The complementary processes of pattern completion and pattern separation are thought to be essential for successful memory storage and recall. The dentate gyrus (DG) and proximal CA3 (pCA3) regions have been implicated in pattern separation, in part through extracellular recording studies of these areas. However, the DG contains two types of excitatory cells: granule cells of the granule layer and mossy cells of the hilus. Little is known about the firing properties of mossy cells in freely moving animals, and it is unclear how their activity may contribute to the mnemonic functions of the hippocampus. Furthermore, tetrodes in the dentate granule layer and pCA3 pyramidal layer can also record mossy cells, thus introducing ambiguity into the identification of cell types recorded. Using a random forests classifier, we classified cells recorded in DG (Neunuebel and Knierim, 2014) and pCA3 (Lee et al., 2015) of 16 male rats and separately examined the responses of granule cells, mossy cells, and pCA3 pyramidal cells in a local/global cue mismatch task. All three cell types displayed low correlations between the population representations of the rat's position in the standard and cue-mismatch sessions. These results suggest that all three excitatory cell types within the DG/pCA3 circuit may act as a single functional unit to support pattern separation. Mossy cells in the dentate gyrus (DG) are an integral component of the DG/pCA3 circuit. While the role of granule cells in the circuitry and computations of the hippocampus has been a focus of study for decades, the contributions of mossy cells have been largely overlooked. Recent studies have revealed the spatial firing properties of mossy cells in awake behaving animals, but how the activity of these highly active cells contributes to the mnemonic functions of the DG is uncertain. We separately analyzed mossy cells, granule cells, and pCA3 cells and found that all three cell types respond similarly to a local/global cue mismatch, suggesting that they form a single functional unit supporting pattern separation.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6880467PMC
http://dx.doi.org/10.1523/JNEUROSCI.0940-19.2019DOI Listing

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