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, 07. Mai 2022 - 12. Mai 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)

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, S. 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), S. 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), S. 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, 20. Juli 2022 - 22. Juli 2022. (angenommen)

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), S. 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), S. S252 - S253. 33rd European College of Neuropsychopharmacology Congress (ECNP 2020) , 12. September 2020 - 15. September 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, S. 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), S. 894 - 895. 6th Congress of the European-Academy-of-Neurology (EAN), 23. Mai 2020 - 26. Mai 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), S. 104 - 104. 34. Deutscher Krebskongress informativ. innovativ. integrativ. Optimale Versorgung für alle, Berlin, Germany, 19. Februar 2020 - 22. Februar 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, 16. Juni 2018 - 21. Juni 2018. (2018)

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)

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)

Scherf, N.: Einige Gedanken und Fragen zum Umgang mit und zur Veröffentlichung von Bioimaging-Datenanalysen. 5. FDM-Workshop 2022, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (2022)

Scherf, N.: Machine learning in computational microscopy. 11th IMPRS NeuroCom Summer School, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (2022)

Beylier, C.; Scherf, N.; Doeller, C. F.; Menghi, N.: Representation in machine learning: A neuro-cognitive approach. French-German Research and Innovation Network for AI workshop, Inria Headquarters Domaine de Voluceau, Versaille, Frankreich (2022)

Niehaus, S.: Automated quality monitoring for more reliable integration of neural networks into medical workflows. AI.Lounge (Data Science / AI in Lifescience), Leipzig, Germany (2022)