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由脊柱比例经济最大化或线体积最小化驱动的皮质成分层次结构

Cortical Composition Hierarchy Driven by Spine Proportion Economical Maximization or Wire Volume Minimization.

作者信息

Karbowski Jan

机构信息

Institute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Poland.

出版信息

PLoS Comput Biol. 2015 Oct 5;11(10):e1004532. doi: 10.1371/journal.pcbi.1004532. eCollection 2015 Oct.

Abstract

The structure and quantitative composition of the cerebral cortex are interrelated with its computational capacity. Empirical data analyzed here indicate a certain hierarchy in local cortical composition. Specifically, neural wire, i.e., axons and dendrites take each about 1/3 of cortical space, spines and glia/astrocytes occupy each about (1/3)(2), and capillaries around (1/3)(4). Moreover, data analysis across species reveals that these fractions are roughly brain size independent, which suggests that they could be in some sense optimal and thus important for brain function. Is there any principle that sets them in this invariant way? This study first builds a model of local circuit in which neural wire, spines, astrocytes, and capillaries are mutually coupled elements and are treated within a single mathematical framework. Next, various forms of wire minimization rule (wire length, surface area, volume, or conduction delays) are analyzed, of which, only minimization of wire volume provides realistic results that are very close to the empirical cortical fractions. As an alternative, a new principle called "spine economy maximization" is proposed and investigated, which is associated with maximization of spine proportion in the cortex per spine size that yields equally good but more robust results. Additionally, a combination of wire cost and spine economy notions is considered as a meta-principle, and it is found that this proposition gives only marginally better results than either pure wire volume minimization or pure spine economy maximization, but only if spine economy component dominates. However, such a combined meta-principle yields much better results than the constraints related solely to minimization of wire length, wire surface area, and conduction delays. Interestingly, the type of spine size distribution also plays a role, and better agreement with the data is achieved for distributions with long tails. In sum, these results suggest that for the efficiency of local circuits wire volume may be more primary variable than wire length or temporal delays, and moreover, the new spine economy principle may be important for brain evolutionary design in a broader context.

摘要

大脑皮层的结构和定量组成与其计算能力相互关联。此处分析的实证数据表明局部皮层组成存在一定层次结构。具体而言,神经纤维,即轴突和树突各自占据约1/3的皮层空间,棘突和神经胶质/星形胶质细胞各自占据约(1/3)²,而毛细血管占据约(1/3)⁴。此外,跨物种的数据分析表明这些比例大致与脑大小无关,这表明它们在某种意义上可能是最优的,因此对脑功能很重要。是否存在某种原则以这种不变的方式设定它们呢?本研究首先构建了一个局部回路模型,其中神经纤维、棘突、星形胶质细胞和毛细血管是相互耦合的元素,并在单一数学框架内进行处理。接下来,分析了各种形式的纤维最小化规则(纤维长度、表面积、体积或传导延迟),其中,只有纤维体积最小化能提供与实证皮层比例非常接近的现实结果。作为一种替代方案,提出并研究了一种名为“棘突经济最大化”的新原则,它与皮层中每个棘突大小的棘突比例最大化相关,产生同样良好但更稳健的结果。此外,将纤维成本和棘突经济概念的组合视为一个元原则,发现该命题仅比纯粹的纤维体积最小化或纯粹的棘突经济最大化略好,但前提是棘突经济成分占主导。然而,这样一个组合元原则比仅与纤维长度、纤维表面积和传导延迟最小化相关的约束产生的结果要好得多。有趣的是,棘突大小分布的类型也起作用,对于长尾分布能更好地与数据达成一致。总之,这些结果表明,对于局部回路的效率而言,纤维体积可能比纤维长度或时间延迟更主要的变量,此外,新的棘突经济原则在更广泛的背景下可能对大脑进化设计很重要。

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