Speech, Language and Cognition in
Brains, Minds and Machines
Publications - Preprints
Publications - Preprints
Preprints
2025
Krauss, P. & Schilling, A.
Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions.
arXiv: 2501.10072
arxiv.org/abs/2501.10072
Banerjee, A., Schilling, A. & Krauss, P. (2025).
Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT.
arXiv: 2501.08053
arxiv.org/abs/2501.08053
Hildebrandt, F., Maier, A., Krauss, P.* & Schilling, A.* (2025).
Refusal Behavior in Large Language Models: A Nonlinear Perspective.
arXiv: 2501.08145
arxiv.org/abs/2501.08145
Kissane, H., Schilling, A. & Krauss, P. (2025).
Probing Internal Representations of Multi-Word Verbs in Large Language Models.
arXiv: 2502.04789
2024
Krauss, P., Hösch, J., Metzner, C., Maier, A., Uhrig, P., & Schilling, A. (2024).
Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT.
arXiv: 2405.02024
arxiv.org/abs/2405.02024
Ramezani, P., Schilling, A., & Krauss, P. (2024).
Analysis of Argument Structure Constructions in the Large Language Model BERT.
arXiv:2408.04270
arxiv.org/abs/2408.04270
Kissane, H., Schilling, A., & Krauss, P. (2024).
Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT.
arXiv:2412.14670
Koelbl, N., Mueller-Voggel, N., Rampp, S., Kaltenhaeuser, M., Tziridis, K., Krauss, P., & Schilling, A. (2024).
Analyzing Differences in Processing Nouns and Verbs in the Human Brain using Combined EEG and MEG Measurements.
bioRxiv
doi.org/10.1101/2024.12.04.626813
Krauss, P., Koelbl, N., Mueller-Voggel, N., Rampp, S., Kaltenhaeuser, M., Tziridis, K., & Schilling, A. (2024).
Temporal and Hemispheric Dynamics in Neural Processing of Auditory and Speech Stimuli Across Linguistic Complexity: A MEG Source Space Study.
bioRxiv
doi.org/10.1101/2024.12.05.626939
Kissane, H., Tziridis, K., Schilling, A., Krauss, P., & Herbst, T. (2024).
Cognitive Dynamics of Verb-Particle Constructions: An Eye-Tracking Study.
bioRxiv
doi.org/10.1101/2024.12.05.626940
Immertreu, M., Schilling, A., Maier, A., & Krauss, P. (2024).
Probing for Consciousness in Machines.
arXiv: 2411.16262
Metzner, C., Schilling, A., Maier, A., & Krauss, P. (2024).
Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing.
arXiv: 2411.10047
Ramezani, P., Schilling, A., & Krauss, P. (2024).
Analysis of Argument Structure Constructions in a Deep Recurrent Language Model.
arXiv:2408.03062
arxiv.org/abs/2408.03062
Metzner, C., Schilling, A., Maier, A., & Krauss, P. (2024)
Recurrence Resonance - Noise-Enhanced Dynamics in Recurrent Neural Networks.
arXiv:2408.05579
arxiv.org/abs/2408.05579
Schneider, L., Krauss, P., Schiering, N., Syben, Ch., Schielein, R., & Maier, A. (2024)
Data-driven Modeling in Metrology - A Short Introduction, Current Developments and Future Perspectives
arXiv:2406.16659
arxiv.org/abs/2406.16659
Tziridis, K., Neubert, B., Seehaus, A. R. A., Krauss, P., Schilling, A., Brüggemann, P., Mazurek, B., & Schulze, H. (2024).
Correlation of Non-Auditory Comorbidities and Hearing Loss in Tinnitus Patients.
Preprints 2024, 2024021763
www.preprints.org/manuscript/202402.1763/v1
2023
Stoewer, P., Schilling, A., Maier, A., & Krauss, P. (2023).
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations.
arXiv:2401.01364
arxiv.org/abs/2401.01364
Stoewer, P., Schilling, A., Maier, A., & Krauss, P. (2023)
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings.
arXiv: 2307.01577
arxiv.org/abs/2307.01577
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.
arXiv: 2302.07588
arxiv.org/abs/2302.07588
Schüller, A., Schilling, A., Krauss, P., & Reichenbach, T. (2023)
Early subcortical response at the fundamental frequency of continuous speech measured with MEG.
bioRxiv 546296
doi.org/10.1101/2023.06.23.546296
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.
bioRxiv 547608
doi.org/10.1101/2023.07.03.547608
Metzner, C., Schilling, A., Traxdorf, M., Schulze, H., Tziridis, K., & Krauss, P. (2023)
Extracting continuous sleep depth from EEG data without machine learning.
arXiv:2301.06755
arxiv.org/abs/2301.06755
Metzner, C., Yamakou, M., Voelkl, D., Schilling, A., & Krauss, P. (2023)
Quantifying and maximizing the information flux in recurrent neural networks.
arXiv: 2301.12892
arxiv.org/abs/2301.12892
Metzner, C., Schilling, A., & Krauss, P. (2023).
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD).
arXiv:2311.16621
arxiv.org/abs/2311.16621
Tziridis, K., Rasheed, J., Krauss, P., Schilling, A., & Schulze, H. (2023).
Tinnitus is associated with increased extracellular matrix density in the auditory cortex.
Authorea Preprints.
essopenarchive.org/doi/full/10.22541/au.170020631.15815554
2022
Schilling, A., Tziridis, K., Schulze, H., & Krauss, P. (2022).
Behavioral assessment of Zwicker tone percepts in rodents.
bioRxiv
doi.org/10.1101/2022.12.22.521554
Stoewer, P., Schilling, A., Maier, A., & Krauss, P. (2022).
Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Concepts.
arXiv:2210.16062
arxiv.org/abs/2210.16062
Metzner, C., Schilling, A., Traxdorf, M., Tziridis, K., Schulze, H. & Krauss, P. (2022).
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity.
arXiv:2206.01922
arxiv.org/abs/2206.01922
Schilling, A., Gerum, R., Boehm, C., Rasheed, J., Metzner, C., Maier, A., Reindl, C., Hamer, H., & Krauss, P. (2022).
Deep learning based decoding of local field potentials.
bioRxiv
doi.org/10.1101/2022.10.14.512209
Schilling, A., Sedley, W., Gerum, R., Metzner, C., Tziridis, K., Maier, A., Schulze, H., Zeng, F.-G., Friston, K.J., & Krauss, P. (2022).
Predictive coding and stochastic resonance as fundamental principles of auditory perception.
arXiv:2204.03354
arxiv.org/abs/2204.03354
Garibyan, A., Schilling, A., Boehm, C., Zankl, A., & Krauss, P. (2022).
Neural Correlates of Linguistic Collocations During Continuous Speech Perception.
bioRxiv
doi.org/10.1101/2022.03.25.485771
Stoewer, P., Schlieker, C., Schilling, A., Metzner, C., Maier, A., & Krauss, P. (2022).
Neural Network based Successor Representation of Space and Language
arXiv:2202.11190
arxiv.org/abs/2202.11190
2021
Metzner, C. & Krauss, P. (2021).
Dynamical Phases and Resonance Phenomena in Information-Processing Recurrent Neural Networks.
arXiv:2108.02545
arxiv.org/abs/2108.02545
Metzner, C., Schilling, A., Traxdorf, M., Schulze, H. & Krauss, P. (2021).
Sleep as a random walk – Superstatistical analysis of EEG data across sleep stages.
bioRxiv
doi.org/10.1101/2021.06.25.449874
Boensel, F., Krauss, P., Metzner, C. & Yamakou, M. (2021).
Control of noise-induced coherent oscillations in time-delayed neural motifs.
arXiv:2106.11361
Maier, A., Köstler, H., Heisig, M., Krauss, P. & Yang, S.H. (2021).
Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future
arXiv:2108.04543
arxiv.org/abs/2108.04543
2020
Krauss, P. & Schilling, A. (2020).
Towards a Cognitive Computational Neuroscience of Auditory Phantom Perceptions.
arXiv:2010.01914
Krauss, P. & Maier, A. (2020).
Will we ever have conscious Machines?
arXiv:2003.14132
Krauss, P., Metzner, C., Joshi, N., Schulze, H., Traxdorf, M., Maier, A. & Schilling, A. (2020).
Analysis and Visualization of Sleep Stages based on Deep Neural Networks.
bioRxiv
https://doi.org/10.1101/2020.06.25.170464
Krauss, P. (2020).
Improved pure tone sensitivity after simulated hearing loss
bioRxiv
https://doi.org/10.1101/2020.05.29.124321
Schilling, A., Tomasello, R., Henningsen-Schomers, M.R., Zankl, A., Surendra, K., Haller, M., Karl, V., Uhrig, P., Maier, A. & Krauss, P. (2020).
Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods.
bioRxiv
https://doi.org/10.1101/2020.04.21.052720
Schilling, A., Tziridis, K., Schulze, H. & Krauss, P. (2020).
The Stochastic Resonance model of auditory perception:
A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition.
bioRxiv
https://doi.org/10.1101/2020.03.27.011163
Schilling, A., Gerum, R., Zankl, A., Metzner, C., Maier, A. & Krauss, P. (2020).
Intrinsic noise improves speech recognition in a computational model of the auditory pathway.
bioRxiv
https://doi.org/10.1101/2020.03.16.993725
Jeschke, M., Happel, M.F.K., Tziridis, K., Krauss, P., Schilling, A., Schulze, H., & Ohl, F.W. (2020).
Acute and long-term circuit-level effects in the auditory cortex after sound trauma.
bioRxiv
https://doi.org/10.1101/2020.03.06.980730
2019
Gerum, R., Erpenbeck, A., Krauss, P., & Schilling, A. (2019).
Sparsity through evolutionary pruning prevents neuronal networks from overfitting.
arXiv:1911.10988
2018
Krauss, P., Prebeck, K., Schilling, A., & Metzner, C. (2018).
Stochastic Resonance in three-neuron motifs.
arXiv:1811.12091
Krauss, P., Schuster, M., Dietrich, V., Schilling, A, Schulze, H & Metzner, C. (2018).
Weight statistics controls dynamics in recurrent neural networks.
bioRxiv
https://doi.org/10.1101/475319
Krauss, P., Zankl, A., Schilling, A., Schulze, H. & Metzner, C. (2018)
Analysis of structure and dynamics in three-neuron motifs.
arXiv:1811.05225
Schilling, A., Metzner, C., Rietsch, J., Gerum, R., Schulze, H., & Krauss, P. (2018).
How deep is deep enough? - Quantifying class separability in the hidden layers of deep neural networks.
arXiv:1811.01753
Schilling, A, Gerum, R., Krauss, P., Metzner, C., Tziridis, K. & Schulze, H. (2018).
Objective estimation of sensory thresholds based on neurophysiological parameters.
arXiv:1811.02335
Gerum, R., Rahlfs, H., Streb, M., Krauss, P., Metzner, C., Tziridis, K., Günther, M., Schulze, H., Kellermann, W. & Schilling, A. (2018).
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.
arXiv:1804.09667
Forster, J., Wendler, O., Buchheidt-Doerfler, I., Krauss, P., Schilling, A., Sterna, E., Schulze, H., & Tziridis, K. (2018).
Tinnitus development is associated with synaptopathy of inner hair cells in Mongolian gerbils.
bioRxiv
https://doi.org/10.1101/304576
2016
Krauss, P., Metzner, C., Schilling, A., Tziridis, K., Traxdorf M., & Schulze, H. (2016).
A statistical method for analyzing and comparing spatiotemporal cortical activation patterns.
arXiv:1611.07677
Krauss, P., Tziridis, K., Schilling, A., Metzner, C., & Schulze, H. (2016).
Stochastic resonance controlled upregulation of internal noise after hearing loss as a putativecorrelate of tinnitus-related neuronal hyperactivity.
arXiv:1603.04721
2015
Krauss, P., Metzner, C., Tziridis, K., & Schulze, H. (2015).
Adaptive stochastic resonance based on output autocorrelations.
arXiv:1504.05032
2011
Krauss, P., Metzner, C., Lange, J., Lang, N., & Fabry, B. (2011).
Reconstructing fiber networks from confocal image stacks.
arXiv:1111.3861
Metzner, C., Krauss, P., & Fabry, B. (2011).
Poresizes in random line networks.
arXiv:1110.1803