Expected Costs of Mental Efforts are Updated When People Exert Effort, not by Prospective Information

Abstract

To understand why people avoid mental effort, it is crucial to reveal the mechanisms by which we learn and decide about mental effort costs. This study investigated whether mental effort cost learning aligns with temporal-difference (TD) learning or alternative mechanisms. Model-based fMRI analyses showed no correlation between cost prediction errors (CPEs) and activity in the dorsomedial frontal cortex/dorsal anterior cingulate cortex (dmFC/dACC) or striatum at the time of a fully informative effort cue about upcoming effort demands, contradicting the TD hypothesis. Instead, CPEs correlate with dmFC/dACC (positively) and caudate (negatively) activity at effort completion. Furthermore, only activity patterns at effort completion predict subsequent choices. These results show that decision policies are updated retrospectively at effort completion, updating expected costs with prediction error between experienced effort and prior expectations, demonstrating mental effort cost learning is retrospective, and imply that adaptive learning of mental effort cost does not follow canonical TD learning. Significance StatementUnderstanding how people learn about mental effort costs is essential for advancing theories of motivation and cognitive control. However, the algorithms supporting such learning remain unclear. This study addressed this gap and found that temporal-difference learning, commonly used to explain reward learning, could not account for how people learn about effort. Instead, decision policies were updated retrospectively at effort completion, based on a prediction error between experienced effort and prior expectations. These findings reveal that mental effort cost learning is fundamentally retrospective and imply that it relies on mechanisms distinct from canonical temporal-difference learning.