Novelty-seeking impairment in addiction

Information-seeking is an important aspect of human cognition. Despite its adaptive role, we have rather limited understanding on the mechanisms that subtend information-seeking in healthy individuals and in psychopathological populations. Here, we aim to formalize the computational basis of healthy human information behavior, as well as how those components may be compromised in behavioral addiction. We focus on gambling disorder, a form of addiction without the confound of substance consumption. We investigate and model human behavior using a novel decision-making task and a novel reinforcement learning model. Our results indicate that healthy information behavior is motivated by both novelty and general knowledge (or information). In contrast, problem gamblers have a specific deficit in novelty processing in choice behavior, but not in general information. This finding sheds light both on the computational mechanisms underlying healthy human information behavior, and on how they can go awry in behavioral addiction.