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根据工作记忆负荷的有效连接变化:面孔和位置工作记忆任务的 fMRI 研究。

Changes in effective connectivity according to working memory load: an FMRI study of face and location working memory tasks.

机构信息

Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea.

出版信息

Psychiatry Investig. 2012 Sep;9(3):283-92. doi: 10.4306/pi.2012.9.3.283. Epub 2012 Sep 6.

Abstract

OBJECTIVE

The functional strategic mechanisms in the brain during performing visuospatial working memory tasks, especially tasks with heavy load, are controversial. We conducted the functional magnetic resonance imaging (fMRI) while sixteen subjects were performing face- and location-matching n-back tasks to examine causal relations within the frontoparietal networks.

METHODS

We applied a sophisticated method, the structural equation modeling (SEM), to the fMRI data. The imaging data were analyzed by extracting the task-related eigenseries using the principal component analysis (PCA) and then by applying a form of data-driven model called the automated search method.

RESULTS

The SEM analyses revealed a functional shift of network connectivity from the right to the left hemisphere with increasing load in the face-matching n-back tasks while the location-matching tasks required bilateral activation. In the locating matching n-back tasks, a pattern of parallel processing was observed in the left phonological loop and the right inferior parietal regions. Furthermore, object working memory-related activities in the left hemisphere reliably contributed to performance of both the face- and location-matching 2-back tasks.

CONCLUSION

Our results are consistent with previous reports in terms of demonstrating parallel and distributed information processing during performing working memory tasks with heavy loads. Our results additionally suggest a dynamic shift between the fast imagery circuit (right hemisphere) and the stable verbal circuit (left hemisphere), depending on task load.

摘要

目的

在执行视觉空间工作记忆任务(尤其是高负荷任务)时,大脑中的功能策略机制存在争议。我们对 16 名被试执行面孔和位置匹配 n 回任务时进行了功能磁共振成像(fMRI),以检查额顶网络内的因果关系。

方法

我们将结构方程模型(SEM)应用于 fMRI 数据。使用主成分分析(PCA)提取与任务相关的特征序列,并应用一种称为自动搜索方法的数据驱动模型,对成像数据进行分析。

结果

SEM 分析显示,在面孔匹配 n 回任务中,随着负荷的增加,网络连接从右侧向左侧发生功能转移,而位置匹配任务需要双侧激活。在位置匹配 n 回任务中,观察到左语音回路和右下顶叶区域的并行处理模式。此外,左半球的物体工作记忆相关活动可靠地有助于面孔和位置匹配 2 回任务的表现。

结论

我们的结果与之前的报告一致,即在执行高负荷工作记忆任务时,表现出并行和分布式信息处理。此外,我们的结果还表明,根据任务负荷,在快速意象回路(右半球)和稳定的言语回路(左半球)之间存在动态转移。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e618/3440479/f79642978f4c/pi-9-283-g001.jpg

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