The Central Nervous System can be considered as an aggregate of neurons specialized in both the transmission and transfomation of information. Information here has been used for many purposes, but the most important one is probably to generate a representation of the "extenal" world that allows the organism to react properly to changes in its extenal environment. These functions range from such basic ones as detection of changes that may lead to tissue damage and eventual destruction of the organism and the implementation of avoidance reactions to more elaborate representations of the extemal world implying recognition of shapes, sounds and textures as the basis of planned action or even reflection. The question is, how can we hope to understand the complexity inherent in this range of functionalities? One of the distinguishing features of the last two decades has been the availability of computational power that has impacted the many areas of science concerned with this question.
An effort has been made within this book to cross boundaries and to have active scientists from different backgrounds and disciplines explain the basic principles which guide their investigations with the hope that this will lay the basis for a future collaborative effort to understand the principles of neural networks.
I. Scales of Analysis.- Neuronal networks of the mammalian brain have functionally different classes of neurons: Suggestions for a taxonomy of membrane ionic conductances.- Electrical coupling in networks containing oscillators.- Dynamical approach to collective brain.- Schema-theoretic models of arm, hand, and eye movements.- Cooperative distributed problem solving between (and within) intelligent agents.- II. Processing of Sensory Information.- Spinal processing of impulse trains from sensory receptors.- Central control of sensory information.- Parallel and serial processing in the somatosensory system.- Cortical representation of touch.- An introduction to human haptic exploration and recognition of objects for neuroscience and AI.- Common principles in auditory and visual processing.- III. Visual Processing.- Neuronal substrate of ligth-induced attraction and withdrawal in crayfish: A case of behavioral selection.- Neural and psychophysical models of chromatic and achromatic visual processes.- Computational vision: A probabilistic view of the multi-module paradigm.- State of the art in image processing.- Shape recognition in mind, brain, and machine.- IV. Learning And Knowledge Representation.- Contrasting properties of NMD A-dependent and NMDA-independent forms of LTP in hippocampal pyramidal cells.- Kindling.- Learning automata: An alternative to artificial neural networks.- Learning, from a logical point of view.- Knowledge representation for speech processing.- Data management and inference strategies in a human gait pathology expert system.- V. Neuronal Systems For Motor Integration.- Entrainment of the spinal neuronal network generating locomotion.- Cortical representation of intended movements.- Saccadic and fixation sytems of oculomotor control in monkey superior colliculus.- Modulatory effects on prey-recognition in amphibia: A theoretical- experimental study.- VI. Robotics And Control.- Outline for a theory of motor behavior: Involving cooperative actions of the cerebellum, basal ganglia, and cerebral cortex.- Neural networks and adaptive control.- Robustness issues in robot manipulators.- Symbolic planning versus neural control in robots.- Divine inheritance vs. experience in the world: Where does the knowledge base come from?.- VII. A Concluding Perspective.- Methodological considerations in Cognitive Science.- Viewpoints and controversies.
Series: Springer Series in Synergetics
Number Of Pages: 579
Country of Publication: DE
Dimensions (cm): 24.41 x 16.99
Weight (kg): 0.93