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使用图模Dirichlet 能量定位视觉短期记忆绑定的时间功能动态。

Locating Temporal Functional Dynamics of Visual Short-Term Memory Binding using Graph Modular Dirichlet Energy.

机构信息

Institute for Digital Communications, University of Edinburgh, West Mains Rd, Edinburgh, EH9 3FB, UK.

Alzheimer Scotland Dementia Research Centre, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.

出版信息

Sci Rep. 2017 Feb 10;7:42013. doi: 10.1038/srep42013.

Abstract

Visual short-term memory binding tasks are a promising early marker for Alzheimer's disease (AD). To uncover functional deficits of AD in these tasks it is meaningful to first study unimpaired brain function. Electroencephalogram recordings were obtained from encoding and maintenance periods of tasks performed by healthy young volunteers. We probe the task's transient physiological underpinnings by contrasting shape only (Shape) and shape-colour binding (Bind) conditions, displayed in the left and right sides of the screen, separately. Particularly, we introduce and implement a novel technique named Modular Dirichlet Energy (MDE) which allows robust and flexible analysis of the functional network with unprecedented temporal precision. We find that connectivity in the Bind condition is less integrated with the global network than in the Shape condition in occipital and frontal modules during the encoding period of the right screen condition. Using MDE we are able to discern driving effects in the occipital module between 100-140 ms, coinciding with the P100 visually evoked potential, followed by a driving effect in the frontal module between 140-180 ms, suggesting that the differences found constitute an information processing difference between these modules. This provides temporally precise information over a heterogeneous population in promising tasks for the detection of AD.

摘要

视觉短期记忆绑定任务是阿尔茨海默病(AD)的一个有前途的早期标志物。为了揭示这些任务中 AD 的功能缺陷,首先研究未受损的大脑功能是有意义的。对健康年轻志愿者执行任务的编码和维持期间,我们进行了脑电图记录。我们通过对比仅显示在屏幕左右两侧的形状(Shape)和形状-颜色绑定(Bind)条件,来探测任务的瞬态生理基础。特别地,我们引入并实现了一种名为模块化狄利克雷能量(MDE)的新技术,该技术允许使用前所未有的时间精度对功能网络进行稳健而灵活的分析。我们发现,在对右侧屏幕条件进行编码期间,与形状条件相比,在枕部和额部模块中,绑定条件下的连接性与全局网络的集成度较低。使用 MDE,我们能够在 100-140ms 之间区分出枕部模块中的驱动效应,与视觉诱发电位 P100 吻合,随后在 140-180ms 之间出现额部模块中的驱动效应,表明所发现的差异构成了这些模块之间的信息处理差异。这为 AD 检测有希望的任务中的异构人群提供了时间上精确的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54c9/5301217/3c5b6c594891/srep42013-f1.jpg

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