Department of Physics and Astronomy, Western University, London, ON, Canada.
Brain and Mind Institute, Western University, London, ON, Canada.
Brain Struct Funct. 2021 Apr;226(3):817-832. doi: 10.1007/s00429-020-02211-6. Epub 2021 Feb 1.
Diffusion tractography is a non-invasive technique that is being used to estimate the location and direction of white matter tracts in the brain. Identifying the characteristics of white matter plays an important role in research as well as in clinical practice that relies on finding the relationship between the structure and function of the brain. An Ising model implemented on a structural connectivity (SC) has proven to explain the spontaneous fluctuations in the brain at criticality using brain's structure depicted by white matter tracts. Since the SC is the only input of the model, identifying the tractography technique which provides a SC that delivers the highest prediction of the brain's intrinsic activity via the generalized Ising model (GIM) is essential. Hence an Ising model is simulated on SCs generated using two different acquisition schemes (single and multi-shell) and two different tractography approaches (deterministic and probabilistic) and analyzed at criticality across 69 healthy subjects. Results showed that by introducing the GIM, predictability of the empirical correlation matrix increases on average from 0.2 to 0.6 compared to the predictability using the empirical connectivity matrix directly. It is also observed that the SC generated using deterministic tractography without fractional anisotropy resulted in the highest correlation coefficient value of 0.65 between the simulated and empirical correlation matrices. Additionally, calculated dimensionalities per simulation illustrated that the dimensionality depends upon the method of tractography that has been used to extract the SC.
扩散轨迹是一种非侵入性技术，用于估计大脑中白质束的位置和方向。识别白质的特征在研究以及依赖于发现大脑结构和功能之间关系的临床实践中都起着重要作用。在结构连接（SC）上实现的伊辛模型已被证明可以使用由白质束描绘的大脑结构在临界点解释大脑的自发波动。由于 SC 是模型的唯一输入，因此确定提供通过广义伊辛模型（GIM）对大脑内在活动进行最高预测的 SC 的轨迹技术至关重要。因此，在 69 名健康受试者中，在临界点对使用两种不同采集方案（单壳和多壳）和两种不同轨迹技术（确定性和概率性）生成的 SC 上模拟了伊辛模型，并进行了分析。结果表明，通过引入 GIM，与直接使用经验连通性矩阵相比，经验相关矩阵的可预测性平均从 0.2 增加到 0.6。还观察到，使用没有分数各向异性的确定性轨迹生成的 SC 导致模拟和经验相关矩阵之间的相关系数值最高为 0.65。此外，每个模拟计算的维度表明，维度取决于用于提取 SC 的轨迹技术。
