Principles of Cognition in
Brains and Machines
Computational neuroscience, empirical brain research and physical constraints of intelligent systems
Computational neuroscience, empirical brain research and physical constraints of intelligent systems
Preprints
2025
Koelbl, N., Rampp, S., Kaltenhaeuser, M., Tziridis, K., Maier, A., Kinfe, T., Chavarriaga, R., Krauss, P.* & Schilling, A.*
Prediction, Syntax and Semantic Grounding in the Brain and Large Language Models.
bioRxiv
doi.org/10.1101/2025.06.05.658007
* contributed equally
Koelbl, N, Tziridis, K., Maier, A., Kinfe, T., Chavarriaga, R., Schilling, A. & Krauss, P.
The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities.
arXiv:2506.08511
arxiv.org/abs/2506.08511
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
Kissane, H., Koelbl, N., Schilling, A. & Krauss, P. (2025)
Different Multiword Verb Categories are Processed Differentially in the Brain: An Evidence from EEG Analysis and Decoding.
bioRxiv
doi.org/10.1101/2025.06.06.658278
Metzner, C., Schilling, A., Maier, A., & Krauss, P.
Organizational Regularities in Recurrent Neural Networks.
arXiv:2505.22047
arxiv.org/abs/2505.22047
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