Scientists are at work, both in Europe and in the US, to understand the Brain. There are different approaches to do that, and there is also a lot of debate on the validity of each, as there were (and still are) many on the kind of knowledge that can be extracted by looking at the genome.
One of the basic objection is that no matter how precisely you can detect structures inside a brain (like in the goal of the Human Connectome project) they are a picture of THAT brain and are surely different from those you would derive from other brains. Hence, it is "impossible" to derive sound knowledge on the "workings" of brains by looking at the structure of one brain.
I understand this objection but I am more confident that the kind of "abstract" understanding that can be derived through the fine identification of structure in a brain can indeed tell us quite a lot on the workings of "brains". Similarly by looking at roads topology in a city can provide some good understanding on the overall working of roads (traffic) in cities, although there are no two cities alike in terms of roads. And similarly to what we are starting to see from the knowledge we are acquiring from the sequencing of the genome. Clearly, the more "pictures" we can get the more we can hope to create a conceptual representation of brain structures and of their work and interworking.
This is what is being done around the world, and this is what scientists at the USC, Institute for neuroimaging and informatics University of Southern California, have been doing. They have published in the journal Frontiers in Neuroscience the first map of connectivity in the White Matter of human brain, looking at data derived from the analyses of 110 brains.
Data have been gathered through MRI scans and the first analyses are pointing out that not all connections are equally (functionally) important.
This analyses has been done through simulation by interrupting certain pathways and seeing how the corresponding grey areas would be affected. Neurologists know that there are areas in the grey matter that are more important than others and the same goes with areas in the white matter (that is basically providing the connectivity pathways to the grey matter). However, the correspondence between the importance of grey areas with white areas is not straightforward. It looks like some crucial functional disabilities may occur as result of damage to parts of the white matter that are not connecting any important grey matter area and viceversa.
In a way, this reminds me of the strange properties emerging from a small world system where stronger nodes are not necessarily the most important ones when a global system view is taken because often less important nodes are clustered in networks that can compensate for the loss of more important nodes.
This seems to be true for our brain as well and this helps in explaining why certain lesions that appear severe do not have a big impact on functionality of the brain whilst other apparently less important may result in great functional loss and low chances for recovery.
I found interesting that this research is being carried out by the Institute for neuroimaging and informatics, notice the Informatics part. And I found fascinating that these researchers are studying the brain structures by using tools applied in the studying of social networks!
The science of networks (and small worlds) is helping us to understand emergent behaviour, something that we have been used to call "thinking" and "emotions".