School of Physics, University of Sydney, Sydney, NSW 2006, Australia; Brain Dynamics Center, Sydney Medical School-Western, University of Sydney, Westmead, New South Wales 2145, Australia.
School of Physics, University of Sydney, Sydney, NSW 2006, Australia; Brain Dynamics Center, Sydney Medical School-Western, University of Sydney, Westmead, New South Wales 2145, Australia.
J Theor Biol. 2014 Apr 21;347:118-36. doi: 10.1016/j.jtbi.2013.12.027. Epub 2014 Jan 4.
Probing neural activity with functional magnetic resonance imaging (fMRI) relies upon understanding the hemodynamic response to changes in neural activity. Although existing studies have extensively characterized the temporal hemodynamic response, less is understood about the spatial and spatiotemporal hemodynamic responses. This study systematically characterizes the spatiotemporal response by deriving the hemodynamic response due to a short localized neural drive, i.e., the spatiotemporal hemodynamic response function (stHRF) from a physiological model of hemodynamics based on a poroelastic model of cortical tissue. In this study, the model's boundary conditions are clarified and a resulting nonlinear hemodynamic wave equation is derived. From this wave equation, damped linear hemodynamic waves are predicted from the stHRF. The main features of these waves depend on two physiological parameters: wave propagation speed, which depends on mean cortical stiffness, and damping which depends on effective viscosity. Some of these predictions were applied and validated in a companion study (Aquino et al., 2012). The advantages of having such a theory for the stHRF include improving the interpretation of spatiotemporal dynamics in fMRI data; improving estimates of neural activity with fMRI spatiotemporal deconvolution; and enabling wave interactions between hemodynamic waves to be predicted and exploited to improve the signal to noise ratio of fMRI.
利用功能磁共振成像 (fMRI) 探测神经活动依赖于理解神经活动变化的血液动力学反应。尽管现有研究广泛描述了时间血液动力学反应，但对空间和时空血液动力学反应的了解较少。本研究通过从基于皮质组织的多孔弹性模型的血液动力学生理模型中推导出由于短暂局部神经驱动引起的血液动力学响应，即时空血液动力学响应函数 (stHRF)，系统地描述了时空响应。在本研究中，澄清了模型的边界条件，并推导出了由此产生的非线性血液动力学波动方程。从这个波动方程中，可以从 stHRF 中预测出阻尼线性血液动力学波动。这些波的主要特征取决于两个生理参数：波传播速度，它取决于平均皮质刚度，而阻尼取决于有效粘度。这些预测中的一些在一项配套研究 (Aquino 等人，2012 年) 中得到了应用和验证。具有这样的 stHRF 理论的优点包括：改善 fMRI 数据中时空动力学的解释；改善 fMRI 时空去卷积的神经活动估计；并能够预测血液动力学波之间的波相互作用并加以利用，以提高 fMRI 的信噪比。
