Exécution de notre outil de synthèse sur un nouvel article
Vérifiez l’article ci-dessous, puis lancez sa synthèse.
Semantic encoding during language comprehension at single-cell resolution
Mohsen Jamali (Harvard University, Massachusetts General Hospital), Benjamin L. Grannan (Harvard University, Massachusetts General Hospital), Jing Cai (Harvard University, Massachusetts General Hospital), Arjun R. Khanna (Harvard University, Massachusetts General Hospital), William Muñoz (Harvard University, Massachusetts General Hospital), Irene Caprara (Harvard University, Massachusetts General Hospital), Angelique Christine Paulk (Harvard University, Massachusetts General Hospital), Sydney S. Cash (Harvard University, Massachusetts General Hospital), Evelina G. Fedorenko (McGovern Institute for Brain Research, Massachusetts Institute of Technology), Ziv M. Williams (Harvard University, Massachusetts General Hospital)
Résumé : Abstract From sequences of speech sounds 1,2 or letters 3 , humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing 4–12 , the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words’ meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.