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Spatial Embedding of fMRI for Investigating Local Coupling in Human Brain

机译:功能磁共振成像的空间嵌入,用于研究人脑中的局部耦合

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In this paper, we have investigated local spatial couplings in the human brain by applying nonlinear dynamicaltechniques on fMRI data. We have recorded BOLD-contrast echo-planar fMRI data along with high-resolution T1-weighted anatomical images from the resting brain of healthy human subjects and performed physiological correctionon the functional data. The corrected data from resting subjects is spatially embedded into its phase space and thelargest Lyapunov exponent of the resulting attractor is calculated and whole slice maps are obtained. In addition, wesegment the high-resolution anatomical image and obtain a down sampled mask corresponding to gray and whitematter, which is used to obtain mean indices of the exponents for both the tissues separately. The results show theexistence of local couplings, its tissue specificity (more local coupling in gray matter than white matter) and dependenceon the size of the neighborhood (larger the neighborhood, lesser the coupling). We believe that these techniques capturethe information of a nonlinear and evolving system like the brain that may not be evident from static linear methods.The results show that there is evidence of spatio-temporal chaos in the brain, which is a significant finding hitherto notreported in literature to the best of our knowledge. We try to interpret our results from healthy resting subjects based onour knowledge of the native low frequency fluctuations in the resting brain and obtain a better understanding of thelocal spatial behavior of fMRI. This exploratory study has demonstrated the utility of nonlinear dynamical techniqueslike spatial embedding in analyzing fMRI data to gain meaningful insights into the working of human brain.
机译:在本文中,我们通过对fMRI数据应用非线性动力学技术研究了人脑中的局部空间耦合。我们已经记录了BOLD对比度回波平面fMRI数据以及来自健康人类受试者的静息大脑的高分辨率T1加权解剖图像,并对功能数据进行了生理校正。来自静止对象的校正数据在空间上嵌入其相空间中,并计算所得吸引子的最大Lyapunov指数,并获得整个切片图。另外,分割高分辨率的解剖图像并获得对应于灰色和白色物质的向下采样的蒙版,该蒙版用于分别获取两个组织的指数的均值。结果显示了局部偶联的存在,其组织特异性(灰质中的局部偶联比白质中的局部偶联更多)以及对邻域大小的依赖性(邻域越大,偶联越小)。我们相信这些技术可以捕获非线性和不断发展的系统(如大脑)的信息,而静态线性方法可能无法发现这些信息。结果表明,大脑中存在时空混沌的证据,这是迄今为止尚未报道的重要发现。据我们所知,文学。我们试图根据我们对静息大脑固有的低频波动的了解来解释健康静息受试者的结果,并更好地了解fMRI的局部空间行为。这项探索性研究已经证明了非线性动力学技术(如空间嵌入)在分析fMRI数据中获得实用性,从而获得了对人脑工作的有意义的见解。

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