As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field.
KeywordsNeuroimaging; Genetics; Heritability; High-angular resolution diffusion imaging (HARDI); ACE modeling Evidence that genetic and environmental factors shape human brain structure and function has been accumulating for nearly two centuries. Our knowledge has broadened considerably since the early attempts to identify genetic variations in cranial capacity and brain weight. Modern neuroimaging technology offers an unprecedented opportunity to search for genetic and environmental influences among thousands of voxels in individual high resolution brain images. Moreover, the data acquired has the potential to enhance our understanding of human behaviour by serving as an intermediate phenotype. Like any emerging field, neuroimaging genetics faces its own share of challenges. In this article, we describe some of those challenges and provide examples of how we have attempted to address them in our own research with magnetic resonance imaging (MRI).At the time of writing this article, reviews of MRI investigations of monozygotic (MZ) and dizygotic (DZ) twins have already concluded that brain macrostructure is significantly heritable (e.g., grey and white matter, lobar and whole brain volumes; see Peper et al., 2007;Schmitt et al., 2007) and that volumetric measures can serve as intermediate phenotypes for intellectual