Simplexity is an emerging concept that expresses a possible complementary relationship between complexity and simplicity. The brain has been known as the most complex structure, and tremendous effort has been spent to study how it works. By understanding complex function of the brain, one can hope to unravel the mystery of its diseases and its biological systems. We propose herein an entropy-based framework for analysis of complexity with a particular application to the study of white matter changes of the human brain. In this analysis, the proposed approach takes into account both morphological structure and image intensity values of MRI scans to construct the complexity profiles of the brain. It has been realized that the quantity and spatial distribution of white matter changes play an important role in cognitive decline (i.e. dementia) and other neuropsychiatric disorders (i.e. multiple sclerosis, depression) as well as in other dementia disorders such as Alzheimers disease. Thus, the results can be utilized as a tool for automated quantification and comparison of various spatial distributions and orientations of age-related white matter changes where manual analysis is difficult and leads to different sensitivities for the respective MRI-based information of the brain.