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<p>Semantic control enables flexible retrieval and manipulation of stored knowledge. A left-lateralized network including the inferior frontal gyrus, posterior middle temporal gyrus, and dorsal medial prefrontal cortex has been implicated in this process. However, the functional differentiation within each region and their interactions remain unclear. Combining functional MRI and transcranial magnetic stimulation, we demonstrate that all three regions are causally involved in semantic control. Anterior subregions are engaged under hard semantic tasks, whereas posterior subregions respond more generally. Machine learning prediction analyses indicate that combined activity across these regions predicts semantic performance better than any region alone. Dynamic causal modeling further reveals that semantic control demands modulate both self-inhibition and interregional connectivity. Bayesian multiple regression shows that stimulation effects in frontal cortex are best explained by an interaction between local activation and electric field strength, while effects in temporal cortex are better predicted by task-dependent network connectivity. These findings highlight the distributed and interactive mechanisms underlying flexible knowledge retrieval.</p>

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Functional differentiation and interactions among inferior, medial frontal and posterior temporal cortex in semantic control

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月11日

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  • Jiaxuan Liu,
  • Xiuyi Wang,
  • Hanqing Zhang,
  • Junjie Yang,
  • Xiaowei Gao,
  • Zhongqi Li,
  • Yaling Wang,
  • Zhe Hu,
  • Junjing Li,
  • Wanjing Li,
  • Yien Huang,
  • Jiali Chen,
  • Lizhang Zeng,
  • Xuchu Weng,
  • Binke Yuan

摘要

Semantic control enables flexible retrieval and manipulation of stored knowledge. A left-lateralized network including the inferior frontal gyrus, posterior middle temporal gyrus, and dorsal medial prefrontal cortex has been implicated in this process. However, the functional differentiation within each region and their interactions remain unclear. Combining functional MRI and transcranial magnetic stimulation, we demonstrate that all three regions are causally involved in semantic control. Anterior subregions are engaged under hard semantic tasks, whereas posterior subregions respond more generally. Machine learning prediction analyses indicate that combined activity across these regions predicts semantic performance better than any region alone. Dynamic causal modeling further reveals that semantic control demands modulate both self-inhibition and interregional connectivity. Bayesian multiple regression shows that stimulation effects in frontal cortex are best explained by an interaction between local activation and electric field strength, while effects in temporal cortex are better predicted by task-dependent network connectivity. These findings highlight the distributed and interactive mechanisms underlying flexible knowledge retrieval.