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人类大脑BOLD自发活动中血流的拓扑视图。

Topological View of Flows Inside the BOLD Spontaneous Activity of the Human Brain.

作者信息

Don Arjuna P H, Peters James F, Ramanna Sheela, Tozzi Arturo

机构信息

Computational Intelligence Laboratory, University of Manitoba, Winnipeg, MB, Canada.

Applied Computer Science, University of Winnipeg, Winnipeg, MB, Canada.

出版信息

Front Comput Neurosci. 2020 Apr 22;14:34. doi: 10.3389/fncom.2020.00034. eCollection 2020.

Abstract

Spatio-temporal brain activities with variable delay detectable in resting-state functional magnetic resonance imaging (rs-fMRI) give rise to highly reproducible structures, termed cortical lag threads, that propagate from one brain region to another. Using a computational topology of data approach, we found that persistent, recurring blood oxygen level dependent (BOLD) signals in triangulated rs-fMRI videoframes display previously undetected topological findings, i.e., vortex structures that cover brain activated regions. Measure of persistence of vortex shapes in BOLD signal propagation is carried out in terms of Betti numbers that rise and fall over time during spontaneous activity of the brain. Importantly, a topology of data given in terms of geometric shapes of BOLD signal propagation offers a practical approach in coping with and sidestepping massive noise in neurodata, such as unwanted dark (low intensity) regions in the neighborhood of non-zero BOLD signals. Our findings have been codified and visualized in plots able to track the non-trivial BOLD signals that appear intermittently in a sequence of rs-fMRI videoframes. The end result of this tracking of changing lag structures is a so-called persistent barcode, which is a pictograph that offers a convenient visual means of exhibiting, comparing, and classifying brain activation patterns.

摘要

在静息态功能磁共振成像(rs-fMRI)中可检测到具有可变延迟的时空脑活动,从而产生了高度可重复的结构,称为皮质滞后线,其从一个脑区传播到另一个脑区。使用数据的计算拓扑方法,我们发现三角化rs-fMRI视频帧中持续出现的血氧水平依赖(BOLD)信号显示出以前未检测到的拓扑结果,即覆盖脑激活区域的涡旋结构。在脑自发活动期间,根据随时间上升和下降的贝蒂数来测量BOLD信号传播中涡旋形状的持续性。重要的是,以BOLD信号传播的几何形状给出的数据拓扑为应对和规避神经数据中的大量噪声提供了一种实用方法,例如非零BOLD信号附近不需要的暗(低强度)区域。我们的发现已被整理并可视化在能够跟踪在rs-fMRI视频帧序列中间歇出现的非平凡BOLD信号的图中。这种对变化的滞后结构的跟踪的最终结果是一个所谓的持久条形码,它是一种象形图,提供了一种方便的视觉手段来展示、比较和分类脑激活模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c48d/7189216/2bea7cb90010/fncom-14-00034-g0001.jpg

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