A very interesting paper by Kitano “Biological Robustness” (published in 2004 in Nature Genetics journal) offers a very insightful summary on what biological robustness is and how it emerges in networks. Kitano demonstrates how small-world architecture and the existence of an interconnected core control center both increase the robustness of a system.
A very interesting paper by Fontanini & Katz (2008) published in Neurophysiology journal proposes a model that shows how similar sensory stimuli can elicit different responses in the same organism.
Polysingularity is a condition where multiple solutions are possible and yet only some are actualized at any moment of time. It’s a study of how affordances (or environmental opportunities) come into contact with the human capacity to believe and make choices. Polysingularity is best described through the framework of networks where the node’s current state and future condition is dynamically determined by its specificity as well as the multiplicities it belongs to.
Venture fiction is a practice of creating enterprises in order to communicate ideas and not the other way round. It uses the framework of network analysis to conceive of itself and its interactions with the real. Each iteration is a shift from one node to another within a dynamic network, which has capabilities to produce both wandering movement and oscillating multidimensional patterns. Each venture is a strange attractor among many and it is the fiction that propels the entrepreneur to travel between them and to create the new ones.
In this research we propose a method for visualizing text’s polysingularity: the multiple clusters of meaning circulation contained within a text. These clusters can be described as “strange attractors” (to use the term from dynamical systems theory), which are actualized during the process of reading. We use network analysis in order to plot the text’s structure onto a two-dimensional plane and represent these strange attractors as the communities of co-occurring nodes, positioned within the graph depending on their influence for the production of meaning.