Perl Yonatan Sanz, Zamora-Lopez Gorka, Montbrió Ernest, Monge-Asensio Martí, Vohryzek Jakub, Fittipaldi Sol, Campo Cecilia González, Moguilner Sebastián, Ibañez Agustín, Tagliazucchi Enzo, Yeo B T Thomas, Kringelbach Morten L, Deco Gustavo
Department of Physics, University of Buenos Aires, Buenos Aires, Argentina.
National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina.
Netw Neurosci. 2023 Jun 30;7(2):632-660. doi: 10.1162/netn_a_00299. eCollection 2023.
Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart-Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer's patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
考虑到大脑区域的细胞和分子组成、连通性及功能，健康和患病状态下大脑各区域存在很大差异。包含耦合脑区的大规模全脑模型为塑造自发脑活动复杂模式的潜在动力学提供了见解。特别是，异步状态下基于生物物理学的平均场全脑模型被用于证明纳入区域差异的动力学后果。然而，当脑动力学由同步振荡状态支持时（这是大脑中普遍存在的现象），异质性的作用仍知之甚少。在此，我们实现了两个能够呈现不同抽象程度振荡行为的模型：一个唯象的斯图尔特 - 朗道模型和一个精确的平均场模型。这些由结构到功能加权的MRI信号（T1w/T2w）提供信息的模型拟合，使我们能够探索纳入异质性对模拟健康参与者静息态功能磁共振成像记录的影响。我们发现，疾病特异性的区域功能异质性在神经退行性疾病的功能磁共振成像记录的振荡状态内产生了动力学后果，对脑萎缩/结构（阿尔茨海默病患者）有特定影响。总体而言，我们发现当考虑结构和功能区域异质性时，具有振荡的模型表现更好，这表明唯象模型和生物物理模型在霍普夫分岔边缘的行为相似。
