For more information contact Luis Rocha at rocha@lanl.gov
Last Modified: August 7, 2000
Complex systems in general display universal properties that do not depend on the details of the specific manifestation. This fact provides a theoretical basis for being able to study properties in one specific representative of one class of complex systems and extract some generic results that will also transfer and generalize to different members of the same class. Heuristically this has led to the widely used strategy of working with analogies and metaphors. The challenge is to discriminate between true universal properties and mere peculiarities of a system.
Here we discuss some features of brains that we expect to be universal with the expectation that they can be helpful to make quantitative predictions about emergent structures that can be observed on the Internet as a global, self-organized, complex system. Specifically we want to focus on some time-scales that are associated with the formation of the equivalent of cell assemblies. These can take on different ranges similar for instance to some of the characteristic EEG frequency bands in the human brain.
Furthermore we are going to discuss the question of dynamical changes of system parameters that are traditionally assumed constant in simple Hebbian models of learning. For biological brains it has been observed, that the change in synaptic strength (related to the learning rate) is by no means constant but can change not only its absolute magnitude but even its sign. For biological brains this equivalent to unlearning and has been associated with dreaming, a state that seems to be an important feature not only of human brains. One can ask if this general behavioral state might also have an analogue that can be of value for information reorganization on the Internet.