Seizure prediction in epilepsy: from basic mechanisms to clinical applications
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| Weitere Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
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Weinheim
WILEY-VCH
2008
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| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | Literaturangaben |
| Beschreibung: | XXXV, 334 S. Ill., graph. Darst. 25 cm |
| ISBN: | 9783527407569 3527407561 |
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| 245 | 1 | 0 | |a Seizure prediction in epilepsy |b from basic mechanisms to clinical applications |c ed. by Björn Schelter ... |
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| 300 | |a XXXV, 334 S. |b Ill., graph. Darst. |c 25 cm | ||
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| 500 | |a Literaturangaben | ||
| 650 | 4 | |a Convulsions |x Forecasting | |
| 650 | 4 | |a Deep Brain Stimulation |v Congresses | |
| 650 | 4 | |a Epilepsy | |
| 650 | 4 | |a Epilepsy |x therapy |v Congresses | |
| 650 | 4 | |a Forecasting |x methods |v Congresses | |
| 650 | 4 | |a Models, Neurological |v Congresses | |
| 650 | 4 | |a Risk Assessment |v Congresses | |
| 650 | 4 | |a Seizures |x prevention & control |v Congresses | |
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Iv
Contents
Preface XV
Thanks to the Sponsors of the Workshop XVII
List of Contributors XIX
Color Plates XXVII
1 Unpredictability of Seizures and the Burden of Epilepsy 1
Andreas Schulze-Bonhage, Anne Kuhn
1.1 Introduction 1
1.2 Medical Implications of Unpredictability 2
1.2.1 Diagnostic Uncertainty 2
1.2.2 Treatment Options 2
1.2.3 Physical Risks 3
1.2.4 Risks Associated with Continuous Long-term
Antiepileptic Treatment 4
1.3 Psychosocial Consequences of Unpredictability 4
1.3.1 Loss of Control 4
1.3.2 Problems with Coping Strategies 6
1.3.3 Depression and Anxiety 6
1.3.4 Immobility and Vocational Restrictions 7
1.4 Conclusion 8
References 8
2 The History of Seizure Prediction 12
M. Jachan, H. Feldwisch genannt Drentrup, B. Schelter,
J. Timmer
2.1 Introduction 11
2.2 Motivation 11
2.2.1 The Need for a Seizure-prediction Device 12
2.2.2 The Assumed Preictal Phase 14
2.3 A Historical Overview 15
2.3.1 Older Types of Studies 16
Seizure Prediction in Epilepsy. Edited by Bjbrn Schelter, Jens Timmer and Andreas Schulze-Bonhage
Copyright © 2008 WILEY-VCH Verlag GmbH Co. KGaA, Weinheim
ISBN: 978-3-527-4O756-9
VI I Contents
2.3.2 Modern Types of Studies 16
2.3.3 Survey of Prediction Methods 17
2.4 The State of the Art in Seizure Prediction 19
2A.I Partially Solved Issues 19
2.4.2 Unsolved Issues 20
2.5 Seizure Prediction in the Future 21
References 22
3 Impact of Computational Models for an Improved Understanding
of Ictogenesis: From Single Neurons to Networks of Neurons 25
Marie-Therese Horstmann, Andy M'uller, Alexander Rothkegel,
Justus Schwabedal, Christian E. Elger, Klaus Lehnertz
3.1 Introduction 25
3.2 Single Neuron Models 27
3.2.1 Conductance-based Models 28
3.2.2 Single Neuron Models and Epilepsy 29
3.3 Neural Networks 31
3.3.1 Network Characteristics 32
3.4 Neural Mass Models of the EEG 35
3.5 Conclusion 38
References 39
4 Effective and Anatomical Connectivity in a Rat Model of
Spontaneous Limbic Seizure 45
Paul R. Carney, Alex Cadotte, Thomas B. DeMarse, Baba Vemuri,
Thomas H. Mareci, William Ditto
4.1 Introduction 45
4.2 Granger Causality 46
4.2.1 Analysis of Temporal Lobe Seizures 48
4.2.2 Results 50
4.2.3 Discussion 52
4.3 Structural Visualization with Magnetic Resonance 54
4.3.1 Diffusion Tensor Imaging 54
4.3.2 High Angular Resolution Diffusion Imaging 55
4.4 Acknowledgments 57
References 58
5 Network Models of Epileptiform Activity: Explorations in Seizure
Evolution and Alteration 61
Pawel Kudela, William S. Anderson, PiotrJ. Franaszczuk,
Gregory K. Bergey
5.1 Introduction 61
5.2 Time-frequency Analyses of Seizure Dynamics
and Evolution 62
5.3 Model Assumptions and Modeling Approach 63
\
Contents I VII
5.4 Recurrent Neuronal Bursting and Mechanism of Burst
Frequency Decline 64
5.5 Network Models of Epileptiform Activity Disruption
by External Stimulation 67
5.6 Chain Network Model Studies 69
5.7 Networks with Realistic Cortical Architecture 71
5.8 Conclusions 79
5.9 Acknowledgment 80
5.10 Appendix 80
References 81
6 Recurrent Cortical Network Activity and Modulation
of Synaptic Transmission 83
Yousheng Shu
6.1 Introduction 83
6.2 The Ability of the Cortical Network to Generate
Recurrent Activity 84
6.3 Cortical Network Activity as Propagating Electrical Waves 85
6.4 Balance of Excitation and Inhibition during Cortical
Network Activity 86
6.5 Initiation and Termination of Cortical Network
Activity by Electrical Shock 86
6.6 Epileptiform Activity Results from Imbalance of Excitation
and Inhibition 89
6.7 Conduction of Action Potentials in the Axon during Normal
and Epileptiform Activity 89
6.8 Traveling of Subthreshold Potentials in the Axon 90
6.9 Modulation of Intracortical Synaptic Transmission by Presynaptic
Somatic Membrane Potential 91
6.10 Mechanisms Underlying EPSP Facilitation Induced
by Somatic Depolarization 93
6.11 Summary 94
6.12 Acknowledgments 94
References 94
7 Epilepsy as a Disease of the Dynamics of
Neuronal Networks - Models and Predictions 97
Fernando Lopes da Silva
7.1 Introduction 97
7.2 Experimental Observations - Case 1: The WAG/Rij Rat
as a Genetic Model for Absence Epilepsy 98
7.3 Computational Model of the Thalamo-Cortical
Neuronal Networks 99
7.4 Model Predictions 100
7.5 Experimental Observations - Case 2: Hippocampal
Seizures 103
VIM I Contents
7.6 Active Observation: Stimulation with 'Carrier Frequency' -
Changes in Phase Clustering Index (PCI) 104
7.7 Conclusion 106
References 107
8 Neuronal Synchronization and the 'Ictio-centric' vs the Network
Theory for Ictiogenesis: Mechanistic and Therapeutic
Implications for Clinical Epileptology 109
Ivan Osorio, Mark C. Frei, Ying-Cheng Lai
8.1 Seizures and Neuronal Synchronization:
Increased or Decreased Relative to Interictal Values? 109
8.2 The 'Focus' ('Ictio-centric') vs the Network Theory
in Ictiogenesis 112
References 114
9 Cellular Neural Networks and Seizure Prediction:
An Overview 117
P. Fischer, F. Collas, R. Kunz, C. Niederhbfer, H. Reichau,
R. Tetzlaff
9.1 Introduction: Cellular Neural Networks 117
9.2 Spatio-temporal Signal Prediction in Epilepsy by Delay-type
Discrete-time Cellular Nonlinear Networks (DT-CNN) 119
9.3 Identification of EEG-signals by Reaction-Diffusion CNN 121
9.4 A CNN-based Pattern Detection Algorithm 123
9.4.1 Preprocessing the Data 124
9.4.2 Performing the Pattern Detection 124
9.4.3 Detecting Seizures by POI Evaluation 125
9.5 CNN for Approximation of the Effective Correlation
Dimension in Epilepsy 126
References 128
10 Time Series Analysis with Cellular Neural Networks 131
Anton Chernihovskyi, Dieter Krug, Christian E. Elger,
Klaus Lehnertz
10.1 Introduction 131
10.2 Cellular Neural Networks 132
10.3 An Analytical CNN-based Method for Pattern
Detection in Non-stationary and Noisy Time
Series 134
10.4 An Adaptive CNN-based Method to Measure
Synchronization 138
10.4.1 Learning Synchronization in EEG Time Series
with CNN 141
10.5 Conclusions and Outlook 144
References 145
Contents I IX
11 Intrinsic Cortical Mechanisms which Oppose Epileptiform Activity:
Implications for Seizure Prediction 149
AndrewJ. Trevelyan
11.1 Introduction 149
11.2 The Inhibitory Surround in Cortex: In Vivo Studies 150
11.3 In Vitro Studies: Strengths and Weaknesses 151
11.4 Inhibitory Surround in an In Vitro Preparation 153
11.5 Models of the Inhibitory Surround: The Importance
of how Synaptic Inputs are Distributed 157
11.6 Surround Inhibition: Implications for Seizure Prediction 158
References 159
12 Is Prediction of the Time of a Seizure Onset the Only Value
of Seizure-prediction Studies? 163
Anatol Bragin, Jerome Engeljr
12.1 Purpose of Seizure-prediction Research 163
12.2 Seizure Onsets in Patients with MTLE 164
12.3 Factors Triggering Seizure Activity 164
12.4 Simulating Human Electrographic Patterns of Seizure Onsets
in Acute In Vivo Animal Experiments 165
12.5 Conclusions 166
References 167
13 High-frequency Pre-seizure Activity and Seizure Prediction 169
Premysljiruska, John C. R. Jefferys
References 172
14 Characterizing the Epileptic Process with Stochastic Qualifiers
of Brain Dynamics 175
Jens Prusseit, Christian E. Elger, Klaus Lehnertz
14.1 Introduction 175
14.2 Data-driven Fokker-Planck Models 176
14.3 EEG Analysis 178
14.3.1 Markov Property and Characteristics of Estimated
Kramers-Moyal Coefficients 178
14.3.2 Relevance for a Spatial and Temporal Characterization
of the Epileptic Process 182
14.4 Conclusions 185
References 185
15 Bivariate and Multivariate Time Series Analysis
Techniques and their Potential Impact for Seizure Prediction 189
Hannes Osterhage, Stephan Bialonski, Matthews Staniek,
Kaspar Schindler, Tobias Wagner, Christian E. Elger, Klaus Lehnertz
15.1 Introduction 189
15.2 Bivariate Time Series Analysis Techniques 190
i
X I Contents
15.2.1 Measures of Synchronization 190
15.2.2 Phase Synchronization 191
15.2.3 Generalized Synchronization 192
15.3 Information Theoretic Measures 194
15.4 Exemplary Applications 195
15.5 Multivariate Time Series Analysis Techniques 199
15.5.1 Approaches Based on Random Matrix Theory 199
15.5.2 Approaches Based on Network Theory 202
15.6 Conclusions 204
References 204
16 A Multivariate Approach to Correlation Analysis Based on Random
Matrix Theory 209
Markus Muller, Gerold Baier, Christian Rummel, Kaspar Schindler,
Ulrich Stephani
16.1 Introduction 209
16.2 The Equal-time Correlation Matrix 210
16.3 Eigenvalues, Eigenvectors and Interrelations between
Data Channels 211
16.4 Random and Non-random Level Repulsion 213
16.5 RMT Measures: Motivation and Definition 215
16.6 Application to a Test System 218
16.7 Cluster Detection based on Eigenvectors 221
16.8 Application to EEG Recordings 223
16.9 Conclusions 224
References 225
17 Seizure Prediction in Epilepsy: Does a Combination
of Methods Help? 227
Hinnerk Feldwisch genannt Drentrup, Michael Jachan,
Bjbrn Schelter
17.1 Introduction 227
17.2 Materials and Methods 228
17.2.1 The Seizure-prediction Characteristic 228
17.2.2 Combination of Individual Prediction Methods 229
17.2.3 Patient Characteristics 231
17.3 Results 232
17.4 Discussion 234
17.5 Acknowledgments 235
References 235
18 Can Your Prediction Algorithm Beat a Random Predictor? 237
Bjbrn Schelter, Ralph C. Andrzejak, Florian Mormann
18.1 Introduction 237
18.2 Performance Assessment 238
Contents I XI
18.2.1 General Methodology of Seizure Prediction 238
18.2.2 The ROC Curve 239
18.2.3 The Seizure-prediction Characteristic 240
18.3 Statistical Validation 241
18.3.1 The Analytic Random Predictor 241
18.3.2 Bootstrapping Techniques 244
18.4 Conclusion 247
18.5 Acknowledgments 247
References 248
19 Testing a Prediction Algorithm: Assessment of Performance 249
J. Chris Sackellares, Deng-Shan Shiau, Kevin M. Kelly,
Sandeep P. Nair
19.1 Introduction 249
19.2 Correlation between Study Design and Clinical
Application 251
19.3 Statistical Hypothesis 252
19.4 Statistical Justification 253
19.4.1 Prediction Sensitivity 254
19.4.2 False-positive Rate 255
19.5 Discussion and Conclusion 255
References 257
20 Considerations on Database Requirements
for Seizure Prediction 261
Carolin Cierschner, Andreas Schulze-Bonhage
20.1 Introduction 261
20.2 General Requirements for a Prediction Database 262
20.3 Raw Data 262
20.3.1 Annotations to Raw Data 263
20.4 Metadata on Telemetry 264
20.5 Metadata on the Clinically Defined Epilepsy Syndrome 265
20.6 Database Structure 266
References 267
21 Beyond Prediction - Focal Cooling and Optical Activation
to Terminate Focal Seizures 269
Steven M. Rothman
21.1 Introduction 269
21.1.1 Scope of the Problem 269
21.1.2 Alternatives to Permanent Resection
for Neocortical Epilepsy 270
21.2 Cooling and the Brain 271
21.2.1 Methods for Cooling 272
21.2.2 Results of Cooling Experimental Seizures 273
XII I Contents
21.2.3 Future Plans for Cooling 275
21.3 Focal Uncaging for Epilepsy 277
21.3.1 Early Results with Uncaging 278
21.3.2 Uncaging BC204 Suppresses 'Seizure-like'
Activity 279
21.3.3 Future Plans for in vivo Uncaging 280
21.4 Acknowledgments 281
References 281
22 Vagus Nerve and Hippocampal Stimulation
for Refractory Epilepsy 283
Paul Boon, Veerle De Herdt, Annelies Van Dycke, Tine Wyckhuys,
Liesbeth Waterschoot, Riem El Tahry, Dirk Van Roost,
Robrecht Raedt, Wytse Wadman, Kristl Vonck
22.1 Introduction 283
22.2 Vagus Nerve Stimulation 285
22.2.1 Clinical Efficacy and Safety 285
22.2.1.1 Randomised Controlled Trials 285
22.2.1.2 Clinical Trials with Long-term Follow-up 286
22.2.2 Safety, Side-effects and Tolerability 287
22.2.2.1 Ramping up and Long-term Stimulation 287
22.2.2.2 MRI 289
22.2.3 Mechanism of Action 290
22.3 Hippocampal Stimulation 292
22.3.1 Clinical Efficacy and Safety 292
22.3.2 Mechanism of Action 293
22.4 Conclusion 293
References 294
23 Responsive Neurostimulation for the Treatment
of Epileptic Seizures 299
Gregory K. Bergey
23.1 Introduction 299
23.2 Characteristics of Partial Seizures 299
23.3 Types of Neurostimulation 300
23.4 Current Status of Investigations of Responsive
Neurostimulation 302
23.5 Conclusion 305
References 306
24 Chronic Anterior Thalamic Deep-brain
Stimulation as a Treatment for Intractable Epilepsy 307
Richard Wennberg
24.1 Introduction 307
24.2 Anterior Thalamus DBS for Epilepsy 308
24.3 EEG Recordings 313
Contents I XIII
24.4 Conclusions 314
References 315
25 Thoughts about Seizure Prediction from the
Perspective of a Clinical Neurophysiologist 317
Demetrios N. Velis
25.1 Introduction 317
25.2 Appendix: Does the EEGer Need Seizure Prediction? 321
References 322
26 State of Seizure Prediction: A Report on Informal Discussions
with Participants of the Third International Workshop
on Seizure Prediction 325
Hitten P. Zaveri, Mark C. Frei, Ivan Osorio
26.1 Introduction 325
26.2 Modality 327
26.3 Seizure Generation and Models 327
26.4 Academia and Industry 328
26.5 The Question of Seizure Prediction and its Prioritization 328
26.6 Summary 329
26.7 Acknowledgement 330
Index 331 |
| adam_txt |
Iv
Contents
Preface XV
Thanks to the Sponsors of the Workshop XVII
List of Contributors XIX
Color Plates XXVII
1 Unpredictability of Seizures and the Burden of Epilepsy 1
Andreas Schulze-Bonhage, Anne Kuhn
1.1 Introduction 1
1.2 Medical Implications of Unpredictability 2
1.2.1 Diagnostic Uncertainty 2
1.2.2 Treatment Options 2
1.2.3 Physical Risks 3
1.2.4 Risks Associated with Continuous Long-term
Antiepileptic Treatment 4
1.3 Psychosocial Consequences of Unpredictability 4
1.3.1 Loss of Control 4
1.3.2 Problems with Coping Strategies 6
1.3.3 Depression and Anxiety 6
1.3.4 Immobility and Vocational Restrictions 7
1.4 Conclusion 8
References 8
2 The History of Seizure Prediction 12
M. Jachan, H. Feldwisch genannt Drentrup, B. Schelter,
J. Timmer
2.1 Introduction 11
2.2 Motivation 11
2.2.1 The Need for a Seizure-prediction Device 12
2.2.2 The Assumed Preictal Phase 14
2.3 A Historical Overview 15
2.3.1 Older Types of Studies 16
Seizure Prediction in Epilepsy. Edited by Bjbrn Schelter, Jens Timmer and Andreas Schulze-Bonhage
Copyright © 2008 WILEY-VCH Verlag GmbH Co. KGaA, Weinheim
ISBN: 978-3-527-4O756-9
VI I Contents
2.3.2 Modern Types of Studies 16
2.3.3 Survey of Prediction Methods 17
2.4 The State of the Art in Seizure Prediction 19
2A.I Partially Solved Issues 19
2.4.2 Unsolved Issues 20
2.5 Seizure Prediction in the Future 21
References 22
3 Impact of Computational Models for an Improved Understanding
of Ictogenesis: From Single Neurons to Networks of Neurons 25
Marie-Therese Horstmann, Andy M'uller, Alexander Rothkegel,
Justus Schwabedal, Christian E. Elger, Klaus Lehnertz
3.1 Introduction 25
3.2 Single Neuron Models 27
3.2.1 Conductance-based Models 28
3.2.2 Single Neuron Models and Epilepsy 29
3.3 Neural Networks 31
3.3.1 Network Characteristics 32
3.4 Neural Mass Models of the EEG 35
3.5 Conclusion 38
References 39
4 Effective and Anatomical Connectivity in a Rat Model of
Spontaneous Limbic Seizure 45
Paul R. Carney, Alex Cadotte, Thomas B. DeMarse, Baba Vemuri,
Thomas H. Mareci, William Ditto
4.1 Introduction 45
4.2 Granger Causality 46
4.2.1 Analysis of Temporal Lobe Seizures 48
4.2.2 Results 50
4.2.3 Discussion 52
4.3 Structural Visualization with Magnetic Resonance 54
4.3.1 Diffusion Tensor Imaging 54
4.3.2 High Angular Resolution Diffusion Imaging 55
4.4 Acknowledgments 57
References 58
5 Network Models of Epileptiform Activity: Explorations in Seizure
Evolution and Alteration 61
Pawel Kudela, William S. Anderson, PiotrJ. Franaszczuk,
Gregory K. Bergey
5.1 Introduction 61
5.2 Time-frequency Analyses of Seizure Dynamics
and Evolution 62
5.3 Model Assumptions and Modeling Approach 63
\
Contents I VII
5.4 Recurrent Neuronal Bursting and Mechanism of Burst
Frequency Decline 64
5.5 Network Models of Epileptiform Activity Disruption
by External Stimulation 67
5.6 Chain Network Model Studies 69
5.7 Networks with Realistic Cortical Architecture 71
5.8 Conclusions 79
5.9 Acknowledgment 80
5.10 Appendix 80
References 81
6 Recurrent Cortical Network Activity and Modulation
of Synaptic Transmission 83
Yousheng Shu
6.1 Introduction 83
6.2 The Ability of the Cortical Network to Generate
Recurrent Activity 84
6.3 Cortical Network Activity as Propagating Electrical Waves 85
6.4 Balance of Excitation and Inhibition during Cortical
Network Activity 86
6.5 Initiation and Termination of Cortical Network
Activity by Electrical Shock 86
6.6 Epileptiform Activity Results from Imbalance of Excitation
and Inhibition 89
6.7 Conduction of Action Potentials in the Axon during Normal
and Epileptiform Activity 89
6.8 Traveling of Subthreshold Potentials in the Axon 90
6.9 Modulation of Intracortical Synaptic Transmission by Presynaptic
Somatic Membrane Potential 91
6.10 Mechanisms Underlying EPSP Facilitation Induced
by Somatic Depolarization 93
6.11 Summary 94
6.12 Acknowledgments 94
References 94
7 Epilepsy as a Disease of the Dynamics of
Neuronal Networks - Models and Predictions 97
Fernando Lopes da Silva
7.1 Introduction 97
7.2 Experimental Observations - Case 1: The WAG/Rij Rat
as a Genetic Model for Absence Epilepsy 98
7.3 Computational Model of the Thalamo-Cortical
Neuronal Networks 99
7.4 Model Predictions 100
7.5 Experimental Observations - Case 2: Hippocampal
Seizures 103
VIM I Contents
7.6 Active Observation: Stimulation with 'Carrier Frequency' -
Changes in Phase Clustering Index (PCI) 104
7.7 Conclusion 106
References 107
8 Neuronal Synchronization and the 'Ictio-centric' vs the Network
Theory for Ictiogenesis: Mechanistic and Therapeutic
Implications for Clinical Epileptology 109
Ivan Osorio, Mark C. Frei, Ying-Cheng Lai
8.1 Seizures and Neuronal Synchronization:
Increased or Decreased Relative to Interictal Values? 109
8.2 The 'Focus' ('Ictio-centric') vs the Network Theory
in Ictiogenesis 112
References 114
9 Cellular Neural Networks and Seizure Prediction:
An Overview 117
P. Fischer, F. Collas, R. Kunz, C. Niederhbfer, H. Reichau,
R. Tetzlaff
9.1 Introduction: Cellular Neural Networks 117
9.2 Spatio-temporal Signal Prediction in Epilepsy by Delay-type
Discrete-time Cellular Nonlinear Networks (DT-CNN) 119
9.3 Identification of EEG-signals by Reaction-Diffusion CNN 121
9.4 A CNN-based Pattern Detection Algorithm 123
9.4.1 Preprocessing the Data 124
9.4.2 Performing the Pattern Detection 124
9.4.3 Detecting Seizures by POI Evaluation 125
9.5 CNN for Approximation of the Effective Correlation
Dimension in Epilepsy 126
References 128
10 Time Series Analysis with Cellular Neural Networks 131
Anton Chernihovskyi, Dieter Krug, Christian E. Elger,
Klaus Lehnertz
10.1 Introduction 131
10.2 Cellular Neural Networks 132
10.3 An Analytical CNN-based Method for Pattern
Detection in Non-stationary and Noisy Time
Series 134
10.4 An Adaptive CNN-based Method to Measure
Synchronization 138
10.4.1 Learning Synchronization in EEG Time Series
with CNN 141
10.5 Conclusions and Outlook 144
References 145
Contents I IX
11 Intrinsic Cortical Mechanisms which Oppose Epileptiform Activity:
Implications for Seizure Prediction 149
AndrewJ. Trevelyan
11.1 Introduction 149
11.2 The Inhibitory Surround in Cortex: In Vivo Studies 150
11.3 In Vitro Studies: Strengths and Weaknesses 151
11.4 Inhibitory Surround in an In Vitro Preparation 153
11.5 Models of the Inhibitory Surround: The Importance
of how Synaptic Inputs are Distributed 157
11.6 Surround Inhibition: Implications for Seizure Prediction 158
References 159
12 Is Prediction of the Time of a Seizure Onset the Only Value
of Seizure-prediction Studies? 163
Anatol Bragin, Jerome Engeljr
12.1 Purpose of Seizure-prediction Research 163
12.2 Seizure Onsets in Patients with MTLE 164
12.3 Factors Triggering Seizure Activity 164
12.4 Simulating Human Electrographic Patterns of Seizure Onsets
in Acute In Vivo Animal Experiments 165
12.5 Conclusions 166
References 167
13 High-frequency Pre-seizure Activity and Seizure Prediction 169
Premysljiruska, John C. R. Jefferys
References 172
14 Characterizing the Epileptic Process with Stochastic Qualifiers
of Brain Dynamics 175
Jens Prusseit, Christian E. Elger, Klaus Lehnertz
14.1 Introduction 175
14.2 Data-driven Fokker-Planck Models 176
14.3 EEG Analysis 178
14.3.1 Markov Property and Characteristics of Estimated
Kramers-Moyal Coefficients 178
14.3.2 Relevance for a Spatial and Temporal Characterization
of the Epileptic Process 182
14.4 Conclusions 185
References 185
15 Bivariate and Multivariate Time Series Analysis
Techniques and their Potential Impact for Seizure Prediction 189
Hannes Osterhage, Stephan Bialonski, Matthews Staniek,
Kaspar Schindler, Tobias Wagner, Christian E. Elger, Klaus Lehnertz
15.1 Introduction 189
15.2 Bivariate Time Series Analysis Techniques 190
i
X I Contents
15.2.1 Measures of Synchronization 190
15.2.2 Phase Synchronization 191
15.2.3 Generalized Synchronization 192
15.3 Information Theoretic Measures 194
15.4 Exemplary Applications 195
15.5 Multivariate Time Series Analysis Techniques 199
15.5.1 Approaches Based on Random Matrix Theory 199
15.5.2 Approaches Based on Network Theory 202
15.6 Conclusions 204
References 204
16 A Multivariate Approach to Correlation Analysis Based on Random
Matrix Theory 209
Markus Muller, Gerold Baier, Christian Rummel, Kaspar Schindler,
Ulrich Stephani
16.1 Introduction 209
16.2 The Equal-time Correlation Matrix 210
16.3 Eigenvalues, Eigenvectors and Interrelations between
Data Channels 211
16.4 Random and Non-random Level Repulsion 213
16.5 RMT Measures: Motivation and Definition 215
16.6 Application to a Test System 218
16.7 Cluster Detection based on Eigenvectors 221
16.8 Application to EEG Recordings 223
16.9 Conclusions 224
References 225
17 Seizure Prediction in Epilepsy: Does a Combination
of Methods Help? 227
Hinnerk Feldwisch genannt Drentrup, Michael Jachan,
Bjbrn Schelter
17.1 Introduction 227
17.2 Materials and Methods 228
17.2.1 The Seizure-prediction Characteristic 228
17.2.2 Combination of Individual Prediction Methods 229
17.2.3 Patient Characteristics 231
17.3 Results 232
17.4 Discussion 234
17.5 Acknowledgments 235
References 235
18 Can Your Prediction Algorithm Beat a Random Predictor? 237
Bjbrn Schelter, Ralph C. Andrzejak, Florian Mormann
18.1 Introduction 237
18.2 Performance Assessment 238
Contents I XI
18.2.1 General Methodology of Seizure Prediction 238
18.2.2 The ROC Curve 239
18.2.3 The Seizure-prediction Characteristic 240
18.3 Statistical Validation 241
18.3.1 The Analytic Random Predictor 241
18.3.2 Bootstrapping Techniques 244
18.4 Conclusion 247
18.5 Acknowledgments 247
References 248
19 Testing a Prediction Algorithm: Assessment of Performance 249
J. Chris Sackellares, Deng-Shan Shiau, Kevin M. Kelly,
Sandeep P. Nair
19.1 Introduction 249
19.2 Correlation between Study Design and Clinical
Application 251
19.3 Statistical Hypothesis 252
19.4 Statistical Justification 253
19.4.1 Prediction Sensitivity 254
19.4.2 False-positive Rate 255
19.5 Discussion and Conclusion 255
References 257
20 Considerations on Database Requirements
for Seizure Prediction 261
Carolin Cierschner, Andreas Schulze-Bonhage
20.1 Introduction 261
20.2 General Requirements for a Prediction Database 262
20.3 Raw Data 262
20.3.1 Annotations to Raw Data 263
20.4 Metadata on Telemetry 264
20.5 Metadata on the Clinically Defined Epilepsy Syndrome 265
20.6 Database Structure 266
References 267
21 Beyond Prediction - Focal Cooling and Optical Activation
to Terminate Focal Seizures 269
Steven M. Rothman
21.1 Introduction 269
21.1.1 Scope of the Problem 269
21.1.2 Alternatives to Permanent Resection
for Neocortical Epilepsy 270
21.2 Cooling and the Brain 271
21.2.1 Methods for Cooling 272
21.2.2 Results of Cooling Experimental Seizures 273
XII I Contents
21.2.3 Future Plans for Cooling 275
21.3 Focal Uncaging for Epilepsy 277
21.3.1 Early Results with Uncaging 278
21.3.2 Uncaging BC204 Suppresses 'Seizure-like'
Activity 279
21.3.3 Future Plans for in vivo Uncaging 280
21.4 Acknowledgments 281
References 281
22 Vagus Nerve and Hippocampal Stimulation
for Refractory Epilepsy 283
Paul Boon, Veerle De Herdt, Annelies Van Dycke, Tine Wyckhuys,
Liesbeth Waterschoot, Riem El Tahry, Dirk Van Roost,
Robrecht Raedt, Wytse Wadman, Kristl Vonck
22.1 Introduction 283
22.2 Vagus Nerve Stimulation 285
22.2.1 Clinical Efficacy and Safety 285
22.2.1.1 Randomised Controlled Trials 285
22.2.1.2 Clinical Trials with Long-term Follow-up 286
22.2.2 Safety, Side-effects and Tolerability 287
22.2.2.1 Ramping up and Long-term Stimulation 287
22.2.2.2 MRI 289
22.2.3 Mechanism of Action 290
22.3 Hippocampal Stimulation 292
22.3.1 Clinical Efficacy and Safety 292
22.3.2 Mechanism of Action 293
22.4 Conclusion 293
References 294
23 Responsive Neurostimulation for the Treatment
of Epileptic Seizures 299
Gregory K. Bergey
23.1 Introduction 299
23.2 Characteristics of Partial Seizures 299
23.3 Types of Neurostimulation 300
23.4 Current Status of Investigations of Responsive
Neurostimulation 302
23.5 Conclusion 305
References 306
24 Chronic Anterior Thalamic Deep-brain
Stimulation as a Treatment for Intractable Epilepsy 307
Richard Wennberg
24.1 Introduction 307
24.2 Anterior Thalamus DBS for Epilepsy 308
24.3 EEG Recordings 313
Contents I XIII
24.4 Conclusions 314
References 315
25 Thoughts about Seizure Prediction from the
Perspective of a Clinical Neurophysiologist 317
Demetrios N. Velis
25.1 Introduction 317
25.2 Appendix: Does the EEGer Need Seizure Prediction? 321
References 322
26 State of Seizure Prediction: A Report on Informal Discussions
with Participants of the Third International Workshop
on Seizure Prediction 325
Hitten P. Zaveri, Mark C. Frei, Ivan Osorio
26.1 Introduction 325
26.2 Modality 327
26.3 Seizure Generation and Models 327
26.4 Academia and Industry 328
26.5 The Question of Seizure Prediction and its Prioritization 328
26.6 Summary 329
26.7 Acknowledgement 330
Index 331 |
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| any_adam_object_boolean | 1 |
| author2 | Schelter, Björn |
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| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| discipline_str_mv | Medizin |
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| spelling | Seizure prediction in epilepsy from basic mechanisms to clinical applications ed. by Björn Schelter ... Weinheim WILEY-VCH 2008 XXXV, 334 S. Ill., graph. Darst. 25 cm txt rdacontent n rdamedia nc rdacarrier Literaturangaben Convulsions Forecasting Deep Brain Stimulation Congresses Epilepsy Epilepsy therapy Congresses Forecasting methods Congresses Models, Neurological Congresses Risk Assessment Congresses Seizures prevention & control Congresses Nervennetz (DE-588)4041638-0 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Epileptischer Anfall (DE-588)4296181-6 gnd rswk-swf Epilepsie (DE-588)4015035-5 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 2007 Freiburg im Breisgau gnd-content Epileptischer Anfall (DE-588)4296181-6 s Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s DE-604 Epilepsie (DE-588)4015035-5 s Schelter, Björn (DE-588)132505487 edt text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3059962&prov=M&dok_var=1&dok_ext=htm Inhaltstext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016957743&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Seizure prediction in epilepsy from basic mechanisms to clinical applications Convulsions Forecasting Deep Brain Stimulation Congresses Epilepsy Epilepsy therapy Congresses Forecasting methods Congresses Models, Neurological Congresses Risk Assessment Congresses Seizures prevention & control Congresses Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Epileptischer Anfall (DE-588)4296181-6 gnd Epilepsie (DE-588)4015035-5 gnd |
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| title | Seizure prediction in epilepsy from basic mechanisms to clinical applications |
| title_auth | Seizure prediction in epilepsy from basic mechanisms to clinical applications |
| title_exact_search | Seizure prediction in epilepsy from basic mechanisms to clinical applications |
| title_exact_search_txtP | Seizure prediction in epilepsy from basic mechanisms to clinical applications |
| title_full | Seizure prediction in epilepsy from basic mechanisms to clinical applications ed. by Björn Schelter ... |
| title_fullStr | Seizure prediction in epilepsy from basic mechanisms to clinical applications ed. by Björn Schelter ... |
| title_full_unstemmed | Seizure prediction in epilepsy from basic mechanisms to clinical applications ed. by Björn Schelter ... |
| title_short | Seizure prediction in epilepsy |
| title_sort | seizure prediction in epilepsy from basic mechanisms to clinical applications |
| title_sub | from basic mechanisms to clinical applications |
| topic | Convulsions Forecasting Deep Brain Stimulation Congresses Epilepsy Epilepsy therapy Congresses Forecasting methods Congresses Models, Neurological Congresses Risk Assessment Congresses Seizures prevention & control Congresses Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Epileptischer Anfall (DE-588)4296181-6 gnd Epilepsie (DE-588)4015035-5 gnd |
| topic_facet | Convulsions Forecasting Deep Brain Stimulation Congresses Epilepsy Epilepsy therapy Congresses Forecasting methods Congresses Models, Neurological Congresses Risk Assessment Congresses Seizures prevention & control Congresses Nervennetz Modell Epileptischer Anfall Epilepsie Konferenzschrift 2007 Freiburg im Breisgau |
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