<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cai, Jing</style></author><author><style face="normal" font="default" size="100%">Kfir, Yoav</style></author><author><style face="normal" font="default" size="100%">Jamali, Mohsen</style></author><author><style face="normal" font="default" size="100%">Huang, Hesen</style></author><author><style face="normal" font="default" size="100%">Kim, Young Joon</style></author><author><style face="normal" font="default" size="100%">Cash, Sydney S.</style></author><author><style face="normal" font="default" size="100%">Williams, Ziv M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Mapping the neuronal building blocks of human language with language models</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2026/06/17</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.nature.com/articles/s41586-026-10691-5</style></url></web-urls></urls><isbn><style face="normal" font="default" size="100%">0028-08361476-4687</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;meta charset=&quot;UTF-8&quot; /&gt;Humans can convey new and highly diverse information through language. This ability to form and combine words into elaborate phrases and sentences enables us to express inexhaustible meanings and is fundamental to human cognition&lt;sup&gt;&lt;a data-test=&quot;citation-ref&quot; data-track=&quot;click&quot; data-track-action=&quot;reference anchor&quot; data-track-label=&quot;link&quot; href=&quot;https://www.nature.com/articles/s41586-026-10691-5#ref-CR1&quot; id=&quot;ref-link-section-d366672833e459&quot; title=&quot;Brennan, J. R. Language and the Brain: A Slim Guide to Neurolinguistics (Oxford Univ. Press, 2022).&quot;&gt;1&lt;/a&gt;,&lt;a data-test=&quot;citation-ref&quot; data-track=&quot;click&quot; data-track-action=&quot;reference anchor&quot; data-track-label=&quot;link&quot; href=&quot;https://www.nature.com/articles/s41586-026-10691-5#ref-CR2&quot; id=&quot;ref-link-section-d366672833e459_1&quot; title=&quot;Cooper, W. &amp;amp; Paccia-Cooper, J. Syntax and Speech (Harvard Univ. Press, 1980).&quot;&gt;2&lt;/a&gt;,&lt;a data-test=&quot;citation-ref&quot; data-track=&quot;click&quot; data-track-action=&quot;reference anchor&quot; data-track-label=&quot;link&quot; href=&quot;https://www.nature.com/articles/s41586-026-10691-5#ref-CR3&quot; id=&quot;ref-link-section-d366672833e459_2&quot; title=&quot;Horrocks, G. Generative Grammar (Longman Linguistics Library, 1987).&quot;&gt;3&lt;/a&gt;,&lt;a data-test=&quot;citation-ref&quot; data-track=&quot;click&quot; data-track-action=&quot;reference anchor&quot; data-track-label=&quot;link&quot; href=&quot;https://www.nature.com/articles/s41586-026-10691-5#ref-CR4&quot; id=&quot;ref-link-section-d366672833e459_3&quot; title=&quot;Coopmans, C. W., Kaushik, K. &amp;amp; Martin, A. E. Hierarchical structure in language and action: a formal comparison. Psychol. Rev. 130, 935–952 (2023).&quot;&gt;4&lt;/a&gt;,&lt;a aria-label=&quot;Reference 5&quot; data-test=&quot;citation-ref&quot; data-track=&quot;click&quot; data-track-action=&quot;reference anchor&quot; data-track-label=&quot;link&quot; href=&quot;https://www.nature.com/articles/s41586-026-10691-5#ref-CR5&quot; id=&quot;ref-link-section-d366672833e462&quot; title=&quot;Nelson, M. J. et al. Neurophysiological dynamics of phrase-structure building during sentence processing. Proc. Natl Acad. Sci. USA 114, E3669–E3678 (2017).&quot;&gt;5&lt;/a&gt;&lt;/sup&gt;. However, understanding the microscopic&amp;nbsp;cellular building blocks and cortical landscape that precisely&amp;nbsp;underlie human language has remained a challenge. Here we used wide-scale single-neuronal recordings combined with natural language processing models to identify fine-grained linguistic representations across the human frontotemporal cortex during language production. We find that, whereas certain neurons represented the detailed grammatical relationships between words or their parts of speech, others tracked the sentences&amp;rsquo; higher-order syntactic structure, their phrase transitions and sequence. Collectively, these neurons reliably captured the words&amp;rsquo; syntactic and semantic properties but also dynamically incorporated their specific sentence contexts, therefore&amp;nbsp;enabling them to encode information combinatorially and at highly granular levels of detail. We show how these cell populations were locally organized and how their microscale representations differed from that of their wider field potential patterns. We also show how these neurons were distributed broadly across the frontotemporal cortex, but how their ability to encode linguistic information was left-lateralized and varied between&amp;nbsp;cortical regions. Together, these findings identify some of the most basic cellular building blocks by which linguistic information is encoded in humans and begin to define the cortical landscape of language at a combined micro (cellular), meso (local population) and macro (regional) scale.&lt;/p&gt;
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