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Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression

机译:皮质扩散性抑郁症的时空脑血流灌注模式

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Cortical spreading depression (CSD) is an example of one of the most common abnormalities in biophysical brain functioning. Despite the fact that there are many mathematical models describing the cortical spreading depression (CSD), most of them do not take into consideration the role of redistribution of cerebral blood flow (CBF), that results in the formation of spatio-temporal patterns. The paper presents a mathematical model, which successfully explains the CBF role in the CSD process. Numerical study of this model has revealed the formation of stationary dissipative structures, visually analogous to Turing structures. However, the mechanism of their formation is not diffusion. We show these structures occur due to another type of spatial coupling, that is related to tissue perfusion rate. The proposed model predicts that at similar state of neurons the distribution of blood flow and oxygenation may by different. Currently, this effect is not taken into account when the Blood-oxygen-level dependent (BOLD) contrast imaging used in functional magnetic resonance imaging (fMRI). Thus, the diagnosis on the BOLD signal can be ambiguous. We believe that our results can be used in the future for a more correct interpretation of the data obtained with fMRI, NIRS and other similar methods for research of the brain activity.
机译:皮质扩散抑制(CSD)是生物物理脑功能中最常见的异常之一。尽管有许多数学模型描述了皮层扩展性抑郁症(CSD),但大多数模型并未考虑脑血流(CBF)的重新分布的作用,导致时空分布的形成。本文提出了一个数学模型,该模型成功地解释了CBF在CSD过程中的作用。该模型的数值研究揭示了固定耗散结构的形成,在视觉上类似于图灵结构。但是,它们的形成机理不是扩散。我们显示这些结构的发生是由于另一种类型的空间耦合,与组织灌注速率有关。提出的模型预测,在神经元的相似状态下,血流和氧合的分布可能不同。当前,当在功能磁共振成像(fMRI)中使用依赖于血氧水平的(BOLD)对比成像时,尚未考虑此效果。因此,对BOLD信号的诊断可能不明确。我们相信,我们的结果可以在将来用于更正确地解释通过fMRI,NIRS和其他类似方法进行的脑活动研究获得的数据。

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