Novel devaluation methods to explore habits in humans

Habits in humans are commonly studied through outcome devaluation paradigms, but most existing tasks fail to capture the robustness of habitual behavior seen in animal models. I introduce two novel behavioral tasks designed to overcome these limitations. In the first task, ("shooting aliens task", n = 45), I simplified an existing instrumental learning task and implemented a novel intra-block reversal method in which stimulus positions changed unexpectedly within blocks while maintaining the same stimulus-action mappings. Participants also completed a classical devaluation phase with explicit reward changes. In the second task ("hands-attack task", n = 44), which relied on real-life avoidance behavior, devaluation was achieved by reversing reward contingencies and allowing participants to inhibit the dominant avoidance response in favor of a more effortful counterattack. Across both tasks, overtrained conditions led to more errors and longer response times after devaluation, confirming increased insensitivity to outcome change. Intra-block reversals in the shooting aliens task produced stronger habitual signatures than standard whole-block devaluation, revealing a greater cost of overriding automatic responses. In the hands-attack task, even without prior training, participants showed clear markers of habitual behavior, suggesting that real-world action patterns can replicate key features of laboratory habits. Interestingly, participants were more accurate in overriding overtrained responses when attacks were highly familiar, possibly due to enhanced perceptual processing, although this came at the cost of longer response times. These findings introduce two complementary tools that address key limitations in current paradigms: the intra-block reversal increases habit sensitivity without inflating working memory demands, while the hands-attack task captures naturalistic habit expression without artificial training, using a single, ecologically valid session. Both are suited for clinical applications, particularly where time constraints or cognitive load limit the feasibility of traditional approaches.