Diagram of Brain

A team of researchers has modeled in high-resolution the underlying architecture of the human cerebral cortex, showing how different brain regions interact with one another. This is basically an outline of the wiring connections between neurons in the brain's outer layer. This is the most complete mapping of the interconnected brain nodes to date. Apparently this is one of the first maps of the human brain at this level of detail. The researchers used a state-of-the-art diffusion MRI technology to image neural fibers. This new map may allow a better interpretation of brain scans as scientists will now know the underlying mechanisms of brain activation/deactivation. This diagram will give scientists a keener insight into how the brain works.

"In the human brain, neural activation patterns are shaped by the underlying structural connections that form a dense network of fiber pathways linking all regions of the cerebral cortex. Using diffusion imaging techniques, which allow the noninvasive mapping of fiber pathways, we constructed connection maps covering the entire cortical surface. Computational analyses of the resulting complex brain network reveal regions of cortex that are highly connected and highly central, forming a structural core of the human brain."

The brain is extremely complex and being able to have a completely accurate circuit diagram would be a huge boon for understanding many brain diseases.

"Human cerebral cortex consists of approximately 1010 neurons that are organized into a complex network of local circuits and long-range fiber pathways. This complex network forms the structural substrate for distributed interactions among specialized brain systems. Computational network analysis has provided insight into the organization of large-scale cortical connectivity in several species, including rat, cat, and macaque monkey. In human cortex, the topology of functional connectivity patterns has recently been investigated, and key attributes of these patterns have been characterized across different conditions of rest or cognitive load."

It sounds like they basically reduced specific brain regions to nodes and then found the strength of connections between various nodes. A node is made up of a specific amount of neurons that project axons to other brain regions.

"A node with high degree makes many connections (where each connection is counted once), while a node with high strength makes strong connections (where strength is equal to the sum of connection density or weight). A node with high betweenness centrality lies on many of the shortest paths that link other nodes in the network to one another. A node with high efficiency is itself found to be, on average, at a short distance from other nodes in the network."

You can read the paper here. So this is part of the increasing trend towards highly accurate computer models of the brain.
(Image Credit: Indiana University)