Information Technology Reference
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identical, in the dynamics of the brain function we can find constant relations be-
tween “practical attractors” which are relatively stable set neurophysiologic states
that can be identified in brain behaviour. What is more, dynamic brain states, if
they are properly handled mathematically, are characterised by certain deeper rela-
tions which may have a simple logical representation.
The correspondence between the mental states and forms of brain activity does
not concern only surface states which are of an ephemeral (transitory and short-
lasting) character, but also attractor states which exhibit some stability. However,
internal representations, which according to model research must be more stable,
do not translate into similarly stable surface representations, which makes their
empirical study difficult.
In addition, small disturbances in the electro-chemical structure of the brain
cause significant changes at the mental phenomenon level, e.g. bring about mental
illnesses. These are frequently the consequence of the global brain dynamics, de-
pendent on the condition of all its structures, and in most cases no single, well de-
fined anatomical structure responsible for the specific form of psychopathology
can be pinpointed. In the brain, a holistic principle can generally be observed
which consists in all structures contributing to a greater or smaller extent to all
functions. This leads,
inter alia,
to a fact, known for many years, that the brain has
no areas in the anatomic sense which are interconnected so weakly that they could
be eliminated (e.g. excised) without changing its function, although sometimes
those changes may be difficult to detect.
This justifies the claim by John R. Searl [126], that although the neurophysiol-
ogy of the brain does determine the character of the mind, this does not mean that
intelligence or some form of a mind could not be created by the interaction of
elements based on silicone or other, non-carbon compounds. The development of
computer science, and in particular artificial intelligence, has proven that intelli-
gent information processing is also possible using silicone, and the neurochemical
states determining human mental impressions can, in turn, be approximated with a
satisfactory precision using digital devices. However, such 'minds' have a struc-
ture different from that of human minds, which means that the 'way in which they
experience the world' is different because different brain structures must bring
about different minds. So the basic features that a given system should exhibit so
that its aspects can be equated to that of a mind include intentionality, understand-
ing and conscience. At the first glance, these features seem to describe strictly bio-
logical systems, but the evolution in the behaviour of robots and IT systems has
made them of interest to technology as well. We now have many examples of sys-
tems controlled by software that features 'brain-like' methods of information
processing. Another feature of these systems is that only their general properties
are programmable, which allows them to be considered as moving towards inten-
tionality. We currently observe the appearance of a number of technical solutions
featuring an increasing autonomy of operation and it seems that the convergence
limit of this series of better and better models may be intentional systems with in-
creasingly complex structures and purposes of operation.
