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Role of Dimensionality in Predicting the Spontaneous Behavior of the Brain Using the Classical Ising Model and the Ising Model Implemented on a Structural Connectome

机译:维度在使用经典伊辛模型和结构连接体上实现的伊辛模型预测大脑自发行为中的作用

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摘要

There is accumulating evidence that spontaneous fluctuations of the brain are sustained by a structural architecture of axonal fiber bundles. Various models have been used to investigate this structure–function relationship. In this work, we implemented the Ising model using the number of fibers between each pair of brain regions as input. The output of the Ising model simulations on a structural connectome was then compared with empirical functional connectivity data. A simpler two-dimensional classical Ising model was used as the baseline model for comparison purpose. Thermodynamic properties, such as the magnetic susceptibility and the specific heat, illustrated a phase transition from an ordered phase to a disordered phase at the critical temperature. Despite the differences between the two models, the lattice Ising model and the Ising model implemented on a structural connectome (the generalized Ising model) exhibited similar patterns of global properties. To study the behavior of the generalized Ising model around criticality, calculation of the dimensionality and critical exponents was performed for the first time, by introducing a new concept of distance based on structural connectivity. Same value inside the fitting error was found for the dimensionality in both models suggesting similar behavior of the models around criticality.
机译:有越来越多的证据表明,轴突纤维束的结构可以维持大脑的自发性波动。已经使用各种模型来研究这种结构-功能关系。在这项工作中,我们使用每对大脑区域之间的纤维数量作为输入来实现Ising模型。然后将结构连接套上Ising模型仿真的输出与经验功能连接数据进行比较。为了进行比较,将一个更简单的二维经典Ising模型用作基线模型。诸如磁化率和比热的热力学性质说明了在临界温度下从有序相到无序相的相变。尽管这两个模型之间存在差异,但晶格Ising模型和在结构连接体上实现的Ising模型(广义Ising模型)表现出相似的全局特性模式。为了研究广义Ising模型围绕临界性的行为,通过引入基于结构连通性的新距离概念,首次进行了维数和临界指数的计算。在两个模型的维数中,在拟合误差内发现了相同的值,这表明模型在临界度附近具有相似的行为。

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