Suppr超能文献

一种用于概念的多模式体验表示的分布式网络。

A Distributed Network for Multimodal Experiential Representation of Concepts.

机构信息

Departments of Neurology.

Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226.

出版信息

J Neurosci. 2022 Sep 14;42(37):7121-7130. doi: 10.1523/JNEUROSCI.1243-21.2022. Epub 2022 Aug 8.

Abstract

Neuroimaging, neuropsychological, and psychophysical evidence indicate that concept retrieval selectively engages specific sensory and motor brain systems involved in the acquisition of the retrieved concept. However, it remains unclear which supramodal cortical regions contribute to this process and what kind of information they represent. Here, we used representational similarity analysis of two large fMRI datasets with a searchlight approach to generate a detailed map of human brain regions where the semantic similarity structure across individual lexical concepts can be reliably detected. We hypothesized that heteromodal cortical areas typically associated with the default mode network encode multimodal experiential information about concepts, consistent with their proposed role as cortical integration hubs. In two studies involving different sets of concepts and different participants (both sexes), we found a distributed, bihemispheric network engaged in concept representation, composed of high-level association areas in the anterior, lateral, and ventral temporal lobe; inferior parietal lobule; posterior cingulate gyrus and precuneus; and medial, dorsal, ventrolateral, and orbital prefrontal cortex. In both studies, a multimodal model combining sensory, motor, affective, and other types of experiential information explained significant variance in the neural similarity structure observed in these regions that was not explained by unimodal experiential models or by distributional semantics (i.e., word2vec similarity). These results indicate that during concept retrieval, lexical concepts are represented across a vast expanse of high-level cortical regions, especially in the areas that make up the default mode network, and that these regions encode multimodal experiential information. Conceptual knowledge includes information acquired through various modalities of experience, such as visual, auditory, tactile, and emotional information. We investigated which brain regions encode mental representations that combine information from multiple modalities when participants think about the meaning of a word. We found that such representations are encoded across a widely distributed network of cortical areas in both hemispheres, including temporal, parietal, limbic, and prefrontal association areas. Several areas not traditionally associated with semantic cognition were also implicated. Our results indicate that the retrieval of conceptual knowledge during word comprehension relies on a much larger portion of the cerebral cortex than previously thought and that multimodal experiential information is represented throughout the entire network.

摘要

神经影像学、神经心理学和心理物理学证据表明,概念检索选择性地激活特定的感觉和运动脑系统,这些系统参与了所检索概念的获取。然而,目前尚不清楚哪些超模态皮质区域对此过程有贡献,以及它们代表什么样的信息。在这里,我们使用了两种大型 fMRI 数据集的代表性相似性分析,采用搜索灯方法,生成了一幅详细的人类大脑区域图谱,该图谱可以可靠地检测个体词汇概念之间的语义相似性结构。我们假设,与默认模式网络相关的异模态皮质区域通常编码关于概念的多模态经验信息,这与它们作为皮质整合枢纽的假设作用一致。在两项涉及不同概念集和不同参与者(男女)的研究中,我们发现了一个参与概念表示的分布式双侧半球网络,该网络由前、外侧和腹侧颞叶的高级联合区域;下顶叶;后扣带和楔前叶;以及内侧、背侧、腹侧外侧和眶额前皮质组成。在两项研究中,一个结合了感觉、运动、情感和其他类型经验信息的多模态模型解释了这些区域中观察到的神经相似性结构的显著变化,而这种变化不能用单模态经验模型或分布语义(即 word2vec 相似性)来解释。这些结果表明,在概念检索过程中,词汇概念在广泛的高级皮质区域中被表示,尤其是在构成默认模式网络的区域中,并且这些区域编码了多模态经验信息。概念知识包括通过视觉、听觉、触觉和情感等多种感觉模态获得的信息。我们研究了当参与者思考一个单词的含义时,哪些大脑区域编码了组合来自多个模态的信息的心理表象。我们发现,这种表象是在两个半球中广泛分布的皮质区域网络中被编码的,包括颞叶、顶叶、边缘叶和前额叶联合区域。一些传统上与语义认知无关的区域也被牵连进来。我们的结果表明,在单词理解过程中概念知识的检索依赖于比以前想象的更大的一部分大脑皮层,并且整个网络都代表了多模态经验信息。

相似文献

1
A Distributed Network for Multimodal Experiential Representation of Concepts.一种用于概念的多模式体验表示的分布式网络。
J Neurosci. 2022 Sep 14;42(37):7121-7130. doi: 10.1523/JNEUROSCI.1243-21.2022. Epub 2022 Aug 8.
8
Modality-independent encoding of individual concepts in the left parietal cortex.左顶叶皮层中个体概念的模态无关编码。
Neuropsychologia. 2017 Oct;105:39-49. doi: 10.1016/j.neuropsychologia.2017.05.001. Epub 2017 May 3.
10
An Integrated Neural Decoder of Linguistic and Experiential Meaning.语言和体验意义的综合神经解码器。
J Neurosci. 2019 Nov 6;39(45):8969-8987. doi: 10.1523/JNEUROSCI.2575-18.2019. Epub 2019 Sep 30.

引用本文的文献

9
Decomposing unaccusativity: a statistical modelling approach.分解非宾格性:一种统计建模方法。
Lang Cogn Neurosci. 2024;39(9):1189-1211. doi: 10.1080/23273798.2024.2368119. Epub 2024 Jun 25.

本文引用的文献

2
Multiple dimensions underlying the functional organization of the language network.语言网络功能组织的多个维度。
Neuroimage. 2021 Nov 1;241:118444. doi: 10.1016/j.neuroimage.2021.118444. Epub 2021 Jul 31.
6
An Integrated Neural Decoder of Linguistic and Experiential Meaning.语言和体验意义的综合神经解码器。
J Neurosci. 2019 Nov 6;39(45):8969-8987. doi: 10.1523/JNEUROSCI.2575-18.2019. Epub 2019 Sep 30.
7
fMRIPrep: a robust preprocessing pipeline for functional MRI.fMRIPrep:用于功能磁共振成像的强大预处理流水线。
Nat Methods. 2019 Jan;16(1):111-116. doi: 10.1038/s41592-018-0235-4. Epub 2018 Dec 10.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验