Kerstin PREUSCHOFF
Professeure associée
Geneva Finance Research Institute
Ph.D., California Institute of Technology
Uni Pignon - 409
+41 22 379 81 41
Courriel
Brève biographie
Kerstin Preuschoff obtained her PhD in Computation and Neural Systems & Neuroeconomics from the California Institute of Technology. Her research in Neuroeconomics and Neurofinance focusses on the neural basis of decision making under risk. This highly interdisciplinary work covers theoretical and experimental aspects of decision making and risk taking and sits at the intersection of neuroscience, financial economics, computational neuroscience and psychology. Her teaching interests include neuroeconomics, neurofinance and interdisciplinary tools in finance. Prior to joining the University of Geneva, Kerstin Preuschoff was a researcher and lecturer at the Institute for Empirical Research in Economics at the University of Zurich and at the Brain Mind Institute at the EPF Lausanne.
Recherche & publications
M. Lehmann, H. Xu, V. Liakoni, M. Herzog, W. Gerstner, Kerstin Preuschoff, “Evidence for eligibility traces in human learning” arXiv:1707.04192. 2017
E. Miendlarzewska, M. Kometer, Kerstin Preuschoff, “Neurofinance”, Organizational Research Methods, (accepted)
M. Faraji, Kerstin Preuschoff, W. Gerstner, “Balancing New Against Old Information: The Role of Surprise” Neural Computation, (in press)
L. Loued-Khenissi and Kerstin Preuschoff, “Apathy and Noradrenaline: Silent Partners to mild cognitive impairment in Parkinson’s Disease?” Current Opinion in Neurology, 2015 Aug; 28(4): 344-50.
Kerstin Preuschoff is a multi-disciplinary scientist and educator with a passion for communicating science across disciplines and audiences. She first studied electrical engineering in Berlin before obtaining her PhD in computation and neural systems from Caltech. She is currently an associate professor of neurofinance at the University of Geneva. Her research includes all aspects of decision-making - from the neuroscience behind it, to its impact on financial markets. Her primary research focus is the neural basis of decision making under risk and combines theoretical and experimental ap- proaches from neuroscience, financial economics, and psychology.
Sélection de publications
Article
Liakoni, V., Lehmann, M. P., Modirshanechi, A., Brea, J., Lutti, A., Gerstner, W., & Preuschoff, K. (2022). Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making. NeuroImage, 246, 118780. https://doi.org/10.1016/j.neuroimage.2021.118780.
Williams, T. B., Burke, C. J., Nebe, S., Preuschoff, K., Fehr, E., & Tobler, P. N. (2021). Testing models at the neural level reveals how the brain computes subjective value. Proceedings of the National Academy of Sciences, 118 (43), e2106237118. https://doi.org/10.1073/pnas.2106237118.
Loued-Khenissi, L., & Preuschoff, K. (2020). A Bird's eye view from below: Activity in the temporo-parietal junction predicts from-above Necker Cube percepts. Neuropsychologia, 149, 107654. https://doi.org/10.1016/j.neuropsychologia.2020.107654.
Lauffs, M. M., Geoghan, S. A., Favrod, O., Herzog, M. H., & Preuschoff, K. (2020). Risk prediction error signaling: A two-component response? NeuroImage, 214, 116766. https://doi.org/10.1016/j.neuroimage.2020.116766.
Loued-Khenissi, L., Preuschoff, K., Pfeuffer, A., & Einhäuser, W. (2020). Anterior insula reflects surprise in value-based decision-making and perception. NeuroImage, 116549. https://doi.org/10.1016/j.neuroimage.2020.116549.
Loued-Khenissi, L., & Preuschoff, K. (2020). Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain. Frontiers in Artificial Intelligence, 3. https://doi.org/10.3389/frai.2020.00005.
Kometer, M., Miendlarzewska, E. A., & Preuschoff, K. (2019). Neurofinance. Organizational Research Methods, 22 (1), 196-222. https://doi.org/10.1177/1094428117730891.
Döll, O., Loued-Khenissi, L., & Preuschoff, K. (2019). An Overview of Functional Magnetic Resonance Imaging Techniques for Organizational Research. Organizational Research Methods, 22 (1), 17-45. https://doi.org/10.1177/1094428118802631.
Lehmann, M. P., Xu, H. A., Liakoni, V., Herzog, M. H., Gerstner, W., & Preuschoff, K. (2019). One-shot learning and behavioral eligibility traces in sequential decision making. eLife, 8. https://doi.org/10.7554/eLife.47463.
Faraji, M., Preuschoff, K., & Gerstner, W. (2018). Balancing New against Old Information: The Role of Puzzlement Surprise in Learning. Neural Computation, 30 (1), 34-83. https://doi.org/10.1162/neco_a_01025.
Loued-Khenissi, L., & Preuschoff, K. (2015). Apathy and noradrenaline; silent partners to mild cognitive impairment in parkinsons's disease? Current Opinion in Neurology, 28 (4), 344-350. https://doi.org/10.1097/WCO.0000000000000218.
Preuschoff, K., Mohr, P. N. C., & Hsu, M. (2013). Decision making under uncertainty. Frontiers in Neuroscience, 7. https://doi.org/10.3389/fnins.2013.00218.
Preuschoff, K., Rudorf, S., & Weber, B. (2012). Neural Correlates of Anticipation Risk Reflect Risk Preferences. Journal of Neuroscience, 32 (47), 16683-16692. https://doi.org/10.1523/JNEUROSCI.4235-11.2012.
Daunizeau, J., Preuschoff, K., Friston, K., & Stephan, K. (2011). Optimizing Experimental Design for Comparing Models of Brain Function. PLOS Computational Biology, 7 (11). https://doi.org/10.1371/journal.pcbi.1002280.
Preuschoff, K., 't Hart, B., & Einhäuser, W. (2011). Pupil dilation signals surprise: evidence for noradrenaline’s role in decision making. Frontiers in Neuroscience, 5. https://doi.org/10.3389/fnins.2011.00115.
Hein, G., Silani, G., Batson, C. D., & Singer, T. (2010). Neural Responses to Ingroup and Outgroup Members' Suffering Predict Individual Differences in Costly Helping. Neuron, 68 (1), 149-160. https://doi.org/10.1016/j.neuron.2010.09.003.
Singer, T., & Critchley, H. D. (2009). A common role of insula in feelings, empathy and uncertainty. Trends in Cognitive Sciences, 13 (8), 334-340. https://doi.org/10.1016/j.tics.2009.05.001.
Bruguier, A., Preuschoff, K., Quartz, S., & Bossaerts, P. (2008). Investigating signal integration with canonical correlation analysis of fMRI brain activation data. NeuroImage, 41 (1), 35-44. https://doi.org/10.1016/j.neuroimage.2008.01.062.
Schultz, W., Camerer, C., Hsu, M., Fiorillo, C. D., Tobler, P. N., & Bossaerts, P. (2008). Explicit neural signals reflecting reward uncertainty. Philosophical Transactions of the Royal Society B: Biological Sciences, 363 (1511), 3801-3811. https://doi.org/10.1098/rstb.2008.0152.
Preuschoff, K., Quartz, S. R., & Bossaerts, P. (2008). Human Insula Activation Reflects Risk Prediction Errors As Well As Risk. Journal of Neuroscience, 28 (11), 2745-2752. https://doi.org/10.1523/JNEUROSCI.4286-07.2008.
Preuschoff, K., Quartz, S., & Bossaerts, P. (2008). Markowitz in the brain ? Revue d'Économie Politique, 118 (1), 75. https://doi.org/10.3917/redp.181.0075.
Koch, C., & Preuschoff, K. (2007). Betting the house on consciousness. Nature Neuroscience, 10 (2), 140-141. https://doi.org/10.1038/nn0207-140.
Preuschoff, K., & Bossaerts, P. (2007). Adding Prediction Risk to the Theory of Reward Learning. Annals of the New York Academy of Sciences, 1104 (1), 135-146. https://doi.org/10.1196/annals.1390.005.
Preuschoff, K., Bossaerts, P., & Quartz, S. R. (2006). Neural Differentiation of Expected Reward and Risk in Human Subcortical Structures. Neuron, 51 (3), 381-390. https://doi.org/10.1016/j.neuron.2006.06.024.
Présentation à une conférence académique
Preuschoff, K. (2018). Uncertainty and surprise in decision making and learning. The Brain Conferences : Computational Neuroscience of Prediction.
Preuschoff, K. (2017). Decision Neuroscience Meets Finance. 4th Neurofinance meeting.
Preuschoff, K. (2017). Humans utilize an eligibility trace when learning sequential decisions from reward. Reinforcement Learning and Decision Making.
Preuschoff, K. (2017). The eligibility trace in human learning. BMI Symposium @ EPFL.
Preuschoff, K. (2015). A Biological Plausible 3-factor Learning Rule for Expectation Maximization in Reinforcement Learning and Decision Making. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM).
Preuschoff, K. (2015). Computational approaches to choice under uncertainty. Symposium on Biology of Decision Making.
Chapitre
Lebreton, M., & Preuschoff, K. (2019). Neuroeconomics: data analysis. Handbook of Research Methods and Applications in Experimental Economics. Edward Elgar.
Matériel décrivant un nouveau cours ou curriculum
Girardin, M., Berrada, T. N., Chaieb, I., Gibson Brandon, R. N., Hoesli, M. E. R., Krueger, P., ... & Valta, P. (2016). Make Smart Investment Decisions in a Global World. Coursera, Geneva, Suisse.
Autre
Preuschoff, K. (2022). Value representations: Fast and slow. Neuron.
Lehmann, M., Xu, H., Liakoni, V., Preuschoff, K., Gerstner, W., & Herzog, M. (2017). Evidence for eligibility traces in human learning., Suisse.
