Stimulus-independent neural coding of event semantics: Evidence from cross-sentence fMRI decoding

Stimulus-independent neural coding of event semantics: Evidence from cross-sentence fMRI decoding
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事件语义的刺激独立神经编码:来自跨句功能磁共振成像解码的证据

DOI:
10.1101/2020.10.06.327817
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2020
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Asyraff A
Asyraff A
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多变量神经影像学研究表明,大脑以一种容易概括各种刺激的格式来表示单词和对象概念。在这里,我们调查了这是否适用于用句子描述的简单事件的神经表征。参与者以不同的方式观看描述四个事件的句子。多变量分类器被训练成使用句子的子集来区分这四个事件,使我们能够测试对新句子的概括。我们发现,在额叶,颞叶和顶叶区域的左侧网络的神经模式歧视事件的方式,成功地概括了用于描述它们的句子的句法和词汇属性的变化。相比之下,解码的视觉领域是特定的,并未能概括到新的句子。在反向分析中,我们测试了句法和词汇结构的解码,独立于所描述的事件。显示这种编码的区域是有限的,并且在很大程度上落在规范语义网络之外。我们的研究结果表明,一个分布式神经网络代表的意义的事件句子的方式,是强大的变化,其结构和形式。他们认为,语义系统忽视刺激的表面属性,以代表其潜在的概念意义。
Multivariate neuroimaging studies indicate that the brain represents word and object concepts in a format that readily generalises across stimuli. Here we investigated whether this was true for neural representations of simple events described using sentences. Participants viewed sentences describing four events in different ways. Multivariate classifiers were trained to discriminate the four events using a subset of sentences, allowing us to test generalisation to novel sentences. We found that neural patterns in a left-lateralised network of frontal, temporal and parietal regions discriminated events in a way that generalised successfully over changes in the syntactic and lexical properties of the sentences used to describe them. In contrast, decoding in visual areas was sentence-specific and failed to generalise to novel sentences. In the reverse analysis, we tested for decoding of syntactic and lexical structure, independent of the event being described. Regions displaying this coding were limited and largely fell outside the canonical semantic network. Our results indicate that a distributed neural network represents the meaning of event sentences in a way that is robust to changes in their structure and form. They suggest that the semantic system disregards the surface properties of stimuli in order to represent their underlying conceptual significance.
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