Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain

✍ Scribed by Randall C. O'Reilly, Yuko Munakata,

• Year: 2000
• Tongue: English
• Leaves: 533
• Edition: 1
• Category: Library

✦ Synopsis

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena.The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.

✦ Table of Contents

1 Introduction and Overview......Page 30
I Basic Neural Computational Mechanisms......Page 50
2 Individual Neurons......Page 52
3 Networks of Neurons......Page 100
4 Hebbian Model Learning......Page 144
5 Error-Driven Task Learning......Page 176
6 Combined Model and Task Learning, and Other Mechanisms......Page 202
II Large-Scale Brain Area Organization and Cognitive Phenomena......Page 232
7 Large-Scale Brain Area Functional Organization......Page 234
8 Perceptionand Attention......Page 256
9 Memory......Page 304
10 Language......Page 352
11 Higher-Level Cognition......Page 408
12 Conclusions......Page 440
III Simulator Details......Page 454
A Introduction to the PDP++ Simulation Environment......Page 456
B Tutorial for Constructing Simulations in PDP++......Page 464
C Leabra Implementation Reference......Page 484
References......Page 496
Author Index......Page 514
Subject Index......Page 520