[R] A recurrent network model of planning explains hippocampal replay and human behavior

**Paper**: [https://www.biorxiv.org/content/10.1101/2023.01.16.523429v2](https://www.biorxiv.org/content/10.1101/2023.01.16.523429v2)

**Code**: [https://github.com/KrisJensen/planning\_code](https://github.com/KrisJensen/planning_code)

**Abstract**:

>When faced with a novel situation, humans often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here we capture these features of human behavior by developing a neural network model where planning itself is controlled by prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences from …

abstract behavior benefits cortex features futures human humans machinelearning network neural network novel planning spend thinking