Perceptual Representations in Conceptual Tasks

提出的工作的目的是确定知觉表征是否显著进入概念加工。受试者将执行传统上用命题性、非感性知识理论解释的概念性任务，例如，特征列表（椅子的特征通常是正确的）和属性验证（例如，椅子有座位吗）。有趣的是，受试者是否在这些任务中使用感知表征，即使任务上下文并不要求或要求他们这样做。知觉表征的使用将通过两种方式检测：教学对等和知觉工作。当没有接受意象指导的受试者（“中性受试者”）与明确要求使用意象的受试者（“意象受试者”）表现相似时，就会出现教学对等。当中性主体和意象主体的表现都受到知觉变量的影响时，就会发生知觉工作。特征列表和属性验证的初步实验为教学等值和知觉工作提供了强有力的证据，表明中性受试者使用知觉表征。进一步的研究将复制和扩展这些发现。对于特征列表，各种实验研究了知觉表征在概念组合、事件概念、抽象概念、手势和生产模式中的作用。对于属性验证，各种实验使用干扰物相关性，准备时间，部分期望和视角来检查感知表征的作用。在另一个关于特定模式干扰的项目中，几个实验测试了概念知识的感知表征应该产生特定模式的注意干扰的预测。如果这些项目提供证据表明知觉表征在概念处理中起着核心作用，认知和智力理论将需要重大的重新制定。大多数现有的理论认为，智能行为反映了一种抽象的、模态的、任意的思维语言的处理过程，就像电子计算中广泛使用的符号计算机语言一样。根据现有的理论，知觉经验被转导成一组概念符号，这些符号与它们的指称来源没有知觉相似性。另一种较少探索的观点是，概念符号是感知状态的片段，通过选择性注意直接从这些状态中提取出来。由此产生的概念表征不是静态的整体“头脑中的图像”，而是感性符号的系统，它们富有成效地结合在一起，产生无限的概念结构。此外，这些感知符号是分析性的、示意性的、多模态的和动态的，提供了一个丰富的表达系统来表示各种各样的概念，而不仅仅是那些具体对象。直观上，这种感知符号系统比传统的非模拟计算更像现代多媒体计算。不断有证据表明人类存在感知符号系统，这对理解和应用智能以及大脑运作理论和人工智能愿景具有重要意义。与其将智能视为对任意模态符号的操纵，不如将其视为产生于感知符号的生产系统。

The aim of the proposed work is to determine whether perceptual representations enter significantly into conceptual processing. Subjects will perform conceptual tasks that have traditionally been explained with propositional, non-perceptual theories of knowledge, e.g., feature listing (what features are typically true of a chair) and property verification (e.g., does a chair have a seat). Of interest will be whether subjects use perceptual representations in these tasks, even though the task contexts do not require or demand that they do. The use of perceptual representations will be detected in two ways: instructional equivalence and perceptual work. Instructional equivalence occurs when subjects who receive no imagery instructions (`neutral subjects`) perform similarly to subjects explicitly asked to use imagery (`imagery subjects`). Perceptual work occurs when performance of both neutral and imagery subjects is affected by perceptual variables. Initial experiments on feature listing and property verification provide strong evidence for both instructional equivalence and perceptual work, indicating that neutral subjects use perceptual representations. Further studies will replicate and extend these findings. For feature listing, various experiments examine the roles of perceptual representations in conceptual combination, event concepts, abstract concepts, gesture, and production modes. For property verification, various experiments use distractor relatedness, preparation time, part expectancy, and perspective to examine the role of perceptual representations. In an additional project on modality-specific interference, several experiments test the prediction that perceptual representations of conceptual knowledge should produce specific patterns of attentional interference. Should these projects provide evidence that perceptual representations play central roles in conceptual processing, theories of cognition and intelligence would require significant reformulation. Most existing theories assume that intelligent behavior reflects the processing of an abstract, amodal, and arbitrary language of thought, much like the symbolic computer languages used widely in electronic computation. According to existing theories, perceptual experience is transduced into a set of conceptual symbols that bear no perceptual resemblance to their referential origins. An alternative, and much less explored view, is that conceptual symbols are fragments of perceptual states, extracted directly from these states via selective attention. The resulting conceptual representations are not static holistic 'pictures in the head,' but instead are systems of perceptual symbols that combine productively to produce infinite conceptual structures. Additionally, these perceptual symbols are analytic, schematic, multimodal, and dynamic, offering a rich expressive system for representing a wide variety of concepts, not just those for concrete objects. Intuitively, such perceptual symbol systems resemble modern multimedia computing much more than traditional non-analogue computing. Evidence continuing to indicate the presence of a perceptual symbolic system in humans, has strong implications for understanding and applying intelligence as well as theories of the brain's operation and visions of artificial intelligence. Rather than viewing intelligence as the manipulation of arbitrary amodal symbols, it would come to be viewed as arising from a productive system of perceptual symbols.