Towards optimal neuronal wiring through estimation of distribution algorithms

One of the greatest challenges of our time is to understand brain functions. Our goal is to study the existence of an optimal neuronal design, defined as the one that has a minimum total wiring. Many researchers have studied the problem of optimal wiring in neuronal trees. Here we propose a new approach. We start from point clouds formed by the branching points of real neuronal trees and we search for the optimal forest from these point clouds. To do this, we formalize the problem as a forest of degree constrained minimum spanning trees (DCMST). Since the DCMST problem is NP-hard, we will try to solve it using estimation of distribution algorithms, particularly in permutation domains.

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