Whenever neuroscientists want to study the neural substrate of cognition, they first need to train animals to perform cognitive psychology tasks. Unfortunately, even tasks that a person could grasp after a 30 second verbal explanation, might take non-human animals several months to train. The goal of this project is to use deep reinforcement learning to model animal learning in a subset of memory tasks, and then conduct simulation experiments that might inform how to improve training time.
- use deep reinforcement learning to model rodent learning on working memory tasks
- use model to experiment with ways to improve training time.
- investigating basic implementation assumptions
- stimulus coding
- reward structure
- task implementation
- working on curriculum experiments
- pretrain on shorter delay
- pretrain on less noisy stimuli