SCIoI Alumni

Doris Pischedda

Postdoctoral Researcher

Neuroscience

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Photo: SCIoI

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Doris Pischedda

Doris Pischedda

Photo: SCIoI

Doris PIschedda is an external collaborator and former post-doctoral researcher at SCIoI (project 9, “Multimodal Interaction and Communication”). Doris is a neuroscientist interested in the cognitive mechanisms underlying human behavior and the neural representations of cognitive variables that may affect choice and guide action, especially during social interaction, with either humans or artificial agents. Her goal is to characterize and understand these cognitive processes so that they can be synthesized and reproduced in robots. To this purpose, she employs a combination of behavioral tasks, functional magnetic resonance imaging (fMRI), standard analysis methods, and advanced decoding techniques. At SCIoI, she used fMRI experiments to investigate partner-specific neural preparation in human-human and human-robot interaction. The general aim of the project was to identify brain structures that encode information specific to the particular task partner, to understand whether this partner-specific representation remains active during speaking and informs brain areas associated with speech production, and to evaluate to what degree human-robot interactions are processed in exactly the same fashion as human-human interactions. At SCIoI, Doris worked on a project called “Decoding partner-specific neural preparation in task-oriented human-human and human-robot interaction,” which was part of SCIoI Project 9.


Projects

Doris Pischedda is member of:


2756394 Pischedda 1 apa 50 date desc year 19982 https://www.scienceofintelligence.de/wp-content/plugins/zotpress/
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Pischedda, D. (2025). How do people discriminate conversations generated by humans and artificial intelligence? The role of individual variability on people’s judgment. Giornata sul pensiero.
Pischedda, D., Kaufmann, V., Wudarczyk, O., Abdel Rahman, R., Hafner, V. V., Kuhlen, A., & Haynes, J.-D. (2023). Human or AI? The brain knows it! A brain-based Turing Test to discriminate between human and artificial agents. RO-MAN 2023. https://doi.org/10.1109/RO-MAN57019.2023.10309541
Pischedda, D., Erener, S., Kuhlen, A., & Haynes, J.-D. (2023). How do people discriminate conversations generated by humans and artificial intelligence? The role of individual variability on people’s judgment. ESCOP 2023.
Reverberi, C., Pischedda, D., Mantovani, M., Haynes, J.-D., & Rustichini, A. (2022). Strategic complexity and cognitive skills affect brain response in interactive decision-making. Scientific Reports, 12, 15896. https://doi.org/10.1038/s41598-022-17951-0
Henke, L., Guseva, M., Wagemans, K., Pischedda, D., Haynes, J.-D., Jahn, G., & Anders, S. (2022). Surgical face masks do not impair the decoding of facial expressions of negative affect more severely in older than in younger adults. Cognitive Research: Principles and Implications, 7, 63. https://doi.org/10.1186/s41235-022-00403-8
Wudarczyk, O. A., Kirtay, M., Kuhlen, A. K., Abdel Rahman, R., Haynes, J.-D., Hafner, V. V., & Pischedda, D. (2021). Bringing Together Robotics, Neuroscience, and Psychology: Lessons Learned From an Interdisciplinary Project. Frontiers in Human Neuroscience, 15. https://doi.org/10.3389/fnhum.2021.630789
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Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Who is my interlocutor? Partner-specific neural representations during communicative interactions with human or artificial task partners. 5th Virtual Social Interactions (VSI) Conference.
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Pischedda, D., Palminteri, S., & Coricelli, G. (2020). The effect of counterfactual information on outcome value coding in medial prefrontal and cingulate cortex: From an absolute to a relative neural code. The Journal of Neuroscience, 40(16), 3268–3277. https://doi.org/10.1523/JNEUROSCI.1712-19.2020
Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, A., others, Pischedda, D., others, & Schonberg, T. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582, 84–88. https://doi.org/10.1038/s41586-020-2314-9

X-Student Research Group Grants (BUA, summer 2021)

Wissen aus Berlin - 19 July 2022 - Robots become social

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