此,与执行当前任务无关的刺激特征会激活关联的响应,并促进或干扰对任务相关特征的响应,从而导致跨维度的响应一致性效应。实验表明,主动执行任务定义的S-R映射并不需要主动维护S-R映射。取而代之的是,情节记忆的检索有助于任务定义的S-R映射的自动实现。最后,在第三章中,开发了用于跨特征维选择的建模框架,称为多维矢量(MDV)模型。该框架通过指定响应属性如何确定处理刺激中特征维的权重来实现基于动作的选择性注意的想法。五个实验测试了框架的基础假设。 MDV模型很好地说明了实验数据,从而验证了MDV框架。

著录项

  • 作者

    Yagamuchi, Motonori.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Psychology Experimental.;Psychology Psychometrics.;Psychology Cognitive.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 332 p.
  • 总页数 332
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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