Abstract
Pattern separation is a process that minimizes overlap between patterns of neuronal activity representing similar experiences. Theoretical work suggests that the dentate gyrus (DG) performs this role for memory processing but a direct demonstration is lacking. One limitation is the difficulty to measure DG inputs and outputs simultaneously. To rigorously assess pattern separation by DG circuitry, we used mouse brain slices to stimulate DG afferents and simultaneously record granule cells (GCs). Output spiketrains of GCs are more dissimilar than their input spiketrains, demonstrating for the first time temporal pattern separation at the level of single neurons in DG. This phenomenon occurs on millisecond to second timescales through different neural codes and is not explained by simple noise. Pattern separation is cell-type specific and larger in GCs than in fast-spiking interneurons. Finally, different GCs process spiketrains differently, a mechanism that likely helps to separate patterns at the population level.
Footnotes
Funding This work was supported by the University of Wisconsin Institute for Clinical and Translational Research (M.V.J.; NIH/NCATS UL1TR000427) and Lily’s Fund for Epilepsy Research (A.D.M.; 2015 fellow).
Abbreviations
- GC
- granule cell
- FS
- fast-spiking interneuron
- PP
- perforant-path
- R
- Pearson’s correlation coefficient
- NDP
- normalized dot product
- SF
- scaling factor
- SR
- spiking reliability
- Rw
- spiketrain reliability