Li Mengyi, Cheng Dazhi, Chen Chuansheng, Zhou Xinlin
State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
Research association for brain and mathematical learning, Beijing Normal University, Beijing, 100875, China.
Brain Topogr. 2023 Nov;36(6):890-900. doi: 10.1007/s10548-023-00996-3. Epub 2023 Aug 4.
The role of the visuospatial network in mathematical processing has been established, but the role of the semantic neural network in mathematical processing is still poorly understood. The current study used high-definition transcranial direct current stimulation (HD-tDCS) to examine whether the semantic network supports mathematical processing. Using a single-blind, randomized, sham-controlled experimental design, 48 participants were randomly assigned to receive either anodal or sham HD-tDCS on the left middle temporal gyrus (LMTG), a core region of the semantic network. A number series completion task was used to measure mathematical reasoning and an arithmetical computation task was used as a control condition. Both tasks were administered before and after the 20 min HD-tDCS. The results showed that anodal HD-tDCS on the LMTG enhanced performance on the number series completion task, but not on the arithmetical computation task. Trial-level analysis further showed greater improvement at the more difficult problems of the number series completion task. These results demonstrate that the semantic network plays an important role in mathematical processing.
视觉空间网络在数学处理中的作用已得到证实，但语义神经网络在数学处理中的作用仍知之甚少。当前研究使用高清经颅直流电刺激（HD-tDCS）来检验语义网络是否支持数学处理。采用单盲、随机、假刺激对照的实验设计，48名参与者被随机分配接受阳极或假HD-tDCS刺激，刺激部位为语义网络的核心区域——左侧颞中回（LMTG）。使用数字系列完成任务来测量数学推理能力，并使用算术计算任务作为对照条件。两项任务均在20分钟HD-tDCS刺激前后进行。结果显示，对LMTG进行阳极HD-tDCS刺激可提高数字系列完成任务的表现，但对算术计算任务无影响。试验水平分析进一步表明，在数字系列完成任务中较难的问题上有更大的改善。这些结果表明语义网络在数学处理中发挥着重要作用。
