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These are excerpts and elaborations from my book "The Nature of Consciousness"
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The Road from Neurons to
Symbols
Computational models of
neural networks have greatly helped in understanding how a structure like the
brain can perform. Computational models of cognition have improved our
understanding of how cognitive faculties work. But neither group has developed
a theory of how neural processes lead to symbolic processes, of how
electro-chemical reactions lead to reasoning and thought. A bridge is missing between
the physical, electro-chemical, neural processes and the macroscopic mind
processes of reasoning, thinking, knowing, etc., in general, the whole world of
symbols. A bridge is missing between
the neuron and the symbol. Several philosophers have tried to fill the
gap. The "harmony"
theory proposed by the US computer scientist Paul Smolensky is an effort in
this direction. Smolensky worked out a
theory of dynamic systems that perform cognitive tasks at a subsymbolic
level. The task of a perceptual system
can be viewed as the completion of the partial description of static states of
an environment. Knowledge is encoded as
constraints among a set of perceptual features. The constraints and features evolve gradually with
experience. Schemata are collections of
knowledge atoms that become active in order to maximize what he calls
"harmony". The cognitive system is, de facto, an engine for
activating coherent assemblies of atoms and drawing inferences that are
consistent with the knowledge represented by the activated atoms. A harmony function measures the
self-consistency of a possible state of the cognitive system. Such harmony
function obeys a law that resembles simulated annealing (just like the
Boltzmann machine): the best completion is found by lowering the temperature
to zero. The US philosopher Patricia
Churchland aims at a unified theory of cognition and neurobiology, of the
computational theory of the mind and the computational theory of the
brain. According to her program, the
symbols of Fodor's mentalese should be
somehow related to neurons, and abstract laws for cognitive processes should be
reduced to physical laws for neural processes.
Nonetheless, the final
connection, the one between the connectionist model of the brain and the
symbol-processing model of the mind, is still missing. Back to the beginning of the chapter "Connectionism and Neural Machines" | Back to the index of all chapters |
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