Hippocampal-Prefrontal Interactions during Spatial Decision-Making

The hippocampus has been linked to memory encoding and spatial navigation, while the prefrontal cortex is associated with cognitive functions such as decision-making. These regions are hypothesized to communicate in tasks that demand both spatial navigation and decision-making processes. However, the electrophysiological signatures underlying this communication remain to be better elucidated. To investigate the dynamics of the hippocampal-prefrontal interactions, we have analyzed their local field potentials and spiking activity recorded from rats performing an odor-cued spatial alternation task in an 8-shaped maze. We found that the phase coherence of theta peaked around the choice point area of the maze. Moreover, Granger causality revealed a hippocampus->prefrontal cortex directionality of information flow at theta frequency, peaking at starting areas of the maze, and on the reverse direction at delta frequency, peaking near the turn onset. Additionally, the patterns of phase-amplitude cross-frequency coupling within and between the regions also showed spatial selectivity, and a new method revealed that hippocampal theta and prefrontal delta modulated not only gamma amplitude but also inter-regional gamma synchrony. Lastly, we found that the theta rhythm dynamically modulated neurons in both regions, with the highest modulation at the choice area; interestingly, prefrontal cortex neurons were more strongly modulated by the hippocampal theta rhythm than by their local field rhythm. In all, our results reveal maximum electrophysiological interactions between the hippocampus and the prefrontal cortex near the decision-making period of the spatial alternation task. These results corroborate the hypothesis that a dynamic interplay between these regions takes place during spatial decisions.

Spatial preferences account for inter-animal variability during the continual learning of a dynamic cognitive task

Individual animals perform tasks in different ways, yet the nature and origin of that variability is poorly understood. In the context of spatial memory tasks, variability is often interpreted as resulting from differences in memory ability, but the validity of this interpretation is seldom tested since we lack a systematic approach for identifying and understanding factors that make one animal’s behavior different than another. Here we identify such factors in the context of spatial alternation in rats, a task often described as relying solely on memory of past choices. We combine hypothesis-driven behavioral design and reinforcement learning modeling to identify spatial preferences that, when combined with memory, support learning of a spatial alternation task. Identifying these preferences allows us to capture differences among animals, including differences in overall learning ability. Our results show that to understand the complexity of behavior requires quantitative accounts of the preferences of each animal.