Person
Kerstin Preuschoff
This person is no longer with EPFL
Related publications (13)
Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making
Wulfram Gerstner, Johanni Michael Brea, Alireza Modirshanechi, Kerstin Preuschoff, Marco Philipp Lehmann, Vasiliki Liakoni
Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) e ...
ACADEMIC PRESS INC ELSEVIER SCIENCE2022Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain
Kerstin Preuschoff, Leyla Loued-Khenissi
Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivat ...
2020Risk prediction error signaling: A two-component response?
Michael Herzog, Ophélie Gladys Favrod, Kerstin Preuschoff, Marc Michael Lauffs, Sophie Alberta Catherine Geoghan
Organisms use rewards to navigate and adapt to (uncertain) environments. Error-based learning about rewards issupported by the dopaminergic system, which is thought to signal reward prediction errors to make adjustmentsto past predictions. More recently, t ...
2020Anterior insula reflects surprise in value-based decision-making and perception
Kerstin Preuschoff, Leyla Loued-Khenissi
The brain has been theorized to employ inferential processes to overcome the problem of uncertainty. Inference is thought to underlie neural processes, including in disparate domains such as value-based decision-making and perception. Value-based decision- ...
2020One-shot learning and behavioral eligibility traces in sequential decision making
Michael Herzog, Wulfram Gerstner, Kerstin Preuschoff, Marco Philipp Lehmann, He Xu, Vasiliki Liakoni
In many daily tasks, we make multiple decisions before reaching a goal. In order to learn such sequences of decisions, a mechanism to link earlier actions to later reward is necessary. Reinforcement learning (RL) theory suggests two classes of algorithms s ...
2019An Overview of Functional Magnetic Resonance Imaging Techniques for Organizational Research
Kerstin Preuschoff, Leyla Loued-Khenissi
Functional magnetic resonance imaging is a galvanizing tool for behavioral scientists. It provides a means by which to see what the brain does while a person thinks, acts, or perceives, without invasive procedures. In this, fMRI affords us a relatively eas ...
SAGE PUBLICATIONS INC2019Evidence for eligibility traces in human learning
Michael Herzog, Wulfram Gerstner, Kerstin Preuschoff, Marco Philipp Lehmann, He Xu, Vasiliki Liakoni
Whether we prepare a coffee or navigate to a shop: in many tasks we make multiple decisions before reaching a goal. Learning such state-action sequences from sparse reward raises the problem of credit-assignment: which actions out of a long sequence should ...
arXiv2017Balancing New Against Old Information: The Role of Surprise
Wulfram Gerstner, Kerstin Preuschoff, Mohammadjavad Faraji
Surprise is a widely used concept describing a range of phenomena from unexpected events to behavioral responses. We propose a measure of surprise, to arrive at a new framework for surprise-driven learning. There are two components to this framework: (i) a ...
Public Library of Science2016Apathy and noradrenaline: silent partners to mild cognitive impairment in Parkinson's disease?
Kerstin Preuschoff, Leyla Loued-Khenissi
Purpose of review Mild cognitive impairment (MCI) is a comorbid factor in Parkinson's disease. The aim of this review is to examine the recent neuroimaging findings in the search for Parkinson's disease MCI (PD-MCI) biomarkers to gain insight on whether MC ...
Lippincott, Williams & Wilkins2015Explicit neural signals reflecting reward uncertainty
The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, ...
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