Publications by Kerstin Preuschoff

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 SCIENCE2022

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Leyla Loued-Khenissi, Kerstin Preuschoff

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 ...

2020

Risk 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 ...

2020

Anterior insula reflects surprise in value-based decision-making and perception

Leyla Loued-Khenissi, Kerstin Preuschoff

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- ...

2020

One-shot learning and behavioral eligibility traces in sequential decision making

Michael Herzog, Wulfram Gerstner, Marco Philipp Lehmann, Kerstin Preuschoff, 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 ...

2019

An 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 INC2019

Balancing New against Old Information: The Role of Puzzlement Surprise in Learning

Wulfram Gerstner, Kerstin Preuschoff, Mohammadjavad Faraji

2018

Apathy and noradrenaline: silent partners to mild cognitive impairment in Parkinson's disease?

Leyla Loued-Khenissi, Kerstin Preuschoff

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 & Wilkins2015

A biologically plausible 3-factor learning rule for expectation maximization in reinforcement learning and decision making

Wulfram Gerstner, Kerstin Preuschoff, Mohammadjavad Faraji

2015

Investigating signal integration with canonical correlation analysis of fMRI brain activation data

Kerstin Preuschoff

How the brain integrates signals from specific areas has been a longstanding critical question for neurobiologists. Two recent observations suggest a new approach to fMRI data analysis of this question. First, in many instances, the brain analyzes inputs b ...

2008