Prior to the twentieth century, theories of knowledge were inherently perce
ptual. Since then, developments in logic, statistics, and programming langu
ages have inspired amodal theories that rest on principles fundamentally di
fferent from those underlying perception. In addition, perceptual approache
s have become widely viewed as untenable because they are assumed to implem
ent recording systems, not conceptual systems. A perceptual theory of knowl
edge is developed here in the context of current cognitive science and neur
oscience. During perceptual experience, association areas in the brain capt
ure bottom-up patterns of activation in sensory-motor areas. Later, in a to
p-down manner, association areas partially reactivate sensory-motor areas t
o implement perceptual symbols. The storage and reactivation of perceptual
symbols operates at the level of perceptual components - not at the level o
f holistic perceptual experiences. Through the use of selective attention,
schematic representations of perceptual components are extracted from exper
ience 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 compo
nent (e.g., simulations of purr). Not only do such simulators develop for a
spects of sensory experience, they also develop for aspects of propriocepti
on (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungr
y). Once established, these simulators implement a basic conceptual system
that represents types, supports categorization, and produces categorical in
ferences. These simulators further support productivity, propositions, and
abstract concepts, thereby implementing a fully functional conceptual syste
m. Productivity results from integrating simulators combinatorially and rec
ursively to produce complex simulations. Propositions result from binding s
imulators to perceived individuals to represent type-token relations. Abstr
act concepts are grounded in complex simulations of combined physical and i
ntrospective events. Thus, a perceptual theory of knowledge can implement a
fully functional conceptual system while avoiding problems associated with
amodal symbol systems. Implications far cognition, neuroscience, evolution
, development, and artificial intelligence are explored.