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首页> 外文期刊>Biological Cybernetics >Comparison of different neuron models to conductance-based post-stimulus time histograms obtained in cortical pyramidal cells using dynamic-clamp in vitro
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Comparison of different neuron models to conductance-based post-stimulus time histograms obtained in cortical pyramidal cells using dynamic-clamp in vitro

机译：动态神经钳体外皮层锥体细胞中获得的不同电导模型与基于电导的刺激后时间直方图的比较

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摘要

A wide diversity of models have been proposed to account for the spiking response of central neurons, from the integrate-and-fire (IF) model and its quadratic and exponential variants, to multiple-variable models such as the Izhikevich (IZ) model and the well-known Hodgkin–Huxley (HH) type models. Such models can capture different aspects of the spiking response of neurons, but there is few objective comparison of their performance. In this article, we provide such a comparison in the context of well-defined stimulation protocols, including, for each cell, DC stimulation, and a series of excitatory conductance injections, arising in the presence of synaptic background activity. We use the dynamic-clamp technique to characterize the response of regular-spiking neurons from guinea-pig visual cortex by computing families of post-stimulus time histograms (PSTH), for different stimulus intensities, and for two different background activities (low- and high-conductance states). The data obtained are then used to fit different classes of models such as the IF, IZ, or HH types, which are constrained by the whole data set. This analysis shows that HH models are generally more accurate to fit the series of experimental PSTH, but their performance is almost equaled by much simpler models, such as the exponential or pulse-based IF models. Similar conclusions were also reached by performing partial fitting of the data, and examining the ability of different models to predict responses that were not used for the fitting. Although such results must be qualified by using more sophisticated stimulation protocols, they suggest that nonlinear IF models can capture surprisingly well the response of cortical regular-spiking neurons and appear as useful candidates for network simulations with conductance-based synaptic interactions.
机译：提出了各种各样的模型来说明中枢神经元的尖峰响应，从积分并发射（IF）模型及其二次和指数变体，到多变量模型，例如Izhikevich（IZ）模型和著名的霍奇金-赫克斯利（HH）型模型。这样的模型可以捕获神经元突波反应的不同方面，但是几乎没有客观比较它们的性能。在本文中，我们在定义明确的刺激方案的背景下提供了这样的比较，包括针对每个细胞的DC刺激以及在存在突触背景活性的情况下产生的一系列兴奋性电导注射。我们使用动态钳夹技术通过计算刺激后时间直方图（PSTH）族，不同刺激强度以及两种不同背景活动（低刺激和低刺激）来表征豚鼠视觉皮层的规则加长神经元的反应高电导状态）。然后，将获得的数据用于拟合不同类别的模型，例如IF，IZ或HH类型，这些模型受整个数据集的约束。该分析表明，HH模型通常更适合于一系列实验PSTH，但其性能几乎与简单得多的模型（例如指数或基于脉冲的IF模型）相当。通过对数据进行部分拟合，并检查不同模型预测未用于拟合的响应的能力，也得出了类似的结论。尽管必须通过使用更复杂的刺激方案来验证此类结果，但它们表明，非线性IF模型可以令人惊讶地很好地捕获皮质有规律的尖峰神经元的响应，并且可以用作基于电导的突触相互作用的网络模拟的有用候选对象。

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