EXPLORING PARAMETER SPACE IN DETAILED SINGLE NEURON MODELS - SIMULATIONS OF THE MITRAL AND GRANULE CELLS OF THE OLFACTORY-BULB
EXPLORING PARAMETER SPACE IN DETAILED SINGLE NEURON MODELS - SIMULATIONS OF THE MITRAL AND GRANULE CELLS OF THE OLFACTORY-BULB
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DOI：
10.1152/jn.1993.69.6.1948
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发表时间：
1993-06-01
影响因子：
2.5
通讯作者：
BOWER, JM
中科院分区：
文献类型：
--
作者：
BHALLA, US;BOWER, JM
1.详细的房室计算机模拟单个二尖瓣和颗粒细胞的脊椎动物嗅球构建使用以前发表的几何数据。通过比较模型输出与先前发表的实验数据（主要是电流钳记录）来确定电生理特性.通过比较模型输出与超极化电流注入实验的细胞内电位数据，探索每个模型的被动电特性。结果表明，在这两个细胞的膜电阻率是不均匀的，与体细胞有一个显着较低的电阻率比树突。3.这些细胞的活性特性进行了探讨，将活性离子通道建模室。根据文献中的证据，二尖瓣细胞模型包括6种通道类型：快钠、快延迟整流（Kfast）、慢延迟整流（K）、瞬时外向钾电流（KA）、电压和钙依赖性钾电流（KCa）和L型钙电流。颗粒细胞模型包括四种类型的通道：大鼠脑钠，K，KA，和非失活毒蕈碱钾电流（KM）。模型通道基于Hodgkin-Huxley形式主义。4.从文献中获得上述每个通道类别的代表性动力学。实验未知的空间分布的每个通道，获得系统的参数搜索。这些进行了两种方式：大规模的模拟系列，其中每个参数依次变化，和适应多维共轭梯度法。在每种情况下，使用曲线匹配函数将模拟结果与实验数据进行比较，评估模拟和实验电压波形的几个方面的均方差.系统参数变化揭示了一个单一的参数空间的独特区域，其中二尖瓣细胞模型最适合的数据。参数空间的该区域对于参数变化也是非常鲁棒的。具体地说，当钙和慢钾通道集中在肾小球中，在索马和近端次级树突中密度较低时，获得最佳性能。钠和快钾通道的分布，另一方面，是最高的索马和轴突，与整个二级树突轻得多的分布。KA和KCa通道也集中在胞体附近.颗粒细胞模型的参数搜索不受实验数据的限制。几个参数制度，发现了一个很好的匹配的数据。在最简单的这些，钠和钾通道都存在于高密度在索马和周围树突，而KA和KM通道只存在于胞体。二尖瓣细胞模型的进一步操作表明，预测的通道分布可以在生理上得到验证。如果该模型所建议的通道分布是正确的，电压钳位的索马附近的尖峰阈值的电位应导致独立的局部树突动作电位的产生，反映不同树突的活性膜的有效去耦。该模型预测，肾小球簇，索马，和次级树突的每个二尖瓣细胞具有不同的局部电特性，主要是从局部分布的离子通道。它们在功能上也可能是不同的。我们对模型参数的广泛搜索表明，神经元在对参数值变化最鲁棒的参数空间区域中运行。特别是，通道密度的变化多达一个数量级可能对神经元模型的行为具有相对较小的影响。
1. Detailed compartmental computer simulations of single mitral and granule cells of the vertebrate olfactory bulb were constructed using previously published geometric data. Electrophysiological properties were determined by comparing model output to previously published experimental data, mainly current-clamp recordings.2. The passive electrical properties of each model were explored by comparing model output with intracellular potential data from hyperpolarizing current injection experiments. The results suggest that membrane resistivity in both cells is nonuniform, with somatas having a substantially lower resistivity than the dendrites. 3. The active properties of these cells were explored by incorporating active ion channels into modeled compartments. On the basis of evidence from the literature, the mitral cell model included six channel types: fast sodium, fast delayed rectifier (Kfast), slow delayed rectifier (K), transient outward potassium current (KA), voltage- and calcium-dependent potassium current (KCa), and L-type calcium current. The granule cell model included four channel types: rat brain sodium, K, KA, and the noninactivating muscarinic potassium current (KM). Modeled channels were based on the Hodgkin-Huxley formalism. 4. Representative kinetics for each of the channel classes above were obtained from the literature. The experimentally unknown spatial distributions of each included channel were obtained by systematic parameter searches. These were conducted in two ways: large-scale simulation series, in which each parameter was varied in turn, and an adaptation of a multidimensional conjugate gradient method. In each case, the simulated results were compared with experimental data using a curve-matching function evaluating mean squared differences of several aspects of the simulated and experimental voltage waveforms.5. Systematic parameter variations revealed a single distinct region of parameter space in which the mitral cell model best fit the data. This region of parameter space was also very robust to parameter variations. Specifically, optimum performance was obtained when calcium and slow K channels were concentrated in the glomeruli, with a lower density in the soma and proximal secondary dendrites. The distribution of sodium and fast potassium channels, on the other hand, was highest at the soma and axon, with a much lighter distribution throughout the secondary dendrites. The KA and KCa channels were also concentrated near the soma.6. The parameter search of the granule cell model was much less restrained by experimental data. Several parameter regimes were found that gave a good match to the data. In the simplest of these, sodium and K channels were present at high density both at the soma and in the peripheral dendrites, whereas the KA and KM channels were present only in the soma.7. Further manipulation of the mitral cell model suggests that the predicted channel distributions can be verified physiologically. If the channel distributions suggested by the model are correct, voltage clamping the soma to potentials near the spiking threshold should result in the generation of independent local dendritic action potentials reflecting the effective decoupling of the active membranes of the different dendrites. The model predicts that the glomerular tuft, the soma, and the secondary dendrites of each mitral cell have distinct local electrical properties resulting largely from the localized distribution of ion channels. They may also be functionally distinct.8. Our extensive search of model parameters suggests that neurons operate in regions of parameter space that are most robust to changes in parameter values. In particular, changes in channel densities by as much as an order of magnitude may have relatively little effect on the behavior of the neuronal model.