How to build a brain : a neural architecture for biological cognition / Chris Eliasmith.

Format:

Book

Author/Creator:

Eliasmith, Chris, author.

Series:

Oxford Series on Cognitive Models and Architectures

Oxford series on cognitive models and architectures

Language:

English

Subjects (All):

Brain.

Neural circuitry.

Neural networks (Neurobiology).

Cognition.

Cognitive neuroscience.

Cognition--physiology.

Models, Biological.

Nerve Net.

Cognitive Neuroscience.

Medical Subjects:

Cognition--physiology.

Models, Biological.

Nerve Net.

Cognitive Neuroscience.

Cognition.

Physical Description:

1 online resource (xvii, 456 pages) : illustrations.

Other Title:

Neural architecture for biological cognition

Place of Publication:

Oxford ; New York : Oxford University Press, [2013]

Language Note:

English

Summary:

Here, Chris Eliasmith presents a new approach to understanding the neural implementation of cognition in a way that is centrally driven by biological considerations. According to the semantic pointer hypothesis, higher-level cognitive functions in biological systems are made possible by semantic pointers.

Contents:

Cover; Contents; Preface; Acknowledgments; 1 The Science of Cognition; 1.1 The Last 50 Years; 1.2 How We Got Here; 1.3 Where We Are; 1.4 Questions and Answers; 1.5 Nengo: An Introduction; PART I: HOW TO BUILD A BRAIN; 2 An Introduction to Brain Building; 2.1 Brain Parts; 2.2 A Framework for Building a Brain; 2.3 Levels; 2.4 Nengo: Neural Representation; 3 Biological Cognition: Semantics; 3.1 The Semantic Pointer Hypothesis; 3.2 What Is a Semantic Pointer?; 3.3 Semantics: An Overview; 3.4 Shallow Semantics; 3.5 Deep Semantics for Perception; 3.6 Deep Semantics for Action

3.7 The Semantics of Perception and Action3.8 Nengo: Neural Computations; 4 Biological Cognition-Syntax; 4.1 Structured Representations; 4.2 Binding Without Neurons; 4.3 Binding With Neurons; 4.4 Manipulating Structured Representations; 4.5 Learning Structural Manipulations; 4.6 Clean-Up Memory and Scaling; 4.7 Example: Fluid Intelligence; 4.8 Deep Semantics for Cognition; 4.9 Nengo: Structured Representations in Neurons; 5 Biological Cognition-Control; 5.1 The Flow of Information; 5.2 The Basal Ganglia; 5.3 Basal Ganglia, Cortex, and Thalamus; 5.4 Example: Fixed Sequences of Actions

5.5 Attention and the Routing of Information5.6 Example: Flexible Sequences of Actions; 5.7 Timing and Control; 5.8 Example: The Tower of Hanoi; 5.9 Nengo: Question Answering; 6 Biological Cognition-Memory and Learning; 6.1 Extending Cognition Through Time; 6.2 Working Memory; 6.3 Example: Serial List Memory; 6.4 Biological Learning; 6.5 Example: Learning New Actions; 6.6 Example: Learning New Syntactic Manipulations; 6.7 Nengo: Learning; 7 The Semantic Pointer Architecture; 7.1 A Summary of the Semantic Pointer Architecture; 7.2 A Semantic Pointer Architecture Unified Network; 7.3 Tasks

7.4 A Unified View: Symbols and Probabilities7.5 Nengo: Advanced Modeling Methods; PART II: IS THAT HOW YOU BUILD A BRAIN?; 8 Evaluating Cognitive Theories; 8.1 Introduction; 8.2 Core Cognitive Criteria; 8.3 Conclusion; 8.4 Nengo Bonus: How to Build a Brain-a Practical Guide; 9 Theories of Cognition; 9.1 The State of the Art; 9.2 An Evaluation; 9.3 The Same...; 9.4 ...But Different; 9.5 The SPA Versus the SOA; 10 Consequences and Challenges; 10.1 Representation; 10.2 Concepts; 10.3 Inference; 10.4 Dynamics; 10.5 Challenges; 10.6 Conclusion; A: Mathematical Notation and Overview; A.1 Vectors

A.2 Vector SpacesA.3 The Dot Product; A.4 Basis of a Vector Space; A.5 Linear Transformations on Vectors; A.6 Time Derivatives for Dynamics; B: Mathematical Derivations for the NEF; B.1 Representation; B.2 Transformation; B.3 Dynamics; C: Further Details on Deep Semantic Models; C.1 The Perceptual Model; C.2 The Motor Model; D: Mathematical Derivations for the Semantic Pointer Architecture; D.1 Binding and Unbinding Holographic Reduced Representations; D.2 Learning High-Level Transformations; D.3 Ordinal Serial Encoding Model; D.4 Spike-Timing Dependent Plasticity

D.5 Number of Neurons for Representing Structure

Notes:

Description based upon print version of record.

Includes bibliographical references (p. 417-445) and index.

Description based on print version record and online resource.

Description based on publisher supplied metadata and other sources.

ISBN:

0-19-979469-3

1-299-70878-1

OCLC:

852159148