Two distinct neural networks functionally connected to the human hippocampus during pattern separation tasks

Abstract

Previous studies from the human, rodent, and computational research have identified the hippocampus as a core structure mediating pattern separation. However, these investigations have generally focused on the role of distinct subregions of the hippocampus. Less well-understood is how the human hippocampus interacts with other brain regions to support pattern separation. The purpose of this study was to identify the functional networks connected to the hippocampus during delayed matching-to-sample pattern separation tasks promoting either spatial or temporal interference. Results revealed that the hippocampus was functionally connected to two distinct networks. The first network was characterized by correlated activation with the hippocampus primarily in bilateral temporal regions. This network was differentially related to spatial and temporal conditions, suggesting hippocampal connectivity to this network is modulated by interference type. A secondary network was characterized by correlations between the left hippocampus and several other sparsely distributed brain regions, including bilateral cerebellum and frontal and temporal cortices. This network was not modulated by interference type, suggesting that it may be a domain-general pattern separation network. We suggest that the hippocampus may play a role in integrating information from these networks to support performance on pattern separation tasks.