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How to build a brain : a neural architecture for biological cognition /
One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biol...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Oxford ; New York :
Oxford University Press,
[2013]
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| Colección: | Oxford series on cognitive models and architectures.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Eliasmith, Chris, |e author. | |
| 245 | 1 | 0 | |a How to build a brain : |b a neural architecture for biological cognition / |c Chris Eliasmith. |
| 264 | 1 | |a Oxford ; |a New York : |b Oxford University Press, |c [2013] | |
| 264 | 4 | |c ©2013 | |
| 300 | |a 1 online resource (xvii, 456 pages) : |b illustrations | ||
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| 490 | 1 | |a Oxford series on cognitive models and architectures | |
| 520 | |a One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biological detail seriously, while addressing cognitive phenomena. The Semantic Pointer Architecture (SPA) introduced in this book provides a set of tools for constructing a wide range of biologically constrained perceptual, cognitive, and motor models. Examples of such models are provided, and they are shown to explain a wide range of data including single cell recordings, neural population activity, reaction times, error rates, choice behavior, and fMRI signals. Each of these models introduces a major feature of biological cognition addressed in the book, including semantics, syntax, control, learning, and memory. These models are not introduced as independent considerations of brain function, but instead integrated to give rise to what is currently the world's largest functional brain model. Along the way, the book considers neural coding, concept representation, neural dynamics, working memory, neuroanatomy, reinforcement learning, and spike-timing dependent plasticity. The book includes 8 detailed, hands-on tutorials exploiting the free Nengo neural simulation environment, providing practical experience with the concepts and models presented throughout. | ||
| 504 | |a Includes bibliographical references (pages 417-445) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a The science of cognition -- An introduction to brain building -- Biological cognition : semantics -- Biological cognition -- syntax -- Biological cognition -- control -- Biological cognition -- memory and learning -- The semantic pointer architecture -- Evaluating cognitive theories -- Theories of cognition -- Consequences and challenges -- A. Mathematical notation and overview -- B. Mathematical derivations for the NEF -- C. Further details on deep semantic models -- D. Mathematical derivations for the semantic pointer architecture -- E. Semantic pointer architecture model details. | |
| 546 | |a English. | ||
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| 650 | 0 | |a Brain. | |
| 650 | 0 | |a Neural circuitry. | |
| 650 | 0 | |a Neural networks (Neurobiology) | |
| 650 | 0 | |a Cognition. | |
| 650 | 6 | |a Cerveau. | |
| 650 | 6 | |a Réseaux nerveux. | |
| 650 | 6 | |a Réseaux neuronaux (Neurobiologie) | |
| 650 | 6 | |a Cognition. | |
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| 650 | 7 | |a cognition. |2 aat | |
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| 650 | 7 | |a PSYCHOLOGY |x Neuropsychology. |2 bisacsh | |
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| 650 | 7 | |a Cognition |2 fast | |
| 650 | 7 | |a Neural circuitry |2 fast | |
| 650 | 7 | |a Neural networks (Neurobiology) |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Eliasmith, Chris. |t How to build a brain. |d New York, NY : Oxford University Press, [2013] |z 9780199794546 |w (DLC) 2012046211 |w (OCoLC)822667362 |
| 830 | 0 | |a Oxford series on cognitive models and architectures. | |
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