Li Grace NgaYin, Hoffman-Kim Diane
Department of Molecular Pharmacology, Physiology, and Biotechnology and Center for Biomedical Engineering, Brown University, Providence, RI 02912, USA.
J Neurosci Methods. 2008 Sep 30;174(2):202-14. doi: 10.1016/j.jneumeth.2008.07.001. Epub 2008 Jul 11.
Precise axon growth is required for making proper connections in development and after injury. One method of studying axon guidance and growth is through in vitro outgrowth assays that present controlled microenvironments. In this study, we applied circular statistical methods to evaluate directional neurite response. Visualization of data on a circular scale allows more accurate representation of the data, as neurite angles are inherently expressed on a circle. Here, the direction of neurite outgrowth from dorsal root ganglia derived neurons on different substrate types was quantitatively measured. Further, simulations of datasets with known circular parameters reflecting expected neurite angle distributions from different substrate types were also generated. Circular statistical methods were utilized and compared to linear statistical models widely used in the neuroscience literature. For small samples, Rao's spacing test showed the smallest occurrence of Type I errors (false positives) when tested against simulated uniform distributions. V-test and Rayleigh's test showed highest statistical power when tested against a unimodal distribution with known and unknown mean direction, respectively. For bimodal samples, Watson's U(2)-test showed the highest statistical power. Overall, circular statistical uniformity tests showed higher statistical power than linear non-parametric tests, particularly for small samples (n=5). Circular analysis methods represent a useful tool for evaluation of directionality of neurite outgrowth with applications including: (1) assessment of neurite outgrowth potential; (2) determination of isotropy of cellular responses to single and multiple cues and (3) determination of the relative strengths of cues present in a complex environment.
在发育过程和损伤后建立正确的连接需要精确的轴突生长。研究轴突导向和生长的一种方法是通过体外生长试验，该试验提供可控的微环境。在本研究中，我们应用圆形统计方法来评估神经突的定向反应。在圆形尺度上对数据进行可视化处理能够更准确地呈现数据，因为神经突角度本质上是在圆周上表达的。在这里，我们定量测量了背根神经节衍生神经元在不同底物类型上的神经突生长方向。此外，还生成了具有已知圆形参数的数据集模拟，这些参数反映了不同底物类型预期的神经突角度分布。我们使用了圆形统计方法，并与神经科学文献中广泛使用的线性统计模型进行了比较。对于小样本，当与模拟均匀分布进行测试时，Rao间距检验显示出最小的I型错误（假阳性）发生率。当分别与已知和未知平均方向的单峰分布进行测试时，V检验和瑞利检验显示出最高的统计功效。对于双峰样本，Watson的U(2)检验显示出最高的统计功效。总体而言，圆形统计均匀性检验比线性非参数检验具有更高的统计功效，特别是对于小样本（n = 5）。圆形分析方法是评估神经突生长方向性的有用工具，其应用包括：（1）评估神经突生长潜力；（2）确定细胞对单一和多个线索反应的各向同性；（3）确定复杂环境中存在的线索的相对强度。
