The inverted multilayer perceptron as a consistency measuring device in neuroanatomical image analysis

This protocol describes the use of optical imaging and artificial neural networks to analyze the complex patterns of transsynaptic transfer of WGA-HRP from olfactory bulbar axon terminals to olfactory tubercle projection neurons. This constitutes a unique application of neural networks to pattern recognition in a neuroanatomical tract-tracing study. Furthermore, the type of neural network used in this study, i.e., the inverted multilayer perceptron, possesses a novel construction that suits it for measuring consistency in data clusters. In the experiment described, the perceptron functioned as a consistency measuring device that revealed nonlinear relationships between the site of bulbar injection and the degree of regional labeling in the olfactory tubercle. Nonparametric statistical tests were used concurrently to validate the results of this previously untested form of the multilayer perceptron.