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Defining novel indicators of implicit reward-related learning in EEG data

Change of an EEG signal (P1 amplitude) over the course of a learning experiment. Depending on their performance, participants received monetary gain (upper panel) or loss (lower panel) or zero-outcome (both panels).
Image: Annekathrin Schacht

Which stimuli from our environment we can process massively depends on their relevance, defined by a number of different factors. These factors include not only physical stimulus features (e.g. brightness, contrast, loudness) but also their relevance in a given context. Here, motivational and emotional relevance play a crucial role and determine whether and how we perceive and process stimuli. To allow adaptive behavior, relevance of stimuli can dynamically change through e.g., associative learning mechanisms. In this project, we aimed at identifying neural markers of these changes in high-resolution EEG measures. Based on novel analyses approaches, we could show that increased motivational relevance declines over time, presumably due to attention shifts and predictive coding.

Project leaders

Prof. Dr. Anne Schacht

Prof. Dr. Anne Schacht +49 551 39-20625 +49 551 39-13570 Contact Profile

Fred Wolf +49 551 5176 - 423 Contact Profile