A landscape parametric profile approach for rat brain image analysis.

Abstract

This paper develops the use of the landscape parametric profile as a descriptive and interpretative method of analyzing metabolic activity data obtained by neuroimaging techniques such as 2-deoxyglucose autoradiography. The method is suggested as an initial survey-type approach that can be used to map regional activity throughout the coronal planes of a rat brain and to compare relative differences in the patterns of activity between different brains. Images are acquired using preexisting image analysis software and then transformed to landscape parametric profiles derived from each matrix array. The image profile analysis tasks are done using commercially available software for matrix computations such as MATLAB. An effective way of interpreting activity differences between brains is presented by plotting the results from a randomized blocks ANOVA significance test combined with the average profiles of different subjects within the same experimental group. The method greatly reduces the computational burden associated with image averaging and statistical comparison of brains from different subjects while preserving the richness in topographic metabolic information. One significant advantage of the method is that it results in figures that are readily depicted and interpretable in black and white.