|Title:||Dynamics of Attentional Selection Under Conflict: Toward a Rational Bayesian Account||Authors:||ANGELA YU-CHEN LIN
|Keywords:||attention; Bayesian; conflict; decision making; Eriksen||Issue Date:||2009||Journal Volume:||35||Journal Issue:||3||Start page/Pages:||700-717||Source:||Journal of Experimental Psychology: Human Perception and Performance||Abstract:||
The brain exhibits remarkable facility in exerting attentional control in most circumstances, but it also suffers apparent limitations in others. The authors' goal is to construct a rational account for why attentional control appears suboptimal under conditions of conflict and what this implies about the underlying computational principles. The formal framework used is based on Bayesian probability theory, which provides a convenient language for delineating the rationale and dynamics of attentional selection. The authors illustrate these issues with the Eriksen flanker task, a classical paradigm that explores the effects of competing sensory inputs on response tendencies. The authors show how 2 distinctly formulated models, based on compatibility bias and spatial uncertainty principles, can account for the behavioral data. They also suggest novel experiments that may differentiate these models. In addition, they elaborate a simplified model that approximates optimal computation and may map more directly onto the underlying neural machinery. This approximate model uses conflict monitoring, putatively mediated by the anterior cingulate cortex, as a proxy for compatibility representation. The authors also consider how this conflict information might be disseminated and used to control processing. © 2009 American Psychological Association.
|ISSN:||00961523||DOI:||10.1037/a0013553||SDG/Keyword:||article; attention; Bayes theorem; conflict; decision making; discrimination learning; human; pattern recognition; reaction time; receptive field; statistical model; Attention; Bayes Theorem; Conflict (Psychology); Decision Making; Discrimination Learning; Field Dependence-Independence; Humans; Likelihood Functions; Pattern Recognition, Visual; Reaction Time|
|Appears in Collections:||環境工程學研究所|
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