Visualizing nervous systems, both the raw images and their reconstructions, is a hot field for a good reason. Once we have these sort of maps we’ll be able to make much more precisely quantitative statements about how the information flow in neuronal networks is constrained.
On this front, in Nov ’11 Chung et al published a paper describing their research into visualizing mouse brain-wide data generated by a knife-edge scanning microscope. The 29 s, soundless video below shows one of their data sets sweeping through each of the imaging planes (sagittal, coronal, and horizontal).
You can view the data set in a web browser here. It is still in “beta” mode and on my browser it is pretty slow, but worth the wait.
At high zoom, the data is fairly precise. In my screenshot below, you can make out individual somata.
Specimen: C57BL/6J Mouse; Stain: Golgi; Dimension: 600 x 375 x 10 (pixels); Current Layers: 2951 - 2960
The Golgi is called a “sparse” stain because it marks only a subset of the neurons, typically ~1%. On the plus side, it is considered to stain neurons randomly, so any conclusions drawn from the connectivity differences between brain regions in this data set should not be systematically biased.
Of course, we’d first have to convert the image stacks to structure calls, which is far from a settled problem.
Reference
Chung JR, Sung C, Mayerich D, Kwon J, Miller DE, Huffman T, Keyser J, Abbott LC and Choe Y (2011) Multiscale exploration of mouse brain microstructures using the knife-edge scanning microscope brain atlas. Front. Neuroinform. 5:29. doi: 10.3389/fninf.2011.00029
