AUTHOR=Jafari Mamaghani Mehrdad , Andersson Mikael , Krieger Patrik 

TITLE=Spatial point pattern analysis of neurons using Ripley's K-function in 3D

JOURNAL=Frontiers in Neuroinformatics

VOLUME=Volume 4 - 2010

YEAR=2010

URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2010.00009

DOI=10.3389/fninf.2010.00009

ISSN=1662-5196

ABSTRACT=The aim of this paper is to apply a non-parametric statistical tool, Ripley’s Kfunction, 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 poses lesser of 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.