Multi-scale correlation structure of gene expression in the brain

The mammalian brain is best understood as a multi-scale hierarchical neural system, in the sense that connection and function occur on multiple scales from micro to macro. Modern genomic-scale expression profiling can provide insight into methodologies that elucidate this architecture. We present a methodology for understanding the relationship of gene expression and neuroanatomy based on correlation between gene expression profiles across tissue samples. A resulting tool, NeuroBlast, can identify networks of genes co-expressed within or across neuroanatomic structures. The method applies to any data modality that can be mapped with sufficient spatial resolution, and provides a computation technique to elucidate neuroanatomy via patterns of gene expression on spatial and temporal scales. In addition, from the perspective of spatial location, we discuss a complementary technique that identifies gene classes that contribute to defining anatomic patterns.

► The architecture of the mammalian brain can be understood as a multiscale hierarchical neural system. ► Large scale gene expression studies elucidate the role of the transcriptome in defining neuroanatomic structure. ► Image mapping and registration enables the development of neuroinformatics tools for data mining. ► Complementary techniques of correlation based search and local expression analysis are powerful means of discovering structure. ► These results generalize across to multiple data modalities and species.