时空血流动力学的响应模式分解
Response-mode decomposition of spatio-temporal haemodynamics.
作者信息
Pang J C, Robinson P A, Aquino K M
机构信息
School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia Center for Integrative Brain Function, University of Sydney, Sydney, New South Wales 2006, Australia
School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia Center for Integrative Brain Function, University of Sydney, Sydney, New South Wales 2006, Australia.
出版信息
J R Soc Interface. 2016 May;13(118). doi: 10.1098/rsif.2016.0253.
The blood oxygen-level dependent (BOLD) response to a neural stimulus is analysed using the transfer function derived from a physiologically based poroelastic model of cortical tissue. The transfer function is decomposed into components that correspond to distinct poles, each related to a response mode with a natural frequency and dispersion relation; together these yield the total BOLD response. The properties of the decomposed components provide a deeper understanding of the nature of the BOLD response, via the components' frequency dependences, spatial and temporal power spectra, and resonances. The transfer function components are then used to separate the BOLD response to a localized impulse stimulus, termed the Green function or spatio-temporal haemodynamic response function, into component responses that are explicitly related to underlying physiological quantities. The analytical results also provide a quantitative tool to calculate the linear BOLD response to an arbitrary neural drive, which is faster to implement than direct Fourier transform methods. The results of this study can be used to interpret functional magnetic resonance imaging data in new ways based on physiology, to enhance deconvolution methods and to design experimental protocols that can selectively enhance or suppress particular responses, to probe specific physiological phenomena.
利用从基于生理的皮质组织多孔弹性模型导出的传递函数，分析对神经刺激的血氧水平依赖（BOLD）反应。传递函数被分解为对应于不同极点的分量，每个极点都与具有固有频率和色散关系的响应模式相关；这些共同产生总的BOLD反应。通过分解分量的频率依赖性、空间和时间功率谱以及共振，分解分量的特性能够更深入地理解BOLD反应的本质。然后，传递函数分量被用于将对局部脉冲刺激（称为格林函数或时空血液动力学响应函数）的BOLD反应分离为与潜在生理量明确相关的分量反应。分析结果还提供了一种定量工具，用于计算对任意神经驱动的线性BOLD反应，其实现速度比直接傅里叶变换方法更快。本研究结果可用于基于生理学以新的方式解释功能磁共振成像数据，以增强反卷积方法，并设计能够选择性增强或抑制特定反应的实验方案，从而探究特定的生理现象。
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