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Visual Mental Imagery Activates Topographically Organized Visual Cortex: PET Investigations.视觉心理意象激活具有拓扑组织的视觉皮层:PET 研究。
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Segregating Semantic from Phonological Processes during Reading.阅读过程中语义与语音加工的分离。
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A linear structural equation model for covert verb generation based on independent component analysis of FMRI data from children and adolescents.基于 fMRI 数据的儿童和青少年隐蔽动词生成的线性结构方程模型。
Front Syst Neurosci. 2011 Jun 1;5:29. doi: 10.3389/fnsys.2011.00029. eCollection 2011.
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Cortical and subcortical contributions to absence seizure onset examined with EEG/fMRI.皮层和皮层下对癫痫发作起始的影响的 EEG/fMRI 研究。
Epilepsy Behav. 2010 Aug;18(4):404-13. doi: 10.1016/j.yebeh.2010.05.009. Epub 2010 Jun 26.
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Neural representation of abstract and concrete concepts: a meta-analysis of neuroimaging studies.抽象和具体概念的神经表示:神经影像学研究的元分析。
Hum Brain Mapp. 2010 Oct;31(10):1459-68. doi: 10.1002/hbm.20950.
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A group independent component analysis of covert verb generation in children: a functional magnetic resonance imaging study.儿童内隐动词生成的群组独立成分分析:一项功能磁共振成像研究。
Neuroimage. 2010 May 15;51(1):472-87. doi: 10.1016/j.neuroimage.2009.12.108. Epub 2010 Jan 4.
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Sensory-motor brain network connectivity for speech comprehension.言语理解的感觉运动脑网络连通性。
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Independent component analysis for brain fMRI does not select for independence.用于脑功能磁共振成像的独立成分分析并未选择独立性。
Proc Natl Acad Sci U S A. 2009 Jun 30;106(26):10415-22. doi: 10.1073/pnas.0903525106. Epub 2009 Jun 25.
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Neural network of speech monitoring overlaps with overt speech production and comprehension networks: a sequential spatial and temporal ICA study.语音监测神经网络与公开言语产生及理解神经网络重叠:一项序列时空独立成分分析研究。
Neuroimage. 2009 Oct 1;47(4):1982-91. doi: 10.1016/j.neuroimage.2009.05.057. Epub 2009 May 27.
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Multiple neural networks supporting a semantic task: an fMRI study using independent component analysis.支持语义任务的多个神经网络:一项使用独立成分分析的功能磁共振成像研究
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采用功能磁共振成像和独立成分分析研究语义关联。

Semantic association investigated with functional MRI and independent component analysis.

机构信息

Department of Neurology, University of Cincinnati, Cincinnati, OH 45267-0525, USA.

出版信息

Epilepsy Behav. 2011 Apr;20(4):613-22. doi: 10.1016/j.yebeh.2010.11.010. Epub 2011 Feb 4.

DOI:10.1016/j.yebeh.2010.11.010
PMID:21296027
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3078943/
Abstract

Semantic association, an essential element of human language, enables discourse and inference. Neuroimaging studies have revealed localization and lateralization of semantic circuitry, making substantial contributions to cognitive neuroscience. However, because of methodological limitations, these investigations have only identified individual functional components rather than capturing the behavior of the entire network. To overcome these limitations, we have implemented group independent component analysis (ICA) to investigate the cognitive modules used by healthy adults performing the fMRI semantic decision task. When compared with the results of a standard general linear modeling (GLM) analysis, ICA detected several additional brain regions subserving semantic decision. Eight task-related group ICA maps were identified, including left inferior frontal gyrus (BA44/45), middle posterior temporal gyrus (BA39/22), angular gyrus/inferior parietal lobule (BA39/40), posterior cingulate (BA30), bilateral lingual gyrus (BA18/23), inferior frontal gyrus (L>R, BA47), hippocampus with parahippocampal gyrus (L>R, BA35/36), and anterior cingulate (BA32/24). Although most of the components were represented bilaterally, we found a single, highly left-lateralized component that included the inferior frontal gyrus and the medial and superior temporal gyri, the angular and supramarginal gyri, and the inferior parietal cortex. The presence of these spatially independent ICA components implies functional connectivity and can be equated with their modularity. These results are analyzed and presented in the framework of a biologically plausible theoretical model in preparation for similar analyses in patients with right- or left-hemispheric epilepsies.

摘要

语义联想是人类语言的基本要素,使我们能够进行话语和推理。神经影像学研究揭示了语义回路的定位和侧化,为认知神经科学做出了重要贡献。然而,由于方法学的限制,这些研究仅确定了单个的功能成分,而没有捕捉到整个网络的行为。为了克服这些限制,我们实施了组独立成分分析(ICA)来研究健康成年人执行 fMRI 语义决策任务时使用的认知模块。与标准的一般线性建模(GLM)分析结果相比,ICA 检测到了几个额外的支持语义决策的大脑区域。确定了 8 个与任务相关的组 ICA 图谱,包括左额下回(BA44/45)、中后颞叶(BA39/22)、角回/下顶叶(BA39/40)、后扣带回(BA30)、双侧舌回(BA18/23)、额下回(左>右,BA47)、海马体伴旁海马回(左>右,BA35/36)和前扣带回(BA32/24)。虽然大多数成分都是双侧代表的,但我们发现了一个高度左偏侧的单一成分,包括额下回、内侧和上颞叶、角回和缘上回,以及下顶叶。这些空间上独立的 ICA 成分的存在意味着功能连接,可以与它们的模块性等同。这些结果在一个生物上合理的理论模型框架内进行分析和呈现,为分析右侧或左侧癫痫患者的类似结果做好准备。