Similar functional networks predict performance in both perceptual and value-based decision tasks

Abstract

There are numerous commonalities between perceptual and preferential decision processes. For instance, previous studies have shown that both of these decision types are influenced by context. Also, the same computational models can explain both. However, the neural processes and functional connections that underlie these similarities between perceptual and value-based decisions are still unclear. Hence, in the current study, we examine whether perceptual and preferential processes can be explained by similar functional networks utilizing data from the Human Connectome Project. We used resting-state functional magnetic resonance imaging data to predict performance of 2 different decision-making tasks: a value-related task (the delay discounting task) and a perceptual task (the flanker task). We then examined the existence of shared predictive-network features across these 2 decision tasks. Interestingly, we found a significant positive correlation between the functional networks, which predicted the value-based and perceptual tasks. In addition, a larger functional connectivity between visual and frontal decision brain areas was a critical feature in the prediction of both tasks. These results demonstrate that functional connections between perceptual and value-related areas in the brain are inherently related to decision-making processes across domains.

Keywords: functional connectivity; machine learning; perceptual decision-making; preferential decision-making; resting-state fMRI.