Evaluation of neurite outgrowth anisotropy using a novel application of circular analysis

Abstract

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.