Based on the mathematics of nonlinear Dynamical System Theory, neurocognition can be analyzed by convergent fluid and transient neurodynamics in abstract n-dimensional system phase spaces in the form of nonlinear vector fields, vector streams or vector flows (the so-called "vectorial form"). This processual or dynamical perspective on cognition, including the dynamical binding mechanisms in cognitive neuroarchitectures, has the advantage of a more accurately modeling of the transient cognitive processes. Thus, neurocognition can be considered as being organized by integrative synchronization mechanisms which best explain the liquid flow of neurocognitive information orchestrated in a network of positive and/or negative feedback loops in the subcortical and cortical areas. The human neurocognitive system can be regarded as a nonlinear, dynamical and open nonequilibrium system. This new fluid or liquid perspective in cognitive science and cognitive neuroscience can be regarded as a contribution towards bridging the gap between the discrete, abstract symbolic description of propositions in the mind, and their continuous, numerical implementation in self-organizing neural networks modelling the neural information processing in the human brain.
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