By borrowing mathematical tools from theoretical physics, scientists have recently developed a theory that explains why the brain tissue of humans and other vertebrates is segregated into the familiar "grey matter" and "white matter."

Grey matter contains local networks of neurons that are wired by dendrites and mostly nonmyelinated local axons. White matter contains long-range axons that implement global and fast communication via often myelinated axons. What is the evolutionary advantage of segregating the brain into white and gray matter rather than intermixing them?

To answer this question, the authors - Quan Wen a graduate student from the Department of Physics and Astronomy, State University of New York, and Dmitri B. Chklovskii, a neuroscientist from Cold Spring Harbor Laboratory, New York - assumed that evolution had maximized brain functionality.
"We posit that brain functionality requires high interconnectivity and short conduction delays. Based on this assumption we searched for the optimal brain architecture by comparing different candidate designs. We found that the optimal design depends on the number of neurons, interneuronal connectivity, and axon diameter. In particular, the requirement to connect neurons with many fast axons drives the segregation of the brain into white and grey matter", the authors write.
"Although we do not know whether competing desiderata of short time delay and high interconnectivity were crucial factors driving evolution of vertebrate brains, our theory makes testable predictions."

Thus, the authors made theoretical estimates of various aspects of the brain such as cortical thickness and structure, the average axon fascicle size in the mammalian neotriatum and avian telencephalon, and the inner core diameter of the spinal cord.

The comparison between the theoretical predictions and the empirical observations is very good. Thus, the theory gives insight both on why various neurological regions such as the cerebral cortex and spinal cord, have their observed structure and on the factors that are favored by evolution.