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

在日常场景中，搜索的目标并不是孤立出现的，而是嵌入到非目标或干扰项的配置中。如果目标相对于分心物的位置是不变的，这种空间偶然性被内隐地学习并引导视觉扫描(语境线索效应；Chun&酱，1998；Geyer等，2010b)。在预测编码模型方面，内隐结构学习可以被概念化为涉及输入和原因之间的关联的逐渐获得(Friston，2010；Conci等人，2012)。也就是说：搜索引导预测(关于目标的位置)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，语境预测的有效性在很大程度上依赖于自下而上的知觉输入和语境记忆之间的一致性：在配置学习之后，在不变的干扰因素语境中将目标重新定位到意想不到的位置完全取消了语境提示，并且来自不变语境的收益随着接触改变的显示而恢复得非常缓慢(Zellin等人。2014年)。本提案将使用行为和神经科学方法来研究视觉搜索中语境学习的自上而下-自下而上的平衡。

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.