Testing the role of learned regularities in visual working memory: The nature of chunking for continuous visual features

工作记忆允许人们在短时间内记住信息，并利用这些信息进行工作。例如，在做数学题时，工作记忆是用来记住数字并操纵它们的；在开车时，工作记忆被用来在你检查换车道是否安全时记住其他车辆的位置。工作记忆的容量非常有限，因此在任何给定的时间内只能准确地记住少数几个项目，而这种有限的容量对人们执行许多认知任务的能力构成了强烈的限制。工作记忆容量的一个众所周知的方面是它受学习的影响：将经常遇到的信息“分块”成压缩的、有意义的单元，可以更有效地表示，并允许我们在工作记忆中存储更多的信息。例如，记住一串随机的7个数字比记住我们自己的电话号码需要更多的认知能力。目前的研究调查了学习如何增加我们可以通过分块处理的信息量的认知和神经基础，以及“分块”的内容在多大程度上被主动存储在工作记忆中，而不是在我们学习后被卸载到长期记忆中。重要的是，一个人在工作记忆中能够记住的信息量已经被证明与许多其他认知能力（包括智力）有关，工作记忆的中断在临床疾病中很常见，比如注意力缺陷多动障碍和精神分裂症。因此，关于如何存储和使用这些信息的新知识对于理解个体之间重要差异的本质以及这些差异如何受到学习的影响至关重要。此外，在许多现实情况下，同时保持许多物体或事件的细节，以便实时做出明智的决定（例如，在驾驶时改变车道）是至关重要的。这项研究将告诉我们在这种情况下学习是如何影响工作记忆容量的。除了这项分块工作，该提案还包括开发工具，使科学家能够测量记忆表现，并在更广泛的个体中这样做（例如，通过基于互联网的实验），以及一个扩展组件，以培训和招募代表性不足的群体的学生为特色。该研究使用工作记忆的行为和电生理测量来测试特定项目的详细信息在块学习中的作用。拟议的研究旨在区分两种可能的理论解释，即块如何在工作记忆中实例化，一种基于无内容指针，另一种基于对象及其特征的分层存储。一系列的行为实验询问人们对物体视觉特征的表征是如何受到学习的影响的，特别是学习的规律在多大程度上导致人们在工作记忆中失去对视觉物体细节的访问。在这些行为实验之后，使用脑电图（EEG）进行重复和扩展，分析与事件相关的电位，对侧延迟活动，这提供了工作记忆中信息量的衡量标准。行为学和电生理测量共同揭示了学习和分块处理如何影响我们在工作记忆中记住信息的能力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Working memory allows people to hold information in mind over a short period of time, and to work with this information. For example, while doing a math problem, working memory is used to hold in mind the numbers and manipulate them; and while driving, working memory is used to hold in mind the locations of other cars as you check whether it is safe to change lanes. Working memory has a severely limited capacity, such that only a few items can be accurately held in mind at any given time, and this limited capacity provides a strong constraint on people’s ability to perform many cognitive tasks. One well-known aspect of working memory capacity is that it is affected by learning: “chunking” frequently encountered information into compressed, meaningful units allows more efficient representations, and allows us to store more in working memory. For example, remembering a random string of 7 numbers is much more cognitively demanding than remembering our own phone number. The current research investigates the cognitive and neural basis of how learning increases the amount of information that we can process via chunking, and the extent to which the contents of “chunks” are actively stored in working memory vs. off-loaded into long-term memory after we have learned them. Importantly, the amount of information a person is able to hold in mind in working memory has been shown to be related to many other cognitive abilities (including intelligence), and disruptions of working memory are common in clinical disorders like attention deficit hyperactivity disorder and schizophrenia. Therefore, new knowledge regarding how this information is stored and used is critical for understanding the nature of important differences between individuals and how such differences may be impacted by learning. In addition, in many real-world situations it is vital to maintain detail about many objects or events at once, to make informed decisions in real time (e.g., changing lanes while driving). This research will inform how learning affects working memory capacity in such situations. In addition to this work on chunking, the proposal also includes the development of tools to allow scientists to measure memory performance and to do so in a wider variety of individuals (i.e., via internet-based experiments), as well as an outreach component, featuring the training and recruitment of students from underrepresented groups.The research uses behavioral and electrophysiological measures of working memory to test the role of item-specific, detailed information in chunk learning. The proposed studies are meant to distinguish between two potential theoretical explanations for how chunks are instantiated in working memory, one based on content-free pointers and the other based on hierarchical storage of objects and their features. A sequence of behavioral experiments asks how people’s representation of the visual features of objects is affected by learning, and in particular the extent to which learned regularities cause people to lose access to the details of visual objects in working memory. These behavioral experiments are followed by replications and extensions using electroencephalography (EEG), which will be analyzed to look at an event-related potential, the contralateral delay activity, which provides a measure of the amount of information held in working memory. Together, the behavioral and electrophysiological measures inform how learning and chunking affect our capacity to hold information in mind in working memory.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.