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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• Integrative synchronization mechanisms in connectionist cognitive neuroarchitectures