Publications

Guney, O. B.; Kücükahmetler, D.; Ozkan, H.: Source-free domain adaptation for SSVEP-based brain-computer interfaces. Journal of Neural Engineering 22 (5), 056028 (2025)

Mueller, K.; Scherf, N.; Grimmer, T.; Diehl‐Schmid, J.; Danek, A.; Levin, J.; Wiltfang, J.; Anderl‐Straub, S.; Otto, M.; Schroeter, M. L. et al.; FTLD Consortium Germany: Criminal behavior in frontotemporal dementia: A multimodal MRI study. Human Brain Mapping 46 (11), e70308 (2025)

Forster, C.; Stephani, T.; Grund, M.; Panagoulas, E.; Al, E.; Hofmann, S.; Nikulin, V. V.; Villringer, A.: Pre-stimulus beta power mediates explicit and implicit perceptual biases in distinct cortical areas. Communications Psychology 3 (1), 93 (2025)

Hofmann, S.; Goltermann, O.; Scherf, N.; Müller, K.-R.; Löffler, M.; Villringer, A.; Gaebler, M.; Witte, A. V.; Beyer, F.: The utility of explainable AI for MRI analysis: Relating model predictions to neuroimaging features of the aging brain. Imaging Neuroscience 3, imag_a_00497 (2025)

Abedi, M.; Shekarchizadeh, N.; Bazin, P.-L.; Scherf, N.; Lier, J.; Bergner, C.-C.; Alzheimer’s Disease Neuroimaging Initiative; Köhler, W.; Kirsten, T.: HeteroMRI: Robust white matter abnormality classification across multi-scanner MRI data. GigaScience 14, giaf092 (2025)

Filip, P.; Lasica, A.; Kiakou, D.; Mueller, K.; Keller, J.; Urgošík, D.; Novák, D.; Jech, R.: Sweet spot for resting-state functional MRI effect of deep brain stimulation in dystonia lies in the lower pallidal area. NeuroImage: Clinical 45, 103750 (2025)

Grigoryan, K.; Mueller, K.; Wagner, M.; Masri, D.; Pine, K.; Villringer, A.; Sehm, B.: Short-term BCI intervention enhances functional brain connectivity associated with motor performance in chronic stroke. NeuroImage: Clinical 46, 103772 (2025)

Ruthig, P.; Müller, G.; Fink, M.; Scherf, N.; Morawski, M.; Schönwiesner, M.: Hemispheric asymmetry of intracortical myelin orientation in the mouse auditory cortex. European Journal of Neuroscience 61 (2), e16675 (2025)

Wu, Q.; Kiakou, D.; Mueller, K.; Köhler, W.; Schroeter, M. L.: Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging: A systematic review and meta-analysis. NeuroImage: Clinical 45, 103757 (2025)

Kücükahmetler, D.; Hemmann, M. J.; von Aehrenfeld, J. M.; Amthor, M.; Deubel, C.; Scherf, N.; Taha, D.: A comparative empirical study of relative embedding alignment in neural dynamical system forecasters. In: Proceedings of the NeurIPS 2025 Workshop on Symmetry and Geometry in Neural Representations. (2025)

Graepler, S.; Scherf, N.; Wienhard, A.; Taha, D.: On the impact of topological regularization on geometrical and topological alignment in autoencoders: An empirical study. In: Proceedings of the NeurIPS 2025 Workshop NeurReps. (2025)

Gholamzadeh, E.; Singla, K.; Scherf, N.: Predicting microbial interactions using graph neural networks. In: Proceedings of the NeurIPS 2025 Workshop NPGML. (2025)

Beltran-Velandia, F.; Scherf, N.; Bogdan, M.: Correcting the modified stochastic synaptic model of synaptic dynamics refinement of vesicle and neurotransmitters functions. In: Artificial Neural Networks and Machine Learning – ICANN 2025, Vol. 16068, pp. 404 - 415 (Eds. Senn, W.; Sanguineti, M.; Saudargiene, A.; Tetko, I. V.; Villa, A. E. P. et al.). Springer Nature Switzerland, Cham (2025)

Torbati, N.; Gaebler, M.; Hofmann, S.; Scherf, N.: Geometry matters: Insights from Ollivier Ricci Curvature and Ricci Flow into representational alignment. In: Proceedings of the NeurIPS 2025 Workshop on Symmetry and Geometry in Neural Representations. (2025)

Milosevic, N.; Müller, J.; Scherf, N.: Central path proximal policy optimization. In: Proceedings of the 2025 International Conference on Machine Learning. (2025)

Milosevic, N.; Müller, J.; Scherf, N.: Embedding safety into RL: A new take on trust region methods. In: Proceedings of the 42nd International Conference on Machine Learning, Vol. 267, pp. 44199 - 44224. (2025)

Torbati, N.; Gaebler, M.; Hofmann, S.; Scherf, N.: Exploring geometric representational alignment through Ollivier Ricci curvature and Ricci flow. In: Proceedings of the ICLR 2025 Workshop Re-Align. (2025)

Hofmann, S.: Deep learning models in cognitive neurosciences. Max Planck School of Cognition, Cognition Academy, Dresden, Germany (2025)

Kiakou, D.; Lasica, A.; Mueller, K.; Filip, P.; Růžička, F.; Hofmann, S.; Urgosik, D.; Burdová, K.; Jech, R.: Volume of tissue activated and patient characteristics predict deep brain stimulation outcomes in Parkinson's disease. 12th MindBrainBody Symposium, Berlin, Germany (2025)

Kücükahmetler, D.; Dixit, S.; Schad, D. C.: Brain encoding models. Lecture: Lecture/Workshop, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, October 01, 2025 - March 31, 2026