Implementation of activity-dependent synaptic plasticity rules for a large-scale biologically realistic model of the hippocampus.
A large-scale computational model of the hippocampus should consider plasticity at different time scales in order to capture the non-stationary information processing behavior of the hippocampus more accurately. This paper presents a computational model that describes hippocampal long-term potentiation/depression (LTP/LTD) and short-term plasticity implemented in the NEURON simulation environment. The LTP/LTD component is based on spike-timing-dependent plasticity (STDP). The short-term plasticity component modifies a previously defined deterministic model at a population synapse level to a probabilistic model that can be implemented at a single synapse level. The plasticity mechanisms are validated and incorporated into a large-scale model of the entorhinal cortex projection to the dentate gyrus. Computational expense of the added plasticity was also evaluated and shown to increase simulation time by less than a factor of two. This model can be easily included in future large-scale hippocampal simulations to investigate the effects of LTP/LTD and short-term plasticity in conjunction with other biological considerations on system function.
Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA. bsrobins@usc.edu
Brian S
BS
Robinson
Gene J
GJ
Yu
Phillip J
PJ
Hendrickson
Dong
D
Song
Theodore W
TW
Berger
D000200:Action Potentials / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D018728:Entorhinal Cortex / Q000502:physiology; D006624:Hippocampus / Q000502:physiology*; D008959:Models, Neurological; D009473:Neuronal Plasticity / Q000502:physiology*; D051381:Rats; D015203:Reproducibility of Results; D013569:Synapses / Q000502:physiology