Topic: model-based learning

Since its initial conceptualization by Edward Tolman, cognitive maps – i.e., task-derived internal representations of an environment – have been found in multiple brain regions. In mammalian brains, the orbitofrontal cortex (OFC) can produce a flexible cognitive map underpinning model-based learning. Recent results have shown that this function is compatible with the canonical value-encoding role ascribed to OFC, whereby this region guides decision-making by providing a representation of reward. Hence, recent theories have suggested that the OFC integrates activity from other brain regions and

Generative models provide a powerful interpretive framework in neural reinforcement learning. However, given the complexity of behavior, models are often proposed in the absence of structurally different alternatives, poten-tially weakening their explanatory force. We employ a data-driven methodology (choice-wide behavioral associa-tion study; CBAS; Kastner et al. BioRxiv 2024), to examine such limitations. We use a dataset of human subjects performing a two-step task that was designed to test the interplay between model-based and model free learning (Gillan et al. eLife 2016). The subjects al