Abstract
The mammalian brain is by far the most advanced organ to have evolved and the underlying biology is extremely complex. However, with aging populations and sedentary lifestyles, the prevalence of neurological disorders is increasing around the world. Consequently, there is a dire need for technologies that can help researchers to better understand the complexity of the brain and thereby accelerate therapies for diseases with origin in the central nervous system. One such technology is light-sheet fluorescence microscopy (LSFM) which in combination with whole organ immunolabelling has made it possible to visualize an intact mouse brain with single cell resolution. However, the price for this level of detail comes in form of enormous datasets that often challenges extraction of quantitative information. One approach for analyzing whole brain data is to align the scanned brains to a reference brain atlas. Having a fixed spatial reference provides each voxel of the sample brains with x-, y-, z-coordinates from which it is possible to obtain anatomical information on the observed fluorescence signal. An additional and important benefit of aligning light sheet data to a reference brain is that the aligned data provides a digital map of gene expression or cell counts which can be deposited in databases or shared with other scientists. This review focuses on the emerging field of virtual neuroscience using digital brain maps and discusses some of challenges incurred when registering LSFM recorded data to a standardized brain template.
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