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Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.
The investigation of the relationships between a behavior pattern and its underlying sensory and neurophysiological mechanisms in both man and animals dates back well into the last century. However, the concepts and findings of ethology and experimental psychology, together with an improved understanding of how the nervous system is organized and how neurons interact with each other, have only in the last 30 years laid the groundwork for an in-depth analysis. The many technological advances achieved in neurophysiology and neuroanatomy have also played an important role in this. The study of the neuronal bases of behavior - for which the term "neuroethology" has been coined - has thus become one of the central themes of neuroscience. Kenneth David Roeder, who died in 1979, was one of the pioneers of this field of research. It is to him that the contributions in this book are dedicated. K.D. Roeder was among the first to attempt to define the correlation between the natural behavior of an experimental animal and the activity of single sensory and nerve cells. The ques tions he asked, his experimental approach, and his fundamental discoveries are pre sented in an introductory chapter.
The articles gathered in this volume represent examples of a unique approach to the study of mental phenomena: a blend of theory and experiment, informed not just by easily measurable laboratory data but also by human introspection. Subjects such as approach and avoidance, desire and fear, and novelty and habit are studied as natural events that may not exactly correspond to, but at least correlate with, some (known or unknown) electrical and chemical events in the brain.
This volume presents an international group of researchers who model animal and human behavior--both simple and complex. The models presented focus on such subjects as the pattern of eating in meals and bouts, the energizing and shaping impact of reinforcers on behavior, transitive inferential reasoning, responding to a compound stimulus, avoidance and escape learning, recognition memory, category formation, generalization, the timing of adaptive responses, and chromosomes exchanging information. The chapters are united by a common interest in adaptive behavior--whether of human, animal, or artificial system--and clearly demonstrate the rich variety of ways in which this fascinating area of research can be approached. In so doing, the book demonstrates the range of thought that qualifies as theorizing in the contemporary study of the mechanisms of adaptive behavior. It has two purposes: to bring together a very wide range of approaches in one place and to give authors space to explain how their ideas developed. Journal literature often presents fully-formed theories with no explanation of how an idea came to have the shape in which it is presented. In this volume, however, leaders in different fields provide background on the development of their ideas. Where once psychologists and a few zoologists had this field to themselves, now various types of computer scientists have added great energy to the mix.
The most conspicuous function of the nervous system is to control animal behav ior. From the complex operations of learning and mentation to the molecular con figuration of ionic channels, the nervous system serves as the interface between an animal and its environment. To study and understand the fundamental mecha nisms underlying the control of behavior, it is often both necessary and desirable to employ biological systems with characteristics especially suitable for answering specific questions. In neurobiology, many invertebrates have become established as model systems for investigations at both the systems and the cellular level. Large, readily identifiable neurons have made invertebrates especially useful for cellular studies. The fact that these neurons occur in much smaller numbers than those in higher animals also makes them important for circuit analysis. Although important differences exist, some of the questions that would be tech nically impossible to answer with vertebrates can become experimentally tractable with invertebrates.
Originally published in 1991, this title was the result of a symposium held at Harvard University. It presents some of the exciting interdisciplinary developments of the time that clarify how animals and people learn to behave adaptively in a rapidly changing environment. The contributors focus on aspects of how recognition learning, reinforcement learning, and motor learning interact to generate adaptive goal-oriented behaviours that can satisfy internal needs – an area of inquiry as important for understanding brain function as it is for designing new types of freely moving autonomous robots. Since the authors agree that a dynamic analysis of system interactions is needed to understand these challenging phenomena – and neural network models provide a natural framework for representing and analysing such interactions – all the articles either develop neural network models or provide biological constraints for guiding and testing their design.
This is the second volume to be based on a series of symposia being held periodically on the neurobiology of conditioning. The first, entitled Conditioning: Representation of Involved Neural Functions was based on a symposium held in Asilomar, Cali fornia, in October 1982 (Woody, 1982). The present volume is based on a sym posium, organized by D. Alkon and C. Woody, held at the Marine Biological Laboratory in Woods Hole, Massachusetts in November 1983. This series of sym posia and their publication are more than justified by the extraordinary progress be ing made during recent years in all branches of neuroscience and its application to our understanding of some of the basic neuronal mechanisms of conditioning and learning. Invertebrate models of conditioning have been used by many in the attempt to obtain a more thoroughly controlled analysis at the single cellular and synaptic level of the mechanisms involved in elementary conditioning in a simple nervous system. Examples of this approach are presented in this volume and utilize insects (grasshopper), crustacea (crayfish), and particularly the relatively simple nervous systems of mollusks (Aplysia and Hermissenda). In such preparations it is possible to carry out precise electrophysiological and neurochemical studies of single iden tified cells and synapses involved in such simple processes as habituation and sensitization, as well as simple forms of "associative" conditioning, usually using simple aversive or withdrawal reflexes.
The first volume in this new series from The Center for the Study of Child and Adolescent Development at The Pennsylvania State University focuses on the relationship between the biological stress circuits and the behavioral concomitants to stress in animals and humans. The participants at this conference, a tribute to Dean Evan G. Pattishall, Jr., discuss the developmental implications of their work in relation to the periods of infancy, childhood, and adolescence. For professionals, clinicians, and researchers in clinical, developmental, experimental, and health psychology, behavioral medicine, psychiatry, psychotherapy, and the neurosciences.
Neural Models of Plasticity: Experimental and Theoretical Approaches is an outgrowth of a conference that was held at Woods Hole, Massachusetts, in the spring of 1987. The purpose of that conference was to review recent developments in both areas and to foster communication between those researchers pursuing theoretical approaches and those pursuing more empirical approaches. Contributions have been solicited from individuals who represent both ends of the spectrum of approaches as well as those using a combination of the two. These indicate that our knowledge of the plastic capabilities of the nervous system is accelerating rapidly due to rapid advances in the understanding of basic subcellular and molecular mechanisms of plasticity, and because of the computational capabilities and plastic properties that emerge from neural networks and assemblies. The book contains 19 chapters and opens with a study on the role of the neuromodulator in associative learning of the marine mollusk Hermissend. Subsequent chapters examine topics such as learning and memory in Aplysia; the Hebb rule for synaptic plasticity; olfactory processing and associative memory in the mollusk Limax maximus; simulation of a classically conditioned response; and the neural substrates of memory, focusing on the role of the hippocampus.