Background and Objectives: Mnemonic discrimination (MD) may be dependent on oscillatory perforant path input frequencies to the hippocampus in a “U” shaped fashion, where some studies show that slow and fast input frequencies support MD, while other studies show that intermediate frequencies disrupt MD. We hypothesise that pattern separation (PS) underlies frequency-dependent MD performance. We aim to study, in a computational model of the hippocampal dentate gyrus (DG), the network and cellular mechanisms governing this putative “U” shaped PS relationship. Methods: We implemented a biophysical model of the DG that produces the hypothesised “U”-shaped input frequency-PS relationship, and its associated oscillatory electrophysiological signatures. We subsequently evaluated the network’s PS ability using an adapted spatiotemporal task. We undertook systematic lesion studies to identify the network-level mechanisms driving the “U” shaped input frequency-PS relationship. A minimal circuit of a single granule cell (GC) stimulated with oscillatory inputs was also used to study potential cellular-level mechanisms. Results: Lesioning synapses onto GCs did not impact the “U”-shaped input frequency-PS relationship. Furthermore, GC inhibition limits PS performance for fast frequency inputs, while enhancing PS for slow frequency inputs. GC interspike interval was found to be input frequency dependent in a “U”-shaped fashion, paralleling frequency-dependent PS observed at the network level. Additionally, GCs showed an attenuated firing response for fast frequency inputs. Conclusions: Independent of network-level inhibition, GCs may intrinsically be capable of producing a “U” shaped input frequency-PS relationship. GCs may preferentially decorrelate slow and fast inputs via spike timing reorganisation and high frequency filtering.
Model Type: Realistic Network
Region(s) or Organism(s): Dentate gyrus
Simulation Environment: NEURON