@article{LehnertzAnsmannBialonskietal.2014, author = {Lehnertz, Klaus and Ansmann, Gerrit and Bialonski, Stephan and Dickten, Henning and Geier, Christian and Porz, Stephan}, title = {Evolving networks in the human epileptic brain}, series = {Physica D: Nonlinear Phenomena}, volume = {267}, journal = {Physica D: Nonlinear Phenomena}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0167-2789}, doi = {10.1016/j.physd.2013.06.009}, pages = {7 -- 15}, year = {2014}, abstract = {Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.}, language = {en} } @article{SchwabedalSippelBrandtetal.2018, author = {Schwabedal, Justus T. C. and Sippel, Daniel and Brandt, Moritz D. and Bialonski, Stephan}, title = {Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning}, doi = {10.48550/arXiv.1809.08443}, year = {2018}, abstract = {Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle.}, language = {en} } @article{KarnatakKantzBialonski2017, author = {Karnatak, Rajat and Kantz, Holger and Bialonski, Stephan}, title = {Early warning signal for interior crises in excitable systems}, series = {Physical Review E}, volume = {96}, journal = {Physical Review E}, number = {4}, issn = {2470-0053}, doi = {10.1103/PhysRevE.96.042211}, pages = {042211}, year = {2017}, language = {en} } @article{NgamgaBialonskiMarwanetal.2016, author = {Ngamga, Eulalie Joelle and Bialonski, Stephan and Marwan, Norbert and Kurths, J{\"u}rgen and Geier, Christian and Lehnertz, Klaus}, title = {Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data}, series = {Physics Letters A}, volume = {380}, journal = {Physics Letters A}, number = {16}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0375-9601}, doi = {10.1016/j.physleta.2016.02.024}, pages = {1419 -- 1425}, year = {2016}, abstract = {We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.}, language = {en} } @article{BialonskiCaronSchloenetal.2016, author = {Bialonski, Stephan and Caron, David A. and Schloen, Julia and Feudel, Ulrike and Kantz, Holger and Moorthi, Stefanie D.}, title = {Phytoplankton dynamics in the Southern California Bight indicate a complex mixture of transport and biology}, series = {Journal of Plankton Research}, volume = {38}, journal = {Journal of Plankton Research}, number = {4}, publisher = {Oxford University Press}, address = {Oxford}, issn = {1464-3774}, doi = {10.1093/plankt/fbv122}, pages = {1077 -- 1091}, year = {2016}, abstract = {The stimulation and dominance of potentially harmful phytoplankton taxa at a given locale and time are determined by local environmental conditions as well as by transport to or from neighboring regions. The present study investigated the occurrence of common harmful algal bloom (HAB) taxa within the Southern California Bight, using cross-correlation functions to determine potential dependencies between HAB taxa and environmental factors, and potential links to algal transport via local hydrography and currents. A simulation study, in which Lagrangian particles were released, was used to assess travel times due to advection by prevailing ocean currents in the bight. Our results indicate that transport of some taxa may be an important mechanism for the expansion of their distributions into other regions, which was supported by mean travel times derived from our simulation study and other literature on ocean currents in the Southern California Bight. In other cases, however, phytoplankton dynamics were rather linked to local environmental conditions, including coastal upwelling events. Overall, our study shows that complex current patterns in the Southern California Bight may contribute significantly to the formation and expansion of HABs in addition to local environmental factors determining the spatiotemporal dynamics of phytoplankton blooms.}, language = {en} } @article{BialonskiAnsmannKantz2015, author = {Bialonski, Stephan and Ansmann, Gerrit and Kantz, Holger}, title = {Data-driven prediction and prevention of extreme events in a spatially extended excitable system}, series = {Physical Review E}, volume = {92}, journal = {Physical Review E}, number = {4}, issn = {2470-0053}, doi = {10.1103/PhysRevE.92.042910}, pages = {042910}, year = {2015}, language = {en} } @article{MulhernBialonskiKantz2015, author = {Mulhern, Colm and Bialonski, Stephan and Kantz, Holger}, title = {Extreme events due to localization of energy}, series = {Physical Review E}, volume = {91}, journal = {Physical Review E}, number = {1}, issn = {2470-0053}, doi = {10.1103/PhysRevE.91.012918}, pages = {012918}, year = {2015}, language = {en} } @article{GeierLehnertzBialonski2015, author = {Geier, Christian and Lehnertz, Klaus and Bialonski, Stephan}, title = {Time-dependent degree-degree correlations in epileptic brain networks: from assortative to dissortative mixing}, series = {Frontiers in Human Neuroscience}, journal = {Frontiers in Human Neuroscience}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1662-5161}, doi = {10.3389/fnhum.2015.00462}, year = {2015}, language = {en} } @article{GeierBialonskiElgeretal.2015, author = {Geier, Christian and Bialonski, Stephan and Elger, Christian E. and Lehnertz, Klaus}, title = {How important is the seizure onset zone for seizure dynamics?}, series = {Seizure}, volume = {25}, journal = {Seizure}, issn = {1059-1311}, doi = {10.1016/j.seizure.2014.10.013}, pages = {160 -- 166}, year = {2015}, language = {en} } @article{BialonskiLehnertz2013, author = {Bialonski, Stephan and Lehnertz, Klaus}, title = {Assortative mixing in functional brain networks during epileptic seizures}, series = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, volume = {23}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, number = {3}, doi = {10.1063/1.4821915}, pages = {033139}, year = {2013}, language = {en} } @incollection{BialonskiLehnertz2013, author = {Bialonski, Stephan and Lehnertz, Klaus}, title = {From time series to complex networks: an overview}, series = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction}, booktitle = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction}, isbn = {978-981-4525-36-7}, doi = {10.1142/9789814525350_0010}, pages = {132 -- 147}, year = {2013}, abstract = {The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.}, language = {en} } @book{Bialonski2012, author = {Bialonski, Stephan}, title = {Inferring complex networks from time series of dynamical systems: Pitfalls, misinterpretations, and possible solutions}, publisher = {Universit{\"a}ts- und Landesbibliothek Bonn}, address = {Bonn}, pages = {Online-Ausgabe (III, 135 S. : Ill., graph. Darst.)}, year = {2012}, language = {en} } @incollection{Bialonski2016, author = {Bialonski, Stephan}, title = {Are interaction clusters in epileptic networks predictive of seizures?}, series = {Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics}, booktitle = {Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics}, publisher = {CRC Press}, isbn = {978-143983886-0}, pages = {349 -- 355}, year = {2016}, language = {en} } @article{BialonskiWellmerElgeretal.2006, author = {Bialonski, Stephan and Wellmer, J{\"o}rg and Elger, Christian E. and Lehnertz, Klaus}, title = {Interictal focus localization in neocortical lesional epilepsies with synchronization cluster analysis}, series = {Epilepsia}, volume = {47}, journal = {Epilepsia}, issn = {0013-9580}, pages = {36}, year = {2006}, language = {en} } @incollection{LehnertzBialonskiHorstmannetal.2010, author = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias}, title = {Epilepsy}, series = {Reviews of Nonlinear Dynamics and Complexity, Volume 2}, booktitle = {Reviews of Nonlinear Dynamics and Complexity, Volume 2}, publisher = {Wiley-VCH}, isbn = {9783527628001}, doi = {10.1002/9783527628001.ch5}, pages = {159 -- 200}, year = {2010}, language = {en} } @article{LehnertzBialonskiHorstmannetal.2009, author = {Lehnertz, Klaus and Bialonski, Stephan and Horstmann, Marie-Therese and Krug, Dieter and Rothkegel, Alexander and Staniek, Matth{\"a}us and Wagner, Tobias}, title = {Synchronization phenomena in human epileptic brain networks}, series = {Journal of neuroscience methods}, volume = {183}, journal = {Journal of neuroscience methods}, number = {1}, issn = {0165-0270}, doi = {10.1016/j.jneumeth.2009.05.015}, pages = {42 -- 48}, year = {2009}, language = {en} } @incollection{OsterhageBialonskiStanieketal.2008, author = {Osterhage, Hannes and Bialonski, Stephan and Staniek, Matth{\"a}us and Schindler, Kaspar and Wagner, Tobias and Elger, Christian E. and Lehnertz, Klaus}, title = {Bivariate and multivariate time series analysis techniques and their potential impact for seizure prediction}, series = {Seizure Prediction in Epilepsy: From Basic Mechanisms to Clinical Applications}, booktitle = {Seizure Prediction in Epilepsy: From Basic Mechanisms to Clinical Applications}, publisher = {Wiley-VCH}, address = {Weinheim}, isbn = {978-3-527-62519-2}, doi = {10.1002/9783527625192.ch15}, pages = {189 -- 208}, year = {2008}, language = {en} } @article{SchindlerBialonskiHorstmannetal.2008, author = {Schindler, Kaspar A. and Bialonski, Stephan and Horstmann, Marie-Therese and Elger, Christian E. and Lehnertz, Klaus}, title = {Evolving functional network properties and synchronizability during human epileptic seizures}, series = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, volume = {18}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, number = {3}, issn = {1089-7682}, doi = {10.1063/1.2966112}, pages = {033119}, year = {2008}, language = {en} } @article{BialonskiAllefeldWellmeretal.2008, author = {Bialonski, Stephan and Allefeld, C. and Wellmer, J. and Elger, C. and Lehnertz, K.}, title = {An approach to identify synchronization clusters within the epileptic network}, series = {Klinische Neurophysiologie}, volume = {39}, journal = {Klinische Neurophysiologie}, number = {1}, doi = {10.1055/s-2008-1072881}, pages = {A79}, year = {2008}, language = {en} } @article{BialonskiSchindlerElgeretal.2008, author = {Bialonski, Stephan and Schindler, K. and Elger, C. E. and Lehnertz, Klaus}, title = {Lateralized characteristics of the evolution of EEG correlation during focal onset seizures: a mechanism to prevent secondary generalization?}, series = {Epilepsia}, volume = {49}, journal = {Epilepsia}, issn = {0013-9580}, pages = {11 -- 11}, year = {2008}, abstract = {Rationale: Previous studies [Topolnik et al., Cereb Cortex 2003; 13: 883; Schindler et al., Brain 2007; 130: 65] indicate that the termination of focal onset seizures may be causally related to an increase of global neuronal correlation during the second half of the seizures. This increase was observed to occur earlier in complex partial seizures than in secondarily generalized seizures. We here address the question whether such an increase of neuronal correlation prior to seizure end is indeed a global phenomenon, involving both hemispheres or whether there are side-specific differences. Methods: We analyzed 20 focal onset seizures (10 complex partial, 10 secondarily generalized seizures) recorded in 13 patients who underwent presurgical evaluation of focal epilepsies of different origin. EEG was recorded intracranially from bilaterally implanted subdural strip and intrahippocampal depth electrodes. Utilizing a moving window approach, we investigated the evolution of the maximum cross correlation for all channel combinations during seizures. For each moving window the mean value of the maximum cross correlation (MCC) between all electrode contacts was computed separately for each hemisphere. After normalization of seizure durations, MCC values of the ipsi- and contralateral hemisphere for all seizures were determined. Results: We observed that the MCC of the contralateral hemisphere in complex partial seizures increased during the first half of the seizure, whereas, for the same time interval, the MCC of the ipsilateral hemisphere even declined below the level of the pre-seizure period. In contrast, no significant differences between both hemispheres could be observed for secondarily generalized seizures where both hemispheres showed a simultaneous increase of MCC during the second half of the seizures. The level of MCC for the contralateral hemisphere was higher for complex partial seizures than for secondarily generalized seizures during the first half of the seizure. Conclusions: Our findings indicate that there are indeed lateralized differences in the evolution of global neuronal correlation during complex partial and secondarily generalized seizures. The observed contralateral increase of neuronal correlation during complex partial seizures might indicate an emerging self-organizing mechanism for preventing the spread of seizure activity.}, language = {en} }