Abstract

The aim of this paper is to apply a non-parametric statistical tool, Ripley’s K-function, to analyze the 3-dimensional distribution of pyramidal neurons. Ripley’s K-function is a widely used tool in spatial point pattern analysis. There are several approaches in 2D domains in which this function is executed and analyzed. Drawing consistent inferences on the underlying 3D point pattern distributions in various applications is of great importance as the acquisition of 3D biological data now poses lesser of a challenge due to technological progress. As of now, most of the applications of Ripley’s K-function in 3D domains do not focus on the phenomenon of edge correction, which is discussed thoroughly in this paper. The main goal is to extend the theoretical and practical utilization of Ripley’s K-function and corresponding tests based on bootstrap resampling from 2D to 3D domains

Keywords

Ripley’s K-function; edge correction in 3D; bootstrap resampling

Published in

Frontiers in Neuroinformatics
2010, Volume: 4, number: 9, article number: 9

UKÄ Subject classification

Neurosciences


Publication identifier

DOI: https://doi.org/10.3389/fninf.2010.00009

Permanent link to this page (URI)

https://res.slu.se/id/publ/31170