计算机科学
稳健性(进化)
理解力
人工神经网络
人工智能
语言模型
计算
自然语言处理
生物
生物化学
算法
基因
程序设计语言
作者
Tamar I. Regev,Colton Casto,Eghbal A. Hosseini,Markus Adamek,Anthony L. Ritaccio,Jon T. Willie,Peter Brunner,Evelina Fedorenko
标识
DOI:10.1101/2022.12.30.522216
摘要
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. Leveraging the high spatiotemporal resolution of intracranial recordings, we examined responses to sentences and linguistically degraded conditions and discovered three response profiles that differ in their temporal dynamics. These profiles appear to reflect different temporal receptive windows (TRWs), with average TRWs of about 1, 4, and 6 words, as estimated with a simple one-parameter model. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multi-scale representations of linguistic input-a property that may be critical for the efficiency and robustness of language processing.
科研通智能强力驱动
Strongly Powered by AbleSci AI