Speech, Language and Cognition in
Brains, Minds and Machines
Publications
Book
Krauss, P.
Künstliche Intelligenz und Hirnforschung - Neuronale Netze, Deep Learning und die Zukunft der Kognition
Springer 2023
link.springer.com/book/10.1007/978-3-662-67179-5
Peer-reviewed Journal Articles and Conference Papers
Under Review
Schilling, A., Gerum, R., Boehm, C., Rasheed, J., Metzner, C., Maier, A., Reindl, C., Hamer, H., & Krauss, P.
Deep learning based decoding of local field potentials.
preprint: doi.org/10.1101/2022.10.14.512209
Metzner, C., Schilling, A., & Krauss, P.
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD).
preprint: arxiv.org/abs/2311.16621
Stoewer, P., Schilling, A., Maier, A., & Krauss, P.
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations.
preprint: arxiv.org/abs/2401.01364
Tziridis, K., Rasheed, J., Krauss, P., Schilling, A., & Schulze, H.
Tinnitus is associated with increased extracellular matrix density in the auditory cortex.
preprint: essopenarchive.org/doi/full/10.22541/au.170020631.15815554
2024
Metzner, C., Yamakou, M., Voelkl, D., Schilling, A., & Krauss, P. (2024)
Quantifying and maximizing the information flux in recurrent neural networks.
Neural Computation
doi.org/10.1162/neco_a_01651
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.
2023
Surendra, K., Schilling, A., Stoewer, P. Maier, A., & Krauss, P. (2023)
Word class representations spontaneously emerge in a deep neural network trained on next word prediction.
Proceedings of the 2023 IEEE International Conference on Machine Learning and Applications (ICMLA 2023)
Stoewer, P., Schilling, A., Maier, A., & Krauss, P. (2023)
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings.
Proceedings of the 2023 IEEE International Conference on Development and Learning (ICDL 2023)
doi.org/10.1109/ICDL55364.2023.10364535
Schilling, A., Sedley, W., Gerum, R., Metzner, C., Tziridis, K., Maier, A., Schulze, H., Zeng, F.-G., Friston, K.J., & Krauss, P. (2023)
Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception.
Brain
doi.org/10.1093/brain/awad255
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.
2023 International Joint Conference on Neural Networks (IJCNN 2023), IEEE
awarded with the Best Paper Award among more than 1000 accepted papers
doi.org/10.1109/IJCNN54540.2023.10191268
Koelbl, N., Schilling, A., & Krauss, P. (2023)
Adaptive ICA for Speech EEG Artifact Removal.
BioSMART 2023, 5th International Conference on Bio-engineering for Smart Technologies, IEEE
awarded with the Best Student Paper Award
doi.org/10.1109/BioSMART58455.2023.10162054
Schilling, A., Schaette, R., Sedley, W., Gerum, R., Maier, A., & Krauss, P. (2023)
Editorial: Auditory Perception and Phantom Perception in Brains, Minds and Machines.
Frontiers in Neuroscience
www.frontiersin.org/articles/10.3389/fnins.2023.1293552/full
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.
doi.org/10.1016/j.nbscr.2023.100097
Stoewer, 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
doi.org/10.1038/s41598-023-30307-6
Schilling, A., Tziridis, K., Schulze, H., & Krauss, P. (2023).
Behavioral assessment of Zwicker tone percepts in rodents.
Neuroscience
doi.org/10.1016/j.neuroscience.2023.04.011
Stoll, A., Krauss, P., Maier, A., Gerum, R., & Schilling, A. (2023).
Coincidence Detection and Integration Behavior in Spiking Neural Networks.
Cognitive Neurodynamics
link.springer.com/article/10.1007/s11571-023-10038-0
Schulze, H., Schilling, A., Krauss, P. & Tziridis,K. (2023)
The Erlangen model of tinnitus development—New perspective and treatment strategy.
HNO
doi.org/10.1007/s00106-023-01355-1
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.
Journal of Neuroscience
doi.org/10.1523/JNEUROSCI.1247-23.2023
2022
Metzner, C., Schilling, A., Traxdorf, M., Tziridis, K., Schulze, H. & Krauss, P. (2022).
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity.
Scientific Reports
doi.org/10.1038/s41598-022-26498-z
Garibyan, A., Schilling, A., Boehm, C., Zankl, A., & Krauss, P. (2022).
Neural Correlates of Linguistic Collocations During Continuous Speech Perception.
Frontiers in Psychology
doi.org/10.3389/fpsyg.2022.1076339
Schillng, A. & Krauss, P. (2022).
Tinnitus is associated with improved cognitive performance and speech perception -- Can stochastic resonance explain?
Frontiers in Aging Neuroscience
doi.org/10.3389/fnagi.2022.1073149
Stoewer, P., Schlieker, 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
doi.org/10.1038/s41598-022-14916-1
Schilling, A., Gerum, R., Zankl, A., Metzner, C., Maier. A., & Krauss, P. (2022).
Intrinsic noise improves speech recognition in a computational model of the auditory pathway.
Frontiers in Neuroscience
doi.org/10.3389/fnins.2022.908330
Metzner, C. & Krauss, P. (2022).
Dynamics and Information Import in Recurrent Neural Networks.
Frontiers in Computational Neuroscience
doi.org/10.3389/fncom.2022.876315
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
https://iopscience.iop.org/article/10.1088/2516-1091/ac5b13/meta
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
doi.org/10.3389/fnins.2022.831581
Boensel, F., Krauss, P., Metzner, C. & Yamakou, M. (2022).
Control of noise-induced coherent oscillations in three-neuron motifs.
Cognitive Neurodynamics
doi.org/10.1007/s11571-021-09770-2
2021
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
doi.org/10.1016/j.nbscr.2021.100064
Krauss, P. and Tziridis, K. (2021).
Simulated transient hearing loss improves auditory sensitivity.
Scientific Reports
doi.org/10.1038/s41598-021-94429-5
Schilling, A., Tomasello, R., Henningsen-Schomers, M.R., Zankl, A., Surendra, K., Haller, M., Karl, V., Uhrig, P., Maier, A. & Krauss, P. (2021).
Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods.
Language, Cognition and Neuroscience
doi.org/10.1080/23273798.2020.1803375
Metzner, C., Schilling, A., Traxdorf, M., Schulze, H. & Krauss, P. (2021).
Sleep as a random walk – Superstatistical analysis of EEG data across sleep stages.
Communications Biology
doi.org/10.1038/s42003-021-02912-6
Schilling, A., Metzner, C., Gerum, R., Maier, A., & Krauss, P. (2021).
Quantifying the separability of data classes in neural networks.
Neural Networks
doi.org/10.1016/j.neunet.2021.03.035
Yang, Z., Schilling, A., Maier, A. & Krauss, P. (2021).
Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data.
Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021
dx.doi.org/10.1007/978-3-658-33198-6_51
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.
Progress in Brain Research
doi.org/10.1016/bs.pbr.2021.01.025
Jeschke, M., Happel, M.F.K., 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
doi.org/10.3389/fnins.2020.598406
Tziridis, K., Forster, J., Buchheidt-Doerfler, I., Krauss, P., Schilling, A., Wendler, O., Sterna, E. & Schulze, H. (2021).
Tinnitus development is associated with synaptopathy of inner hair cells in Mongolian gerbils.
European Journal of Neuroscience
doi.org/10.1111/ejn.15334
2020
Krauss, P. & Maier, A. (2020).
Will we ever have conscious Machines?
Frontiers in Computational Neuroscience
doi.org/10.3389/fncom.2020.556544
Gerum, R., Erpenbeck, A., Krauss, P. & Schilling, A. (2020).
Sparsity through evolutionary pruning prevents neuronal networks from overfitting.
Neural Networks
doi.org/10.1016/j.neunet.2020.05.007
Knipper, M., van Dijk, P., Schulze, H., Mazurek, B., Krauss, P., Scheper, V., Warnecke, A., Schlee, W., Schwabe, K., Singer, W., Braun, C., Delano, P.H., Fallgatter, A.J., Ehlis, A.-C., Searchfield, G.D., Munk, M.H.J., Baguley, D.M. & Rüttiger, L. (2020).
The neural bases of tinnitus: Lessons from deafness and cochlear implants
Journal of Neuroscience
doi.org/10.1523/JNEUROSCI.1314-19.2020
Schilling, A., Krauss, P., Hannemann, R., Schulze, H. & Tziridis, K. (2020).
Reducing tinnitus intensity: Pilot study to attenuate tonal tinnitus using individually spectrally optimized near-threshold noise.
HNO
doi.org/10.1007/s00106-020-00963-5
2019
Krauss, P., Prebeck, K., Schilling, A. & Metzner, C. (2019).
'Recurrence Resonance' in three-neuron motifs.
Frontiers in Computational Neuroscience
doi.org/10.3389/fncom.2019.00064
Krauss, P., Schuster, M., Dietrich, V., Schilling, A, Schulze, H. & Metzner, C. (2019).
Weight statistics controls dynamics in recurrent neural networks.
PloS one
doi.org/10.1371/journal.pone.0214541
Krauss, P., Zankl, A., Schilling, A., Schulze, H. & Metzner, C. (2019).
Analysis of structure and dynamics in three-neuron motifs.
Frontiers in Computational Neuroscience
doi.org/10.3389/fncom.2019.00005
Krauss, P., Schilling, A., Tziridis, K. & Schulze, H. (2019).
Models of tinnitus development. From cochlea to cortex.
HNO Journal
doi.org/10.1007/s00106-019-0612-z
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.
Somnology
link.springer.com/article/10.1007/s11818-019-0201-0
Dierich, M., Hartmann, S., Dietrich, N., Moeser, P., Brede, F., Johnson Chacko, L., Tziridis, K., Schilling, A., Krauss, P., Hessler, S., Karch, S., Schrott-Fischer, A., Blumer, M., Birchmeier, C., Oliver, D., Moser, T., Schulze, H., Alzheimer, C., Leitner, M. & Huth, T. (2019).
β-secretase BACE1 is required for normal cochlear function.
Journal of Neuroscience
doi.org/10.1523/JNEUROSCI.0028-19.2019
Gerum, R., Rahlfs, H., Streb, M., Krauss, P., Grimm, J., Metzner, C., Tziridis, K., Günther, M., Schulze, H., Kellermann, W. & Schilling, A. (2019).
Open(G)PIAS: An open source solution for the construction of a high-precision Acoustic-Startle-Response (ASR) setup for tinnitus screening and threshold estimation in rodents.
Frontiers in Behavioral Neuroscience
doi.org/10.3389/fnbeh.2019.00140
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
doi.org/10.3389/fnins.2019.00481
2018
Krauss, P., Tziridis, K., Schilling, A. & Schulze, H. (2018).
Cross-modal stochastic resonance as a universal principle to enhance sensory processing.
Frontiers in Neuroscience
doi.org/10.3389/fnins.2018.00578
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
doi.org/10.3389/fnhum.2018.00121
Krauss, P., Metzner, C., Schilling, A., Tziridis, K., Traxdorf M., Wollbrink, A., Rampp, S., Pantev, C., & Schulze, H. (2018).
A statistical method for analyzing and comparing spatiotemporal cortical activation patterns.
Scientific Reports
www.nature.com/articles/s41598-018-23765-w
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
iopscience.iop.org/article/10.1088/1361-6463/aace4c/meta
2017
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
www.nature.com/articles/s41598-017-02644-w
Krauss, P., Schulze, H., & Metzner, C. (2017).
A chemical reaction network to generate random, power-law distributed time intervals.
Artificial Life
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
doi.org/10.3389/fnbeh.2017.00198
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
doi.org/10.3389/fneur.2017.00031
2016
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
doi.org/10.3389/fnins.2016.00597
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) forNoise Trauma Induced Hearing Loss and Tinnitus.
PLoS one
doi.org/10.1371/journal.pone.0157574
2013
Lang, N. R., 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
doi.org/10.1016/j.bpj.2013.09.038
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