During the past two decades, numerous studies have suggested that nerve tissue exhibits fractal characteristics in its morphology. Fractal nature of biological systems is based on the concept of self-similarity, first introduced by Benoit Mandelbrot in 1975. The main parameter of fractal analysis, fractal dimension, is an indirect measure of complexity of the structure (i.e. tissue). Changes in fractal dimension in many tissues have been associated with numerous physiological and pathological processes, such as ageing, cell apoptosis etc. Another method for quantification of structural changes, commonly applied as an addition to fractal analysis, is Gray level co-occurrence matrix (GLCM) method. GLCM method is commonly used for quantifying features of tissue texture, such as textural entropy (level of chaos and disorder) which is, according to some authors, an indirect parameter of tissue structural degradation and deterioration. Relationship between fractal dimension and texture entropy in nervous tissue is unknown. In our study, 50 digital micrographs of brain cingulate cortex (figure 1), obtained from 10 healthy male Swiss albino mice (5 per animal), were made and converted to binary and 8-bit grey scale format. The tissue was previously stained using Feulgen method. Fractal and GLCM analysis of the micrographs were done in ImageJ software and its plugins (National Institutes of Health, Bethesda, MD). Average value of fractal dimension was 1.45±0.11, and average entropy was 5.72±0.34. There was a statistically significant (p<0.05) negative correlation between fractal dimension and entropy in brain cingulate cortex architecture. Fractal dimension increased and entropy decreased and vice versa. These results indicate that complexity of cingulum tissue is inversely correlated with the level of structural disorder. To our knowledge, this is the first study to test the existence and strength of such relationship. The results are in accordance with the findings of other authors on behavior of these two parameters during cell and tissue aging.