For almost five decades of its existence, imaging neuroscience—the research branch that uses noninvasive brain imaging to provide inferences about brain structure and function, has focused almost exclusively on studies pertaining to well-controlled laboratory experiments or brain pathologies. There is a recent focus on the interaction between individual and the exposome, a construct encompassing not only the natural and built environment but also social and aesthetic components of it. Some of these studies use imaging neuroscience methods to investigate the rich ensemble of associations and causal relationships between exposome variables and the human brain. In this chapter, we present the well-established domain of computational anatomy that uses magnetic resonance imaging data and sophisticated algorithms to provide a flexible framework for statistical analysis in brain space. We cover the basic principles of feature extraction and statistical analysis to point toward some limitations and corresponding new in vivo brain histology developments helping to circumvent previous interpretational shortcomings. The aim is to provide a sufficient methodological background that will allow for understanding computational anatomy and functional imaging findings and will motivate formulating own questions in the context of environmental neuroscience.