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Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics

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...

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Autores principales: Nakai, Tomoya, Sakai, Kuniyoshi L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224410/
https://www.ncbi.nlm.nih.gov/pubmed/25379713
http://dx.doi.org/10.1371/journal.pone.0111439
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author Nakai, Tomoya
Sakai, Kuniyoshi L.
author_facet Nakai, Tomoya
Sakai, Kuniyoshi L.
author_sort Nakai, Tomoya
collection PubMed
description 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.
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spelling pubmed-42244102014-11-18 Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics Nakai, Tomoya Sakai, Kuniyoshi L. PLoS One Research Article 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. Public Library of Science 2014-11-07 /pmc/articles/PMC4224410/ /pubmed/25379713 http://dx.doi.org/10.1371/journal.pone.0111439 Text en © 2014 Nakai, Sakai http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Nakai, Tomoya
Sakai, Kuniyoshi L.
Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title_full Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title_fullStr Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title_full_unstemmed Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title_short Neural Mechanisms Underlying the Computation of Hierarchical Tree Structures in Mathematics
title_sort neural mechanisms underlying the computation of hierarchical tree structures in mathematics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4224410/
https://www.ncbi.nlm.nih.gov/pubmed/25379713
http://dx.doi.org/10.1371/journal.pone.0111439
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