The Neural Correlates of Individual Differences in Reinforcement Learning during Pain Avoidance and Reward Seeking

Organisms learn to gain reward and avoid punishment through action-outcome associations. Reinforcement learning (RL) offers a critical framework to understand individual differences in this associative learning by assessing learning rate, action bias, pavlovian factor (i.e., the extent to which action values are influenced by stimulus values), and subjective impact of outcomes (i.e., motivation to seek reward and avoid punishment). Nevertheless, how these individual-level metrics are represented in the brain remains unclear. The current study leveraged fMRI in healthy humans and a probabilistic learning go/no-go task to characterize the neural correlates involved in learning to seek reward and avoid pain. Behaviorally, participants showed a higher learning rate during pain avoidance relative to reward seeking. Additionally, the subjective impact of outcomes was greater for reward trials and associated with lower response randomness. Our imaging findings showed that individual differences in learning rate and performance accuracy during avoidance learning were positively associated with activities of the dorsal anterior cingulate cortex, midcingulate cortex, and postcentral gyrus. In contrast, the pavlovian factor was represented in the precentral gyrus and superior frontal gyrus (SFG) during pain avoidance and reward seeking, respectively. Individual variation of the subjective impact of outcomes was positively predicted by activation of the left posterior cingulate cortex. Finally, action bias was represented by the supplementary motor area (SMA) and pre-SMA whereas the SFG played a role in restraining this action tendency. Together, these findings highlight for the first time the neural substrates of individual differences in the computational processes during RL.