Toward building a decision-making paradigm for dynamic and real-world addictive behaviors

The decision-making framework and computational models have been instrumental in revealing the neurocognitive processes that underlie human behaviors, significantly enhancing our understanding of the human mind. However, traditional approaches often fall short in closely mimicking real-world behaviors due to their oversimplified nature, inability to capture the dynamic aspects of the human mind, and heavy reliance on secondary (e.g., monetary) rewards that have limited ecological utility. This article summarizes the evolution and recent developments of computational approaches in understanding human cognition and decision-making, with a particular focus on addiction. We highlight the transition from conventional laboratory-based methods to innovative approaches that more effectively simulate real-world scenarios. These advanced approaches leverage state-of-the-art computational techniques to capture dynamic psychological processes, contributing to the ongoing development and advances in the field.