Visual search following explicit or implicit category rule training

视觉搜索性能差影响了许多视力障碍者的生活质量，视野 视力下降(中心凹或周边)和其他低视力问题。搜索涉及多个潜在的神经过程 包括对刺激的注意和随后的分类的指导，这必然依赖于 周边视力和中心凹视力。我们的中心假设是中央和中央之间的差异 周边视觉将导致分类搜索指导(定向)之间的系统性分离 注意)和分类。近年来，搜索文献开始探索分类搜索， 然而，这项工作仍处于初级阶段。通过将搜索和分类文献联系起来，我们可以开始 描述基本类别表示如何影响搜索性能。 一种著名的分类理论，称为Covis(言语系统和隐含系统之间的竞争) 假设外显的(可用言语表述的)类别规则学习是由前额叶皮质调节的，而内隐的 (非言语的)规则学习是由与联想学习相关的皮层下结构介导的。多数 分类搜索历史上使用了自然类别，这可能会使两个系统都有不同的 学位。我们将使用分类文献中常见的简单知觉刺激来分离范畴 搜索绩效受显性系统和隐性系统的调节。此外，我们还将描述决策 基本费率和收益等对分类搜索性能的影响。这项针对健康青年的研究 控制是开发新的途径来训练患有低视力、视觉障碍的人的必要的第一步。 视野丧失(即中央或外周视力丧失)和有各种视觉认知缺陷的人。例如, 用明确的可用语言表述的规则来培训人员(在适当的时候，例如指出特定的特征 在周边视觉中容易被注意)，可以导致更容易和更快的视觉搜索训练。然而，很多 日常生活中的分类很可能是通过内隐(非语言)方式学习的，因此基于表现 反馈训练和通过反复暴露逐步联想学习可以提高搜索和 分类结果。 在拟议的实验中，参与者将进行内隐或外显类别规则学习，然后 将监控眼球运动的搜索。眼球运动使我们能够区分 将空间注意力引导到搜索目标(指导)和分类过程的能力发生了变化。通过 研究大脑中独立的学习系统对确定类别成员资格的贡献， 分类可变性的影响，以及决策的影响(基本利率和收益)，我们将系统地 描述导致显式和隐式分类搜索效率低下的原因。

Poor visual search performance affects the quality of life for many people with vision impairments, visual field loss (foveal or peripheral) and other low vision issues. Search involves multiple underlying neural processes including the guidance of attention to and subsequent categorization of stimuli, which necessarily rely on peripheral and foveal vision respectively. Our central hypothesis is that differences between central and peripheral vision will result in systematic disassociations between categorical search guidance (directing attention) and categorization. In recent years, the search literature has begun to explore categorical search, however, this work is still in its infancy. By bridging the search and categorization literatures, we can begin to characterize how the underlying category representation affects search performance. A prominent categorization theory, called COVIS (for COmpetition between Verbal and Implicit Systems) posits that explicit (verbalizable) category rule learning is mediated by the prefrontal cortex, while implicit (nonverbalizable) rule learning is mediated by subcortical structures related to associative learning. Most categorical search has historically utilized natural categories, which likely engage both systems to varying degrees. We will utilize simple perceptual stimuli common to the categorization literature to isolate categorical search performance mediated by explicit and implicit systems. In addition, we will also characterize decisional influences like base-rates and payoffs on categorical search performance. This research in healthy young controls is a necessary first step to develop new avenues to train individuals suffering from low vision, visual field loss (i.e. central or peripheral vision loss) and those with various visual cognitive deficits. For example, training people with an explicit verbalizable rule (when appropriate, such as pointing out specific features that are easily attended in peripheral vision), may result in easier and faster visual search training. However, much of the classification in daily life is likely learned via implicit (nonverbal) means and thus performance based feedback training and gradual associative learning through repeated exposure may improve search and classification outcomes. In the proposed experiments, participants will perform implicit or explicit category rule learning followed by search in which eye movements will be monitored. The eye movements allow us to distinguish between changes in the ability to direct spatial attention to search targets (guidance) and categorization processes. By examining the contribution of separate learning systems in the brain to determine category membership, the effects of categorical variability, and decisional influences (base-rates and payoffs), we will systematically characterize what makes explicit and implicit categorical search inefficient.