BRAIN CIRCUITS
| Collection | International Encyclopedia of Systems and Cybernetics |
|---|---|
| Year | 2004 |
| Vol. (num.) | 2(1) |
| ID | ◀ 329 ▶ |
| Object type | Discipline oriented, General information |
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.
See also
Synaptic weights