Grounding Symbolic Operations in the Brain's Modal Systems

Abstract

A central theme of modern cognitive science is that symbolic interpretation underlies human intelligence. The human brain does not simply register images, as do cameras or other recording devices. A collection of images or recordings does not make a system intelligent. Instead, symbolic interpretation of image content is essential for intelligent activity. What cognitive operations underlie symbolic interpretation? Across decades of analysis, a consistent set of symbolic operations has arisen repeatedly in logic and knowledge engineering: binding types to tokens; binding arguments to values; drawing inductive inferences from category knowledge; predicating properties and relations of individuals; combining symbols to form complex symbolic expressions; representing abstract concepts that interpret metacognitive states. It is difficult to imagine performing intelligent computation without these operations. For this reason, many theorists have argued that symbolic operations are central, not only to artificial intelligence but to human intelligence (e.g., Fodor, 1975; Pylyshyn, 1973). Symbolic operations provide an intelligent system with considerable power for interpreting its experience. Using type-token binding, an intelligent system can place individual components of an image into familiar categories (e.g., categorizing components of an image as people and cars). Operations on these categories then provide rich inferential knowledge that allows the perceiver to predict how categorized individuals will behave, and to select effective actions that can be taken (e.g., a perceived person may talk, cars can be driven).

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