Doris Pischedda

External collaborator
mail: doris.pischedda@charite.de

Doris Pischedda 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 uses fMRI experiments to investigate partner-specific neural preparation in human-human and human-robot interaction. The general aim of the project is 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.

Doris is currently working on a project called “Decoding partner-specific neural preparation in task-oriented human-human and human-robot interaction,” which is part of SCIoI Project 09.

 

 

 

SCIoI Publications:

Wudarczyk, O. A., Kirtay, M., Pischedda, D., Hafner, V. V., Haynes, J.-D., Kuhlen, A. K., & Abdel Rahman, R. (2021). Robots facilitate human language production. Scientific Reports, 11(1), 16737. https://doi.org/10.1038/s41598-021-95645-9
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
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
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
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O. A., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Am I speaking to a human, a robot, or a computer? Neural representations of task partners in communicative interactions with humans or artificial agents. Neuroscience 2021.
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.
Kirtay, M., Wudarczyk, O. A., Pischedda, D., Kuhlen, A. K., Abdel Rahman, R., Haynes, J.-D., & Hafner, V. V. (2020). Modeling robot co-representation: state-of-the-art, open issues, and predictive learning as a possible framework. 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 1–8. https://doi.org/10.1109/ICDL-EpiRob48136.2020.9278031
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
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
Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) im Rahmen der Exzellenzstrategie des Bundes und der Länder – EXC-2002/1 – Projektnummer 390523135 .
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany ́s Excellence Strategy – EXC-2002/1 – Projectnumber 390523135.

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