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Good-enough attentional guidance
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AI
DOI：10.1016/j.tics.2023.01.007.png)
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Abstract
En 中文
Theories of attention posit that attentional guidance operates on information held in a target template within memory. The template is often thought to contain veridical target features, akin to a photograph, and to guide attention to objects that match the exact target features. However, recent evidence suggests that attentional guidance is highly flexible and often guided by non-veridical features, a subset of features, or only associated features. We integrate these findings and propose that attentional guidance maximizes search efficiency based on a 'good-enough' principle to rapidly localize candidate target objects. Candidates are then serially interrogated to make target-match decisions using more precise information. We suggest that good-enough guidance optimizes the speed- accuracy-effort trade-offs inherent in each stage of visual search.
Keywords:
VISUAL-SEARCH
NEURAL MECHANISMS
TARGET TEMPLATES
SELECTIVE ATTENTION
DECISION-MAKING
TOP-DOWN
MEMORY
CATEGORY
FEATURES
COLOR
Journal
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