Understanding visual-working-memory encoding as a visual search for multiple targets

对环境的体验通过偏向信息的选择来影响有意识的知觉。大多数有意识的视觉信息处理都是通过一种叫做视觉工作记忆(VWM)的系统进行的。VWM的容量受到严重限制，因此一次只对环境中可用信息的一小部分进行编码和表示。此外，即使在那些进入VWM的物品中，表现质量也有很大差异。这种项目间差异的原因在很大程度上仍不清楚。我认为，这种可变性的很大一部分出现在编码过程中：不是被动地吸收所有相关信息，直到VWM容量耗尽，VWM编码的特征可能是视觉场景(例如，对象的不同显著程度)和观察者(例如，对环境的体验：预测性编码)之间的主动交互。通过对这一想法的考察，该项目旨在填补视觉视觉记忆文献中的一个关键空白，并将研究单位的范围扩展到加工链的下一步：主动选择视觉信息以进行进一步处理(维护)。该项目将视觉视觉记忆编码的两个中央注意机制联系起来：优先图和焦点空间注意。优先级地图是视觉场景的空间表示，它从对象的特定特征中抽象出来，并在每个位置提供单个优先级值，反映了自下而上的显著程度、自上而下的目标和以前的经验(任务历史)的组合。在WP1中检验的主要假设是优先级映射决定编码成VWM的质量。这将通过优先图的两个贡献者的(实验性)变化来检验，这两个因素在VWM研究中迄今基本上被忽视，即对象的显着性(WP1a)和任务历史(WP1b)。WP2将通过将一个物体升级到特殊状态来检查焦点空间注意是否有助于VWM编码。这一特殊状态一直是激烈的争论和广泛的实证研究的主题，但目前尚不清楚是什么使一个对象在没有明确提示的情况下进入这种状态，以及处于特殊状态的对象在多大程度上与拥有最高优先级有质的不同。利用各种已验证的模型中的元素，将开发一个新的VWM编码计算模型，以相当详细地解释预期的复杂数据模式，并对涉及的认知机制进行原则性的理解。此外，先前被验证用于视觉搜索的注意分配的电生理标记将被用于理解影响VWM编码的注意动力学，并将被集成到模型中。总而言之，本项目将研究各种主动知觉机制是否以及如何影响注意选择以外的物体处理。

Experience with the environment influences conscious perception by biasing the selection of information. Most conscious processing of visual information goes via a system called visual working memory (VWM). VWM is severely limited in its capacity so that only a tiny fraction of the information available in the environment is encoded and represented at a time. Furthermore, even among those objects that made it into VWM, representational quality varies considerably. The reasons for this inter-item variability remain largely unknown. I suggest that a huge share of this variability emerges during encoding: instead of passively absorbing all relevant information until VWM capacity is exhausted, VWM encoding might be characterized by an active interaction between the visual scene (e.g., different saliencies of the objects) and the observer (e.g., experience with the environment: predictive coding). By examining this idea, the project aims to close a crucial gap in the VWM literature and to extend the scope of the research unit to the next step in the processing chain: active selection of visual information for further processing (maintenance).The project relates two central attentional mechanisms to VWM encoding: priority maps and focal spatial attention. A priority map is a spatial representation of the visual scene that abstracts from specific features of objects and instead provides a single priority value at each location, reflecting a combination of bottom-up saliency, top-down goals, and previous experiences (task history). The main hypothesis tested in WP1 is that the priority map determines the quality of encoding into VWM. This will be examined via (experimental) variations in the two contributors to the priority map that were so far largely neglected in VWM research, namely the objects’ saliencies (WP1a) and task history (WP1b). WP2 will examine whether focal spatial attention contributes to VWM encoding by upgrading one object into a special state. This special state has been the subject of vigorous debates and extensive empirical investigation, but it is as yet unknown what brings an object into that state if it is not explicitly cued and in how far being in the special state is qualitatively different from having the highest priority.Using elements from various validated models, a new computational model of VWM encoding will be developed to explain the expected complex data patterns in considerable detail and to gain a principled understanding of the cognitive mechanisms involved. Furthermore, electrophysiological markers of attention allocations that were previously validated for visual search will be used to understand the attentional dynamics that influence VWM encoding and will also be integrated into the model. In sum, the present project will examine whether and how various mechanisms of active perception affect object processing beyond attentional selection.