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International Conference on Brain Informatics

BI 2017: Brain Informatics pp 95–106Cite as

Stronger Activation in Widely Distributed Regions May not Compensate for an Ineffectively Connected Neural Network When Reading a Second Language

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10654))

Abstract

Even though how bilinguals process the second language (L2) still remain disputable, it is agreed that L2 processing involve more brain areas and activate common regions more strongly. It interested us to probe why heavier manipulation of cortical regions did not guarantee a high language proficiency. Since the responses of individual brain regions were inadequate to explain how the brain enabled behavior, we sought to explore this question at the neural network prospect via the Psychophysiological interaction (PPI) analysis. We found that Chinese English bilinguals adopted the assimilation/accommodation strategy to read L2, and English activated common brain areas more strongly. However, the whole brain voxel-wise analysis of effective connectivity showed that these brain areas formed a less synchronized network, which may indicate an ineffective neural network of L2. Our findings provided a possible explanation why the proficiency level of L2 was always lower than L1, and suggested that future fMRI studies may better explore language issues by depicting functional connectivity efficacy.

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (31400962, 81571752, 81371630), China Postdoctoral Science Foundation Funded Project (2015M582400), the Fundamental Research Funds for the Central Universities (RW150401), Shenzhen Peacock Plan (KQTD2015033016104926), Shanxi Nova Program (2014KJXX-34), and the Shenzhen Science and Technology Program (JCYJ20160608173106220). There are no conflicts of interest.

Author information

Authors and Affiliations

  1. Department of Linguistics, Xidian University, Xi’an, 710071, China

    Hao Yan

  2. Center for Language and Brain, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China

    Hao Yan

  3. Department of Biomedical Engineering, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China

    Chuanzhu Sun, Shan Wang & Lijun Bai

Authors
  1. Hao Yan
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  2. Chuanzhu Sun
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  3. Shan Wang
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  4. Lijun Bai
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Corresponding author

Correspondence to Hao Yan .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Yi Zeng

  2. Beijing Normal University, Beijing, China

    Yong He

  3. KTH Royal Institute of Technology and Karolinska Institute, Stockholm, Sweden

    Jeanette Hellgren Kotaleski

  4. University of California, San Diego, San Diego, California, USA

    Maryann Martone

  5. Chinese Academy of Sciences, Beijing, China

    Bo Xu

  6. Allen Institute for Brain Science, Seattle, Washington, USA

    Hanchuan Peng

  7. Wuhan National Lab Optoelectronics, Huazhong University of Science and Technology, Wuhan, China

    Qingming Luo

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Yan, H., Sun, C., Wang, S., Bai, L. (2017). Stronger Activation in Widely Distributed Regions May not Compensate for an Ineffectively Connected Neural Network When Reading a Second Language. In: Zeng, Y., et al. Brain Informatics. BI 2017. Lecture Notes in Computer Science(), vol 10654. Springer, Cham. https://doi.org/10.1007/978-3-319-70772-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-70772-3_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70771-6

  • Online ISBN: 978-3-319-70772-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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