Case by case visualization of the results.

Positional data in the form of x-y coordinates for the neurons in the pictures are analyzed by calculating the average "neighborhood" for a typical neuron. The average neighborhood comes form the calculation of the neighborhood of individual neurons.

Results for the neighborhood map are calculated by first sitting on each neuron and developing a neuron count as a function of x-y coordinates. Once this grid is calculated for each neuron, a total grid comes from the average of all the individual grids from a single slice. The result thus is an average of what a typical neuron on that particular slice would observe on its surroundings.

A Java application as well as a downloadable program that calculates the neuronal density is available here.

In the following presentation we have chosen to visualize the results in a 3 dimensional surface because light-shadow effects permit us to appreciate the valleys and mountains of the surface landscape. Mountains represent high neuronal density, while valleys represent a low neuronal density. The colors also correlate with the neuronal density being green the lowest and red the highest.

Results for M458, a control case; and for M474, an alzheimer case, are presented. Also, the comparison of the averages over slices for both cases.