Mood state and conflict adaptation: an update and a diffusion model analysis
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Updated: Jan 5, 2026

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
Published on: April 9, 2019
Stefanie Schuch1, Sebastian Pütz2
1Institute of Psychology, RWTH Aachen University, Jägerstr. 17-19, 52066, Aachen, Germany. schuch@psych.rwth-aachen.de.
Abstract:
The present study investigated the affective modulation of conflict adaptation. In a first step, we conducted a direct replication of a previous study (Schuch & Pütz, 2018). Positive vs. negative mood state was induced by a success-failure manipulation (between-groups, N = 40 per group). In a subsequent task-switching experiment, the congruency sequence effect was assessed in task repetitions and task switches, measuring conflict adaptation within tasks and between tasks, respectively. We found conflict adaptation (averaged across task repetitions and task switches) to be enhanced in negative mood. We did not replicate our previous finding of enhanced conflict adaptation in task switches in positive mood. In a second step, we combined the replication data with the original data set, yielding a larger database with N = 80 per mood group. Using diffusion modeling, we explored the affective modulation of conflict adaptation in task repetitions. Conflict adaptation was reflected in drift rate, consistent with the idea that response conflict triggers an increase in processing selectivity, thereby attenuating the influence of the irrelevant stimulus dimension. Conflict adaptation was also reflected in boundary separation, suggesting that response conflict on the previous trial triggered an increase in response caution. The mood manipulation did not seem to affect processing selectivity (as captured by drift rate) but affected the setting of response caution (as captured by the boundary separation parameter), with faster and more error-prone responding in the negative than positive mood group. We discuss theoretical implications of these findings, and also briefly consider the affective modulations of other cognitive control measures.
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