A classification method to distinguish cell-specific responses elicited by current pulses in hippocampal CA1 pyramidal cells.
A classification method to distinguish cell-specific responses elicited by current pulses in hippocampal CA1 pyramidal cells.
复制标题
一种区分海马 CA1 锥体细胞中电流脉冲引起的细胞特异性反应的分类方法。
DOI：
10.1162/neco.2007.07-07-564
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发表时间：
2008
影响因子：
2.9
通讯作者：
Holmes,WilliamR
中科院分区：
文献类型：
--
作者：
Ambros-Ingerson,José;Grover,LawrenceM;Holmes,WilliamR
锥体细胞的阈上电生理反应分为爆发和尖峰等大类。然而，目前尚不清楚在一个类别中，所有细胞的反应变异性范围是否一致，或者每个细胞是否具有可以区分的独特和一致的特征。比较阈上反应时的一个主要困难是，在其他非常相似的轨迹中尖峰时间的轻微变化使传统指标无效。为了解决这些问题，我们开发了一种新的距离测量基准点的基础上量化的动作电位列车的痕迹之间的相似性，并将其与分类技术一起应用于一组体外膜片钳记录从CA1锥体细胞。我们测试了给定细胞对重复电流刺激的反应是否会聚集在一起，但仍与其他细胞的反应不同。我们发现，去极化和超极化电流脉冲在每个细胞中引起的反应，集群和系统地区别于其他细胞的反应。基准点距离的测量是更有效的比其他方法的基础上的尖峰时间和电压梯度相平面。去极化轨迹比超极化轨迹更可靠地区分，结合两种评分甚至更有效。这些结果表明，每个CA1锥体细胞具有独特的属性，可以检测和定量与这里讨论的方法。这种独特性可能是由于形态或膜通道密度和动力学的轻微变化，或这些元素的大的协调变化。在构建神经功能网络模型时，确定实际来源及其可变性程度非常重要，以确保关键机制在这些范围内的变化面前具有鲁棒性。这里提出的分析工具可以帮助构建详细的细胞模型，以匹配实验记录，阐明神经元电生理变异的来源。
The suprathreshold electrophysiological responses of pyramidal cells have been grouped into large classes such as bursting and spiking. However, it is not known whether, within a class, response variability ranges uniformly across all cells or whether each cell has a unique and consistent profile that can be differentiated. A major difficulty when comparing suprathreshold responses is that slight variations in spike timing in otherwise very similar traces render traditional metrics ineffective. To address these issues, we developed a novel distance measure based on fiducial points to quantify the similarity among traces with trains of action potentials and applied it together with classification techniques to a set of in vitro patch clamp recordings from CA1 pyramidal cells. We tested if responses to repeated current stimulation of a given cell would cluster together yet remain distinct from those of other cells. We found that depolarizing and hyperpolarizing current pulses elicited responses in each cell that clustered and were systematically distinguishable from responses in other cells. The fiducial-point distance measure was more effective than other methods based on spike times and voltage-gradient phase planes. Depolarizing traces were more reliably differentiated than hyperpolarizing traces, and combining both scores was even more effective. These results suggest that each CA1 pyramidal cell has unique properties that can be detected and quantified with methods discussed here. This uniqueness may be due to slight variations in morphology or membrane channel densities and kinetics, or to large, coordinated variations in these elements. Ascertaining the actual sources and their degree of variability is important when constructing network models of neural function to ensure that key mechanisms are robust in the face of variations within these ranges. The analytical tools presented here can assist in constructing detailed cell models to match experimental records to elucidate the sources of electrophysiological variability in neurons.