Integrative Synchronization Mechanisms in Cognitive Neuroarchitectures of Modern Connectionism
The Mind and Brain are usually considered as one and the same nonlinear, complex dynamical system, in which information processing can be described with vector and tensor transformations and with attractors in multidimensional state spaces. Thus, an internal neurocognitive representation concept consists of a dynamical process which filters out statistical prototypes from the sensorial information in terms of coherent and adaptive n-dimensional vector fields. These prototypes serve as a basis for dynamic, probabilistic predictions or probabilistic hypotheses on prospective new data (see the recently introduced approach of "predictive coding" in neurophilosophy). Furthermore, the phenomenon of sensory and language cognition would thus be based on a multitude of self-regulatory complex dynamics of synchronous self-organization mechanisms, in other words, an emergent "flux equilibrium process" ("steady state") of the total collective and coherent neural activity resulting from the oscillatory actions of neuronal assemblies. In perception it is shown how sensory object informations, like the object color or the object form, can be dynamically related together or can be integrated to a neurally based representation of this perceptual object by means of a synchronization mechanism ("feature binding"). In language processing it is shown how semantic concepts and syntactic roles can be dynamically related together or can be integrated to neurally based systematic and compositional connectionist representations by means of a synchronization mechanism ("variable binding") solving the Fodor-Pylyshyn-Challenge. Since the systemtheoretical connectionism has succeeded in modeling the sensory objects in perception as well as systematic and compositional representations in language processing with this vector- and oscillation-based representation format, a new, convincing theory of neurocognition has been developed, which bridges the neuronal and the cognitive analysis level.
The book describes how elementary neuronal information is combined in perception and language, so it becomes clear how the brain processes this information to enable basic cognitive performance of the humans.
Table of Contents
Preface. Introduction: Theory of an Integrative Neurocognition. PART 1: FOUNDATIONS OF COGNITIVE SCIENCE. Cognitive Science: Integrative Theory of Cognition, Cognitivism and Computationalism. (General) Theory of (Nonlinear) Dynamical Systems and the Paradigm of Self-Organization. Theoretical Paradigms in Cognitive Science and in Theoretical Neurophilosophy. Integrative Synchronization Mechanisms and Models in the Cognitive Neurosciences. Mathematical, Physical and Neuronal Entropy Based Information Theory. PART 2: COGNITIVE NEUROARCHITECTURES IN NEUROINFORMATICS, IN COGNITIVE SCIENCE AND IN COMPUTATIONAL NEUROSCIENCE. Systematic Class of Classic Vector Based Architecture Typs. Systematic Class of Attractor Based Architecture Typs. Systematic Class of Oscillator Based Architecture Typs. Systematic Class of System Dynamic Based and Synapse Based Architecture Typs. Systematic Class of Information Based Architecture Typs. Epilogue: Discussion, Evaluation and Future Research. Bibliography. Index.
Harald Maurer is a post-doctoral researcher at the Wilhelm-Schickard-Institute for Computer Science, in the Department of Mathematical Logic and Theory of Language (University of Tübingen). He is published in journals such as "Computational Cognitive Science" and "Journal for General Philosophy of Science," is a lecturer at the Universities of Tübingen, Heidelberg and Magdeburg since 2012. He has presented his research at the universities of Tübingen, Berlin, Magdeburg, Leipzig, Bochum, Stuttgart and at the Max-Planck-Institute for Brain Research in Frankfurt/Main.