AbstractVisual perception operates in an object-based manner, by integrating associated features via attention. Working memory allows a flexible access to a limited number of currently relevant objects, even when they are occluded or physically no longer present. Recently, it has been shown that we compensate for small changes of an object’s feature over memory episodes, which can support its perceptual stability. This phenomenon was termed ‘serial dependence’ and has mostly been studied in situations that comprised only a single relevant object. However, since we are typically confronted with situations where several objects have to be perceived and held in working memory, the central question of how we selectively create temporal stability of several objects has remained unsolved. As different objects can be distinguished by their accompanying context features, like their color or temporal position, we tested whether serial dependence is supported by the congruence of context features across memory episodes. Specifically, we asked participants to remember the motion directions of two sequentially presented colored dot fields per trial. At the end of a trial one motion direction was cued for continuous report either by its color (Experiment 1) or serial position (Experiment 2). We observed serial dependence, i.e., an attractive bias of currently toward previously memorized objects, between current and past motion directions that was clearly enhanced when items had the same color or serial position across trials. This bias was particularly pronounced for the context feature that was used for cueing and for the target of the previous trial. Together, these findings demonstrate that coding of current object representations depends on previous representations, especially when they share similar content and context features. Apparently the binding of content and context features is not completely erased after a memory episode, but it is carried over to subsequent episodes. As this reflects temporal dependencies in natural settings, the present findings reveal a mechanism that integrates corresponding bundles of content and context features to support stable representations of individualized objects over time.
Context information supports serial dependence of multiple visual objects across memory episodes
