Abstract
Animals use prior experience to assign absolute (good or bad) and relative (better or worse) value to new experience. These learned values guide appropriate later decision making. Even though our understanding of how the valuation system computes absolute value is relatively advanced, the mechanistic underpinnings of relative valuation are unclear. Here, we uncover mechanisms of absolute and relative aversive valuation in Drosophila. Three types of punishment-sensitive dopaminergic neurons (DANs) respond differently to electric shock intensity. During learning, these punishment-sensitive DANs drive intensity-scaled plasticity at their respective mushroom body output neuron (MBON) connections to code absolute aversive value. In contrast, by comparing the absolute value of current and previous aversive experiences, the MBON-DAN network can code relative aversive value by using specific punishment-sensitive DANs and recruiting a specific subtype of reward-coding DANs. Behavioral and physiological experiments revealed that a specific subtype of reward-coding DAN assigns a "better than" value to the lesser of the two aversive experiences. This study therefore highlights how appetitive-aversive system interactions within the MB network can code and compare sequential aversive experiences to learn relative aversive value.