Case Studies: A new way to see our science
November 11, 2014
Our data is big, and beautiful, but how can scientists use it to actually make observations about the brain? A heat map, like the one pictured here from the Allen Human Brain Atlas, contains an enormous amount of information about the genes expressed in each region of the brain. But faced with so much information, where do we begin?
The new Case Studies feature on brain-map.org is an interactive way for scientists to walk through our large-scale data and get a sense of the wealth of knowledge they can glean. At first glance, the heat map is a dizzying array of colors. But look a little closer and patterns start to emerge.
The top and left sides of the heat map list regions of the brain, and each square on the map is colored to show how similar or distinct the pair of regions is in terms of their genetic profiles. Blue represents a high degree of similarity between regions, and red virtually no similarity. (Notice the diagonal blue line from the top left to the bottom right—this is each region compared to itself, so the similarity is one hundred percent.)
The patterns of colors can tell us a great deal about the borders between regions of the brain, and about the nature of gene expression in each region. Scrolling through the data in the Case Study, we can make some striking observations. For instance, gene expression across the brain’s cortex is fairly consistent, without much variation between sub-regions. The major exception to this rule is the visual cortex, which stands out dramatically from the rest of the surface of the brain with its different set of genes. Regions like the cerebellum also pop out on the heat map as blue squares, showing that there is very little genetic variation between its regions, but that the cerebellum itself has little genetically in common with any other region of the brain.
This information is crucial to scientists who want to know more about both the structure and function of the different regions in the human brain, and how these characteristics may change in light of diseases like Alzheimer’s and Parkinson’s.