2 research outputs found
Collective Intelligence and Neurodynamics: Functional Homologies
A deep understanding of the dynamics of the human nervous system requires the
simultaneous study of multiple spatiotemporal scales from the level of
neurotransmitters up to the level of human cultures. This is likely impossible
for technical and ethical reasons. Piecemeal analysis provides some
understanding of the dynamics at single levels, but this does not illuminate
the interactions between levels which are, at the very least, of great
importance clinically. It would be useful to have an accessible biological
system which could serve as a proxy for the nervous system and from which
useful insights might be obtained. Functional homologies between the nervous
system and collective intelligence systems, in particular social insect
colonies, are described. It is proposed that social insects colonies could
serve as functional proxies for nervous systems. Thus a multiscale study of
social insect colonies may provide insights into the dynamics of nervous
systems
Transients as the Basis for Information Flow in Complex Adaptive Systems
Information is the fundamental currency of naturally occurring complex adaptive systems, whether they are individual organisms or collective social insect colonies. Information appears to be more important than energy in determining the behavior of these systems. However, it is not the quantity of information but rather its salience or meaning which is significant. Salience is not, in general, associated with instantaneous events but rather with spatio-temporal transients of events. This requires a shift in theoretical focus from instantaneous states towards spatio-temporal transients as the proper object for studying information flow in naturally occurring complex adaptive systems. A primitive form of salience appears in simple complex systems models in the form of transient induced global response synchronization (TIGoRS). Sparse random samplings of spatio-temporal transients may induce stable collective responses from the system, establishing a stimulus⁻response relationship between the system and its environment, with the system parsing its environment into salient and non-salient stimuli. In the presence of TIGoRS, an embedded complex dynamical system becomes a primitive automaton, modeled as a Sulis machine