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Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics

机译:数学中分层树结构计算的神经机制

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摘要

Whether mathematical and linguistic processes share the same neural mechanisms has been a matter of controversy. By examining various sentence structures, we recently demonstrated that activations in the left inferior frontal gyrus (L. IFG) and left supramarginal gyrus (L. SMG) were modulated by the Degree of Merger (DoM), a measure for the complexity of tree structures. In the present study, we hypothesize that the DoM is also critical in mathematical calculations, and clarify whether the DoM in the hierarchical tree structures modulates activations in these regions. We tested an arithmetic task that involved linear and quadratic sequences with recursive computation. Using functional magnetic resonance imaging, we found significant activation in the L. IFG, L. SMG, bilateral intraparietal sulcus (IPS), and precuneus selectively among the tested conditions. We also confirmed that activations in the L. IFG and L. SMG were free from memory-related factors, and that activations in the bilateral IPS and precuneus were independent from other possible factors. Moreover, by fitting parametric models of eight factors, we found that the model of DoM in the hierarchical tree structures was the best to explain the modulation of activations in these five regions. Using dynamic causal modeling, we showed that the model with a modulatory effect for the connection from the L. IPS to the L. IFG, and with driving inputs into the L. IFG, was highly probable. The intrinsic, i.e., task-independent, connection from the L. IFG to the L. IPS, as well as that from the L. IPS to the R. IPS, would provide a feedforward signal, together with negative feedback connections. We indicate that mathematics and language share the network of the L. IFG and L. IPS/SMG for the computation of hierarchical tree structures, and that mathematics recruits the additional network of the L. IPS and R. IPS.
机译:数学和语言过程是否共享相同的神经机制一直存在争议。通过检查各种句子结构,我们最近证明,左下额回(L. IFG)和左上arg回(L. SMG)的激活受合并度(DoM)的调节,该程度用于衡量树结构的复杂性。在本研究中,我们假设DoM在数学计算中也很重要,并阐明了分层树结构中的DoM是否会调节这些区域中的激活。我们测试了涉及线性和二次序列的递归计算的算术任务。使用功能性磁共振成像,我们发现在测试条件下,L。IFG,L。SMG,双侧顶内沟(IPS)和早孕有明显的激活作用。我们还证实了L. IFG和L. SMG中的激活没有记忆相关因素,并且双侧IPS和前胎的激活与其他可能因素无关。此外,通过拟合八个因素的参数模型,我们发现分层树结构中的DoM模型是解释这五个区域中激活调制的最佳方法。使用动态因果模型,我们证明了从L. IPS到L. IFG的连接具有调制效果,并有驱动L. IFG的输入的模型很有可能。从L.IFG到L.IPS的固有(即与任务无关)连接以及从L.IPS到R.IPS的固有连接将提供前馈信号以及负反馈连接。我们指出,数学和语言共享L. IFG和L. IPS / SMG的网络,用于计算层次树结构,而数学则招募了L. IPS和R. IPS的其他网络。

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