真实场景中的注意：注意模板的灵活性与稳定性如何权衡

To prioritize the visual processing of task-relevant objects in our surroundings, we rely on an attentional template—an internal representation of object features that guides attention toward potential targets. Decades of research have characterized attentional templates for simple targets in artificial arrays. How could templates function in real-world search, where target appearance is variable and objects are embedded in complex, dynamic scenes? We consider two possibilities: (i) flexible templates that are adapted to changing scene contexts and (ii) stable (‘one-size-fits-all’) templates that generalize across contexts. We review recent behavioral and neuroimaging evidence for both possibilities and discuss how optimal search depends on balancing the relative costs and benefits of template adaptation, enabling efficient attention ‘in the wild’.

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