Salience network resting-state functional connectivity predicts self-controlled decision-making
Jasmin Stein1, Franziska M Korb2, Thomas Goschke2
1Faculty of Psychology, TU Dresden, Dresden, D-01069, Germany. jasmin.stein@tu-dresden.de.
Abstract:
Salience network functional integration with the central executive network and the default mode network at rest has been shown to predict real-life self-control. It has been proposed that a network interaction index reflecting stronger functional integration of the salience network with the central executive network and reduced functional connectivity of the salience network with the default mode network represents a trait neural correlate of successful self-control exertion. Here, we attempted to replicate this result using data from our own study where 121 participants completed an fMRI self-control task comprising real-life scenarios and data from a second study (N = 79) retrieved from OpenNeuro (dataset ID: ds002643) where participants completed an fMRI food choice task. We could not replicate the proposed role of salience network resting-state functional connectivity in self-controlled decision-making in either of those data sets. Instead, we found evidence for the exact opposite effect, specifically a negative association between self-control performance and the network interaction index. The role of analysis pipelines, appropriate network ROIs, and the measurement of self-control are discussed in the context of our findings.
More Related Videos
Related Concept Videos
Decision Making
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Reason and Intuition
High-Level and Low-Level Awareness


