Publications

    2026

  • J. Meyer zu Bexten, B. Franczyk, N. Scherf, S. M. Hofmann, 2026, "From Clever Hans to Hypotheses: Interpreting EEG foundational transformers", Foundation Models for the Brain and Body, NeurIPS 2026 Workshop.

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  • N. Torbati, M. Gaebler, S. M. Hofmann, N. Scherf, 2026, "Geometry matters: Insights from Ollivier Ricci curvature and Ricci flow into representational alignment", Proceedings of Machine Learning Research (PMLR), Vol. 282.

  • S. M. Hofmann, A. Ciston, A. Koushik, F. Klotzsche, M. N. Hebart, K.-R. Müller, A. Villringer, N. Scherf, A. Hilsmann, V. V. Nikulin, M. Gaebler, 2026, "Dynamic presentation in 3D modulates face similarity judgements: A human-aligned encoding model approach", Royal Society Open Science.

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  • N. Herzog, L. Vähäsarja, P. Reinfeld, N. Scherf, S. M. Hofmann, C. Andreou, A. Villringer, C. Mulert, 2026, "From surface to depth: Using deep learning to predict striatal fMRI reward signaling from EEG", Imaging Neuroscience.

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  • C. Beylier, A. Fleig, H. Selder, S. M. Hofmann, N. Scherf, 2026, "Attention trajectories as a diagnostic axis for deep reinforcement learning", Transactions on Machine Learning Research (TMLR).

    • 2025

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

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    • 2024

  • C. Beylier, S. M. Hofmann, N. Scherf, 2024, "Revealing the learning process in reinforcement learning agents through attention-oriented metrics", NeurIPS 2024 Workshop on Scientific Methods for Understanding Deep Learning (SciForDL).

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    • 2023

  • H. Schlögl, A. Villringer, K. Miehle, M. Fasshauer, M. Stumvoll, K. Mueller, 2023, "Metreleptin robustly increases resting-state brain connectivity in treatment-naïve female patients with lipodystrophy", Journal of the Endocrine Society.

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  • H. Schlögl, L. Janssen, M. Fasshauer, K. Miehle, A. Villringer, M. Stumvoll, K. Mueller, 2023, "Reward processing during monetary incentive delay task after leptin substitution in lipodystrophy - An fMRI case series", Journal of the Endocrine Society.

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  • Manifold Learning
    K. Mueller, F. Thiel, B. Taskin, F. Beutner, A. Teren, V. K. Dubovoy, H. E. Möller, A. Villringer, M. L. Schroeter, 2023, "Brain dysconnectivity with heart failure", Brain Communications.

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  • E. Williams, M. Kienast, E. Medawar, J. Reinelt, A. Merola, S. A. I. Klopfenstein, A. R. Flint, P. Heeren, A.-S. Poncette, F. Balzer, et al., 2023, "A standardized clinical data harmonization pipeline for scalable AI application deployment (FHIR-DHP): Validation and usability study", JMIR Medical Informatics (JMI).

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  • K. I. Paul, K. Mueller, P.-N. Rousseau, A. Glathe, N. A. Taatgen, F. Cnossen, P. Lanzer, A. Villringer, C. Steele, 2023, "Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill", NeuroImage.

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  • Manifold Learning
    M. L. Schroeter, J. Godulla, F. Thiel, B. Taskin, F. Beutner, V. K. Dubovoy, A. Teren, J. Camilleri, S. Eickhoff, A. Villringer, et al., 2023, "Heart failure decouples the precuneus in interaction with social cognition and executive functions", Scientific Reports.

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  • L. Lampe, H.-J. Huppertz, S. Anderl-Straub, F. Albrecht, T. Ballarini, S. Bisenius, K. Mueller, S. Niehaus, K. Fassbender, K. Fliessbach, et al., 2023, "Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging", NeuroImage: Clinical.

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  • R. Torrecuso, K. Mueller, Š. Holiga, T. Sieger, J. Vymazal, F. Růžička, J. Roth, E. F. Růžička, M. L. Schroeter, R. Jech, et al., 2023, "Improving fMRI in Parkinson's disease by accounting for brain region-specific activity patterns", NeuroImage: Clinical.

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  • D. Kiakou, A. Adamopoulos, N. Scherf, 2023, "Graph-based disease prediction in neuroimaging: Investigating the impact of feature selection", Advances in Experimental Medicine and Biology (AEMB).

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  • Manifold Learning
    K.-R. Müller, S. Hofmann, 2023, "Interpreting deep learning models for multi-modal neuroimaging", Proceedings of the 11th International Winter Conference on Brain-Computer Interface (BCI).

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    • 2022

  • Manifold Learning
    P. Filip, R. Jech, A. Fečíková, P. Havránková, F. Růžička, K. Mueller, D. Urgošík, 2022, "Restoration of functional network state towards more physiological condition as the correlate of clinical effects of pallidal deep brain stimulation in dystonia", Brain Stimulation.

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  • Manifold Learning
    N. Koutsouleris, C. Pantelis, D. Velakoulis, P. McGuire, D. B. Dwyer, M.-F. Urquijo-Castro, R. Paul, S. Dong, D. Popovic, O. Oeztuerk, et al., 2022, "Exploring links between psychosis and frontotemporal dementia using multimodal machine learning: Dementia praecox revisited", JAMA Psychiatry.

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  • P. Paschou, Y. Jin, K. Müller-Vahl, H. E. Möller, R. Rizzo, P. J. Hoekstra, V. Roessner, N. Mol Debes, Y. Worbe, A. Hartmann, et al., 2022, "Enhancing neuroimaging genetics through meta-analysis for Tourette syndrome (ENIGMA-TS): A worldwide platform for collaboration", Frontiers in Psychiatry.

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  • M. Polyakova, K. Mueller, K. Arélin, L. Lampe, F. S. Rodriguez, T. Luck, J. Kratzsch, K.-T. Hoffmann, S. Riedel-Heller, A. Villringer, et al., 2022, "Increased serum NSE and S100B indicate neuronal and glial alterations in subjects under 71 years with mild neurocognitive disorder/mild cognitive impairment", Frontiers in Cellular Neuroscience.

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  • K. Mueller, F. Růžička, M. Slovák, Z. Forejtová, P. Dušek, P. Dušek, R. Jech, T. Serranová, 2022, "Symptom-severity-related brain connectivity alterations in functional movement disorders", NeuroImage: Clinical.

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  • L. Maiello, L. Ball, M. Micali, F. Iannuzzi, N. Scherf, R.-T. Hoffmann, M. Gama de Abreu, P. Pelosi, R. Huhle, 2022, "Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning", Frontiers in Physiology.

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  • R. Jech, K. Mueller, 2022, "Investigating network effects of DBS with fMRI", Connectomic Deep Brain Stimulation.

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  • R. Torrecuso, K. Mueller, Š. Holiga, D. Urgosik, J. Vymazal, T. Sieger, F. Růžička, E. Růžička, M. L. Schroeter, R. Jech, et al., 2022, "Different brain areas require different analysis models: fMRI observations in Parkinson's disease", ISMRM 31st Annual Meeting & Exhibition.

  • E. Williams, M. Kienast, E. Medawar, J. Reinelt, A. Merola, S. A. I. Klopfenstein, A. R. Flint, P. Heeren, A.-S. Poncette, F. Balzer, et al., 2022, "FHIR-DHP: A standardized clinical data harmonisation pipeline for scalable AI application deployment", Medrxiv.

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  • L. Hahn, S. B. Eickhoff, K. Mueller, L. Schilbach, H. Barthel, K. Fassbender, K. Fliessbach, J. Kornhuber, J. Prudlo, M. Synofzik, et al., 2022, "Resting-state alterations in behavioral variant frontotemporal dementia are related to the distribution of monoamine and GABA neurotransmitter systems", Medrxiv.

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  • K. I. Paul, K. Mueller, P.-N. Rousseau, A. Glathe, N. A. Taatgen, F. Cnossen, P. Lanzer, A. Villringer, C. Steele, 2022, "Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill", Biorxiv.

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