Abstract
“Pavlovian” or “motivational” biases are the phenomenon that the valence of prospective outcomes modulates action invigoration: the prospect of reward invigorates actions, while the prospect of punishment suppresses actions. Effects of the valence of prospective outcomes are well established, but it remains unclear how the magnitude of outcomes (“stake magnitude”) modulates these biases. In this pre-registered study (N = 55), we manipulated stake magnitude (high vs. low) in an orthogonalized Motivational Go/NoGo Task. We tested whether higher stakes (a) strengthen biases or (b) elicit cognitive control recruitment, enhancing the suppression of biases in motivationally incongruent conditions. Confirmatory tests showed that high stakes slowed down responding, especially in motivationally incongruent conditions. However, high stakes did not affect whether a response was made or not, and did not change the magnitude of Pavlovian biases. Reinforcement-learning drift- diffusion models (RL-DDMs) fit to the data suggested that response slowing was best captured by stakes prolonging the non-decision time. There was no effect of the stakes on the response threshold (as in typical speed-accuracy tradeoffs). In sum, these results suggest that high stakes slow down responses without affecting the expression of Pavlovian biases in behavior. We speculate that this slowing under high stakes might reflect heightened cognitive control, which is however ineffectively used, or reflect positive conditioned suppression, i.e., the interference between goal-directed and consummatory behaviors, a phenomenon previously observed in rodents that might also exist in humans. Pavlovian biases and slowing under high stakes may arise in parallel to each other.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
1.Major rewriting of the Introduction section, so that we now: a.explicitly define Pavlovian biases b.motivate why Pavlovian biases should become stronger under high stakes 2.Extension of the Results section, so that we now: a.motivate and explain reinforcement-learning drift-diffusion models (RL-DDMs) and their particular implementation for our task b.document more extensively the different models and model comparison steps 3.Major rewriting of the Discussion section, so that we now: a.explain how cognitive control (specifically response slowing) can occur in situa-tions where it is irrelevant for task performance and thus used inefficiently b.discuss whether stakes might lead both to bias amplification and heightened cog-nitive control recruitment, with both effects cancelling each other out c.explain the potential mechanisms underlying positive conditioned suppression d.discuss more explicitly how serotonin might play a role in positive conditioned suppression
