DISTRIBUTED INTELLIGENT PROCESSING SYSTEM
The brain is assumed as a Distributed Intelligent Processing System (DIPS)
composed of agents having some specialization in solving defined problems,
such that reasoning becomes a cooperative activity among as much as possible
decentralized and loosely coupled collection of these agents that may provide
the solution of a given problem. DIPS’ intelligence emerges as a function
of how versatile are the relations shared by these agents; of how plastic
may be the commitments for actions among them, and of agent specialization.
The complexity of agent enrollment (h(c)) in solving a task is proposed to
be quantified by the entropy of the available communication resources minus
the entropy of the communication resources actually used to solve the task.
The linear correlation coefficient calculated for the task event related activity
was as taken as a measurement of the possibility of information exchange among
neurons from different cortical areas, and it was used to calculated h(c).
The calculated h(c) values for the EEG activity recorded by each 10/20 system
electrode while the individual is solving a cognitive task are collor encoded
to produce the corresponding Cognitive Brain Mapping (CBM). CBMs are different
for different cognitive tasks and also varied with the different experimental.
The calculated h(c) values for different cognitive tasks correlate with individual
IQ measured by means of standard tests. Also, response times and error rates
were found to be correlated with h(c).