Theta-band oscillations (3-8 Hz) in the mammalian hippocampus organize the temporal structure of cortical inputs, resulting in a phase code that enables rhythmic input sampling for episodic memory formation and spatial navigation. However, it remains unclear what evolutionary pressures might have driven the selection of theta over higher-frequency bands that could potentially provide increased input sampling resolution. Here, we address this question by introducing a theoretical framework that combines the efficient coding and neural oscillatory sampling hypotheses, focusing on the information rate (bits/s) of phase coding neurons. We demonstrate that physiologically realistic noise levels create a trade-off between the speed of input sampling, determined by oscillation frequency, and encoding precision in rodent hippocampal neurons. This speed-precision trade-off results in a maximum information rate of ∼1-2 bits/s within the theta frequency band, thus confining the optimal oscillation frequency to the low end of the spectrum. We also show that this framework accounts for key hippocampal features, such as the preservation of the theta band along the dorsoventral axis despite physiological gradients, and the modulation of theta frequency and amplitude by running speed. Extending the analysis beyond the hippocampus, we propose that theta oscillations could also support efficient stimulus encoding in the visual cortex and olfactory bulb. More broadly, our framework lays the foundation for studying how system features, such as noise, constrain the optimal sampling frequencies in both biological and artificial brains.

The primate posterior parietal cortex (PPC) withholds a unified representation of the visual space supporting visual exploration, while the hippocampus (HPC) provides a memory-based cognitive place map of the environment. To probe the interactions between these two representations, i.e. between view and place, we compared neural activity in the two regions of macaques navigating a virtual maze. We show that a large proportion of PPC neurons displayed spatial selectivity, along with the HPC. We hypothesized that such modulation by self-position might stem from visual cues processing through saccades and fixations. Accordingly, we found saccade-modulated neurons and cells driven by direct fixations on maze paths or landmarks in both brain regions. These populations of "path" and "landmark cells" gave rise to task-relevant maze segmentation, specific to each region. Finally, both regions anticipated landmarks before they appeared in the field of view, suggesting a shared knowledge of the spatial layout. Altogether, these findings highlight the neural processes that make up place, combining visual exploration of objects in space with memory-driven actions.