Robinson Brian S, Yu Gene J, Hendrickson Phillip J, Song Dong, Berger Theodore W
Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1366-9. doi: 10.1109/EMBC.2012.6346192.
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.
一个大规模的海马体计算模型应该考虑不同时间尺度下的可塑性,以便更准确地捕捉海马体的非平稳信息处理行为。本文提出了一个计算模型,该模型描述了在NEURON模拟环境中实现的海马体长时程增强/抑制(LTP/LTD)和短期可塑性。LTP/LTD组件基于尖峰时间依赖性可塑性(STDP)。短期可塑性组件将先前在群体突触水平定义的确定性模型修改为可以在单个突触水平实现的概率模型。这些可塑性机制经过验证,并被纳入到内嗅皮层向齿状回投射的大规模模型中。还评估了添加可塑性后的计算成本,结果表明模拟时间增加不到两倍。该模型可以很容易地纳入未来的大规模海马体模拟中,以研究LTP/LTD和短期可塑性与其他生物学因素相结合对系统功能的影响。