Do Jongrok, James Oliver, Kim Yee-Joon
Center for Cognition and Sociality, Institute for Basic Science, Daejeon 34126, Republic of Korea.
iScience. 2024 Jun 4;27(7):110173. doi: 10.1016/j.isci.2024.110173. eCollection 2024 Jul 19.
Recent human brain imaging studies have identified widely distributed cortical areas that represent information about the meaning of language. Yet, the dynamic nature of widespread neural activity as a correlate of the semantic information processing remains poorly explored. Our state space analysis of electroencephalograms (EEGs) recorded during semantic match-to-category task show that depending on the semantic category and decision path chosen by participants, whole-brain delta-band dynamics follow distinct trajectories that are correlated with participants' response time on a trial-by-trial basis. Especially, the proximity of the neural trajectory to category decision-specific region in the state space was predictive of participants' decision-making reaction times. We also found that posterolateral regions primarily encoded word categories while postero-central regions encoded category decisions. Our results demonstrate the role of neural dynamics embedded in the evolving multivariate delta-band activity patterns in processing the semantic relatedness of words and the semantic category-based decision-making.
最近的人类脑成像研究已经确定了广泛分布的皮层区域，这些区域代表有关语言意义的信息。然而，作为语义信息处理相关的广泛神经活动的动态性质仍未得到充分探索。我们对在语义匹配类别任务中记录的脑电图（EEG）进行的状态空间分析表明，根据参与者选择的语义类别和决策路径，全脑δ波段动态遵循不同的轨迹，这些轨迹在逐次试验的基础上与参与者的反应时间相关。特别是，神经轨迹在状态空间中与类别决策特定区域的接近程度可预测参与者的决策反应时间。我们还发现，后外侧区域主要编码单词类别，而后中央区域编码类别决策。我们的结果证明了嵌入在不断演变的多变量δ波段活动模式中的神经动力学在处理单词的语义相关性和基于语义类别的决策中的作用。
