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El Ouardi L, Yeou M, Faroqi-Shah Y. Neural correlates of pronoun processing: An activation likelihood estimation meta-analysis. BRAIN AND LANGUAGE 2023; 246:105347. [PMID: 37847932 PMCID: PMC11305457 DOI: 10.1016/j.bandl.2023.105347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/30/2023] [Accepted: 10/10/2023] [Indexed: 10/19/2023]
Abstract
Pronouns are unique linguistic devices that allow for the expression of referential relationships. Despite their communicative utility, the neural correlates of the operations involved in reference assignment and/or resolution, are not well-understood. The present study synthesized the neuroimaging literature on pronoun processing to test extant theories of pronoun comprehension. Following the PRISMA guidelines and thebest-practice recommendations for neuroimaging meta-analyses, a systematic literature search and record assessment were performed. As a result, 16 fMRI studies were included in the meta-analysis, and were coded in Scribe 3.6 for inclusion in the BrainMap database. The activation coordinates for the contrasts of interest were transformed into Talairach space and submitted to an Activation Likelihood Estimation (ALE) meta-analysis in GingerALE 3.0.1. The results indicated that pronoun processing had functional convergence in the left posterior middle and superior temporal gyri, potentially reflecting the retrieval, prediction and integration roles of these areas for pronoun processing.
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Affiliation(s)
- Loubna El Ouardi
- Department of Hearing and Speech Sciences, University of Maryland, College Park, Maryland, United States; Applied Language and Culture Studies Laboratory, Chouaib Doukkali University, El Jadida, Morocco.
| | - Mohamed Yeou
- Applied Language and Culture Studies Laboratory, Chouaib Doukkali University, El Jadida, Morocco
| | - Yasmeen Faroqi-Shah
- Department of Hearing and Speech Sciences, University of Maryland, College Park, Maryland, United States
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Wang J, Wang X, Zou J, Duan J, Shen Z, Xu N, Chen Y, Zhang J, He H, Bi Y, Ding N. Neural substrate underlying the learning of a passage with unfamiliar vocabulary and syntax. Cereb Cortex 2023; 33:10036-10046. [PMID: 37491998 DOI: 10.1093/cercor/bhad263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/27/2023] Open
Abstract
Speech comprehension is a complex process involving multiple stages, such as decoding of phonetic units, recognizing words, and understanding sentences and passages. In this study, we identify cortical networks beyond basic phonetic processing using a novel passage learning paradigm. Participants learn to comprehend a story composed of syllables of their native language, but containing unfamiliar vocabulary and syntax. Three learning methods are employed, each resulting in some degree of learning within a 12-min learning session. Functional magnetic resonance imaging results reveal that, when listening to the same story, the classic temporal-frontal language network is significantly enhanced by learning. Critically, activation of the left anterior and posterior temporal lobe correlates with the learning outcome that is assessed behaviorally through, e.g. word recognition and passage comprehension tests. This study demonstrates that a brief learning session is sufficient to induce neural plasticity in the left temporal lobe, which underlies the transformation from phonetic units to the units of meaning, such as words and sentences.
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Affiliation(s)
- Jing Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Xiaosha Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Jiajie Zou
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Jipeng Duan
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Zhuowen Shen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Nannan Xu
- School of Linguistic Sciences and Arts, Jiangsu Normal University, Xuzhou 221009, China
| | - Yan Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Jianfeng Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Hongjian He
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Nai Ding
- Key Laboratory for Biomedical Engineering of Ministry of Education, Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
- MOE Frontier Science Center for Brain Science & Brain-machine Integration, Zhejiang University, Hangzhou 310027, China
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Yang X, Lin N, Wang L. Situation updating during discourse comprehension recruits right posterior portion of the multiple-demand network. Hum Brain Mapp 2023; 44:2129-2141. [PMID: 36602295 PMCID: PMC10028651 DOI: 10.1002/hbm.26198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 12/01/2022] [Accepted: 12/17/2022] [Indexed: 01/06/2023] Open
Abstract
Discourse comprehension involves the construction of a mental representation of the situation model as well as a continuous update of this representation. This mental update is cognitively demanding and likely engages the multiple-demand network. However, there is little evidence for the involvement of the multiple-demand network during situation updating. In this study, we used fMRI to test whether situation updating based on the change of spatial location activated the multiple-demand network. In a discourse comprehension task, readers read two-sentence discourses in which the second sentence either continues or introduces a shift of the spatial location information presented in the first sentence. Compared to situation continuation, situation updating reliably activated the right superior parietal lobule. This area is a part of the multiple-demand network as defined by a digit N-back localizer task and locates within the dorsal attention network as defined in the previous study by Yeo et al. in 2011. Our results provide evidence for the reliable involvement of a specific area of the multiple-demand network in situation updating during high-level discourse processing.
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Affiliation(s)
- XiaoHong Yang
- Department of Psychology, Renmin University of China, Beijing, China
| | - Nan Lin
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Lin Wang
- Department of Psychology, Tufts University, Medford, Massachusetts, USA
- Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
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Ma X, Tao Y, Yang Y. Factors inducing complexities in musical embedded structure processing. Neuropsychologia 2022; 169:108153. [PMID: 35114217 DOI: 10.1016/j.neuropsychologia.2022.108153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 12/31/2021] [Accepted: 01/06/2022] [Indexed: 10/19/2022]
Abstract
The organizational structure of music is similar to that found in language, involving a large number of complicated hierarchical and embedded structures. The factors inducing complexities and difficulties in embedded structure processing are important subjects of inquiry in areas of cognitive neuroscience, such as music and language domains. Enlightened by relevant linguistic theories, this study investigated the influence of dependency lengthening and structural shift on musical embedded sequences processing. Results showed that final chords in sequences with long dependence elicited larger ERAN and N5 under near-key shift conditions, while elicited larger ERAN and LPC under far-key shift conditions, when compared to the sequences with short dependence; Further, the final chords in sequences with far-key shift elicited larger N5 under short dependence conditions, while elicited larger LPC under long dependence conditions when compared to the sequences with near-key shift. These results indicate that both dependency lengthening and structure shift could be the factors inducing complexities and difficulties in the processing of musical embedded structures, and there might be some common mechanisms underlying the processing of center-embedded structure across music and language domains.
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Affiliation(s)
- Xie Ma
- Faculty of Education, Yunnan Normal University, Kunming, China; Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Key Laboratory of Educational Informatization for Nationalities, Yunnan Normal University, Kunming, China
| | - Yun Tao
- Faculty of Education, Yunnan Normal University, Kunming, China; Key Laboratory of Educational Informatization for Nationalities, Yunnan Normal University, Kunming, China
| | - Yufang Yang
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
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Jin L, Li C, Zhang Y, Yuan T, Ying J, Zuo Z, Gui S. The Functional Reorganization of Language Network Modules in Glioma Patients: New Insights From Resting State fMRI Study. Front Oncol 2021; 11:617179. [PMID: 33718172 PMCID: PMC7953055 DOI: 10.3389/fonc.2021.617179] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/12/2021] [Indexed: 12/11/2022] Open
Abstract
Background Prior investigations of language functions have focused on the response profiles of particular brain regions. However, the specialized and static view of language processing does not explain numerous observations of functional recovery following brain surgery. To investigate the dynamic alterations of functional connectivity (FC) within language network (LN) in glioma patients, we explored a new flexible model based on the neuroscientific hypothesis of core-periphery organization in LN. Methods Group-level LN mapping was determined from 109 glioma patients and forty-two healthy controls (HCs) using independent component analysis (ICA). FC and mean network connectivity (mNC: l/rFCw, FCb, and FCg) were compared between patients and HCs. Correlations between mNC and tumor volume (TV) were calculated. Results We identified ten separate LN modules from ICA. Compared to HCs, glioma patients showed a significant reduction in language network functional connectivity (LNFC), with a distinct pattern modulated by tumor position. Left hemisphere gliomas had a broader impact on FC than right hemisphere gliomas, with more reduced edges away from tumor sites (p=0.011). mNC analysis revealed a significant reduction in all indicators of FC except for lFCw in right hemisphere gliomas. These alterations were associated with TV in a double correlative relationship depending on the tumor position across hemispheres. Conclusion Our findings emphasize the importance of considering the modulatory effects of core-periphery mechanisms from a network perspective. Preoperative evaluation of changes in LN caused by gliomas could provide the surgeon a reference to optimize resection while maintaining functional balance.
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Affiliation(s)
- Lu Jin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chuzhong Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yazhuo Zhang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Taoyang Yuan
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianyou Ying
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Songbai Gui
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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Coopmans CW, Nieuwland MS. Dissociating activation and integration of discourse referents: Evidence from ERPs and oscillations. Cortex 2020; 126:83-106. [DOI: 10.1016/j.cortex.2019.12.028] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/30/2019] [Accepted: 12/20/2019] [Indexed: 10/25/2022]
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How working memory capacity modulates the time course of semantic integration at sentence and discourse level. Neuropsychologia 2020; 140:107383. [PMID: 32057933 DOI: 10.1016/j.neuropsychologia.2020.107383] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 11/25/2019] [Accepted: 02/09/2020] [Indexed: 11/21/2022]
Abstract
During comprehension, language users not only immediately integrate information from local sentence context, but also information from global discourse context for full understanding. In the present study, we examined whether the time course of these integration processes is constrained by language users' working memory capacity. Sentence and discourse stimuli were constructed. For the sentence stimuli, each sentence contained a critical word that was either congruent or incongruent with its preceding sentence context. For the discourse stimuli, each discourse contained four sentences with a target word embedded at the final sentence and the target word was either congruent or incongruent with the information provided at the first sentence of the discourse. Participants of high and low working memory span were instructed to read for comprehension. Our results showed that while the high span readers showed the N400 and P600 effects to semantically incongruent words, the low span readers only showed the P600 effect. This pattern was found regardless of whether the incongruent words were placed at sentence or discourse context. These results suggest that the low span readers are relatively delayed than the high span ones at both sentence- and discourse-level semantic integration and indicate that working memory functions have greater influence than context scope on the time course of semantic integration.
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Yang X, Li H, Lin N, Zhang X, Wang Y, Zhang Y, Zhang Q, Zuo X, Yang Y. Uncovering cortical activations of discourse comprehension and their overlaps with common large-scale neural networks. Neuroimage 2019; 203:116200. [PMID: 31536803 DOI: 10.1016/j.neuroimage.2019.116200] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 09/11/2019] [Accepted: 09/15/2019] [Indexed: 02/04/2023] Open
Abstract
We conducted a meta-analysis of 78 task-based functional magnetic resonance imaging (fMRI) studies (1976 total participants) to reveal underlying brain activations and their overlap with large-scale neural networks in the brain during general discourse comprehension and its sub-processes. We found that discourse comprehension involved a neural system consisting of widely distributed brain regions that comprised not only the bilateral perisylvian language zones, but also regions in the superior and medial frontal cortex and the medial temporal lobe. Moreover, this neural system can be categorized into several sub-systems representing various sub-processes of discourse comprehension, with the left inferior frontal gyrus and middle temporal gyrus serving as core regions across all sub-processes. At a large-scale network level, we found that discourse comprehension relied most heavily on the default network, particularly on its dorsal medial subsystem. The pattern associated with large-scale network cooperation varied according to the respective sub-processes required. Our results reveal the functional dissociation within the discourse comprehension neural system and highlight the flexible involvements of large-scale networks.
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Affiliation(s)
- XiaoHong Yang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - HuiJie Li
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nan Lin
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - XiuPing Zhang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - YinShan Wang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ying Zhang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qian Zhang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - XiNian Zuo
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - YuFang Yang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China.
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