TDRL models in dopamine research
Temporal difference reinforcement learning (TDRL)-based models have been remarkably successful in explaining the activity of midbrain dopamine neurons.
Work evaluating the assumptions of these models is increasingly critical to advancing the field.
Because of the diversity of TDRL models, work evaluating their assumptions should identify the particular defining aspects of the TDRL framework being tested, ideally aspects that hold across different models.
Furthermore, a deep evaluation of model performance requires exploration of state spaces and model architectures that fairly reflect the known complexity of the behavioral representations and neural systems involved.
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(25)00033-6
