Katja Dörschner Boyaci, Ph.D.
Prof.
Giessen University
FB 06 Psychology and Sports-Sciences
Otto-Behaghel-Str., 10F2
35394 Giessen, Germany
Kurzinfo
Research in my lab aims to uncover the mechanisms by which the brain is able to construct a rich perceptual experience from sensory input. Specifically, we concentrate on understanding the computational and neural mechanisms that allow humans to judge material qualities from static and dynamic images, and to find out how experiences and interactions with materials and objects shape perceptual expectations
project-related publications
Cavdan, M., Doerschner, K., Drewing, K. (2022). Haptic Discrimination of Different Types of Soft Materials. In: H. Seifi, et al. Haptics: Science, Technology, Applications. EuroHaptics 2022. Lecture Notes in Computer Science, vol 13235. Springer, Cham.
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Cavdan, M., Goktepe, N., Drewing, K., & Doerschner, K. (2023). Assessing the representational structure of softness activated by words. Scientific Reports, 13(1), 8974. find paper
Dövencioǧlu, D. N., Üstün, F. S., Doerschner, K., & Drewing, K. (2022). Hand explorations are determined by the characteristics of the perceptual space of real-world materials from silk to sand. Scientific Reports, 12(1), 14785. find paper
Kaiser, D., Stecher, R., & Doerschner, K. (2023). EEG decoding reveals neural predictions for naturalistic material behaviors. bioRxiv, 2023-02. find paper
Kaiser, D., Stecher, R., & Doerschner, K. (2024). EEG decoding reveals neural predictions for naturalistic material behaviors. Journal of Neuroscience43, no. 29 (2023): 5406-5413. find paper
Lin, L. P. Y., Cavdan, M., Doerschner, K., & Drewing, K. (2023, July). The Influence of Surface Roughness and Surface Size on Perceived Pleasantness. In 2023 IEEE World Haptics Conference (WHC) (pp. 417-424). IEEE. find paper
Malik, A., Doerschner, K., & Boyaci, H. (2023). Unmet expectations about material properties delay perceptual decisions. Vision Research, 208, 108223. find paper
Schmid AC, Barla P, & Doerschner, K (2023). Material category of visual objects computed from specular image structure. Nature Human Behaviour, 7(7), 1152-1169. find paper
former project-related publications
Alley, L. M., Schmid, A. C., & Doerschner, K. (2020). Expectations affect the perception of material properties. Journal of Vision, 20(12), 1-1. find paper
Cavdan, M., Doerschner, K. & Drewing, K. (2021). Task and material properties interactively affect softness explorations along different dimensions. IEEE Transactions on Haptics.
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Cavdan, M., Drewing, K., & Doerschner, K. (2021). The look and feel of soft are similar across different softness dimensions. Journal of vision, 21(10), 20-20.
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Cavdan, M., Ennis, R., Drewing, K. & Doerschner, K. (2021). Constraining haptic exploration with sensors and gloves hardly changes the multidimensional structure of softness perception. In 2021 IEEE World Haptics Conference (WHC) (pp. 31-36), IEEE.
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Cavdan, M., Freund, A., Trieschmann, A. K., Doerschner, K. & Drewing, K. (2020). From Hate to Love: How Learning Can Change Affective Responses to Touched Materials. In: Nisky I., Hartcher-O’Brien J., Wiertlewski M., Smeets J. (eds) "Haptics: Science, Technology, Applications". EuroHaptics 2020. Lecture Notes in Computer Science, vol 12272. Springer, Cham. find paper
Doerschner, K., Fleming, R. W., Yilmaz, O., Schrater, P. R., Hartung, B., & Kersten, D. (2011). Visual motion and the perception of surface material. Current Biology, 21(23), 2010-2016.
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Schmid, A. C., Boyaci, H., & Doerschner, K. (2021). Dynamic dot displays reveal material motion network in the human brain. NeuroImage, 117688.
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Schmid, A., Doerschner, K. (2018). The contribution of optical and mechanical properties to the perception of soft and hard breaking materials. Journal of Vision, 18(1), 14, 1-32.
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Schmid, A.C. & Doerschner, K. (2019). Representing stuff in the human brain. Current Opinion in Behavioral Sciences, 30, 178-185.
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Toscani, M., Yücel, E. I., & Doerschner, K. (2019). Gloss and speed judgments yield different fine tuning of saccadic sampling in dynamic scenes. i-Perception<, 10(6), 2041669519889070.
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