Le Trang Thi, Luong Do Anh Quan, Joo Hyosung, Kim Dongseok, Woo Jihwan
Department of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Department of Biomedical Engineering, University of Ulsan, Ulsan, Republic of Korea.
Sci Rep. 2024 Dec 30;14(1):31918. doi: 10.1038/s41598-024-83417-0.
Semantic processing is an essential mechanism in human language comprehension and has profound implications for speech brain-computer interface technologies. Despite recent advances in brain imaging techniques and data analysis algorithms, the mechanisms underlying human brain semantic representations remain a topic of debate, specifically whether this occurs through the activation of selectively separated cortical regions or via a network of distributed and overlapping regions. This study investigates spatiotemporal neural representation during the perception of semantic words related to faces, numbers, and animals using electroencephalography. Source-level analysis focuses on contrasting neural responses to different semantic categories. Critical intervals used in the source contrast analysis are defined using the peak duration of global field power. Effective connectivity, determined through a causality analysis of brain regions activated for semantic processing, is explored. The findings reveal the necessity of a distributed network of regions for processing specific semantic categories and provide evidence suggesting the existence of a neural substrate for semantic representations.
语义处理是人类语言理解中的一种基本机制,对语音脑机接口技术具有深远影响。尽管脑成像技术和数据分析算法最近取得了进展,但人类大脑语义表征的潜在机制仍是一个争论的话题,特别是这是通过选择性分离的皮层区域的激活还是通过分布式和重叠区域的网络来实现的。本研究使用脑电图研究在感知与面孔、数字和动物相关的语义词期间的时空神经表征。源水平分析侧重于对比对不同语义类别的神经反应。源对比分析中使用的关键间隔是根据全局场功率的峰值持续时间定义的。通过对为语义处理而激活的脑区进行因果分析来确定有效连接性,并进行探索。研究结果揭示了处理特定语义类别的分布式区域网络的必要性,并提供了表明存在语义表征神经基础的证据。