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

对环境的体验通过对信息选择的偏向影响有意识的感知。大多数视觉信息的有意识处理是通过一个叫做视觉工作记忆（VWM）的系统进行的。VWM的能力受到严重限制，因此一次只能对环境中可用的一小部分信息进行编码和表示。此外，即使在那些进入VWM的对象中，表现质量也存在很大差异。造成这种项目间差异的原因在很大程度上仍然未知。我认为这种可变性的很大一部分出现在编码过程中：而不是被动地吸收所有相关信息，直到VWM容量耗尽，VWM编码可能以视觉场景（例如，物体的不同显著性）和观察者（例如，与环境的经验：预测编码）之间的主动交互为特征。通过研究这一想法，该项目旨在填补VWM文献中的一个关键空白，并将研究单元的范围扩展到处理链的下一个步骤：为进一步处理（维护）主动选择视觉信息。该项目将两个中心注意机制与VWM编码联系起来：优先图和焦点空间注意。优先级图是从对象的特定特征中抽象出来的视觉场景的空间表示，而是在每个位置提供一个单一的优先级值，反映自下而上的显著性、自上而下的目标和以前的经验（任务历史）的组合。在WP1中测试的主要假设是优先映射决定了编码到VWM的质量。这将通过优先级图的两个贡献者的（实验）变化来检验，这些变化在VWM研究中迄今在很大程度上被忽视，即对象的显著性（WP1a）和任务历史（WP1b）。WP2将研究焦点空间注意是否通过将一个物体升级到特殊状态来促进VWM编码。这种特殊状态一直是激烈辩论和广泛实证研究的主题，但目前尚不清楚，如果没有明确的暗示，是什么使一个对象进入这种状态，以及处于这种特殊状态与具有最高优先级在本质上有多大不同。使用来自各种验证模型的元素，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，并获得对所涉及的认知机制的原则性理解。此外，先前在视觉搜索中验证的注意分配的电生理标记将用于理解影响VWM编码的注意动力学，并将被整合到模型中。总之，本项目将研究主动感知的各种机制是否以及如何影响注意选择以外的对象加工。

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.