Wednesday, February 11, 2015

Thinking in Loops: Basic Building Blocks of Causal Loop Networks in the 5-Node-Model

The study of neural networks’ dynamic properties that in part show chaotic behavior focuses on two major areas. Cognitive sciences try to understand the mental system acting as a whole, which can be investigated by understanding the brain from a holist point of view. Neuroscience, on the other hand, attempts to analyze specialized circuits that can be modeled as causal loop networks. These circuits may in part be mapped out by sophisticated investigation of the electric and physiologic activity in the brain, taking on a reductionist perspective. However, their dynamics does not build on sequences of cause and effect. They show emergent eigen-behavior. To work with recurrent systems (organizations, brains, societies, groups, cultures, etc.), it is important to understand both causal loop dynamics between individual nodes that produce emergent behavior and subjective experience of individual nodes within a network that cannot be seen from outside. This article discusses an ancient model that can be used to investigate and characterize closed-loop systems, shifting back and forth between holistic and individualistic perspectives to promote integrative thinking.

Stoll, J. D. (2015). Thinking in Loops: Basic Building Blocks of Causal Loop Networks in the 5-Node-Model (PDF)