Dr. rer. nat. Patrick Krauß

2025

• Ramezani, P., Krauß, P., & Schilling, A. (Eds.) (2025). Analysis of argument structure constructions in the large language model BERT. .
  URL: https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1477246/full
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2024

• Krauß, P. (2024). Artificial Intelligence and Brain Research: Neural Networks, Deep Learning and the Future of Cognition. Berlin / Heidelberg: Springer.
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• Kölbl, N., Tziridis, K., Krauß, P., & Schilling, A. (2024). Methodological Considerations in the Analysis of Acoustically Evoked Neural Signals: A Comparative Study of Active EEG, Passive EEG and MEG. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Orlando, FL, US: Institute of Electrical and Electronics Engineers Inc..
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• Metzner, C., Yamakou, M., Voelkl, D., Schilling, A., & Krauß, P. (2024). Quantifying and Maximizing the Information Flux in Recurrent Neural Networks. Neural Computation, 36(3), 351-384. https://doi.org/10.1162/neco_a_01651
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• Oikonomou, E., Juli, Y., Kolan, R.R., Kern, L., Gruber, T., Alzheimer, C.,... Huth, T. (2024). A deep learning approach to real-time Markov modeling of ion channel gating. Communications Chemistry. https://doi.org/10.1038/s42004-024-01369-y
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• Schilling, A., Gerum, R., Böhm, C., Rasheed, J., Metzner, C., Maier, A.,... Krauß, P. (2024). Deep learning based decoding of single local field potential events. NeuroImage, 297. https://doi.org/10.1016/j.neuroimage.2024.120696
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• Schilling, A., & Krauß, P. (2024). The Bayesian brain: world models and conscious dimensions of auditory phantom perception. Journal of Neurophysiology, 132(2), 317-318. https://doi.org/10.1152/jn.00263.2024
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• Schneider, L.-S., Krauß, P., Schiering, N., Syben, C., Schielein, R., & Maier, A. (2024). Data-driven modeling in metrology - A short introduction, current developments and future perspectives. Technisches Messen, 91(9), 480-503. https://doi.org/10.1515/teme-2024-0004
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• Schüller, A., Schilling, A., Krauß, P., & Reichenbach, T. (2024). The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions. Journal of Cognitive Neuroscience, 36(3), 475-491. https://doi.org/10.1162/jocn_a_02103
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• Tziridis, K., Maul, A., Rasheed, J., Krauß, P., Schilling, A., & Schulze, H. (2024). Tinnitus is associated with increased extracellular matrix density in the auditory cortex of Mongolian gerbils. BMC Neuroscience, 25. https://doi.org/10.1186/s12868-024-00904-w
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2023

• Gerum, R., Erpenbeck, A., Krauß, P., & Schilling, A. (2023). Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology. In 2023 International Joint Conference on Neural Networks (IJCNN). Gold Coast, QLD, AU: Institute of Electrical and Electronics Engineers Inc..
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• Kölbl, N., Schilling, A., & Krauß, P. (2023). Adaptive ICA for Speech EEG Artifact Removal. In 2023 5th International Conference on Bio-engineering for Smart Technologies (BioSMART). Paris, FR: Institute of Electrical and Electronics Engineers Inc..
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• Metzner, C., Schilling, A., Traxdorf, M., Schulze, H., Tziridis, K., & Krauß, P. (2023). Extracting continuous sleep depth from EEG data without machine learning. Neurobiology of Sleep and Circadian Rhythms, 14. https://doi.org/10.1016/j.nbscr.2023.100097
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• Schilling, A., Schaette, R., Sedley, W., Gerum, R.C., Maier, A., & Krauß, P. (2023). Editorial: Auditory perception and phantom perception in brains, minds and machines. Frontiers in Neuroscience, 17. https://doi.org/10.3389/fnins.2023.1293552
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• Schilling, A., Sedley, W., Gerum, R.C., Metzner, C., Tziridis, K., Maier, A.,... Krauß, P. (2023). Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception. Brain, 146(12), 4809-4825. https://doi.org/10.1093/brain/awad255
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• Schilling, A., Tziridis, K., Schulze, H., & Krauß, P. (2023). Behavioral Assessment of Zwicker Tone Percepts in Gerbils. Neuroscience, 520, 39-45. https://doi.org/10.1016/j.neuroscience.2023.04.011
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• Schulze, H., Schilling, A., Krauß, P., & Tziridis, K. (2023). Erlanger Modell der Tinnitusentstehung – Perspektivwechsel und neue Behandlungsstrategie. HNO. https://doi.org/10.1007/s00106-023-01355-1
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• Schüller, A., Schilling, A., Krauß, P., Rampp, S., & Reichenbach, T. (2023). Attentional modulation of the cortical contribution to the frequency-following response evoked by continuous speech. The Journal of Neuroscience, 43(44), 7429-7440. https://doi.org/10.1523/JNEUROSCI.1247-23.2023
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• Stoll, A., Maier, A., Krauß, P., Gerum, R., & Schilling, A. (2023). Coincidence detection and integration behavior in spiking neural networks. Cognitive Neurodynamics. https://doi.org/10.1007/s11571-023-10038-0
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• Stöwer, P., Schilling, A., Maier, A., & Krauß, P. (2023). Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. In Proceedings of the IEEE International Conference on Development and Learning 2023 (ICDL). Macau.
  URL: https://ieeexplore.ieee.org/abstract/document/10364535
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• Stöwer, P., Schilling, A., Maier, A., & Krauß, P. (2023). Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts. Scientific Reports. https://doi.org/10.1038/s41598-023-30307-6
  URL: https://www.nature.com/articles/s41598-023-30307-6
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• Surendra, K., Schilling, A., Stöwer, P., Maier, A., & Krauß, P. (2023). Word class representations spontaneously emerge in a deep neural network trained on next word prediction. In M. Arif Wani, Mihai Boicu, Moamar Sayed-Mouchaweh, Pedro Henriques Abreu, Joao Gama (Eds.), Proceedings - 22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023 (pp. 1481-1486). Jacksonville, FL, USA: Institute of Electrical and Electronics Engineers Inc..
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2022

• Garibyan, A., Schilling, A., Boehm, C., Zankl, A., & Krauß, P. (2022). Neural correlates of linguistic collocations during continuous speech perception. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1076339
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• Maier, A., Köstler, H., Heisig, M., Krauß, P., & Yang, S.H. (2022). Known operator learning and hybrid machine learning in medical imaging - A review of the past, the present, and the future. Progress in Biomedical Engineering, 4(2). https://doi.org/10.1088/2516-1091/ac5b13
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• Metzner, C., & Krauß, P. (2022). Dynamics and Information Import in Recurrent Neural Networks. Frontiers in Computational Neuroscience, 16. https://doi.org/10.3389/fncom.2022.876315
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• Metzner, C., Schilling, A., Traxdorf, M., Tziridis, K., Maier, A., Schulze, H., & Krauß, P. (2022). Classification at the accuracy limit: facing the problem of data ambiguity. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-26498-z
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• Schilling, A., Gerum, R., Metzner, C., Maier, A., & Krauß, P. (2022). Intrinsic Noise Improves Speech Recognition in a Computational Model of the Auditory Pathway. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.908330
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• Schilling, A., & Krauß, P. (2022). Tinnitus is associated with improved cognitive performance and speech perception-Can stochastic resonance explain? Frontiers in Aging Neuroscience, 14. https://doi.org/10.3389/fnagi.2022.1073149
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• Stöwer, P., Krauß, P., & Maier, A. (2022). Neural network based successor representations to form cognitive maps. Poster presentation at Bernstein Conference, Berlin.
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• Stöwer, P., Schliecker, C., Schilling, A., Metzner, C., Maier, A., & Krauß, P. (2022). Neural network based successor representations to form cognitive maps of space and language. Scientific Reports. https://doi.org/10.1038/s41598-022-14916-1
  URL: https://www.nature.com/articles/s41598-022-14916-1
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• Tziridis, K., Brunner, S., Schilling, A., Krauß, P., & Schulze, H. (2022). Spectrally Matched Near-Threshold Noise for Subjective Tinnitus Loudness Attenuation Based on Stochastic Resonance. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.831581
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2021

• Bönsel, F., Krauß, P., Metzner, C., & Yamakou, M. (2021). Control of noise-induced coherent oscillations in three-neuron motifs. Cognitive Neurodynamics, 16, 941-960. https://doi.org/10.1007/s11571-021-09770-2
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• Jeschke, M., Happel, M.F., Tziridis, K., Krauß, P., Schilling, A., Schulze, H., & Ohl, F.W. (2021). Acute and Long-Term Circuit-Level Effects in the Auditory Cortex After Sound Trauma. Frontiers in Neuroscience, 14. https://doi.org/10.3389/fnins.2020.598406
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• Krauß, P., Metzner, C., Joshi, N., Schulze, H., Traxdorf, M., Maier, A., & Schilling, A. (2021). Analysis and visualization of sleep stages based on deep neural networks. Neurobiology of Sleep and Circadian Rhythms, 10. https://doi.org/10.1016/j.nbscr.2021.100064
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• Krauß, P., & Tziridis, K. (2021). Simulated transient hearing loss improves auditory sensitivity. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-94429-5
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• Metzner, C., Schilling, A., Traxdorf, M., Schulze, H., & Krauß, P. (2021). Sleep as a random walk: a super-statistical analysis of EEG data across sleep stages. Communications Biology, 4(1). https://doi.org/10.1038/s42003-021-02912-6
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• Schilling, A., Maier, A., Gerum, R., Metzner, C., & Krauß, P. (2021). Quantifying the separability of data classes in neural networks. Neural Networks, 139, 278-293. https://doi.org/10.1016/j.neunet.2021.03.035
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• Schilling, A., Tziridis, K., Schulze, H., & Krauß, P. (2021). The stochastic resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition. In Progress in Brain Research. Elsevier B.V..
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• Stöwer, P., Krauß, P., & Maier, A. (2021). The Hippocampus learns a language model with the help of the Successor Representation. Poster presentation at Montreal AI & Neuroscience 2021, Montreal.
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• Tziridis, K., Forster, J., Buchheidt-Dörfler, I., Krauß, P., Schilling, A., Wendler, O.,... Schulze, H. (2021). Tinnitus development is associated with synaptopathy of inner hair cells in Mongolian gerbils. European Journal of Neuroscience. https://doi.org/10.1111/ejn.15334
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• Yang, Z., Schilling, A., Maier, A., & Krauß, P. (2021). Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data. In Christoph Palm, Heinz Handels, Klaus Maier-Hein, Thomas M. Deserno, Andreas Maier, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 211-216). Regensburg, DE: Springer Science and Business Media Deutschland GmbH.
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2020

• Gerum, R., Erpenbeck, A., Krauß, P., & Schilling, A. (2020). Sparsity through evolutionary pruning prevents neuronal networks from overfitting. Neural Networks, 128, 305-312. https://doi.org/10.1016/j.neunet.2020.05.007
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• Knipper, M., van Dijk, P., Schulze, H., Mazurek, B., Krauß, P., Scheper, V.,... Rüttiger, L. (2020). The Neural Bases of Tinnitus: Lessons from Deafness and Cochlear Implants. The Journal of Neuroscience, 40(38), 7190-7202. https://doi.org/10.1523/JNEUROSCI.1314-19.2020
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• Krauß, P., & Maier, A. (2020). Will We Ever Have Conscious Machines? Frontiers in Computational Neuroscience, 14. https://doi.org/10.3389/fncom.2020.556544
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• Schilling, A., Krauß, P., Hannemann, R., Schulze, H., & Tziridis, K. (2020). Reduktion der Tinnituslautstärke: Pilotstudie zur Abschwächung von tonalem Tinnitus mit schwellennahem, individuell spektral optimiertem Rauschen. HNO. https://doi.org/10.1007/s00106-020-00963-5
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• Schilling, A., Tomasello, R., Henningsen-Schomers, M.R., Zankl, A., Surendra, K., Haller, M.,... Krauß, P. (2020). Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods. Language, Cognition and Neuroscience. https://doi.org/10.1080/23273798.2020.1803375
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2019

• Dierich, M., Hartmann, S., Dietrich, N., Möser, P., Brede, F., Johnson Chacko, L.,... Huth, T. (2019). β-Secretase BACE1 Is Required for Normal Cochlear Function. The Journal of Neuroscience, 39(45), 9013-9027. https://doi.org/10.1523/JNEUROSCI.0028-19.2019
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• Gerum, R., Rahlfs, H., Streb, M., Krauß, P., Grimm, J., Metzner, C.,... Schilling, A. (2019). Open(G)PIAS: An open-source solution for the construction of a high-precision acoustic startle response setup for tinnitus screening and threshold estimation in rodents. Frontiers in Behavioral Neuroscience, 13. https://doi.org/10.3389/fnbeh.2019.00140
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• Krauß, P., Prebeck, K., Schilling, A., & Metzner, C. (2019). "Recurrence Resonance" in Three-Neuron Motifs. Frontiers in Computational Neuroscience, 13. https://doi.org/10.3389/fncom.2019.00064
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• Krauß, P., Schilling, A., Tziridis, K., & Schulze, H. (2019). Models of tinnitus development. From cochlea to cortex. HNO, 67(3), 172-177. https://doi.org/10.1007/s00106-019-0612-z
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• Krauß, P., Schuster, M., Dietrich, V., Schilling, A., Schulze, H., & Metzner, C. (2019). Weight statistics controls dynamics in recurrent neural networks. PLoS ONE, 14(4). https://doi.org/10.1371/journal.pone.0214541
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• Krauß, P., Zankl, A., Schilling, A., Schulze, H., & Metzner, C. (2019). Analysis of Structure and Dynamics in Three-Neuron Motifs. Frontiers in Computational Neuroscience, 13. https://doi.org/10.3389/fncom.2019.00005
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• Schilling, A., Gerum, R., Krauß, P., Metzner, C., Tziridis, K., & Schulze, H. (2019). Objective estimation of sensory thresholds based on neurophysiological parameters. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2019.00481
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• Schilling, A., Gerum, R., Krauß, P., Metzner, C., Tziridis, K., & Schulze, H. (2019). Objective estimation of sensory thresholds based on neurophysiological parameters. Frontiers in Neuroscience, 13(MAY). https://doi.org/10.3389/fnins.2019.00481
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• Traxdorf, M., Krauß, P., Schilling, A., Schulze, H., & Tziridis, K. (2019). Microstructure of cortical activity during sleep reflects respiratory events and state of daytime vigilance. Somnologie, 23(2), 72-79. https://doi.org/10.1007/s11818-019-0201-0
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2018

• Krauß, P., Metzner, C., Schilling, A., Tziridis, K., Traxdorf, M., Wollbrink, A.,... Schulze, H. (2018). A statistical method for analyzing and comparing spatiotemporal cortical activation patterns. Scientific Reports, 8. https://doi.org/10.1038/s41598-018-23765-w
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• Krauß, P., Schilling, A., Bauer, J., Tziridis, K., Metzner, C., Schulze, H., & Traxdorf, M. (2018). Analysis of Multichannel EEG Patterns During Human Sleep: A Novel Approach. Frontiers in Human Neuroscience, 12. https://doi.org/10.3389/fnhum.2018.00121
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• Krauß, P., Tziridis, K., Schilling, A., & Schulze, H. (2018). Cross-modal stochastic resonance as a universal principle to enhance sensory processing. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2018.00578
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• Krauß, P., Tziridis, K., Schilling, A., & Schulze, H. (2018). Cross-Modal Stochastic Resonance as a Universal Principle to Enhance Sensory Processing. Frontiers in Neuroscience, 12. https://doi.org/10.3389/fnins.2018.00578
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• Metzner, C., Lange, J., Krauß, P., Wunderling, N., Übelacker, J., Martin, F., & Fabry, B. (2018). Pressure-driven collective growth mechanism of planar cell colonies. Journal of Physics D-Applied Physics. https://doi.org/10.1088/1361-6463/aace4c
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• Metzner, C., Lange, J., Krauß, P., Wunderling, N., Übelacker, J., Martin, F., & Fabry, B. (2018). Pressure-driven collective growth mechanism of planar cell colonies. Journal of Physics D: Applied Physics, 51(30). https://doi.org/10.1088/1361-6463/aace4c
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2017

• Gollnast, D., Tziridis, K., Krauß, P., Schilling, A., Hoppe, U., & Schulze, H. (2017). Analysis of Audiometric Differences of Patients with and without Tinnitus in a Large Clinical Database. Frontiers in Neurology, 8. https://doi.org/10.3389/fneur.2017.00031
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• Krauß, P., Metzner, C., Schilling, A., Schütz, C., Tziridis, K., Fabry, B., & Schulze, H. (2017). Adaptive stochastic resonance for unknown and variable input signals. Scientific Reports, 7(1), 2450. https://doi.org/10.1038/s41598-017-02644-w
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• Krauß, P., Schulze, H., & Metzner, C. (2017). A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals. Artificial Life, 23(4), 518-527. https://doi.org/10.1162/ARTL_a_00245
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• Schilling, A., Krauß, P., Gerum, R., Metzner, C., Tziridis, K., & Schulze, H. (2017). A New Statistical Approach for the Evaluation of Gap-prepulse Inhibition of the Acoustic Startle Reflex (GPIAS) for Tinnitus Assessment. Frontiers in Behavioral Neuroscience, 11. https://doi.org/10.3389/fnbeh.2017.00198
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2016

• Krauß, P., Tziridis, K., Buerbank, S., Schilling, A., & Schulze, H. (2016). Therapeutic Value of Ginkgo biloba Extract EGb 761® in an Animal Model (Meriones unguiculatus) for Noise Trauma Induced Hearing Loss and Tinnitus. PLoS ONE, 11(6), e0157574. https://doi.org/10.1371/journal.pone.0157574
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• Krauß, P., Tziridis, K., Metzner, C., Schilling, A., Hoppe, U., & Schulze, H. (2016). Stochastic Resonance Controlled Upregulation of Internal Noise after Hearing Loss as a Putative Cause of Tinnitus-Related Neuronal Hyperactivity. Frontiers in Neuroscience, 10. https://doi.org/10.3389/fnins.2016.00597
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2013

• Lang, N., Münster, S., Metzner, C., Krauß, P., Schürmann, S., Lange, J.,... Fabry, B. (2013). Estimating the 3D pore size distribution of biopolymer networks from directionally biased data. Biophysical Journal, 105(9), 1967-75. https://doi.org/10.1016/j.bpj.2013.09.038
  URL: http://www.sciencedirect.com/science/article/pii/S0006349513010862
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2012

• Krauß, P., Metzner, C., Lange, J., Lang, N., & Fabry, B. (2012). Parameter-free binarization and skeletonization of fiber networks from confocal image stacks. PLoS ONE, 7(5). https://doi.org/10.1371/journal.pone.0036575
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2011

• Metzner, C., Krauß, P., & Fabry, B. (2011). Poresizes in random line networks. arXiv.
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