Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability
•We developed a connectomic atlas of language (LANG) grounded on a unique task-fMRI database (InLang).•InLang consists of 13 fMRI language tasks, addressing the need of task diversity.•We identified the crucial subnetworks of the language connectome (Nets) and their anatomo-functional correlates.•We...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Jg. 263; S. 119672 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Inc
01.11.2022
Elsevier Limited Elsevier |
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| ISSN: | 1053-8119, 1095-9572, 1095-9572 |
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| Abstract | •We developed a connectomic atlas of language (LANG) grounded on a unique task-fMRI database (InLang).•InLang consists of 13 fMRI language tasks, addressing the need of task diversity.•We identified the crucial subnetworks of the language connectome (Nets) and their anatomo-functional correlates.•We have shown the versatility of their connectivity as a function of language demand (flexibility).•We estimated how individual factors influence the language connectivity (variability).
Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions. |
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| AbstractList | Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions. •We developed a connectomic atlas of language (LANG) grounded on a unique task-fMRI database (InLang).•InLang consists of 13 fMRI language tasks, addressing the need of task diversity.•We identified the crucial subnetworks of the language connectome (Nets) and their anatomo-functional correlates.•We have shown the versatility of their connectivity as a function of language demand (flexibility).•We estimated how individual factors influence the language connectivity (variability). Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions. Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions. |
| ArticleNumber | 119672 |
| Author | Roger, E. Perrier, P. Rodrigues De Almeida, L. Baciu, M. Baraduc, P. Cousin, E. Schwartz, J.L. Vilain, A. Perrone-Bertolotti, M. Achard, S. Loevenbruck, H. Dohen, M. |
| Author_xml | – sequence: 1 givenname: E. orcidid: 0000-0003-1542-751X surname: Roger fullname: Roger, E. email: elise.roger@univ-grenoble-alpes.fr organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France – sequence: 2 givenname: L. surname: Rodrigues De Almeida fullname: Rodrigues De Almeida, L. organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France – sequence: 3 givenname: H. surname: Loevenbruck fullname: Loevenbruck, H. organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France – sequence: 4 givenname: M. surname: Perrone-Bertolotti fullname: Perrone-Bertolotti, M. organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France – sequence: 5 givenname: E. surname: Cousin fullname: Cousin, E. organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France – sequence: 6 givenname: J.L. surname: Schwartz fullname: Schwartz, J.L. organization: CNRS, GIPSA-Lab, Grenoble-INP, Université Grenoble Alpes, CNRS, Grenoble 38000, France – sequence: 7 givenname: P. surname: Perrier fullname: Perrier, P. organization: CNRS, GIPSA-Lab, Grenoble-INP, Université Grenoble Alpes, CNRS, Grenoble 38000, France – sequence: 8 givenname: M. surname: Dohen fullname: Dohen, M. organization: CNRS, GIPSA-Lab, Grenoble-INP, Université Grenoble Alpes, CNRS, Grenoble 38000, France – sequence: 9 givenname: A. surname: Vilain fullname: Vilain, A. organization: CNRS, GIPSA-Lab, Grenoble-INP, Université Grenoble Alpes, CNRS, Grenoble 38000, France – sequence: 10 givenname: P. surname: Baraduc fullname: Baraduc, P. organization: CNRS, GIPSA-Lab, Grenoble-INP, Université Grenoble Alpes, CNRS, Grenoble 38000, France – sequence: 11 givenname: S. surname: Achard fullname: Achard, S. organization: CNRS, Inria, Grenoble INP, LJK, Université Grenoble Alpes, Grenoble 38000, France – sequence: 12 givenname: M. surname: Baciu fullname: Baciu, M. organization: CNRS, LPNC, Université Grenoble Alpes, BSHM, Université Savoie Mont Blanc, UMR 5105, Cedex, Grenoble 38000, France |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36209795$$D View this record in MEDLINE/PubMed https://hal.univ-grenoble-alpes.fr/hal-03811050$$DView record in HAL |
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| CitedBy_id | crossref_primary_10_1002_hbm_26650 crossref_primary_10_1080_13854046_2023_2281708 crossref_primary_10_1093_braincomms_fcaf191 crossref_primary_10_1016_j_neurobiolaging_2024_09_013 crossref_primary_10_1038_s41467_023_39131_y crossref_primary_10_1162_IMAG_a_63 crossref_primary_10_1038_s42003_023_04733_1 crossref_primary_10_1044_2024_AJSLP_24_00201 crossref_primary_10_1007_s00429_024_02846_9 crossref_primary_10_3389_fnhum_2023_1283069 crossref_primary_10_1111_tops_12736 crossref_primary_10_1111_jnp_12406 crossref_primary_10_1007_s00429_025_02923_7 crossref_primary_10_1162_imag_a_00551 crossref_primary_10_1016_j_bandl_2025_105630 |
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| Copyright | 2022 Copyright © 2022. Published by Elsevier Inc. Copyright Elsevier Limited Nov 2022 Attribution |
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| DOI | 10.1016/j.neuroimage.2022.119672 |
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| Keywords | Functional connectivity fMRI Networks Connectome Language |
| Language | English |
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| Title | Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability |
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