Dynamic systems theory offers conceptual andmathematical tools for describing the performance ofneural systems at very different levels oforganization. Three aspects of the dynamic paradigmare discussed, namely neural rhythms, neural andmental development, and macroscopic brain theories andmodels.

This paper proposes that neurodynamic system theory may be used to connect structural and functional aspects of neural organization. The paper claims that generalized causal dynamic models are proper tools for describing the self-organizing mechanism of the nervous system. In particular, it is pointed out that ontogeny, development, normal performance, learning, and plasticity, can be treated by coherent concepts and formalism. Taking into account the self-referential character of the brain, autopoiesis, endophysics and hermeneutics are offered as elements of a poststructuralist (...) brain (-mind-computer) theory. (shrink)

We clarify the arguments in Neural organization: Structure, function, and dynamics, acknowledge important contributions cited by our critics, and respond to their criticisms by charting directions for further development of our integrated approach to theoretical and empirical studies of neural organization. We first discuss functional organization in general (behavior versus cognitive functioning, the need to study body and brain together, function in ontogeny and phylogeny) and then focus on schema theory (noting that schema theory is not just a top-down theory (...) and discussing the transition from action-oriented perception to cognition). We then turn to dynamical organization, with a focus first on neural modeling and dynamics (clarifying the multiple functions of neurons and brain regions, and looking further at various forms of dynamics) and second on learning, development, and self-organization (looking at monoaminergic systems, reinforcement, self-organization, postnatal development, and disease). We close with a brief philosophical discussion of postmodernism and reductionism. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) Function: Control (...) of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. Key Words: cognitive maps; computational neuroscience; dynamics; hippocampus; memory; modular architectonics; neural modeling; neural organization; neural plasticity; rhythmogenesis; Szentágothai. (shrink)

Instead of commenting directly on Foundations of Language: Brain, Meaning, Grammar, Evolution, I provide some remarks from an interdisciplinary view. Language theory is examined from the perspective of the theory of complex systems. The gestural-vocal dichotomy, network theory, evolutionary mechanisms/algorithms, chaos theory, and constructive approach are briefly mentioned.

Philosophical, dynamical, neural, network-theoretical, and cognitive ingredients of Tsuda's brain theory are discussed and anayzed. The integrative approach emphasized by Tsuda would be a welcome one.

Some dichotomies related to modeling electrocortical activities are analyzed. Attractor neural networks versus biologically motivated models, near-equilibrium versus nonequilibrium processes, linear and nonlinear dynamics, stochastic and chaotic patterns, local and global scale simulation of cortical activities are discussed.