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非词汇语言解码过程中振荡活动的时间动态:来自莫尔斯电码和脑磁图的证据。

Temporal dynamics of oscillatory activity during nonlexical language decoding: Evidence from Morse code and magnetoencephalography.

机构信息

Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Düsseldorf, Germany.

Neurological Center Mainkofen, Deggendorf, Germany.

出版信息

Hum Brain Mapp. 2023 Dec 1;44(17):6185-6197. doi: 10.1002/hbm.26505. Epub 2023 Oct 4.

Abstract

Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script-as for example in reading-is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine-grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time-frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event-related reduction in beta- and alpha-band power were found in left inferior frontal cortex and angular gyrus, respectively, while event-related theta-band power increase was found at frontal midline. These induced oscillations reflect working-memory encoding, long-term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time- and frequency-resolved manner.

摘要

理解编码语言,如书面文字或莫尔斯电码,需要非词汇和词汇处理组件以并行和交互的方式进行操作。解码书面文字——例如阅读——通常非常快,这使得对词汇和非词汇成分及其潜在神经机制的研究具有挑战性。在当前的研究中,我们旨在通过使用莫尔斯电码作为语言解码的模型来解决这个问题。莫尔斯电码的解码速度较慢,因此可以更好地、更精细地研究语言解码的词汇和非词汇成分。在当前的研究中,我们使用脑磁图(MEG)研究了莫尔斯电码非词汇解码的各种成分的影响。为此,我们在之前的研究中确定了与莫尔斯电码解码和单词理解显著相关的脑区中重建了低于 40Hz 的时频响应。在左侧额下回和角回中分别发现了与事件相关的β和α频带功率的减少,而在额中线处发现了与事件相关的θ频带功率的增加。这些诱导的振荡分别反映了工作记忆编码、长期记忆检索和高要求的认知控制。总之,通过使用莫尔斯电码和 MEG,我们能够以时间和频率分辨的方式识别语言解码的皮质网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d31a/10619365/e2f7b9907465/HBM-44-6185-g001.jpg

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