University of Southern California, Los Angeles, CA.
Google Brain, Mountain View, California.
Hum Brain Mapp. 2017 Dec;38(12):6096-6106. doi: 10.1002/hbm.23814. Epub 2017 Sep 20.
Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances. However, while brain regions that represent lower-level semantic units, such as words and sentences, have been identified, questions remain about the neural representation of narrative comprehension, which involves inferring cumulative meaning. To address these questions, we exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning. Using a new technique in natural language processing, we calculated the distributed representations of these stories (capturing the meaning of the stories in high-dimensional semantic space), and demonstrate that using these representations we can identify the specific story a participant was reading from the neural data. Notably, this was possible even when the distributed representations were calculated using stories in a different language than the participant was reading. Our results reveal that identification relied on a collection of brain regions most prominently located in the default mode network. These results demonstrate that neuro-semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages. Hum Brain Mapp 38:6096-6106, 2017. © 2017 Wiley Periodicals, Inc.
从语义单元的共同词汇中汲取灵感，人类构建了叙事，其意义超越了其单个话语。然而，尽管已经确定了代表较低层次语义单元（如单词和句子）的大脑区域，但关于叙事理解的神经表示仍存在疑问，因为叙事理解涉及推断累积意义。为了解决这些问题，我们在 fMRI 扫描过程中让英语、汉语和波斯语母语者接触母语翻译的相同故事。我们使用自然语言处理中的一种新技术来计算这些故事的分布式表示（在高维语义空间中捕捉故事的含义），并证明我们可以使用这些表示来从神经数据中识别参与者正在阅读的特定故事。值得注意的是，即使使用参与者正在阅读的不同语言的故事来计算分布式表示，这也是可能的。我们的结果表明，识别依赖于一组大脑区域，这些区域最突出地位于默认模式网络中。这些结果表明，叙事的神经语义编码发生在高于单个语义单元的水平，并且这种编码在个体和语言之间都是系统的。人类大脑映射 38:6096-6106, 2017. © 2017 Wiley Periodicals, Inc.
