The hippocampus and medial prefrontal cortex during flexible behavior

The solving of complex tasks requires the functions of more than one brain area and their interaction. Whilst spatial navigation and memory is dependent on the hippocampus, flexible behavior relies on the medial prefrontal cortex (mPFC). To further examine the roles of the hippocampus and mPFC, we recorded their neural activity during a task that depends on both of these brain regions. With tetrodes, we recorded the extracellular activity of dorsal hippocampal CA1 (HPC) and mPFC neurons in Long-Evans rats performing a rule-switching task on the plus-maze. The plus-maze task had a spatial component since it required navigation along one of the two start arms and at the maze center a choice between one of the two goal arms. Which goal contained a reward depended on the rule currently in place. After an uncued rule change the animal had to abandon the old strategy and switch to the new rule, testing cognitive flexibility. Investigating the coordination of activity between the HPC and mPFC allows determination during which task stages their interaction is required. Additionally, comparing neural activity patterns in these two brain regions allows delineation of the specialized functions of the HPC and mPFC in this task. We analyzed neural activity in the HPC and mPFC in terms of oscillatory interactions, rule coding and replay. We found that theta coherence between the HPC and mPFC is increased at the center and goals of the maze, both when the rule was stable or has changed. Similar results were found for locking of HPC and mPFC neurons to HPC theta oscillations. However, no differences in HPC-mPFC theta coordination were observed between the spatially- and cue-guided rule. Phase locking of HPC and mPFC neurons to HPC gamma oscillations was not modulated by maze position or rule type. We found that the HPC coded for the two different rules with cofiring relationships between cell pairs. However, we could not find conclusive evidence for rule coding in the mPFC. Spatially-selective firing in the mPFC generalized between the two start and two goal arms. With Bayesian positional decoding, we found that the mPFC reactivated non-local positions during awake immobility periods. Replay of these non-local positions could represent entire behavioral trajectories resembling trajectory replay of the HPC. Furthermore, mPFC trajectory-replay at the goal positively correlated with rule-switching performance. Finally, HPC and mPFC trajectory replay occurred independently of each other. These results show that the mPFC can replay ordered patterns of activity during awake immobility, possibly underlying its role in flexible behavior.