BRAIN CIRCUITS 1)5)
C. KOCH and G. LAURENT write: "Brain circuits are not Boolean networks, where connectivity is everything. They are not made of static, linear neurons, isotropic nets, or constant connection weights…. A more realistic accounting of the dynamic nature of neuronal ensembles and their nonrandom, inhomogeneous connectivity topologies has been incorporated by TONONI and his colleagues into a formal definition of "neuronal complexity" using concepts drawn from information theory. These concepts express the degree of interactions between elements of a neuronal population… Complexity will be high if a large number of subassemblies of varied sizes can be formed within the population" (1999, p.97).
Further on they add: "The standard von NEUMANN computer architecture enforces a strict separation between memory and computation. Software and hardware, which can be easily separated in a computer, are completely interwoven in brains… Furthermore, brains wire themselves up during development as well as during adult life, by modifying, updating, replacing connections, and even in some circuits by generating new neurons. While brains do indeed perform something akin to information processing, they differ profoundly from any existing computer in the scale of their intrinsic structural and dynamic complexity" (Ibid, p.98)
As stated by the authors, much work will still be needed to reach a better understanding of brain circuits.
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Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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