Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, 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 record- ing 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 stor- age and reactivation of perceptual symbols operates at the level of perceptual components - not at the level of holistic perceptual expe- riences. 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 com- mon 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 introspec- tion (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 ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially 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 per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.

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Perceptual symbol systems.

The environments in which we live and the tasks we must perform to survive and reproduce have shaped the design of our perceptual systems through evolution and experience. Therefore, direct measurement of the statistical regularities in natural environments (scenes) has great potential value for advancing our understanding of visual perception. This review begins with a general discussion of the natural scene statistics approach, of the different kinds of statistics that can be measured, and of some existing measurement techniques. This is followed by a summary of the natural scene statistics measured over the past 20 years. Finally, there is a summary of the hypotheses, models, and experiments that have emerged from the analysis of natural scene statistics.

Visual Perception and the Statistical Properties of Natural Scenes

There are few constructs that are as ubiquitous across traditions of management and organizational research, and indeed the social sciences more generally, as that of frame or framing. The widespread popularity and use of the concept has led to rich streams of research, ranging from work in managerial cognition and decision-making to strategic and organizational change, and social movements and institutions. At the same time, the popularity of framing across these literatures has perhaps also come at a price. Indeed, it has meant that these streams of research have essentially developed along separate paths, despite the prospect and promise of a greater connection between them. In this paper, our general aim is to consolidate and advance the current body of research on framing in the management and organizational literature. We do this by providing an extensive review of the key research traditions on framing across this literature, noting the salient contributions to date and highlighting potenti...

Putting Framing in Perspective: A Review of Framing and Frame Analysis across the Management and Organizational Literature

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.

Perceptions of perceptual symbols

http://barsaloulab.org/Online_Articles/1998-Goldstone_Barsalou-Cognition-reuniting_cognition_perception.pdf

Reuniting perception and conception.

Components of conceptual representation. From feature lists to recursive frames

Explanations have become increasingly recognized as central to learning and intelligence. To explore the content and construction of human explanations, detailed protocol analyses were performed on the explanations that subjects produced while learning about a fictional system. During the system learning phase of the experiment, subjects received a series of diagrams for a system and then explained how it worked. During the troubleshooting phase, in the absence of the diagrams, subjects explained relations between problematic symptoms and their faults. To examine the evolution of explanations with learning, subjects explained the same system diagrams and the same symptom-fault relations multiple times. Explanations varied considerably between system learning and troubleshooting, indicating that different goals produced different explanations. During system learning, subjects focused almost exclusively on functional explanations, exhibiting no trend toward deeper mechanistic explanations over time. To construct these functional understandings, subjects primarily instantiated existing knowledge in memory, specializing it to explain the purposes of individual components. During troubleshooting, subjects still focused on function but included a much wider variety of functional information in their explanations as well as higher proportions of topographical and mechanistic information. Rather than focusing on individual components, subjects focused on qualitative relations between components as they

http://barsaloulab.org/Online_Articles/1995-Hale_Barsalou-JLS-explanation_content_construction.pdf

Explanation Content and Construction During System Learning and Troubleshooting

The Training Analytics Support (TAS) framework encompasses a theory and associated analysis stages intended to facilitate training design. Through execution of these stages, the TAS framework will allow training developers to define portfolios tailored to the needs of each trainee, track trainee mastery status across careers, and dynamically adjust portfolios to target ongoing training to specific areas in need of remediation. This document summarizes the six stages of training analytics within the TAS framework and briefly describes the manual and automated methods used to instantiate each stage.

Christopher R. Hale

Papers

Components of conceptual representation. From feature lists to recursive frames

Explanation Content and Construction During System Learning and Troubleshooting

A training analytics support framework for operational training design