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Fragmentation: loss of global coherence or breakdown of modularity in functional brain architecture?

机译:碎片化:丧失整体一致性或功能性大脑结构的模块性崩溃?

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摘要

Psychiatric illnesses characterized by disorganized cognition, such as schizophrenia, have been described in terms of fragmentation and hence understood as reduction in functional brain connectivity, particularly in prefrontal and parietal areas. However, as graph theory shows, relatively small numbers of nonlocal connections are sufficient to ensure global coherence in the modular small-world network structure of the brain. We reconsider fragmentation in this perspective. Computational studies have shown that for a given level of connectivity in a model of coupled nonlinear oscillators, modular small-world networks evolve from an initially random organization. Here we demonstrate that with decreasing connectivity, the probability of evolving into a modular small-world network breaks down at a critical point, which scales to the percolation function of random networks with a universal exponent of α = 1.17. Thus, according to the model, local modularity systematically breaks down before there is loss of global coherence in network connectivity. We, therefore, propose that fragmentation may involve, at least in its initial stages, the inability of a dynamically evolving network to sustain a modular small-world structure. The result is in a shift in the balance in schizophrenia from local to global functional connectivity.
机译:精神分裂症等以认知障碍为特征的精神疾病已被描述为碎片化,因此被理解为功能性大脑连通性降低,尤其是在额叶和顶叶区域。但是,正如图论所示,相对少量的非本地连接足以确保大脑的模块化小世界网络结构的全局一致性。我们从这个角度重新考虑碎片化。计算研究表明,对于耦合非线性振荡器模型中的给定连接水平,模块化小世界网络是从最初的随机组织演变而来的。在这里,我们证明,随着连通性的降低,发展成为模块化小世界网络的概率在临界点处分解,该临界点扩展为具有通用指数α= 1.17的随机网络的渗透函数。因此,根据该模型,在失去网络连接的全局一致性之前,本地模块化会系统性地崩溃。因此,我们建议,至少在其初始阶段,碎片化可能涉及无法动态发展的网络来维持模块化的小世界结构。结果导致精神分裂症的平衡从局部功能连接转变为全局功能连接。

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