Sinossi
While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors related to the connectivity, the intraneuronal parameters, the initial state and the stimulation conditions (Chapter 5). This work was initiated at the Computer and Information Science Depart ment of the University of Massachusetts, Amherst, and completed at the Institut de c Lber n e t Lca of the Universitat Politecnica de Catalunya, Barcelona. Computers at the latter place have adopted Catalan as their mother tongue and thus some computer-made figures in this monograph, specially those in Chapter 5, appear labeled in that tongue.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
1 — Introduction.- 2 — Experimental Data and Previous Models.- 3 — Modelling and Simulation of a Plastic Pacemaker Neuron.- 4 — Analytic Study of the Entrainment Patterns.- 5 — Modelling and Simulation of a Network of Plastic Pacemaker Neurons.- 6 — Conclusions and Future Prospects.- A — Neuronal physiology..- B — Properties of mappings from the unit circle onto itself..- C — Glossary of Catalan labels in computer-made figures..- References.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Temporal-Pattern Learning in Neural Models (Lecture Notes in Biomathematics)
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Temporal-Pattern Learning in Neural Models
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors related to the connectivity, the intraneuronal parameters, the initial state and the stimulation conditions (Chapter 5). This work was initiated at the Computer and Information Science Depart ment of the University of Massachusetts, Amherst, and completed at the Institut de c Lber n e t Lca of the Universitat Politecnica de Catalunya, Barcelona. Computers at the latter place have adopted Catalan as their mother tongue and thus some computer-made figures in this monograph, specially those in Chapter 5, appear labeled in that tongue. 236 pp. Englisch. Codice articolo 9783540160465
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Temporal-Pattern Learning in Neural Models
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Temporal-Pattern: Learning in Neural Models.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and post. Codice articolo 4882894
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Temporal-Pattern Learning in Neural Models
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Springer, Springer Vieweg Dez 1985, 1985
ISBN 10: 3540160469
ISBN 13: 9783540160465
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors related to the connectivity, the intraneuronal parameters, the initial state and the stimulation conditions (Chapter 5). This work was initiated at the Computer and Information Science Depart ment of the University of Massachusetts, Amherst, and completed at the Institut de c Lber n e t Lca of the Universitat Politecnica de Catalunya, Barcelona. Computers at the latter place have adopted Catalan as their mother tongue and thus some computer-made figures in this monograph, specially those in Chapter 5, appear labeled in that tongue.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 236 pp. Englisch. Codice articolo 9783540160465
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Temporal-Pattern Learning in Neural Models
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Springer, Springer Vieweg, 1985
ISBN 10: 3540160469
ISBN 13: 9783540160465
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - While the ability of animals to learn rhythms is an unquestionable fact, the underlying neurophysiological mechanisms are still no more than conjectures. This monograph explores the requirements of such mechanisms, reviews those previously proposed and postulates a new one based on a direct electric coding of stimulation frequencies. Experi mental support for the option taken is provided both at the single neuron and neural network levels. More specifically, the material presented divides naturally into four parts: a description of the experimental and theoretical framework where this work becomes meaningful (Chapter 2), a detailed specifica tion of the pacemaker neuron model proposed together with its valida tion through simulation (Chapter 3), an analytic study of the behavior of this model when submitted to rhythmic stimulation (Chapter 4) and a description of the neural network model proposed for learning, together with an analysis of the simulation results obtained when varying seve ral factors related to the connectivity, the intraneuronal parameters, the initial state and the stimulation conditions (Chapter 5). This work was initiated at the Computer and Information Science Depart ment of the University of Massachusetts, Amherst, and completed at the Institut de c Lber n e t Lca of the Universitat Politecnica de Catalunya, Barcelona. Computers at the latter place have adopted Catalan as their mother tongue and thus some computer-made figures in this monograph, specially those in Chapter 5, appear labeled in that tongue. Codice articolo 9783540160465
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