Functional Neuroscience, 3-Volume Set

Cover
Volume1
Cover
Half Title
Title Page
Copyright Page
Original Title Page
Original Copyright Page
Table of Contents
Preface
Introduction
1: Basic Neurophysiology
I. Fundamentals of Neurophysiology
A. Basic Structure
B. Action Potential
C. Synaptic Transmission
D. Neuronal Integrative Function
II. Functional Neuroanatomy
A. Definitions
B. The Organization of Sensory Systems
C. The Organization of the Motor System
D. The Organization of the Limbic System
III. Neurochemical Neuroanatomy
2: Functional Electrophysiology
I. Introduction
II. The Genesis of EEG
A. Unitary Sources of EEG
B. Intraneuronal Slow Waves
C. Contributions of Glia Cells
D. Contributions from Action Potentials
E. Contributions by Summated Synaptic Potentials
F. Contributions by Afterpotentials
G. Contributions by Intrinsic Membrane Oscillations
III. Statistical Organization of EEC Generators
IV. Significance of Degree of Coherence of Cell Populations
3: The Genesis of Alpha Rhythms and EEG Synchronizing Mechanisms
I. Introduction
II. Thalamocortical Coordination in the Production of Spindles
III. Mechanisms of Synchronization as Revealed by Intracellular Analysis
IV. Thalamocortical Gating Functions
A. EEG Scanning Mechanisms
B. The Phenomenon of Perceptual Framing
C. Control Systems and Thalamocortical Loop Processes
4: Neurophysiology of Arousal and Attention
I. Introduction
II. The Reticular Activating System
III. Reciprocal Interrelations in the Control of Arousal
A. The Control of Sleep-Wakefulness
B. Rostral and Caudal Influence of Reticular Formation
IV. Changes in Single Unit Discharge during Arousal and Attention
V. Changes in Neural Coherence during Attention
A. Sensory-Motor Interaction
B. Changes in State
C. Further Changes in Coherence during Attention
VI. Anatomic Substrates of Attention Focusing
VII. Involuntary and Volitional Attention
VIII. Mechanisms of Attention Shift and Attention Fixation
5: Neurophysiology of Emotion
I. Introduction
II. Aspects of Emotional Behavior
A. Autonomic Activity and Emotions
B. Emotional Experience
III. Atavistic Behavior
IV. Hierarchical Organization of Emotional Systems
A. The Spinal Cord and Brain Stem
B. The Hypothalamus
C. The Thalamus
D. The Limbic System
E. The Neocortex
6: Information Representation
I. Introduction
II. Information and Representational Systems: A Definition
III. Organization of Local Representation Systems
A. Hierarchical Organization of Representational Systems
B. Multidimensionality of Sensory Unit Responses
C. Evoked Potential Correlates of Sensory Representation
IV. Anatomic and Temporal Changes in the Organization of Global Representational Systems
A. Expansion of Global Representational Systems
B. Changes in Complexity of Global Representational Systems
7: The Neural Representation of Time
I. Introduction
II. External or Objective Time
III. The Construction of Subjective Time
IV. Neural Representational Systems
V. Labeled Rhythms and Time Reconstruction
A. Neural Loop Model of Time Representation
B. Application of the Model to the Labeled Frequency Findings
VI. Conclusions
8: The Chemical Basis of Memory
I. What Is the Basis of Memory and How Is It Made?
A. The Consolidation Phase
B. The "Trace" Theory
C. Facilitation of Consolidation
D. Critical Substance and Critical Shift
E. Threshold of Consciousness
F. The Multiple Trace Theory
G. Does Critical Shift in Some Cells Contradict Statistical Theory?
H. Mechanisms of Stable Information Storage
II. Chemical Transfer of Learning
III. Present Uncertainty of the Field
IV. The Derepressor Hypothesis
V. Ethical Problems of Learning Enhancement
9: The Localization of Function—Where is Memory?
I. The Localizationist Position
II. The Antilocalizationist Viewpoint
III. The Search for the Engram
IV. Recent Evidence against Localization of Function
V. Is the Visual Cortex Essential for Pattern Vision?
VI. Single- versus Multiple-Stage Lesions
VII. A Note of Caution
VIII. Implications for Remediation of Brain Damage
A. Hippocampus
B. Frontal Cortex
IX. Lateralization: The Split Brain
X. Localization of Speech Function
XI. Effects of Cortical Stimulation
XII. Evidence against Strict Localization of Language Function
XIII. Functional Pluripotentialism: Graded Localization
XIV. Compensation by Reorganization of Function
XV. The Localization of Electrophysiological Changes during Learning
A. Tracer Technique
B. Many Brain Regions Participate in Learned Behaviors
C. Average Response Computation
D. Increase Similarity of Average Responses in Different Brain Regions
E. Widespread Neuronal Involvement in Learned Behaviors
10: How Do We Remember?
I. Exogenous and Endogenous Components of EEG Activity
A. Assimilation of the Rhythm
B. Functional Significance of Assimilated Rhythms
C. Generalization
II. Exogenous and Endogenous Components of Evoked Response
A. New Components Appear during Learning
B. Readout to Absent but Expected Events
C. Readout during Generalization
D. Difference Waveshapes
E. Differential Generalization
F. Differing Facets of the Same Experience
III. "Modes" of Response
IV. Behavioral Prediction by Pattern Recognition Methods
V. Anatomic Distribution of the Engram
A. Algebraic Treatment of Evoked Potential Processes
B. Computation of Residuals
C. Anatomic Distribution of Exogenous and Endogenous Residuals
VI. Cellular Participation in Memory
A. Statistical Features of Neuronal Activity
B. Unit Activity in Conditioned Responses
C. Similar Patterns in Elements of an Ensemble
VII. Mass Action Revisited
VIII. Neuronal Activity during Readout of Specific Memories
IX. Generality of Conclusions Based on Tracer Technique
A. Relevance to Different Modalities of Information
B. "Readout" of Other Types of Information
C. Readout to "Imaginary "Stimuli
D. Relevance to Continuous Environmental Stimuli
11: Activation of Memories by Electrical Stimulation of the Brain: A Direct Test of Statistical Theory
I. Rationale for the Use of Electrical Stimulation to Test Statistical Theory
II. Prior Studies of Stimulus Generalization
A. Stimulus Generalization to Brain Stimuli after Peripheral Training
B. Stimulus Generalization after Training to Subcortical Stimulation
C. Stimulus Generalization to Cortical Sites after Training to Cortical Stimulation
D. Stimulus Generalization to Subcortical Sites after Cortical Training
E. Stimulus Generalization to Cortical Sites after Subcortical Training
III. Sensory-Sensory Transfer of Frequency Discrimination
IV. Peripheral-Central Transfer of Frequency Discrimination
V. Conflict between Simultaneous Sensory and Central Stimuli
VI. Central-Central Transfer of Frequency Discrimination
VII. Perceptual Integration of Stimuli Simultaneously Delivered to Different Sites
VIII. Conflict Studies between Simultaneous Central Stimuli
IX. Summary of Conflict Studies
X. Electrophysiological Findings
XI. Conclusions
12: Mental Experience
I. Major Avenues of Investigation of Mental Experience
A. Levels of Information
B. "Experienced Integration" or Consciousness
C. Hypothesis of a Centralized Integrative System
II. Representational Systems
III. Consciousness as a Representational System
IV. The Transformation from Neuronal Activity to Subjective Experience
V. Physical Basis of Consciousness
A. Mind-Matter Dualism
B. The "Hyperneuron"
VI. Representation of an Experience
VII. The Stream of Consciousness
13: Daily Subjective Experience and Psychopathology
I. Bias of Conscious Experience
A. Anatomic Factors
B. Biochemical Factors
C. Experiential Factors
II. "Imaginary" Readout
III. "Abnormal" Consciousness
A. Improper Brain Function
B. Disordered Representational Systems
C. Societal Causes
IV. Electrophysiological Reflections of Abnormal Processes
V. Possible Types of Psychiatric Disorder
References
Author Index
Subject Index
Volume2
Cover
Half Title
Title Page
Copyright Page
Original Title Page
Original Copyright Page
Table of Contents
Foreword
Preface
1: Introduction
I. A Definition of "Neurometrics"
II. Functional Insights Available from Scalp Recordings
III. Limitations of Qualitative Analysis of Brain Electrical Activity
IV. The Neurometric Alternative
2: Diagnostic Electrophysiology
I. EEG Assessment of Neuropathology
A. EEG Recording Methods
1. Electrode Placement
2. Recording Method
3. Recording Derivations or "Montages"
B. Principles of EEG Analysis
C. The Accuracy of EEG Detection of Neuropathology
1. Incidence of Major Neurological Disease
a. Head Injury
b. Paroxysmal Disorders
i. Migraine Headaches
ii. Epilepsy
c. Developmental and Degenerative Defects
d. Cerebrovascular Disease
e. Intracranial Tumors
f. Infectious Diseases
2. Incidence of EEG Abnormalities in Major Neurological Diseases
II. Detection of Neuropathology Using Symmetry of Average Evoked Responses (AER)
III. Localization of Lesion Site by AER Methods
IV. Assessment of Changes in Brain State
V. AER Assessment of Sensory Acuity
A. Evoked Response Audiometry
B. AER Assessment of Visual Acuity
C. AER Assessment of Color Vision
VI. AER Assessment of Other Aspects of Brain Function
A. Indices of Development and Maturation
B. Perceptual and Cognitive Functions
VII. Summary
3: Principles of Neurometric Analysis of Brain Electrical Activity
I. Analysis of the Spontaneous EEG
A. Frequency Analysis
1. Compressed Spectral Array
2. "Neurometric" Displays
a. The "Canonogram"
b. The "Age Dependent Quotient"
B. Symmetry Analysis
II. Average Evoked Response and Variance Computations: General Considerations
A. The Average Evoked Response
B. Variance of the Average Evoked Response
C. t Test for the Significance of Differences between AERs
III. Objective Comparisons Between AERs
A. Symmetry of the AER
B. Assessment of Effects of Altered Conditions
IV. Pattern Recognition Methods
A. Template Methods
1. Amplitude Sorting
2. Cross-Correlation Methods
3. Cross-Spectral Analysis
4. Adaptive Filtering
B. Cluster Analysis
C. Discriminant Analysis
D. Multidimensional Scaling
1. Feasibility
2. Creating Non-Existent Structure
V. Multivariate Factor Analysis
A. Limitations
B. Factor Analysis Methods
C. Classification of Drugs
D. Factor Analysis of AER in Humans
E. "Normal Spaces" and Screening for Pathology
F. Drug Subspaces
G. Pathological Subspaces
VI. Conclusions
4: Automatic Acquisition and Analysis of Electrophysiological Indices of Brain Functions
I. An Automatic Digital Electrophysiological Data Acquisition and Analysis System (DEDAAS)
1. Amplifiers
2. 24-Channel Amplifying System
3. Display System
4. Impedance Testing
5. Variable Gain Analog-to-Digital Conversion
6. Automatic Artifact Control
7. Station Multiplexing
8. Digital Recording, Encoded Protocols and Automatic Analysis
9. Computation of all Bipolar Montages
10. Computer-Controlled Stimulator
11. Computer System
12. Plotter
13. Block Diagram of DEDAAS System
14. Economic Advantages of DEDAAS
II. A Quantitative Electrophysiological Test Battery (NB)
A. EEG Measures
B. Evoked Potential Measures
III. Quantitative Neurometric Indices Extracted from NB Challenges
A. Neurometric Indices Extracted from EEG Measures
B. Neurometric Indices Extracted from EP Measures
IV. Concluding Comments
5: Neurometric Assessment of Brain Dysfunction in Patients with Neuropathology
I. Neurometric Indices Extracted from Spontaneous EEG
A. Indices Derived from Frequency Analysis
1. Abnormality Index
2. Age-Dependent Quotients
B. Indices Derived from Symmetry Analysis
1. Discriminant Functions for Identification of Neuropathology Using Measures of EEG Symmetry
2. Numerical Taxonomy of Neuropathology: Neurometric Discrimination between Types of Neurological Diseases
II. Neurometric Indices Extracted from AER
A. Indices Derived from AER Symmetry Analysis
1. Discriminant Function Separating Normal Subjects from Neurological Patients on the Basis of AER Symmetry
2. Comparison of Effectiveness of AER Symmetry, EEG Symmetry, and Conventional EEG
B. Neurometric Indices Derived by Varimax Factor Analysis of AER Waveshapes
1. Determination of the "Normal AER Space"
2. Regression Factor Analysis of AERs from Patients with Tumors, Strokes, or Epilepsy
3. Multidimensional Scaling Applied to Discrimination between AERs from Normal Subjects and Patients with Tumors
III. Conclusion
6: Neurometric Assessment of Sensory, Perceptual, and Cognitive Processes
I. Introduction
II. AER Assessment of Sensory Acuity
III. AER Assessment of Perceptual Capability
IV. AER Assessment of Shape Perception
V. AER Assessment of Cognitive Processes
A. Control of Afferent Input
B. P-300 or the Late Positive Component of the Human AER
C. Contingent Negative Variation
D. Differential Anatomic Distribution of Exogenous and Endogenous Processes in Man
7: Assessment of Brain Dysfunction in Elderly Patients with Cognitive Impairment
I. Cognitive Deterioration in the Elderly: The Organic Brain Syndrome
II. Electrophysiological Studies of Changes with Aging, with Special Relevance to Organic Brain Syndrome
A. EEC Studies
1. General Changes with Aging
2. Studies of Patients with Organic Brain Syndrome
B. AER Studies
1. General Changes with Aging
2. Studies of Patients with Organic Brain Syndrome
III. Neurometric Features that Discriminate Between Normal Elderly Subjects and Patients with Cognitive Impairment (OBS)
A. Patient Selection
1. Normal Controls
2. Cognitively Impaired Group (OBS)
B. Psychometric Evaluation
C. Neurometric Evaluation
1. Recording Procedures
2. Test Conditions
3. Data Analysis
a. Data Conversion and Editing
b. Neurometric Indices
D. Neurometric Findings
1. Frequency Analysis of Resting EEG
2. Bilateral EEG Synchrony
3. Comparison of Overall Interhemispheric Covariance of Resting EEG
4. Symmetry of AERs from Bilaterally Symmetric Derivations
5. Comparison of Overall Interhemispheric Covariance of AERs
6. Discriminant Functions on Individual Conditions
7. Multivariate Analysis
a. Multiple Discriminant Function
b. "Leave-One-Out" Replication of Discriminant Function
8. Cluster Analysis
a. Method
9. Numerical Taxonomy of the Elderly
IV. Conclusions
8: Neurometric Assessment of Brain Dysfunction in Children with Learning Disabilities
I. Minimal Brain Damage
A. The MBD Syndrome
1. "Learning Disability" and "Learning Disorder"
2. Heterogeneity of Etiology
3. Estimates of Prevalence
B. Relevant Electrophysiological Measures
1. Neonatal Status
a. EEG Measures
b. AER Measures
2. Indices of Maturation
a. EEG Measures
b. Age-dependent EEG Quotient and Maturational Lag
c. AER Measures
C. Electrophysiological Findings in Pharmacotherapy of MBD
II. Neurometric Assessment of 50 Consecutive Children with Learning Difficulties referred to the Neurophysiology Clinic
A. Deviation from EEG and AER Norms
B. Age-Dependent Delta Quotient
C. Abnormality Index
D. Conclusions
III. Comparison Between Previously Categorized Groups of "Normal" and "Learning Disabled" Children Using the Neurometric Test Battery (NB)
A. Subjects, Behavioral Methods, and Criteria for Disability
1. Description of Subjects
2. Psychometric Battery and the Composite Dysfunction (3M) Score
3. The Criterion Problem
4. Need to Compress Measure Sets
B. Factor Analysis of Psychometric Measures
C. Factor Analysis of Neurometric Indices Extracted from the EEC Conditions of the NB
1. Factor Analysis of the Frequency Spectrum
2. Construction of a Compressed Set of Spectral Values
3. Factor Analyses of the 10/20 System
a. Topography of Factors 1–6
b. Similar Factor Structure, Eyes Open or Closed
4. Construction of Set of Multivariate EEG Indices
D. Psychometric Multiple Discriminant Function Separating Normal from Learning Disabled Children
E. Neurometric Multiple Discriminant Function Separating Normal from Learning Disabled Children
1. Further Reduction of EEG Measure Set
2. Neurometric Multiple Discriminant Function
F. Correction of Misclassified Subjects
G. Comparison Between Psychometric and Neurometric Discriminant Functions
1. Canonical Correlations Between Psychometric and Neurometric Measures
2. Regression Analysis of Covariance for Psychometric and Neurometric Discriminant Scores
3. Density Distribution of Psychometric and Neurometric Discriminant Scores
H. Analysis of Variance of EP Conditions of the NB
I. Visual Display as a Method of Data Compression: The Density-Coded Z Transform
J. Cluster Analysis
9: The Perspective for Neurometrics
References
Author Index
Subject Index
Volume3
Cover
Half Title
Title Page
Copyright Page
Original Title Page
Original Copyright Page
Table of Contents
Preface
1: Introduction
I. Neurometrics—Definition
II. Major Applications of Neurometrics in Clinical Neurology
III. Current State of Neurometrics
2: The Electroencephalogram
I. The Genesis of the Electroencephalogram (EEG)
II. Technical Aspects of EEG Recording
A. Electrodes
B. Amplification
C. Electrode Placement
D. Recording Derivations and Montages
E. Artifacts and Interferences
F. Activation Procedures
III. Visual Assessment of the EEG
A. Typical Normal Rhythms
B. Changes of the EEG During Sleep
C. Major Abnormalities Observed in the EEG
D. EEG Characteristics of the Major Neurological Diseases
IV. Critical Aspects of Visual EEG Interpretation
Part I: Introduction to Evoked Responses and Event-Related Potentials
I. The Average Evoked Response
3: Visual Evoked Responses (VERs)
I. Transient VERs to Spatially Unstructured Stimulus Field
A. General Characteristics
B. Changes with Age and Sex
C. Changes with the Characteristics of the Stimulus
D. Clinical Applications
II. Visual Excitability Cycle
III. Steady-State Evoked Responses to Flicker Stimulation
IV. Steady-State Responses to Sine Wave Modulated Light (SML)
V. Transient VERs to Spatially Structured Stimulus Fields
A. General Characteristics
B. Age Dependence
C. Clinical Applications
VI. The Steady-State Pattern Evoked Responses
VII. Conclusions
4: Auditory Evoked Responses (AERs)
I. Introduction
II. Early AER Components or Brain-Stem Auditory Evoked Responses (BAERs)
A. General Characteristics
B. Stimulus Dependence
C. Age Dependence
D. Clinical Applications
III. Middle and Long Latency Components of the AER
A. General Characteristics
B. Age Effect on AERs
C. Effects of Stimulus Characteristics on Middle and Long Latency Components
D. Clinical Applications of Middle and Long Latency Components
IV. Excitability Cycle of AERs
V. The Frequency-Following Response (FFR)
VI. Summary
5: Somatosensory Evoked Responses (SSERs)
I. SSERs to Nonpainful Electrical Nerve Stimulation
A. General Characteristics
B. Age Dependence
C. Clinical Applications
II. SSER Excitability Cycle
III. SSERs to Mechanical Stimulation
IV. SSERs to Painful Stimulation
V. Spinal-Cord Evoked Responses (SCERs)
A. General Characteristics
B. Clinical Applications
VI. Summary
6: Other Event-Related Potentials
I. Contingent Negative Variation (CNV)
A. General Characteristics
B. Clinical Applications
II. The Motor Potentials
A. General Characteristics
B. Clinical Applications
III. Summary
Part II: Quantitative Analysis of Brain Electrical Activity
7: Statistical Bases
I. Introduction
A. Statistical Questions
B. Types of Measurements
C. Probability Models
II. Vectors and Matrices
III. Probability Models
A. Sample Spaces, Random Functions, and Probability Distributions
B. Moments
C. Gaussian Probability Models
D. Stationary, Ergodicity, and Mixing
IV. Analysis of the Structure of the Data
A. Relationships Among the Variables
B. Relationships Between Two Groups of Observed Variables
C. Relationships Between Observed Variables and Hypothetical Variables
D. Relationships of a Set of Observed Variables with Fixed Mathematical Functions or "Standard Variables"
E. Time-Series Models
F. Methods for Studying Interrelationships Between Individuals
V. Sample Comparison Techniques
A. Differences in the Means of Neurometric Values
B. General Formulation of the Problem
C. Methods for Testing Differences Between Samples Obtained from Gaussian Distributions
VI. Statistical Prediction
A. Basic Ideas Underlying Discriminant Analysis
B. Discrimination When the Populations are Gaussian: Ideal Case of Knowledge of Population Parameters
C. Practical Discriminant Analysis
D. Evaluating Discriminant Functions
E. Selection of Variables
8: Fundamental Considerations in Automatic Quantitative Analysis
I. Analog to Digital (AD) Conversion
II. Artifact Rejection
III. Variations of the Internal State of the Subject
IV. Data Processing: Off-Line Versus On-Line Analysis
V. Displays
VI. Selection of the Computer System
9: Review of Major Methods of EEG Analysis
I. Introduction
II. Stochastic Properties of the EEG
III. Time-Domain Analysis
A. Amplitude Analysis
B. Period Analysis
C. Interval-Amplitude Analysis
D. Correlation Analysis
E. Coefficient of Information Transmission of Uncertainty Reduction (CITUR)
F. Normalized Slope Descriptors
IV. Frequency Analysis
A. Power Spectrum
B. Cross Spectrum and Coherence
C. Bispectral Analysis
D. Complex Demodulation (CD)
E. Autoregressive Models of the EEG
V. Topographic Methods
A. Toposcopy
B. Contour-Mapping Techniques
VI. Conclusions
10: A Review of Major Methods of Evoked Response Analysis
I. Introduction
II. Stochastic Properties of the Evoked Responses
III. Estimation of the Evoked Responses
A. Procedures That Assume That the Stimulus-Dependent Activity is Invariant
B. Procedures That Assume That the Stimulus-Dependent Activity is Variable
IV. Hypothesis Testing Between Groups of Evoked Responses
A. t Test
B. Mann-Whitney U Test
C. Linear Discriminant Analysis
D. Nonlinear Discriminant Analysis
V. Analysis of the Structure
A. Linear Transformations
B. Time-Varying Spectra
C. Principal Component Analysis
D. Cluster Analysis
VI. Prediction Methods
VII. Topographic Methods
VIII. Summary
Part III: Neurometric Evaluation in Clinical Neurology
11: EEG Background Activity
I. The Neurometric Approach
II. Frequency Analysis
A. Canonograms
B. The "Deviance" Measure: A Comparison of Power Spectral Features, Normalized Slope Descriptors, and Visual EEG Interpretation
C. Age-Dependent EEG Quotient (ADQ)
D. EEG Pattern Discrimination Using Autoregressive Analysis
III. Interval-Amplitude Analysis: Neurometric Approach
IV. Symmetry Analysis: Polarity Coincidence Correlation Coefficient (PCC) and Signal Energy Ratio (SER)
A. PCC and SER in Adults
B. PCC and SER in Children: Discriminating Normal Children from Children with Neurological Diseases
V. The Z Vector: Spectral Plus Symmetry Analysis
VI. Factor Scores Derived from EEG and VERs Parameters for the Classification of Alcoholic and Schizophrenic Patients
VII. Conclusions
12: Automatic Spike Detection and Seizure Monitoring
I. Introduction
II. Detection Procedures Based on Wave Amplitude
III. Detection Procedures Based on the Measurement of Slope
IV. Detection Procedures Based on Sharpness
V. Detection Procedures Based on Combined Criteria of Amplitude and Duration
VI. Detection Procedures Based on Combined Criteria of Amplitude, Duration, Slope, and Sharpness
VII. Detection of Spikes by Their Comparison with a Template Waveform
VIII. Detection of Nonstationarities in the EEG Using the Autoregressive Model
IX. Summary
13: Neurometric Evaluation of Evoked Responses in Clinical Neurology
I. Introduction
II. Transient Visual Evoked Responses to Flashes
A. Symmetry Analysis
B. Waveform Analysis
III. Transient Visual Evoked Responses to Pattern-Reversal Stimuli
IV. Steady-State Visual Evoked Responses
A. "Driving Curve" for the Evaluation of Brain Damage
B. Discrimination of MS Patients
V. Auditory Evoked Responses
A. Brain-Stem Responses
B. Cortical Auditory Evoked Responses
VI. Somatosensory Evoked Responses
A. Far-Field Potentials in Patients with MS
B. Amplitude and Period of Cortical SSER Components in Brain Lesions
C. Interhemispheric Latency and Amplitude Differences of SSERs to Simultaneous Bilateral Median Nerve Stimulation in Patients with Brain Lesions
D. Somatosensory Evoked Response Train (SSERT): Discrimination of Normal Subjects from MS Patients
E. Somatosensory Conduction Velocity in MS
VII. Methods that Use Combinations of Averaged Evoked Responses to Different Sensory Modalities
A. Amplitude and Latency Values of Pattern-Reversal VERs and Spinal Cord Evoked Responses (SCERs) in Diagnosis of MS
B. Visual, Auditory, and Somatosensory Evoked Responses in the Discrimination of Different Types of Aphasia
C. Visual, Auditory, and Somatosensory Evoked Responses in the Discrimination of Different Neurological Diseases
VIII. Conclusions
Part IV: Summary
14: A Summarized Review on the Principal Electrophysiological Findings in the Major Neurological Diseases
I. Cerebrovascular Disorders
A. EEG
B. Averaged Evoked Responses
C. Conclusions
II. Intracranial Tumors
A. EEG
B. Averaged Evoked Responses
C. Conclusions
III. Epilepsy
A. EEG
B. Averaged Evoked Responses
C. Conclusions
IV. Multiple Scierosis
A. EEG
B. Averaged Evoked Responses
C. Conclusions
15: Conclusions. Strategies for the Use of Neurometrics
References
Author Index
Subject Index