Functional Neuroscience, 3-Volume Set

Description

The late E. Roy John is considered the pioneer in the field of neurometrics – the science of measuring the underlying organization of the brain’s electrical activity. Volume 1, co-authored by Robert W. Thatcher, and Volume 2 both originally published in 1977, were among the first books this field. Volume 3, written by colleague Thalía Harmony, followed in 1984. The field expanded significantly in the 1990s and thousands of articles have subsequently been published. Available together for the first time these 3 volumes were important foundational works for the fields of quantitative electrophysiology and neurometrics. 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