Univ.-Prof. Dr. Frank Scharnowski, MSc
T: +43-1-4277-47120
Summer term 2025
200020 VO Statistics I
200113 SE Advanced Seminar: Mind and Brain
200142 SE Master's Thesis Seminar (A)
540007 SE Seminar for Doctoral Students
Winter term 2024
200142 SE Advanced Seminar: Mind and Brain
200185 SE Master's Thesis Seminar (A)
540007 SE Seminar for Doctoral Students
540019 SE Introduction to CoBeNe
Summer term 2024
200020 VO Statistics I
200113 SE Advanced Seminar: Mind and Brain
200142 SE Master's Thesis Seminar (A)
540007 SE Seminar for Doctoral Students
Lor, C. S., Steyrl, D., Karner, A., Götzendorfer, S. J., Klimesch, A., Eder, S. J., Renz, F. M., Rother, J., Scharnowski, F., & Melinscak, F. (2025). SpiderPhy dataset: A multimodal dataset of Physiological, Psychometric and Behavioral Responses to fear stimuli. Scientific Data, 12(1), 599. https://doi.org/10.1038/s41597-025-04908-x
Zhang, M., Karner, A., Kostorz, K., Shea, S., Steyrl, D., Melinscak, F., Sladky, R., Lor, C. S., & Scharnowski, F. (2025). SpiDa-MRI behavioral and (f)MRI data of adults with fear of spiders. Scientific Data, 12(1), 284. https://doi.org/10.1038/s41597-025-04569-w
Spee, B. T. M., Leder, H., Mikuni, J., Scharnowski, F., Pelowski, M., & Steyrl, D. (2024). Using Machine Learning to Predict Judgments on Western Visual Art Along Content-Representational and Formal-Perceptual Attributes. PLoS ONE, 19(9), Article e0304285. https://doi.org/10.1371/journal.pone.0304285
Mikuni, J., Spee, B. T. M., Forlani, G., Leder, H., Scharnowski, F., Nakamura, K., Watanabe, K., Kawabata, H., Pelowski, M., & Steyrl, D. (2024). Cross-Cultural Comparison of Beauty Judgments in Visual Art Using Machine Learning Analysis of Art Attribute Predictors Among Japanese and German Speakers. Scientific Reports, 14(1), Article 15948. https://doi.org/10.1038/S41598-024-65088-Z
Karner, A., Obenaus, L., Zhang, M., Lor, C., Kostorz, K., Pegler, D., Leopold, M.-L., Melinšcak, F., Steyrl, D., & Scharnowski, F. (2024). Visual attributes of spiders associated with aversiveness in spider-fearful individuals: A machine learning analysis. PsyArXiv. https://doi.org/10.31234/osf.io/ht2pr
Popovova, J., Mazloum, R., Macauda, G., Stämpfli, P., Vuilleumier, P., Frühholz, S., Scharnowski, F., Menon, V., & Michels, L. (2024). Enhanced attention-related alertness following right anterior insular cortex neurofeedback training. Iscience, 27(2), 108915. Article 108915. https://doi.org/10.1016/j.isci.2024.108915
Zhang, M., Karner, A., Kostorz, K., Shea, S., Steyrl, D., Melinšcak, F., Sladky, R., Lor, C., & Scharnowski, F. (2024). SpiDa-MRI, behavioral and (f)MRI data of adults with fear of spiders. bioRxiv. https://doi.org/10.1101/2024.02.07.578564
Karner, A., Zhang, M., Lor, C. S., Steyrl, D., Götzendorfer, S. J., Weidt, S., Melinscak, F., & Scharnowski, F. (2024). The "SpiDa" dataset: self-report questionnaires and ratings of spider images from spider-fearful individuals. Frontiers in Psychology, 15, Article 1327367. https://doi.org/10.3389/fpsyg.2024.1327367
Kostorz, K., Nguyen, T., Pan, Y., Melinšcak, F., Steyrl, D., Hu, Y., Sorger, B., Hoehl, S., & Scharnowski, F. (2023). Towards fNIRS Hyperfeedback: A Feasibility Study on Real-Time Interbrain Synchrony. bioRxiv. https://doi.org/10.1101/2023.12.11.570765
Park, A. H., Patel, H., Mirabelli, J., Eder, S. J., Steyrl, D., Lueger-Schuster, B., Scharnowski, F., O'Connor, C., Martin, P., Lanius, R. A., McKinnon, M. C., & Nicholson, A. (2023). Machine learning models predict PTSD severity and functional impairment: A personalized medicine approach for uncovering complex associations among heterogeneous symptom profiles. Psychological Trauma. https://doi.org/10.1037/tra0001602
Lieberman, J. M., Rabellino, D., Densmore, M., Frewen, P. A., Steyrl, D., Scharnowski, F., Théberge, J., Hosseini-Kamkar, N., Neufeld, R. W. J., Jetly, R., Frey, B. N., Ros, T., Lanius, R. A., & Nicholson, A. A. (2023). A tale of two targets: examining the differential effects of posterior cingulate cortex- and amygdala-targeted fMRI-neurofeedback in a PTSD pilot study. Frontiers in Neuroscience, 17, Article 1229729. https://doi.org/10.3389/fnins.2023.1229729
Pamplona, G. S. P., Heldner, J., Langner, R., Koush, Y., Michels, L., Ionta, S., Salmon, C. E. G., & Scharnowski, F. (2023). Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention. Brain and Behavior, 13(10), Article e3217. https://doi.org/10.1002/brb3.3217
Spee, B. T. M., Mikuni, J., Leder, H., Scharnowski, F., Pelowski, M., & Steyrl, D. (2023). Machine learning revealed symbolism, emotionality, and imaginativeness as primary predictors of creativity evaluations of western art paintings. Scientific Reports, 13(1), Article 12966. https://doi.org/10.1038/s41598-023-39865-1
Lieberman, J. M., Rabellino, D., Densmore, M., Frewen, P. A., Steyrl, D., Scharnowski, F., Théberge, J., Neufeld, R. W. J., Schmahl, C., Jetly, R., Narikuzhy, S., Lanius, R. A., & Nicholson, A. A. (2023). Posterior cingulate cortex targeted real-time fMRI neurofeedback recalibrates functional connectivity with the amygdala, posterior insula, and default-mode network in PTSD. Brain and Behavior, 13(3), Article e2883. https://doi.org/10.1002/brb3.2883
Langner, R., Scharnowski, F., Ionta, S., G Salmon, C. E., Piper, B. J., & Pamplona, G. S. P. (2023). Evaluation of the reliability and validity of computerized tests of attention. PLoS ONE, 18(1), Article e0281196. https://doi.org/10.1371/journal.pone.0281196
Lor, C. S., Zhang, M., Karner, A., Steyrl, D., Sladky, R., Scharnowski, F., & Haugg, A. (2023). Pre- and post-task resting-state differs in clinical populations. NeuroImage: Clinical, 37, Article 103345. https://doi.org/10.1016/j.nicl.2023.103345
Lor, C. S., Haugg, A., Zhang, M., Schneider, L., Herdener, M., Quednow, B. B., Golestani, N., & Scharnowski, F. (2023). Thalamic volume and functional connectivity are associated with nicotine dependence severity and craving. Addiction Biology, 28(1), Article e13261. https://doi.org/10.1111/adb.13261
Terry, J., Ross, R. M., Nagy, T., Salgado, M., Garrido-Vásquez, P., Sarfo, J. O., Cooper, S., Buttner, A. C., Lima, T. J. S., Öztürk, İ., Akay, N., Santos, F. H., Artemenko, C., Copping, L. T., Elsherif, M. M., Milovanović, I., Cribbie, R. A., Drushlyak, M. G., Swainston, K., ... Field, A. P. (2023). Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset). Journal of Open Psychology Data, 11(1), Article 8. https://doi.org/10.5334/jopd.80
Watve, A., Haugg , A., Frei, N., Koush, Y., Willinger, D., Brühl, A. B., Stämpfli, P., Scharnowski, F., & Sladky, R. (2023). Facing emotions: real-time fMRI-based neurofeedback using dynamic emotional faces to modulate amygdala activity. Frontiers in Neuroscience, 17, Article 1286665. https://doi.org/10.3389/fnins.2023.1286665, https://doi.org/10.3389/fnins.2023.1286665
Giordano, V., Bibl, K., Felnhofer, A., Kothgassner, O., Steinbauer, P., Eibensteiner, F., Gröpel, P., Scharnowski, F., Wagner, M., Berger, A., Olischar, M., & Steyrl, D. (2022). Relationship between psychological characteristics, personality traits, and training on performance in a neonatal resuscitation scenario: A machine learning based analysis. Frontiers in Pediatrics , 10, Article 1000544. https://doi.org/10.3389/fped.2022.1000544
Interpretable machine learning for hypothesis
David Steyrl (Speaker), Alexander Karner (Speaker), Blanca Thea Maria Spee (Speaker) & Frank Scharnowski (Speaker)
16 Sept 2024 → 24 Sept 2024
Activity: Talks and presentations › Talk or oral contribution › Science to Science
Department of Cognition, Emotion, and Methods in Psychology
Head
Liebiggasse 5
1010 Wien
Room: O3.41
T: +43-1-4277-47120