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Dynamic Field Theory: Conceptual foundations and applications to neuronally inspired cognitive and developmental robotics

The metaphor of Dynamical Systems has influenced how psychologists, developmental scientists, cognitive scientists, and neuroscientists think about sensori-motor processes and their development [1]. The initial emphasis on motor behavior was expanded when the concept of dynamic activation fields provided access to embodied cognition [2]. Dynamical Field Theory (DFT) offers a framework for thinking about representation-in-the-moment that is firmly grounded in both Dynamical Systems thinking and neurophysiology [3]. Dynamic Neural Fields are formalizations of how neural populations represent the continuous dimensions that characterize perceptual features, movements, and cognitive decisions. Neural fields evolve dynamically under the influence of inputs as well as strong neuronal interaction, generating elementary forms of cognition through dynamical instabilities.