Neural models of the mammalian visual cortex have been used in digital image processing for many years. The neural models have demonstrated a robust talent for extracting image segments that are inherent in the image. This paper will explore the use of a simple neural model for the extraction of texture information. The neural firing patterns in the model are dependent upon the input texture and by examining the neural patterns it is possible to classify the texture in the input image. Two applications presented here are the comparison of performance to other texture analysis techniques using two standard databases and the classification of texture regions in a medical image.