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From The CriticsReviewer: Thomas H. Jobe, MD (University of Illinois at Chicago College of Medicine)
Description: This volume is a systematic presentation of the author's theory of neurocomputation. He has developed the "functional automatism" theory of neurocomputing to a high level of conceptual clarity. He shows how Kolmogorov's theorem (1957) can be applied to the new concept of a "spiking" dendritic tree to explain learning in reflex motor activity and how hierarchies of reflexes can control manipulation of external objects by an organism.
Purpose: The author has successfully applied the functional automatism concept of neurocomputing to motor reflex learning and control. His purpose is also to critique competing theories of neurocomputation.
Audience: This book is intended for neurobiologists, neurologists, neurosurgeons and neuropsychiatrists. It provides an ingenious model of Parkinson's Disease that explains how neurosurgical interventions that damage tissue can actually improve function.
Features: Several excellent diagrams and illustrations are included that illustrate concepts of motor control by hierarchical reflex integration. Experiments that illustrate "functional automatisms" are well illustrated.
Assessment: The author has achieved a lucid and well-argued presentation of his model of neurocomputation. The strength of the model rests on the fact that it originally derives from biological control systems (vonHolst) and then makes use of important analogical extensions to achieve generality and complexity not found in more "mechanical" physics based models such as those of Hopfield and Tank. The author's approach thus stands as an important biological alternative to the dominant mechanistic trend in neural network theory.