360
K. Lehnertz
152. S.H. Strogatz, Exploring complex networks. Nature 410, 268–276 (2001). https://doi.org/10.
1038/35065725
153. R. Surges, J.W. Sander, Sudden unexpected death in epilepsy: mechanisms, prevalence, and
prevention. Curr. Opin. Neurol. 25, 201–207 (2012)
154. E. Taubøll, A. Lundervold, L. Gjerstada, Temporal distribution of seizures in epilepsy.
Epilepsy Res. 8, 153–165 (1991)
155. C.A. Teixeira, B. Direito, M. Bandarabadi, M.L.V. Quyen, M. Valderrama, B. Schelter, A.
Schulze-Bonhage, V. Navarro, F. Sales, A. Dourado, Epileptic seizure predictors based on
computational intelligence techniques: a comparative study with 278 patients. Comput. Meth.
Prog. Biomed. 114, 324–336 (2014). https://doi.org/10.1016/j.cmpb.2014.02.007
156. S.M. Usman, S. Khalid, R. Akhtar, Z. Bortolotto, Z. Bashir, H. Qiu, Using scalp EEG and
intracranial EEG signals for predicting epileptic seizures: review of available methodologies.
Seizure 71, 258–269 (2019)
157. W. Van Drongelen, S. Nayak, D.M. Frim, M.H. Kohrman, V.L. Towle, H.C. Lee, A.B. McGee,
M.S. Chico, K.E. Hecox, Seizure anticipation in pediatric epilepsy: use of Kolmogorov
entropy. Ped. Neurol. 29, 207–213 (2003)
158. P. Van Mierlo, M. Papadopoulou, E. Carrette, P. Boon, S. Vandenberghe, K. Vonck, D. Marinazzo, Functional brain connectivity from EEG in epilepsy: seizure prediction and epileptogenic focus localization. Prog. Neurobiol. 121, 19–35 (2014)
159. G. Varotto, L. Tassi, S. Franceschetti, R. Spreafico, F. Panzica, Epileptogenic networks of
type II focal cortical dysplasia: a stereo-EEG study. NeuroImage 61, 591–598 (2012). https://
doi.org/10.1016/j.neuroimage.2012.03.090
160. J.B. Wagenaar, G.A. Worrell, Z. Ives, M. Dümpelmann, B. Litt, A. Schulze-Bonhage, Collaborating and sharing data in epilepsy research. J. Clin. Neurophysiol. 32, 235 (2015)
161. T.S. Walczak, R.A. Radtke, D.V. Lewis, Accuracy and interobserver reliability of scalp ictal
EEG. Neurology 42(12), 2279-2279 (1992)
162. S. Weisdorf, J. Duun-Henriksen, M.J. Kjeldsen, F.R. Poulsen, S.W. Gangstad, T.W. Kjær,
Ultra-long-term subcutaneous home monitoring of epilepsy–490 days of EEG from nine
patients. Epilepsia 60, 2204–2214 (2019)
163. F. Wendling, P. Benquet, F. Bartolomei, V. Jirsa, Computational models of epileptiform activity. J. Neurosci. Methods 260, 233–251 (2016)
164. T. Wilkat, T. Rings, K. Lehnertz, No evidence for critical slowing down prior to human
epileptic seizures. Chaos 29, 091104 (2019)
165. C. Wilke, G. Worrell, B. He, Graph analysis of epileptogenic networks in human partial
epilepsy. Epilepsia 52, 84–93 (2011). https://doi.org/10.1111/j.1528-1167.2010.02785.x
166. J.R. Williamson, D.W. Bliss, D.W. Browne, J.T. Narayanan, Seizure prediction using EEG
spatiotemporal correlation structure. Epilepsy Behav. 25, 230–238 (2012)
167. M. Winterhalder, T. Maiwald, H.U. Voss, R. Aschenbrenner-Scheibe, J. Timmer, A. SchulzeBonhage, The seizure prediction characteristic: a general framework to assess and compare
seizure prediction methods. Epilepsy Behav. 3, 318–325 (2003)
168. M. Winterhalder, B. Schelter, T. Maiwald, A. Brandt, A. Schad, A. Schulze-Bonhage, J. Timmer, Spatio-temporal patient-individual assessment of synchronization changes for epileptic
seizure prediction. Clin. Neurophysiol. 117, 2399–2413 (2006)
169. S. Wong, A.B. Gardner, A.M. Krieger, B. Litt, A stochastic framework for evaluating seizure
prediction algorithms using hidden Markov models. J. Neurophysiol. 97, 2525–2532 (2007)
170. Y. Zheng, G. Wang, K. Li, G. Bao, J. Wang, Epileptic seizure prediction using phase synchronization based on bivariate empirical mode decomposition. Clin. Neurophysiol. 125,
1104–1111 (2014). https://doi.org/10.1016/j.clinph.2013.09.047
K. Lehnertz
152. S.H. Strogatz, Exploring complex networks. Nature 410, 268–276 (2001). https://doi.org/10.
1038/35065725
153. R. Surges, J.W. Sander, Sudden unexpected death in epilepsy: mechanisms, prevalence, and
prevention. Curr. Opin. Neurol. 25, 201–207 (2012)
154. E. Taubøll, A. Lundervold, L. Gjerstada, Temporal distribution of seizures in epilepsy.
Epilepsy Res. 8, 153–165 (1991)
155. C.A. Teixeira, B. Direito, M. Bandarabadi, M.L.V. Quyen, M. Valderrama, B. Schelter, A.
Schulze-Bonhage, V. Navarro, F. Sales, A. Dourado, Epileptic seizure predictors based on
computational intelligence techniques: a comparative study with 278 patients. Comput. Meth.
Prog. Biomed. 114, 324–336 (2014). https://doi.org/10.1016/j.cmpb.2014.02.007
156. S.M. Usman, S. Khalid, R. Akhtar, Z. Bortolotto, Z. Bashir, H. Qiu, Using scalp EEG and
intracranial EEG signals for predicting epileptic seizures: review of available methodologies.
Seizure 71, 258–269 (2019)
157. W. Van Drongelen, S. Nayak, D.M. Frim, M.H. Kohrman, V.L. Towle, H.C. Lee, A.B. McGee,
M.S. Chico, K.E. Hecox, Seizure anticipation in pediatric epilepsy: use of Kolmogorov
entropy. Ped. Neurol. 29, 207–213 (2003)
158. P. Van Mierlo, M. Papadopoulou, E. Carrette, P. Boon, S. Vandenberghe, K. Vonck, D. Marinazzo, Functional brain connectivity from EEG in epilepsy: seizure prediction and epileptogenic focus localization. Prog. Neurobiol. 121, 19–35 (2014)
159. G. Varotto, L. Tassi, S. Franceschetti, R. Spreafico, F. Panzica, Epileptogenic networks of
type II focal cortical dysplasia: a stereo-EEG study. NeuroImage 61, 591–598 (2012). https://
doi.org/10.1016/j.neuroimage.2012.03.090
160. J.B. Wagenaar, G.A. Worrell, Z. Ives, M. Dümpelmann, B. Litt, A. Schulze-Bonhage, Collaborating and sharing data in epilepsy research. J. Clin. Neurophysiol. 32, 235 (2015)
161. T.S. Walczak, R.A. Radtke, D.V. Lewis, Accuracy and interobserver reliability of scalp ictal
EEG. Neurology 42(12), 2279-2279 (1992)
162. S. Weisdorf, J. Duun-Henriksen, M.J. Kjeldsen, F.R. Poulsen, S.W. Gangstad, T.W. Kjær,
Ultra-long-term subcutaneous home monitoring of epilepsy–490 days of EEG from nine
patients. Epilepsia 60, 2204–2214 (2019)
163. F. Wendling, P. Benquet, F. Bartolomei, V. Jirsa, Computational models of epileptiform activity. J. Neurosci. Methods 260, 233–251 (2016)
164. T. Wilkat, T. Rings, K. Lehnertz, No evidence for critical slowing down prior to human
epileptic seizures. Chaos 29, 091104 (2019)
165. C. Wilke, G. Worrell, B. He, Graph analysis of epileptogenic networks in human partial
epilepsy. Epilepsia 52, 84–93 (2011). https://doi.org/10.1111/j.1528-1167.2010.02785.x
166. J.R. Williamson, D.W. Bliss, D.W. Browne, J.T. Narayanan, Seizure prediction using EEG
spatiotemporal correlation structure. Epilepsy Behav. 25, 230–238 (2012)
167. M. Winterhalder, T. Maiwald, H.U. Voss, R. Aschenbrenner-Scheibe, J. Timmer, A. SchulzeBonhage, The seizure prediction characteristic: a general framework to assess and compare
seizure prediction methods. Epilepsy Behav. 3, 318–325 (2003)
168. M. Winterhalder, B. Schelter, T. Maiwald, A. Brandt, A. Schad, A. Schulze-Bonhage, J. Timmer, Spatio-temporal patient-individual assessment of synchronization changes for epileptic
seizure prediction. Clin. Neurophysiol. 117, 2399–2413 (2006)
169. S. Wong, A.B. Gardner, A.M. Krieger, B. Litt, A stochastic framework for evaluating seizure
prediction algorithms using hidden Markov models. J. Neurophysiol. 97, 2525–2532 (2007)
170. Y. Zheng, G. Wang, K. Li, G. Bao, J. Wang, Epileptic seizure prediction using phase synchronization based on bivariate empirical mode decomposition. Clin. Neurophysiol. 125,
1104–1111 (2014). https://doi.org/10.1016/j.clinph.2013.09.047