<a href="http:&#x2F;&#x2F;www.psychology.emory.edu&#x2F;cognition&#x2F;barsalou&#x2F;papers&#x2F;Barsalou_BBS_1999_perceptual_symbol_systems.pdf" rel="nofollow">http:&#x2F;&#x2F;www.psychology.emory.edu&#x2F;cognition&#x2F;barsalou&#x2F;papers&#x2F;Ba...</a><p>&quot;Abstract: 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&quot;