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分布式神经网络的多重摄动分析:空间忽视的案例。

Multiperturbation analysis of distributed neural networks: the case of spatial neglect.

机构信息

Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem, Israel.

出版信息

Hum Brain Mapp. 2009 Nov;30(11):3687-95. doi: 10.1002/hbm.20797.

DOI:10.1002/hbm.20797
PMID:19449335
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6870892/
Abstract

This study assesses the feasibility of using a multiperturbation analysis (MPA) approach for lesion-symptom mapping. We analyze the relative contribution of damage in different brain regions to the expression of spatial neglect, as revealed in line-bisection performance. The data set comprised of normalized lesion information and bisection test results from 23 first-event right-hemisphere stroke patients. Obtaining quantitative measures of task relevance for different regions of interest (ROIs), the following ROIs were found to be the most contributing: the supramarginal and angular gyri of the inferior parietal lobule, the superior parietal lobule, the anterior part of the temporo-parietal junction connecting the superior temporal and supramarginal gyri, and the thalamus. MPA is likely to play an important role in elucidating the anatomical substrate of complex functions.

摘要

本研究评估了使用多扰动分析(MPA)方法进行病变-症状映射的可行性。我们分析了不同脑区损伤对空间忽略表达的相对贡献,这是通过线二分测试结果揭示的。该数据集包括 23 例首次右侧半球中风患者的归一化损伤信息和二分测试结果。为了获得不同感兴趣区域(ROI)的任务相关性的定量测量,发现以下 ROI 贡献最大:下顶叶的缘上回和角回、顶叶上回、连接上颞叶和缘上回的颞顶交界处的前部,以及丘脑。MPA 可能在阐明复杂功能的解剖学基础方面发挥重要作用。

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Does monocular viewing improve target detection in hemispatial neglect?单眼观察是否能改善半侧空间忽略中的目标检测?
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