Resting-State Functional Connectivity With the Anterior and Posterior Hippocampus: An Analysis of fMRI Data From the Human Connectome Project

Abstract

The anterior and posterior hippocampus exhibit distinct patterns of connectivity and are consequently hypothesized to have distinct functions. While there is evidence that the posterior hippocampus interacts with the default network and the anterior hippocampus interacts with the attention network during memory processes, there are conflicting hypotheses regarding connectivity between the hippocampus and other brain regions during rest. If hippocampal connectivity during rest parallels connectivity during memory, we would expect the anterior hippocampus and posterior hippocampus to have preferential connectivity with the attention network and the default network, respectively. Alternatively, given the association between the hippocampus and the default network, both regions of the hippocampus may have similar levels of connectivity with the default network. We used data from the Human Connectome Project (with 864 participants) to investigate resting-state functional connectivity with the anterior and posterior hippocampus and evaluated the degree of overlap between these patterns of connectivity and the attention network and default network. In direct opposition to the connectivity pattern during memory, resting-state data revealed preferential connectivity between the anterior hippocampus and the default network and between the posterior hippocampus and the attention network. These findings indicate that connectivity with the anterior and posterior hippocampus may differ between rest and active memory processing. One possible explanation for this discrepancy is that, during rest, the specific connectivity patterns supporting memory are less engaged. This does not imply an overall suppression of hippocampal connectivity but rather a relative reduction in engagement with the attention and default networks compared to task-based memory states. Such a shift may facilitate more dynamic network reconfiguration during memory encoding and retrieval.