Chklovskii Dmitri B
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
Neural Comput. 2004 Oct;16(10):2067-78. doi: 10.1162/0899766041732422.
Evolution perfected brain design by maximizing its functionality while minimizing costs associated with building and maintaining it. Assumption that brain functionality is specified by neuronal connectivity, implemented by costly biological wiring, leads to the following optimal design problem. For a given neuronal connectivity, find a spatial layout of neurons that minimizes the wiring cost. Unfortunately, this problem is difficult to solve because the number of possible layouts is often astronomically large. We argue that the wiring cost may scale as wire length squared, reducing the optimal layout problem to a constrained minimization of a quadratic form. For biologically plausible constraints, this problem has exact analytical solutions, which give reasonable approximations to actual layouts in the brain. These solutions make the inverse problem of inferring neuronal connectivity from neuronal layout more tractable.
进化通过最大化大脑功能并最小化构建和维持大脑相关的成本来完善大脑设计。假设大脑功能由神经元连接性决定,而这种连接性通过代价高昂的生物线路来实现,这就引出了以下最优设计问题。对于给定的神经元连接性,找到一种神经元的空间布局,使线路成本最小化。不幸的是,这个问题很难解决,因为可能的布局数量通常极其庞大。我们认为线路成本可能与线路长度的平方成正比,从而将最优布局问题简化为二次型的约束最小化问题。对于生物学上合理的约束条件,这个问题有精确的解析解,这些解能对大脑中的实际布局给出合理的近似。这些解使得从神经元布局推断神经元连接性的逆问题更易于处理。