Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Realistic image synthesis using photon mapping
Realistic image synthesis using photon mapping
Multidimensional Binary Search Trees in Database Applications
IEEE Transactions on Software Engineering
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Understanding how the architecture of neuronal populations contributes to brain function requires three-dimensional representations and analyses. Neuroanatomical techniques are available to locate neurons in animal brains. Repeating an experiment in different individuals yields a collection of point patterns from which common organization principles are generally difficult to extract. We recently addressed the problem of generating statistical density maps to integrate replicated point pattern data into meaningful, interpretable representations. Applications to different neuroanatomical systems illustrated the ability of our method to reveal organization rules that cannot be perceived directly on raw data. To make the method practicable for further applications, the aim of the present paper is to establish general guidelines for appropriate parameter tuning, valid result interpretation as well as efficient implementation. Accordingly, we characterize the method by analyzing the role of its main parameter, by reporting results on its statistical properties and by demonstrating its robustness, using both simulated and real neuroanatomical data.