Laboratory for Perceptual Dynamics, Brain Science Institute RIKEN, Wako-shi Saitama, Japan.
Front Syst Neurosci. 2012 Mar 30;6:20. doi: 10.3389/fnsys.2012.00020. eCollection 2012.
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.
以认知紊乱为特征的精神疾病，如精神分裂症，可以用碎片化来描述，因此可以理解为功能性大脑连接的减少，特别是在前额叶和顶叶区域。然而，正如图论所示，相对较少的非局部连接足以确保大脑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，模块化小世界网络从最初的随机组织中演变而来。在这里，我们证明随着连接性的降低，演变成模块化小世界网络的概率在临界点处崩溃，该临界点与具有通用指数α=1.17的随机网络的渗透函数相标度。因此，根据该模型，在网络连接失去全局一致性之前，局部模块性会系统地崩溃。因此，我们提出碎片化可能至少在其初始阶段涉及动态演化网络维持模块化小世界结构的能力丧失。结果是精神分裂症从局部功能连接到全局功能连接的平衡发生转移。
