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Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology)

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Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology) Cover

 

Synopses & Reviews

Publisher Comments:

This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves.

The book is divided into two parts. The first part provides a tutorial introduction to topics in neuroscience, the psychology of learning and memory, and the theory of neural network models. The second part, the core of the book, reviews computational models of how the hippocampus cooperates with other brain structures — including the entorhinal cortex, basal forebrain, cerebellum, and primary sensory and motor cortices — to support learning and memory in both animals and humans. The book assumes no prior knowledge of computational modeling or mathematics. For those who wish to delve more deeply into the formal details of the models, there are optional "mathboxes" and appendices. The book also includes extensive references and suggestions for further readings.

Synopsis:

This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning.

Synopsis:

This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves.

About the Author

Mark A. Gluck is Associate Professor of Neuroscience at Rutgers University-Newark.Catherine E. Myers is Research Assistant Professor of Psychology at Rutgers University-Newark.

Product Details

ISBN:
9780262072113
Subtitle:
An Introduction to Neural Network Modeling of the Hippocampus and Learning
Author:
Gluck, Mark A.
Author:
Myers, Catherine E.
Publisher:
A Bradford Book
Location:
Cambridge, Mass.
Subject:
General
Subject:
Neuropsychology
Subject:
Neuroscience
Subject:
Memory
Subject:
Neural Networks
Subject:
Computer simulation
Subject:
Hippocampus.
Subject:
Neural networks (neurobiology)
Subject:
Hippocampus (Brain) - Computer simulation
Subject:
Psychology-Mind and Consciousness
Series:
Issues in Clinical and Cognitive Neuropsychology Gateway to Memory
Series Volume:
no. 247
Publication Date:
20001122
Binding:
Hardback
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
Yes
Pages:
464
Dimensions:
9 x 7 in 1.9 lb
Age Level:
from 18

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Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology) New Hardcover
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Product details 464 pages Bradford Book - English 9780262072113 Reviews:
"Synopsis" by , This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning.
"Synopsis" by , This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves.
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