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Invitation to Cog Sci, V. 4 (Methods, Models, and Conceptual Issues)  무료배송

 
지은이 : Osherson
출판사 : MIT
판수 : 2nd edition
페이지수 : 949 pages
ISBN : 0262650460
예상출고일 : 입금확인후 2일 이내
주문수량 :
도서가격 : 55,000원 ( 무료배송 )
적립금 : 1,650 Point
     

 
An Invitation to Cognitive Science provides a point of entry into the vast realm of cognitive science by treating in depth examples of issues and theories from many subfields. The first three volumes of the series cover Language, Visual Cognition, and Thinking. Volume 4, Methods, Models, and Conceptual Issues, expands the series in new directions. The chapters span many areas of cognitive science--including artificial intelligence, neural network models, animal cognition, signal detection theory, computational models, reaction-time methods, and cognitive neuroscience. The volume also offers introductions to several general methods and theoretical approaches for analyzing the mind, and shows how some of these approaches are applied in the development of quantitative models. Rather than general and inevitably superficial surveys of areas, the contributors present "case studies"--detailed accounts of one or two achievements within an area. The goal is to tell a good story, challenging the reader to embark on an intellectual adventure.
Saul Sternberg is Professor of Psychology at the University of Pennsylvania.
1.1 Introduction

1.1.1 Behavior Suggestive of a Cognitive Map

1.1.2 Maps and Navigational Computation

1.1.3 Representational (Symbol-Processing) and Nonrepresentational (Subsymbolic) Theories of Mind

1.1.4 Symbol-Processing Systems

1.1.5 Neural Nets

1.1.6 Difficulty of Reconciling Symbol Processing with Our Current Understanding of Neurobiology

1.1.7 Mental Representations

1.1.8 Summary

1.2 Breaking the Question Down

1.2.1 Can Insects Determine and Remember Angles?

1.2.1.1 The Dance of the Honeybee Symbolizes an Angle

1.2.1.2 Bees Record Landmark Angles

1.2.1.3 Bees Record the Compass Directions of Landmarks

1.2.2 Can Insects Determine and Remember Distances?

1.2.2.1 The Honeybee's Dance Symbolizes Distance

1.2.2.2 Ants Know the Distance Home

1.2.2.3 Locusts and Bees Compute Distance by Triangulation

1.2.3 Can Insects Do Dead Reckoning?

1.2.4 How Do Insects Hold a Course?

1.2.4.1 The Sun Compass Mechanism

1.2.4.2 Clock and Ephemeris: Two Brain-World Isomorphisms

1.2.5 How Do Insects Recognize Landmarks?

1.2.5.1 Terrain Matching

1.2.5.2 View Matching

1.2.6 Do Insects Have an Integrated Map?

1.2.6.1 Bees Sometimes Compute Novel Courses

1.2.6.2 Novel Terrain-Based Course Holding

1.2.6.3 Homing from Release Sites

1.3 Concluding Observations

Suggestions for Further Reading

Problems and Questions for Further Thought

References

About the Author

The Mental Representation of Time: Uncovering a Biological Clock

Editors' Introduction

2.1 Introduction

2.1.1 History of Animal Timing

2.1.2 Importance of Animal Timing

2.2 Distinctness of the Clock

2.2.1 Independence of Two Measures of Behavior

2.2.2 Other Evidence for Distinctness

2.2.3 Importance of Distinctness

2.3 Other Properties of the Clock

2.3.1 The Clock Can Be Stopped Temporarily

2.3.2 The Same Clock Times Light and Sound

2.3.3 The Clock Is Path-Independent

2.3.4 The Clock Times Multiple Intervals by Varying the End Point

2.3.5 The Clock Times Selectively

2.3.6 The Clock Has a Linear Scale

2.3.7 The Clock Depends on an Internal Pacemaker

2.3.8 The Clock Is Precise

2.4 Use of Animals to Study Cognition: Strengths and Weaknesses

2.5 What Have We Learned?

2.5.1 Substance

2.5.2 Method

Suggestions for Further Reading

Problems

Questions for Further Thought

References

About the Author

The Evolution of Cognition: Questions We Will Never Answer

Editors' Introduction

3.1 An Outline of the Argument

3.1.1 An Example from Biology

3.1.2 The Application to Human Cognition

3.2 Traits in Evolution

3.3 History, Form, and Function

3.3.1 Evolutionary Description

3.3.2 Functional Changes

3.3.3 Evolutionary Constraints

3.4 Problems of Reconstruction

3.4.1 Reconstruction of Relationships

3.4.2 Reconstruction of Function and Changes

3.5 Specific Problems in the Evolution of Human Cognition

3.5.1 Human Relations and Ancestors

3.5.2 Ancestors

3.5.3 Homology and Analogy

3.5.3.1 Linguistic Ability

3.6 Function and Selection

3.7 A Final Note to the Reader

Suggestions for Further Reading

Questions for Further Thought

References

About the Author

Consciousness and the Mind: Contributions from Philosophy, Neuroscience, and Psychology

Editors' Introduction

4.1 What Is Consciousness?

4.1.1 Cartesian Dualism

4.1.2 Parallelism

4.1.3 Epiphenomenalism

4.1.4 Constructive Naturalism: An Alternative to Dualism and Materialism

4.2 The Natural Method

4.2.1 Neural Correlates of Subjective Experience: Animal Experiments

4.2.2 Splitting Auditory Attention

4.2.3 Complex Learning without Consciously Accessible Memories

4.3 Four Claims about Consciousness

4.4 Experiential Sensitivity and Informational Sensitivity

4.5 Conscious Inessentialism and the Epiphenomenalist Suspicion

4.6 The Default Assumption against Epiphenomenalism

4.7 An Experiment in Epiphenomenalism

4.8 Further Evidence for a Function for Consciousness

4.8.1 The Role of Consciousness in Skilled Performance

4.8.2 Brain Damage and Defects of Consciousness

4.8.3 The Case against Epiphenomenalism

4.9 Conclusion

Suggestions for Further Reading

Questions for Further Thought

References

About the Authors

Cognitive Algorithms: Questions of Representation and Computation in Building a Theory

Editors' Introduction

5.1 Algorithms, Architectures, and Representations

5.2 A Case Study in Constraint Satisfaction

5.3 Huffman/Clowes Line Labeling

5.4 Varieties of Algorithms

5.5 Waltz/Mackworth Constraint Propagation Algorithm

5.6 Enlarging the Set of Junction Labels

5.7 Parallelizing the Algorithm

5.8 How Many Global Interpretations?

5.9 NP-completeness and Its Implications

5.10 Concluding Observations

Suggestions for Further Reading

Problems and Questions for Further Thought

References

About the Author

A Gentle Introduction to Soar: An Architecture for Human Cognition

Editors' Introduction

6.1 Introduction

6.2 The Idea of Architecture

6.3 What Cognitive Behaviors Have in Common

6.4 Behavior as Movement through Problem Spaces

6.5 Tying the Content to the Architecture

6.6 Memory, Perception, Action, and Cognition

6.7 Detecting a Lack of Knowledge

6.8 Learning

6.9 Putting It All Together: A Soar Model of Joe Rookie

6.10 Stepping Back: The Soar Architecture in Review

6.11 From Architecture to Unified Theories of Cognition

Suggestions for Further Reading

Problems

Questions for Further Thought

References

About the Authors

Learning Arithmetic with a Neural Network: Seven Times Seven Is About Fifty

Editors' Introduction

7.1 Arithmetic Learning

7.2 Neural Networks

7.3 Data Representation

7.4 Arithmetic and Associative Interference

7.5 Doing Mathematics

7.6 Putting the Pieces Together

7.7 A Neural Network Model for Multiplication

7.8 Flexibility: Doing More Than You Learned

Suggestions for Further Reading

Problems

References

About the Author

Models for Reading Letters and Words

Editors' Introduction

8.1 Introduction

8.2 Pattern Recognition

8.2.1 Domains of Pattern Recognition

8.2.2 Computational Models

8.3 Approaches to Pattern Recognition

8.3.1 Template Matching

8.3.2 Feature Analysis

8.4 Letter Recognition

8.4.1 Fuzzy Letters and Continuous Rating Judgments

8.4.2 Discrete Model

8.4.3 Continuous Model

8.4.4 Experimental Test

8.5 Multifactor Experiments

8.6 Models of Recognition

8.6.1 Template Model

8.6.2 Discrete Feature Model

8.6.2.1 Elaborating the Presumed Operations

8.6.2.2 Free Parameters and Their Estimation

8.6.3 Fuzzy Logical Model of Perception

8.6.3.1 Benchmark Measures of Goodness of Fit

8.7 Context Effects in Pattern Recognition

8.7.1 Test of the FLMP

8.7.2 Sentence Context in Word Recognition

8.8 Artificial Neural Network Models

8.8.1 Connectionist Model of Perception

8.8.2 Interactive Activation Model

8.8.3 IAM with Input Noise and Best-One-Wins Decision Rule

8.9 Justification of Computational Modeling

8.9.1 Difficulties in Psychological Inquiry

8.9.2 Implications for Psychological Inquiry

8.10 Metatheoretical Issues and the Computational Approach

8.10.1 Identifiability Issue

8.10.2 Optimality of Pattern Recognition

Note

Suggestions for Further Reading

Problems and Questions for Further Thought

References

About the Author

Inferring Mental Operations from Reaction-Time Data: How We Compare Objects

Editors' Introduction

9.1 Introduction

9.1.1 A Three-Attribute Stimulus Set

9.1.2 Major Issues in Comparing Multiattribute Objects

9.1.2.1 Holistic versus Feature Comparison

9.1.2.2 Sequential versus Parallel Tests

9.1.3 Some Typical Data

9.1.3.1 Data from Geometric Patterns

9.1.3.2. Data from Letter Strings

9.1.4 Plan of the Chapter

9.1.5 Theories, Models, and Data

9.2 Reaction Time to Judge "Different"

9.2.1 Sequential Tests: Defining Properties

9.2.2 Sequential Tests: Prediction of the Number of Tests

9.2.2.1 Effect of Number of Mismatching Features on Number of Tests

9.2.2.2 Effect of Number of Relevant Features on Number of Tests

9.2.2.3 A General Statement of the Two Effects on Number of Tests for "Different" Responses

9.2.3 Sequential Tests: Relation between the Number of Tests and Mean Reaction-Time

9.2.3.1 The Contribution of Residual Operations to Reaction Time

9.2.3.2 Implications of Four Constraints on Test Durations

9.2.4 Sequential Tests: Application to Letter-String Data

9.2.4.1 The Fully Constrained Model

9.2.4.2. Relaxing Constraint 1: Allowing Variable Test Durations

9.2.4.3 Relaxing Constraint 2: Allowing Unequal Residual Durations for "Same" and "Different" Respon...

9.2.4.4. Relaxing Constraint 3: Allowing Unequal Durations of Matches and Mismatches

9.2.4.5. Relaxing Constraint 4: Allowing Unequal Mean Test-Durations for Different Attributes

9.2.4.6 Implications of a Nonballistic Response Process

9.2.4.7 Status of the Squential-Test Model

9.2.5 Parallel Tests: Defining Properties

9.2.5.1 Statistical Facilitation and the Effects of Process Variability

9.2.6 Parallel Tests: Effect of Number of Relevant Features on Mean Reaction-Time

9.2.7 Parallel Tests: Effect of Number of Mismatching Features on Mean Reaction-Time

9.2.7.1 Parallel Variant 1: Equal Fixed Test-Durations

9.2.7.2 Parallel Variant 2: Unequal Mean Test-Durations with Limited Variability

9.2.7.3 Parallel Variant 3: Variable Test-Durations with Unconstrained Means

9.2.7.4 Parallel Variant 4: Variable Test-Durations with Equal Means and Identical Distributions

9.2.7.5 Status of the Parallel- Test Model

9.2.8 Sequential versus Parallel Tests: Inferences Based on Differential Mismatch-Durations

9.2.9 Sequential versus Parallel Tests: Conclusions from "Different" Responses

9.3 Reaction Time to Judge "Same"

9.3.1 Difficulties for Sequential Tests

9.3.2 Parallel Tests Revisited

9.3.2.1 Parallel Variant 1: Equal Fixed Test-Durations

9.3.2.2 Parallel Variant 4: Variable Test-Durations with Equal Means and Identical Distributions

9.3.2.3 Parallel Variant 2: Unequal Mean Test-Durations with Limited Variability

9.3.2.4 Parallel Variant 3: Variable Test-Durations with Unconstrained Means

9.4 Two-Process Mechanisms and Holistic Stimulus-Comparison

9.4.1 Separate Mechanisms for "Same" and "Different" Responses, and Their Temporal Arrangement

9.4.2 The Nature of the Sameness-Detection Process

9.5 Concluding Remarks

Appendix 1: Error Rates and the Interpretation of Reaction-Time Data

Appendix 2: Donders' Subtraction Method and Modern Variants

Glossary

Suggestions for Further Reading

Questions For Further Thought

Notes

References

Models of Visual Search: Finding a Face in the Crowd

Editors' Introduction

10.1 Models and Phenomena

10.1.1 Phenomena

10.1.2 What Is a Model?

10.1.3 A Simple Model of Visual Search

10.2 A Quantitative Model for Visual Search

10.2.1 The Linear Model

10.2.2 Model Parameters and Prediction Error

10.2.3 The Error Surface and Error Minimization

10.2.4 Interpretation of Model Parameters

10.3 Attention and Preattention in Visual Search

10.3.1 Feature Conjunction Searches

10.3.2 Feature Searches

10.3.3 Feature Integration Theory

10.3.4 Ambiguities and Alternative Models

10.3.5 Selective Search

10.3.5.1 Illustrations

10.3.5.2 Predictions for Unbalanced Displays

10.3.5.3 Unbalanced Display Experiments

10.3.6 Selective Search Models

10.3.6.1 Consistent and Inconsistent Selective Search

10.3.6.2 Examples of Evaluating Models Quantitatively

10.3.6.3 Goodness-of-Fit Measures

10.3.7 Guided Search Model

10.3.7.1 Model Mechanisms

10.3.7.2 Predicting Variability and Errors

10.3.7.3 Simulation Parameters

10.3.7.4 Guided Search Predictions

10.3.7.5 Selective Search Models and Triple-Feature Conjunctions

10.3.7.6 Evaluation of Simulation Models

10.3.8 Summary

10.4 Representations in Modeling

10.4.1 Representations in Visual Search

10.4.2 Representation and Process in Other Domains

10.4.3 Some Examples

10.4.3.1 Ordered Sequences

10.4.3.2 Representing Items and Groups

10.4.4 Representation and Process

10.5 Models as Tools for Theory Development

Suggestions for Further Reading

Problems and Questions for Further Thought

References

About the Author

Skill Acquisition and Plans for Actions: Learning to Write with Your Other Hand

Editors' Introduction

11.1 Exercising Handwriting to Introduce Our Topic

11.1.1 The Puzzle of Shape Similarity

11.1.2 Improving Handwriting with Practice

11.1.3 The Goal of This Chapter

11.2 Plans and Planning

11.2.1 Nature of Plans

11.3 Plans in Motor Behavior: Motor Programs

11.3.1 A Movement-Specific Conception of Motor Programs

11.3.2 Generalized Motor Programs

11.3.3 Effector-Independent, Generalized Motor Programs

11.3.4 Evidence for Effector Independence in Handwriting: Shape Similarity

11.3.4.1 A Problem Interpreting Shape Similarity

11.3.4.2 Other Types of Evidence

11.4 Hierarchical Representation of Plans

11.4.1 From Reaching to Playing Shortstop: Development of Hierarchical Plans

11.4.2 Hierarchy in the Motor Programs for Handwriting

11.4.3 Strokes in Handwriting and the Analysis of Tangential Velocity

11.4.4 Hierarchical Structure of Motor Programs: Why Does it Matter?

11.5 Studying Motor Programs: Two Approaches

11.5.1 Planning

11.5.2 Transfer of Learning

11.6 Learning to Write with the Left Hand

11.6.1 Learning to Write with the Left Hand: The Number 1 Team

11.6.2 Learning to Write with the Left Hand: Two Moves to Mate

11.6.3 Learning to Write with the Left Hand: Three to Dine

11.7 Preparations: Identifying Generic Strokes, Characterizing Learning Curves, Methods and Design

11.7.1 Identifying Generic Strokes: G-Strokes

11.7.2 Power Law Learning Functions

11.7.3 A Final Design Issue

11.7.4 Notes on Method

11.7.5 Quantifying Writing Skill

11.7.5.1 Measuring Stroke Angle and Curvature

11.7.5.2 Using Variability to Track Consistency

11.7.5.3 A Composite Measure of Writing Fluency

11.8 Results: How One Righty Learned to Write Lefty

11.8.1 Overall Improvements with Practice

11.8.2 Changes in Fluency When the Words Being Written Change

11.8.2.1 From Word Set 1 to Word Set 2: Same Letters, New Words

11.8.2.2 From Word Set 2 to Word Set 3: Same Strokes, New Letters

11.8.3 Results for the Component Measures

11.8.3.1 The Problem of the Speed-Accuracy Trade-Off

11.8.3.2 Mean Stroke Duration

11.8.3.3 Mean Peak Velocity

11.8.3.4 Stroke Shape Variability

11.8.3.5 Stroke Duration Variability

11.8.4 The Development of Hierarchical Control at the Stroke Level

11.9 What Does It All Mean: Looking for the Writing on the Wall

11.9.1 Conclusions about Hand Independence and Context Specificity of the Hierarchical Representatio...

11.9.2 Summary

11.9.3 Looking beyond the Data

11.9.3.1 More Evidence about the Stroke Level

11.9.3.2 What Might Happen with Lots More Practice?

11.10 Comparing Your Results to Ours

Appendix A: Neurophysiological Levels of Motor Control

Appendix B: Could Extended Training Produce Hand-Dependent Representations at the Letter and/or Word...

Suggestions for Further Reading

Questions for Further Thought

Notes

References

About the Authors

Drawing Conclusions from Data: Statistical Methods for Coping with Uncertainty

Editors' Introduction

12.1 A Memory Experiment

12.2 Summarizing the Memory Experiment

12.3 Statistics and Cognitive Research

12.4 Statistics and the Researcher

12.5 Variability

12.6 Populations and Samples

12.7 Sampling Distributions and Confidence Intervals

12.8 Testing Theories

12.9 Decision Rules and Types of Error

12.10 Null Hypothesis Testing

12.11 Testing the Memory Experiment

12.12 The Analysis of Variance and Interactions

12.13 Counted Data and Chi-Square Tests

12.14 Association and Correlation

Suggestions for Further Reading

Problems and Questions for Further Thought

References

About the Author

Separating Discrimination and Decision in Detection, Recognition, and Matters of Life and...

Editors' Introduction

13.1 Introduction

13.1.1 Detection, Recognition, and Diagnostic Tasks

13.1.2 The Tasks' Two Component Processes: Discrimination and Decision

13.1.3 Diagnosing Breast Cancer by Mammography: A Case Study

13.1.3.1 Reading a Mammogram

13.1.3.2 Decomposing Discrimination and Decision Processes

13.1.4 Scope of This Chapter

13.2 Theory for Separating the Two Processes

13.2.1 Two-by-Two Table

13.2.1.1 Change in Discrimination Acuity

13.2.1.2 Change in the Decision Criterion

13.2.1.3 Separation of Two Processes

13.2.2 Statistical Decision and Signal Detection Theories

13.2.2.1 Assumptions About an Observation

13.2.2.2 Distributions of Observations

13.2.2.3 The Need for a Decision Criterion

13.2.2.4 Decision Criterion Measured by the Likelihood Ratio

13.2.2.5 Optimal Decision Criterion

13.2.2.6 A Traditional Measure of Acuity

13.3 The Relative Operating Characteristic

13.3.1 Obtaining an Empirical ROC

13.3.2 A Measure of the Decision Criterion

13.3.3 A Measure of Discrimination Acuity

13.3.4 Empirical Estimates of the Two Measures

13.4 Illustrations of Decomposition of Discrimination and Decision

13.4.1 Signal Detection during a Vigil

13.4.2 Recognition Memory

13.4.3 Polygraph Lie Detection

13.4.4 Information Retrieval

13.4.5 Weather Forecasting

13.5 Computational Example of Decomposition: A Dice Game

13.5.1 Distributions of Observations

13.5.2 The Optimal Decision Criterion for the Symmetrical Game

13.5.3 The Optimal Decision Criterion in General

13.5.4 The Likelihood Ratio

13.5.5 The Dice Game's ROC

13.5.6 The Game's Generality

13.6 Improving Discrimination Acuity by Combining Observations

13.7 Enhancing the Interpretation of Mammograms

13.7.1 Improving Discrimination Acuity

13.7.1.1 Determining Candidate Perceptual Features

13.7.1.2 Reducing the Set of Features and Designing the Reading Aid

13.7.1.3 Determining the Final List of Features and Their Weights

13.7.1.4 The Merging Aid

13.7.1.5 Experimental Test of the Effectiveness of the Aids

13.7.1.6 Clinical Significance of the Observed Enhancement

13.7.2 Optimizing the Decision Criterion

13.7.2.1 The Expected Value Optimum

13.7.2.2 The Optimal Criterion Defined by a Particular False Positive Proportion

13.7.2.3 Societal Factors in Setting a Criterion

13.7.3 Adapting the Enhancements to Medical Practice

13.8 Detecting Cracks in Airplane Wings: A Second Practical Example

13.8.1 Discrimination Acuity and the Decision Criterion

13.8.2 Positive Predictive Value

13.8.3 Data on the State of the Art in Materials Testing

13.8.4 Diffusion of the Concept of Decomposing Diagnostic Tasks

13.9 Some History

Suggestions for Further Reading

Problems

References

About the Author

Discovering Mental Processing Stages: The Method of Additive Factors

Editors' Introduction

14.1 Introduction

14.1.1 The Search for Modules

14.1.2 The Language of Factorial Experiments

14.1.3 Stages, Selective Modifiability, and Invariant Factor Effects

14.1.4 Plan of the Chapter

14.2 Additive and Interacting Factors

14.2.1 Examples from Naming a Digit

14.2.2 Examples from Searching Memory

14.3 Effects of Factors on a Shopping Trip: A Process with Observable Stages

14.3.1 Jim and Alice's Story

14.3.2 The Stages of Jim's Trip and the Factors That Influence Them

14.3.3 Details of the Effects of Factors on Stages of the Trip

14.3.4 Trip Duration Data: Additive Factors

14.3.5 Trip Duration Data: Interacting Factors

14.3.6 Conclusions from Jim and Alice's Story

14.4 Stage Models and the Effects of Factors on Mental Operations

14.4.1 Stages: The Modules of a Sequential Process

14.4.2 The Subtraction Method of Frans Cornelis Donders (1818-1889)

14.4.3 How Plausible Is It for Mental Processes to Be Sequential?

14.4.4 An Example: Stages in a Choice Reaction

14.4.4.1 Separate Stages for Stimulus Identification and Response Selection

14.4.4.2 Why Are Choices Slowed by Signal Uncertainty?

14.4.5 The Method of Additive Factors

14.5 Some Applications of the Additive-Factor Method

14.5.1 What Else Do We Lose When We Lose Sleep?

14.5.2 How We Prepare to Choose

14.5.3 Retrieving Item versus Context Information from Memory

14.5.4 When We Improve with Practice, What Improves?

14.5.5 Transfer of Information between the Cerebral Hemispheres

14.5.6 Task Switching and the Frontal Lobes: Inference about Stages from Localized Brain Damage

14.5.7 Stages in Speech Production: Real-Time Evidence of a Stage-Specific Effect

14.5.8 Rotation and Magnification of Mental Images

14.5.8.1 Combining Two Image Transformations

14.5.8.2 Mental Rotation in Detail: Application of the Subtraction Method

14.5.9 Doing Two Things at Once: Why Are We Slower?

14.5.9.1 The Overlapping-Tasks Paradigm

14.5.9.2 The Bottleneck/Deferred-Processing Model

14.5.9.3 Some Implications of the Model

14.5.9.4 Tests of Three Implications of the Model

14.5.10 How Do Repetition and Familiarity Speed Word Recognition?

14.5.11 Do Readers Recognize One Word at a Time?

14.5.11.1 Equivalent Substages

14.5.12 Are Characters Encoded in Parallel, Sequentially, or Both?

14.5.13 What Do We Search for When We Search Memory?

14.5.14 How Do We Benefit from Seeing Ahead When We Search a Display?

14.6 The Additive-Factor Method: Concluding Remarks

14.6.1 Processing Stages and Brain Structures

14.6.2 Perspectives from Other Module-Finding Methods

14.6.2.1 Separate Measures

14.6.2.2 Composite Measures

14.6.3 What is "Additive-Factors Logic"?

14.6.4 Extending the Method beyond the Mean

14.6.5 Nonstage Architectures That Produce Additive Effects

14.6.5.1 Alternate Pathways

14.6.5.2 Overlapping Processes

14.6.6 Some Strengths and Limitations of the Method

14.6.7 Design Matters

15.6.7.1 Multiple Factors

14.6.7.2 Multiple Levels

14.6.8 Statistical Issues

14.6.9 The Importance of Ronald A. Fisher (1890-1962)

Suggestions for Further Reading

Notes

References

Brainwaves and Mental Processes: Electrical Evidence of Attention, Perception, and Intent...

Editors' Introduction

15.1 Event-Related Brain Potentials

15.2 The Electrophysiology of Attention

15.2.1 Attention and Information Processing

15.2.2 ERPs during Visual Perception

15.2.3 Selective Attention to Location and Color

15.2.4 ERP Signature of Visual-Spatial Selective Attention

15.2.5 ERP Signature of Attentional Selection Based on Color

15.2.6 The Temporal Organization of Attentional Selection

15.2.7 Conclusions

15.3 The Architecture of Cognition

15.3.1 Mental Chronometry

15.3.2 Transmission of Partial Information

15.3.2.1 Lateralized Readiness Potential

15.3.2.2 Choice-Reaction Go/Nogo Procedure

15.3.3 Experiment 1: Detecting Response Preparation Based on Partial Information

15.3.3.1 LRP on Nogo Trials

15.3.3.2 Alternative Hypotheses

15.3.4 Experiment 2: Further Examination of the LRP on Nogo Trials

15.3.4.1 Dissociating Stimulus and Response Side

15.3.4.2 Effects of the Go/Nogo Discrimination on the LRP

15.3.5 Inferring the Cognitive Architecture of a Simple Task

15.3.5.1 Alternative Cognitive Architectures

15.3.5.2 Cognitive Psychophysiology and Mental Chronometry

15.4 A Brief Tour of Cognitive Psychophysiology

15.4.1 Overview of ERPs

15.4.1.1 The Exogenous-Endogenous Continuum

15.4.1.2 Two Endogenous Components: P300 and N400

15.4.2 Other Measures

15.4.2.1 Cognitive Energetics: Autonomic Measures

15.4.2.2 Event-Related Magnetic Fields

15.4.2.3 Blood Flow and Metabolism: New Brain-Imaging Technologies

15.4.3 Role of Cognitive-Psychophysiological Measures

15.5 The Body as a Window on the Mind

15.5.1 Locating the Sources of ERPs

15.5.2 The Epiphenomenon Problem

15.5.3 A Two-Way Street

Suggestions for Further Reading

Questions for Further Thought

Notes

References

About the Author

Author Index

Subject Index
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