@unpublished{RingersBialonskiSolovevetal.2021, author = {Ringers, Christa and Bialonski, Stephan and Solovev, Anton and Hansen, Jan N. and Ege, Mert and Friedrich, Benjamin M. and Jurisch-Yaksi, Nathalie}, title = {Preprint: Local synchronization of cilia and tissue-scale cilia alignment are sufficient for global metachronal waves}, series = {bioRxiv}, journal = {bioRxiv}, doi = {10.1101/2021.11.23.469646}, pages = {19 Seiten}, year = {2021}, abstract = {Motile cilia are hair-like cell extensions present in multiple organs of the body. How cilia coordinate their regular beat in multiciliated epithelia to move fluids remains insufficiently understood, particularly due to lack of rigorous quantification. We combine here experiments, novel analysis tools, and theory to address this knowledge gap. We investigate collective dynamics of cilia in the zebrafish nose, due to its conserved properties with other ciliated tissues and its superior accessibility for non-invasive imaging. We revealed that cilia are synchronized only locally and that the size of local synchronization domains increases with the viscosity of the surrounding medium. Despite the fact that synchronization is local only, we observed global patterns of traveling metachronal waves across the multiciliated epithelium. Intriguingly, these global wave direction patterns are conserved across individual fish, but different for left and right nose, unveiling a chiral asymmetry of metachronal coordination. To understand the implications of synchronization for fluid pumping, we used a computational model of a regular array of cilia. We found that local metachronal synchronization prevents steric collisions and improves fluid pumping in dense cilia carpets, but hardly affects the direction of fluid flow. In conclusion, we show that local synchronization together with tissue-scale cilia alignment are sufficient to generate metachronal wave patterns in multiciliated epithelia, which enhance their physiological function of fluid pumping.}, language = {en} } @unpublished{BornheimNiklasBlanecketal.2023, author = {Bornheim, Tobias and Niklas, Grieger and Blaneck, Patrick Gustav and Bialonski, Stephan}, title = {Preprint: Speaker attribution in German parliamentary debates with QLoRA-adapted large language models}, series = {Journal for Language Technology and Computational Linguistics}, journal = {Journal for Language Technology and Computational Linguistics}, doi = {10.48550/arXiv.2309.09902}, pages = {8 Seiten}, year = {2023}, abstract = {The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.}, language = {en} } @article{HorstmannBialonskiNoenningetal.2010, author = {Horstmann, Marie-Therese and Bialonski, Stephan and Noenning, Nina and Mai, Heinke and Prusseit, Jens and Wellmer, J{\"o}rg and Hinrichs, Hermann and Lehnertz, Klaus}, title = {State dependent properties of epileptic brain networks: Comparative graph-theoretical analyses of simultaneously recorded EEG and MEG}, series = {Clinical Neurophysiology}, volume = {121}, journal = {Clinical Neurophysiology}, number = {2}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1388-2457}, doi = {10.1016/j.clinph.2009.10.013}, pages = {172 -- 185}, year = {2010}, abstract = {Objective To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval. Methods We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics. Results Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings. Conclusions Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks. Significance An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.}, language = {en} } @article{BialonskiHorstmannLehnertz2010, author = {Bialonski, Stephan and Horstmann, Marie-Therese and Lehnertz, Klaus}, title = {From brain to earth and climate systems: Small-world interaction networks or not?}, series = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, volume = {20}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science}, number = {1}, publisher = {AIP Publishing}, address = {Melville, NY}, issn = {1089-7682}, doi = {10.1063/1.3360561}, pages = {013134}, year = {2010}, abstract = {We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.}, language = {en} } @article{BialonskiWendlerLehnertz2011, author = {Bialonski, Stephan and Wendler, Martin and Lehnertz, Klaus}, title = {Unraveling spurious properties of interaction networks with tailored random networks}, series = {Plos one}, volume = {6}, journal = {Plos one}, number = {8}, publisher = {Plos}, address = {San Francisco}, doi = {10.1371/journal.pone.0022826}, pages = {e22826}, year = {2011}, abstract = {We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erd{\"o}s-R{\´e}nyi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures - known for their complex spatial and temporal dynamics - we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.}, language = {en} } @article{KuhnertBialonskiNoenningetal.2013, author = {Kuhnert, Marie-Therese and Bialonski, Stephan and Noenning, Nina and Mai, Heinke and Hinrichs, Hermann and Helmstaedter, Christoph and Lehnertz, Klaus}, title = {Incidental and intentional learning of verbal episodic material differentially modifies functional brain networks}, series = {Plos one}, volume = {8}, journal = {Plos one}, number = {11}, publisher = {PLOS}, address = {San Francisco}, doi = {10.1371/journal.pone.0080273}, pages = {e80273}, year = {2013}, abstract = {Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.}, language = {en} }