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Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement recording systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The storage and reactivation of perceptual symbols operates at the level of perceptual components--not at the level of holistic perceptual experiences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a common frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and abstract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinatorially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

二十世纪以前，知识理论本质上均基于知觉框架。自此之后，逻辑学、统计学与编程语言领域的发展催生了非模态理论（amodal theories），这类理论所依托的核心原则与知觉理论的底层原则截然不同。此外，知觉研究进路被广泛认为站不住脚，因为其被视作仅能实现记录系统，而非概念系统。本文结合当代认知科学与神经科学的研究背景，提出一种知识的知觉理论。在知觉体验过程中，大脑的联合皮层区会捕获感觉运动脑区产生的自下而上的激活模式。随后，联合皮层区会以自上而下的方式部分激活感觉运动脑区，以此实现知觉符号的运作。知觉符号的存储与复现，运作于知觉组分层面，而非整体知觉体验层面。借助选择性注意，研究者可从体验中提取知觉组分的结构化表征并存储于记忆之中（例如对绿色、呼噜声、温热的单独记忆）。当针对同一知觉组分的记忆围绕共同框架组织起来后，便会形成模拟机制（simulator），该机制可对该组分生成无限多的模拟结果（例如对呼噜声的模拟）。此类模拟机制不仅可针对感官体验的各个方面形成，也可应用于本体感受（proprioception，例如抬举、奔跑）与内省（introspection，例如比较、记忆、愉悦、饥饿）的相关维度。一旦形成，这些模拟机制便会构建出一套基础概念系统，该系统可表征范畴、支持分类任务并生成范畴化推理。此类模拟机制还可支持生成性（productivity）、命题表征（propositions）与抽象概念（abstract concepts）的运作，由此构建出一套功能完备的概念系统。生成性源于对模拟机制进行组合式与递归式整合，以此生成复杂的模拟结果。命题表征则源于将模拟机制与被知觉到的个体进行绑定，以此表征类型-殊型关系（type-token relations）。抽象概念则扎根于对物理事件与内省事件的复合复杂模拟之中。由此可见，知识的知觉理论可构建出功能完备的概念系统，同时规避非模态符号系统（amodal symbol systems）所引发的各类问题。本文还探讨了该理论对认知科学、神经科学、进化论、发展心理学以及人工智能领域的启示。