Nonlinear dynamics of creative thinking. Multimodal processes and the interaction of heteroclinic structures
M.I. Rabinovich† a,
P. Varona‡ b
a BioCircuits Institute, University of California, 9500 Gilman Drive #0328 La Jolla, San Diego, CA, 92093-0328, USA
b Departamento de Ingeniería Informática, Universidad Autónoma de Madrid, Madrid, Spain
The dynamic processes of creative thinking, as confirmed by recent studies using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), are interactions among three main components: the originality of the author, the author's autobiographical memory, and the purpose or stimulus of the process. Different stimuli initiate the excitation of different memory components and, accordingly, different neuronal clusters and brain networks. New data make it possible to build a model of the birth and development of creative thinking, i.e., to elaborate a theory of a process that is itself, by definition, indefinitely structured and unpredictable, with the use of a structurally organized mathematical approach—nonlinear dynamics. The following key concept is discussed: the evolution of thought or the essence of other human creative activity is a dynamic process characterized by internal instability leading to the generation of new information. To construct a nonlinear dynamic model of human creativity, the following ideas common to most mental processes are used: (1) a mathematical model should be based on variables representing the evolution of brain elements in their temporal coherence and should have solutions corresponding to metastable patterns (blocks of knowledge) in the brain, (2) the model is based on competitive dynamics without a winner, i.e., a nonlinear process of interaction of many information elements or spatio-temporal modes, which guarantees sequential switching between metastable states and, as a result, a certain stability of the dynamics of creativity, (3) the model is an open dissipative system in which inhibition is balanced by excitation; as a result, being close to the boundary of instability, it turns out to be extremely sensitive to information influences.
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