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

Torrecuso, R.; Mueller, K.; Holiga, Š.; Urgosik, D.; Vymazal, J.; Sieger, T.; Růžička, F.; Růžička, E.; Schroeter, M. L.; Jech, R. et al.; Möller, H. E.: Different brain areas require different analysis models: fMRI observations in Parkinson's disease. In: Proceedings of the ISMRM 31st Annual Meeting & Exhibition. 2022 ISMRM Conference & Exhibition, May 07, 2022 - May 12, 2022. (2022)

Torrecuso, R.; Mueller, K.; Holiga, Š.; Sieger, T.; Vymazal, J.; Růžička , F.; Roth, J.; Růžička , E.; Schroeter, M. L.; Jech, R. et al.; Möller, H. E.: Improving brain imaging in Parkinson's disease by accounting for simultaneous motor output. In: Proceedings of the ISMRM 28th Annual Meeting & Exhibition. (2020)

Mueller, K.; Prinsen, J.; Zsido, R.; Witte, A. V.; Villringer, A.; Sacher, J.: Hormone-dependent dynamics of hippocampal connectivity across the menstrual cycle. In Neuropsychopharmacology, 51 (Suppl. 1), P867. Springer Nature, New York, NY (2026)

Panagoulas, E.; Chen, X.; Maidhof, B.; Hardikar, S.; Asseyer, S.; Al, E.; Villringer, K.; Mueller, K.; Krause, T.; Jungehülsing, G. J. et al.; Villringer, A.: Lower grey matter concentration in caudate nuclei is associated with subsequent development of central post stroke pain. In Clinical Neurophysiology, 159, p. e53. Elsevier, Amsterdam (2024)

Kiakou, D.; Mueller, K.; Ruzicka, F.; Lasica, A.; Filip, P.; Burdová, K.; Urgosík, D.; Jech, R.: Effects of deep brain stimulation on functional connectivity in Parkinson's disease. In European Journal of Neurology, 30 (Suppl. 1), p. 703 - 703. Rapid Communications, Oxford (2023)

Schlögl, H.; Villringer, A.; Miehle, K.; Stumvoll, M.; Mueller, K.: Metreleptin robustly increases resting-state brain connectivity in patients with lipodystrophy. In Diabetologia, 65 (Suppl. 1), p. S258 - S258. Springer-Verlag Heidelberg, Heidelberg (2022)

Beltran Velandia, F.; Gómez, J.; Suarez, M.; Ojeda, A.; León, E.: Classification of music-evoked emotions from EEG signals using self-organizing maps. In: Proceedings of the International Conference on Electrical, Computer and Energy Technologies. International Conference on Electrical, Computer and Energy Technologies, Prague, Czech Republic, July 20, 2022 - July 22, 2022. (accepted)

Jordan, B.; Fourcade, A.; Gaebler, M.; Scherf, N.; Loheit, A.-C.; Villringer, A.: Linking acute stress and heart rate variability in daily life while accounting for physical activity: A machine learning approach. In Journal of Computational Neuroscience, 49 (Suppl. 1), pp. S193 - S194. Kluwer Academic Publishers, Boston (2021)

Molloy, E.; Möller, H. E.; Regenthal, R.; Villringer, A.; Sacher, J.; Mueller, K.: Altered functional connectivity during combined sequential motor learning and one-week escitalopram administration. In European Neuropsychopharmacology, 40 (Suppl. 1), pp. S252 - S253. 33rd European College of Neuropsychopharmacology Congress (ECNP 2020) , September 12, 2020 - September 15, 2020. Elsevier, Amsterdam (2020)

Polyakova, M.; Beyer, F.; Mueller, K.; Sander, C.; Witte, A. V.; Lampe, L.; Rodrigues, F.; Riedel-Heller, S.; Kratzsch, J.; Hoffmann, K.-T. et al.; Villringer, A.; Schoenknecht, P.; Schroeter, M. L.: The first evidence for correlation between serum BDNF and regional cortical thickness in minor depression. In Psychoneuroendocrinology, 119, p. S33 - S33. Pergamon, Oxford (2020)

Jech, R.; Ruzicka, F.; Urgosik, D.; Holiga, Š.; Möller, H. E.; Roth, J.; Vymazal, J.; Schroeter, M. L.; Ruzicka, E.; Mueller, K.: Levodopa, but not subthalamic deep brain stimulation modulates the resting activity of putamen in Parkinson's disease. In European Journal of Neurology, 27 (Suppl. 1), pp. 894 - 895. 6th Congress of the European-Academy-of-Neurology (EAN), May 23, 2020 - May 26, 2020. Rapid Communications, Oxford (2020)

Zakrzewski, F.; Sommer, L.; Sperling, C.; Zuerich , A.; De Back, W.; Scherf, N.; Roeder, I.; Aust, D.; Hoenscheid, P.; Baretton, G.: Development of a convolutional neural network (CNN)-based classifier for automated tissue and tumor annotation of matrix-assisted laser desorption/ionization (MALDI) data. In Oncology Research and Treatment, 43 (Suppl. 1), p. 104 - 104. 34. Deutscher Krebskongress informativ. innovativ. integrativ. Optimale Versorgung für alle, Berlin, Germany, February 19, 2020 - February 22, 2020. Karger, Basel (2020)

Pine, K.; Vaculciakova, L.; Kirilina, E.; Scherf, N.; Weiskopf, N.: Multi-parameter mapping with 500 µm resolution using a flexible 23-channel RF coil. In Proceedings of the Joint Annual Meeting ISMRM-ESMRMB 2018. Joint Annual Meeting ISMRM-ESMRMB 2018, Paris Expo Porte de Versailles, Paris, France, June 16, 2018 - June 21, 2018. (2018)

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

Hofmann, S.: Explainable A.I. for neuroimage analysis: A general overview and an introduction to the xai4mri toolbox. 40th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB 2024), Barcelona, Spain (2024)

Titone, L.; Milosevic, N.; Meyer, L.: ARC: A framework to control for acoustic and phonological confounds in artificial language learning experiments. Interdisciplinary Advances in Statistical Learning, San Sebastián, Spain (2024)

Scherf, N.: Machine Cognition: A look into the artificial neural network. Session "The question of responsibility - AI and its consequences" at Data Week Leipzig 2024, New Town Hall, Leipzig (2024)

Hofmann, S.; Scherf, N.; Gaebler, M.: Scilaunch your research project. 11th MindBrainBody Symposium 2024, Berlin, Germany (2024)

Hofmann, S.; Milosevic, N.: Künstliche Intelligenz: Ein Blick in die Black Box der Technologie und ihre Grenzen. MACHN 23 Festival – Festival for Tech, Business & Art, Leipzig, Germany (2023)