Graph theoretical analysis of functional network for comprehension of sign language

Lanfang Liu, Xin Yan, Jin Liu, Mingrui Xia, Chunming Lu, Karen Emmorey, Mingyuan Chu, Guosheng Ding

Research output: Contribution to journalArticle

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Abstract

Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t(24) = 2.379, p = 0.026), small-worldness (t(24) = 2.6042, p = 0.016) and modularity (t(24) = 3.513, p = 0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action.

Original languageEnglish
Pages (from-to)55-66
Number of pages11
JournalBrain Research
Volume1671
Early online date6 Jul 2017
DOIs
Publication statusPublished - 15 Sep 2017

Fingerprint

Sign Language
Language
Activation Analysis
Temporal Lobe
Neuroimaging
Hearing
Magnetic Resonance Imaging
Observation

Keywords

  • left ventral pars opercularis
  • Graph theoretical analysis
  • Hub
  • sign language

Cite this

Graph theoretical analysis of functional network for comprehension of sign language. / Liu, Lanfang; Yan, Xin; Liu, Jin; Xia, Mingrui; Lu, Chunming; Emmorey, Karen; Chu, Mingyuan; Ding, Guosheng.

In: Brain Research, Vol. 1671, 15.09.2017, p. 55-66.

Research output: Contribution to journalArticle

Liu, Lanfang ; Yan, Xin ; Liu, Jin ; Xia, Mingrui ; Lu, Chunming ; Emmorey, Karen ; Chu, Mingyuan ; Ding, Guosheng. / Graph theoretical analysis of functional network for comprehension of sign language. In: Brain Research. 2017 ; Vol. 1671. pp. 55-66.
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abstract = "Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t(24) = 2.379, p = 0.026), small-worldness (t(24) = 2.6042, p = 0.016) and modularity (t(24) = 3.513, p = 0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action.",
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AB - Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t(24) = 2.379, p = 0.026), small-worldness (t(24) = 2.6042, p = 0.016) and modularity (t(24) = 3.513, p = 0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action.

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