Univ.-Prof. Dr. Frank Scharnowski, MSc
T: +43-1-4277-47120
Sommersemester 2025
200020 VO Statistik I
200113 SE Vertiefungsseminar: Geist und Gehirn - Mechanisms of exposure therapy as a dynamic feedback system
200142 SE Masterarbeitsseminar
540007 SE DissertantInnen-Seminar - Trends in cognitive and affective neuroscience
Wintersemester 2024
200142 SE Vertiefungsseminar: Geist und Gehirn - Clinical and scientific applications of neurofeedback
200145 SE Anwendungsseminar: Geist und Gehirn - Mechanisms of exposure therapy as a dynamic feedback system
200185 SE Masterarbeitsseminar
540007 SE DissertantInnen-Seminar - Trends in cognitive and affective neuroscience
540019 SE Introduction to CoBeNe
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. Artikel 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), Artikel 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), Artikel 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. Artikel 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, Artikel 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, 17(2), 372-386. 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, Artikel 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), Artikel 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), Artikel 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), Artikel 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), Artikel 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, Artikel 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), Artikel 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), Artikel 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, Artikel 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, Artikel 1000544. https://doi.org/10.3389/fped.2022.1000544
Interpretable machine learning for hypothesis
David Steyrl (Vortragende*r), Alexander Karner (Vortragende*r), Blanca Thea Maria Spee (Vortragende*r) & Frank Scharnowski (Vortragende*r)
16 Sept. 2024 → 24 Sept. 2024
Aktivität: Vorträge › Vortrag › Science to Science
Institut für Psychologie der Kognition, Emotion und Methoden
Leiter
Liebiggasse 5
1010 Wien
Zimmer: O3.41
T: +43-1-4277-47120