@article{202751,
  author = {Carlos Vel{\'a}zquez-Vargas and Nathaniel Daw and Jordan Taylor},
  title = {The role of training variability for model-based and model-free learning of an arbitrary visuomotor mapping},
  abstract = {<p>A fundamental feature of the human brain is its capacity to learn novel motor skills. This<br>capacity requires the formation of vastly different visuomotor mappings. Using a grid navigation<br>task, we investigated whether training variability would enhance the flexible use of a<br>visuomotor mapping (key-to-direction rule), leading to better generalization performance.<br>Experiments 1 and 2 show that participants trained to move between multiple start-target<br>pairs exhibited greater generalization to both distal and proximal targets compared to participants<br>trained to move between a single pair. This finding suggests that limited variability can<br>impair decisions even in simple tasks without planning. In addition, during the training<br>phase, participants exposed to higher variability were more inclined to choose options that,<br>counterintuitively, moved the cursor away from the target while minimizing its actual distance<br>under the constrained mapping, suggesting a greater engagement in model-based<br>computations. In Experiments 3 and 4, we showed that the limited generalization performance<br>in participants trained with a single pair can be enhanced by a short period of variability<br>introduced early in learning or by incorporating stochasticity into the visuomotor mapping.<br>Our computational modeling analyses revealed that a hybrid model between model-free<br>and model-based computations with different mixing weights for the training and generalization<br>phases, best described participants{\textquoteright} data. Importantly, the differences in the modelbased<br>weights between our experimental groups, paralleled the behavioral findings during<br>training and generalization. Taken together, our results suggest that training variability<br>enables the flexible use of the visuomotor mapping, potentially by preventing the consolidation<br>of habits due to the continuous demand to change responses.</p>},
  year = {2024},
  journal = {PLoS Computational Biology},
  url = {https://doi.org/10.1371/journal.pcbi.1012471},
  doi = {10.1371/journal.pcbi.1012471},
}