Project A3. Learning and adaptation of spatial attention templates in visual search

在日常场景中，搜索目标不会孤立出现，而是嵌入在非目标或干扰项的配置中。如果目标相对于干扰物的位置不变，则这种空间随因会被内隐学习并引导视觉扫描（情境线索效应；Chun & Jiang, 1998; Geyer et al., 2010b）。就预测编码模型而言，内隐构形学习可以被概念化为涉及输入和原因之间关联的逐渐习得（Friston, 2010; Conci et al., 2012）。也就是说：搜索导向预测（关于目标位置）是从上下文记忆自上而下传播的，以影响自下而上的搜索过程。然而，上下文预测的有效性在很大程度上取决于自下而上的感知输入和上下文记忆之间的一致性：在配置学习之后，将目标重新定位到未改变的干扰物上下文中的意外位置完全消除了上下文线索，并且随着暴露于变化的显示的增加，从不变上下文中获得的收益只能非常缓慢地恢复（Zellin et al. 2014）。本研究将采用行为和神经科学的方法来研究视觉搜索中情境学习的自顶向下的平衡。

In everyday scenes, searched-for targets do not appear in isolation, but are embedded within configurations of non-target or distractor items. If the position of the target relative to the distractors is invariant, such spatial contingencies are implicitly learned and come to guide visual scanning (contextual-cueing effect; Chun & Jiang, 1998; Geyer et al., 2010b). In terms of predictive coding models, implicit configural learning can be conceptualized as involving the gradual acquisition of associations between input and cause (Friston, 2010; Conci et al., 2012). That is: search-guiding predictions (about the location of a target) are propagated top-down from contextual memory to influence bottom-up search processes. However, the effectiveness of contextual predictions depends heavily on the consistency between bottom-up perceptual input and context memory: following configural learning, re-locating targets to an unexpected location within an unchanged distractor context completely abolishes contextual cueing, and the gains deriving from the invariant context recover only very slowly with increasing exposure to the changed displays (Zellin et al. 2014). The present proposal will employ behavioral and neuroscience methods to investigate the top-down-bottom-up balance of contextual learning in visual search.