Univ.-Prof. Dr. Frank Scharnowski, MSc
T: +43-1-4277-47120
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
Sommersemester 2024
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 2023
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
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), [e0304285]. https://doi.org/10.1371/journal.pone.0304285, 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), [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. [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, [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, [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), [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), [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), [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), [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, [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), [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), [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, [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, [1000544]. https://doi.org/10.3389/fped.2022.1000544
Lor, C. S., Haugg, A., Zhang, M., Schneider, L. M., Herdener, M., Quednow, B. B., Golestani, N., & Scharnowski, F. (2022). Thalamic volume and functional connectivity are associated with nicotine dependence severity and craving. bioRxiv. https://doi.org/10.1101/2022.09.25.509385
Lor, C. S., Zhang, M., Karner, A., Steyrl, D., Sladky, R., Scharnowski, F., & Haugg, A. (2022). Pre- and post-task resting-state differs in clinical populations. bioRxiv. https://doi.org/10.1101/2022.09.20.508750
Interpretable machine learning for hypothesis
David Steyrl (Vortragende*r), Alexander Karner (Vortragende*r), Blanca Thea Maria Spee (Vortragende*r) & Frank Scharnowski (Vortragende*r)
16 Sep. 2024 → 24 Sep. 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