Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nat Hum Behav. 2024 Oct;8(10):1924-1942. doi: 10.1038/s41562-024-01944-2. Epub 2024 Aug 26.
Despite long knowing what brain areas support language comprehension, our knowledge of the neural computations that these frontal and temporal regions implement remains limited. One important unresolved question concerns functional differences among the neural populations that comprise the language network. Here we leveraged the high spatiotemporal resolution of human intracranial recordings (n = 22) to examine responses to sentences and linguistically degraded conditions. We discovered three response profiles that differ in their temporal dynamics. These profiles appear to reflect different temporal receptive windows, with average windows of about 1, 4 and 6 words, respectively. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multiscale representations of linguistic input-a property that may be critical for the efficiency and robustness of language processing.
尽管我们早就知道哪些大脑区域支持语言理解，但对于这些额叶和颞叶区域实施的神经计算，我们的了解仍然有限。一个重要的未解决的问题涉及组成语言网络的神经群体之间的功能差异。在这里，我们利用人类颅内记录的高时空分辨率（n=22）来检查对句子和语言退化条件的反应。我们发现了三种在时间动态上不同的反应模式。这些模式似乎反映了不同的时间接受窗口，平均窗口分别约为 1、4 和 6 个单词。表现出这些模式的神经群体在语言网络中交错排列，这表明所有语言区域都可以直接访问语言输入的不同、多尺度表示——这一特性可能对语言处理的效率和鲁棒性至关重要。
