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Herff SA, Bonetti L, Cecchetti G, Vuust P, Kringelbach ML, Rohrmeier MA. Hierarchical syntax model of music predicts theta power during music listening. Neuropsychologia 2024; 199:108905. [PMID: 38740179 DOI: 10.1016/j.neuropsychologia.2024.108905] [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: 05/17/2023] [Revised: 03/07/2024] [Accepted: 05/06/2024] [Indexed: 05/16/2024]
Abstract
Linguistic research showed that the depth of syntactic embedding is reflected in brain theta power. Here, we test whether this also extends to non-linguistic stimuli, specifically music. We used a hierarchical model of musical syntax to continuously quantify two types of expert-annotated harmonic dependencies throughout a piece of Western classical music: prolongation and preparation. Prolongations can roughly be understood as a musical analogue to linguistic coordination between constituents that share the same function (e.g., 'pizza' and 'pasta' in 'I ate pizza and pasta'). Preparation refers to the dependency between two harmonies whereby the first implies a resolution towards the second (e.g., dominant towards tonic; similar to how the adjective implies the presence of a noun in 'I like spicy … '). Source reconstructed MEG data of sixty-five participants listening to the musical piece was then analysed. We used Bayesian Mixed Effects models to predict theta envelope in the brain, using the number of open prolongation and preparation dependencies as predictors whilst controlling for audio envelope. We observed that prolongation and preparation both carry independent and distinguishable predictive value for theta band fluctuation in key linguistic areas such as the Angular, Superior Temporal, and Heschl's Gyri, or their right-lateralised homologues, with preparation showing additional predictive value for areas associated with the reward system and prediction. Musical expertise further mediated these effects in language-related brain areas. Results show that predictions of precisely formalised music-theoretical models are reflected in the brain activity of listeners which furthers our understanding of the perception and cognition of musical structure.
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Affiliation(s)
- Steffen A Herff
- Sydney Conservatorium of Music, University of Sydney, Sydney, Australia; The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, Australia; Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom; Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Gabriele Cecchetti
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, Australia; Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom; Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Martin A Rohrmeier
- Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Liu Y, Gao C, Wang P, Friederici AD, Zaccarella E, Chen L. Exploring the neurobiology of Merge at a basic level: insights from a novel artificial grammar paradigm. Front Psychol 2023; 14:1151518. [PMID: 37287773 PMCID: PMC10242141 DOI: 10.3389/fpsyg.2023.1151518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/09/2023] [Indexed: 06/09/2023] Open
Abstract
Introduction Human language allows us to generate an infinite number of linguistic expressions. It's proposed that this competence is based on a binary syntactic operation, Merge, combining two elements to form a new constituent. An increasing number of recent studies have shifted from complex syntactic structures to two-word constructions to investigate the neural representation of this operation at the most basic level. Methods This fMRI study aimed to develop a highly flexible artificial grammar paradigm for testing the neurobiology of human syntax at a basic level. During scanning, participants had to apply abstract syntactic rules to assess whether a given two-word artificial phrase could be further merged with a third word. To control for lower-level template-matching and working memory strategies, an additional non-mergeable word-list task was set up. Results Behavioral data indicated that participants complied with the experiment. Whole brain and region of interest (ROI) analyses were performed under the contrast of "structure > word-list." Whole brain analysis confirmed significant involvement of the posterior inferior frontal gyrus [pIFG, corresponding to Brodmann area (BA) 44]. Furthermore, both the signal intensity in Broca's area and the behavioral performance showed significant correlations with natural language performance in the same participants. ROI analysis within the language atlas and anatomically defined Broca's area revealed that only the pIFG was reliably activated. Discussion Taken together, these results support the notion that Broca's area, particularly BA 44, works as a combinatorial engine where words are merged together according to syntactic information. Furthermore, this study suggests that the present artificial grammar may serve as promising material for investigating the neurobiological basis of syntax, fostering future cross-species studies.
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Affiliation(s)
- Yang Liu
- Max Planck Partner Group, School of International Chinese Language Education, Beijing Normal University, Beijing, China
| | - Chenyang Gao
- School of Global Education and Development, University of Chinese Academy of Social Sciences, Beijing, China
| | - Peng Wang
- Method and Development Group (MEG and Cortical Networks), Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Psychology, University of Greifswald, Greifswald, Germany
- Institute of Psychology, University of Regensburg, Regensburg, Germany
| | - Angela D. Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Emiliano Zaccarella
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Luyao Chen
- Max Planck Partner Group, School of International Chinese Language Education, Beijing Normal University, Beijing, China
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Educational System Science, Beijing Normal University, Beijing, China
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Yuan B, Xie H, Wang Z, Xu Y, Zhang H, Liu J, Chen L, Li C, Tan S, Lin Z, Hu X, Gu T, Lu J, Liu D, Wu J. The domain-separation language network dynamics in resting state support its flexible functional segregation and integration during language and speech processing. Neuroimage 2023; 274:120132. [PMID: 37105337 DOI: 10.1016/j.neuroimage.2023.120132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/05/2023] [Accepted: 04/21/2023] [Indexed: 04/29/2023] Open
Abstract
Modern linguistic theories and network science propose that language and speech processing are organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct framewise time-varying language networks and k-means clustering was employed to investigate the temporal-reoccurring patterns. We found that the framewise language network dynamics in resting state were robustly clustered into four states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of speech perception and lexical-phonological processing, speech production, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and was regarded as a baseline state. Temporally, the first three states appeared exclusively in limited time bins (∼15%), and most of the time (> 55%), state 4 was dominant. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in resting state, which forms a dynamic "meta-network" framework to support flexible functional segregation and integration during language and speech processing.
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Affiliation(s)
- Binke Yuan
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.
| | - Hui Xie
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China; Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Zhihao Wang
- CNRS - Centre d'Economie de la Sorbonne, Panthéon-Sorbonne University, France
| | - Yangwen Xu
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento 38123, Italy
| | - Hanqing Zhang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Jiaxuan Liu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Lifeng Chen
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Chaoqun Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Shiyao Tan
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Zonghui Lin
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Xin Hu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Tianyi Gu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Junfeng Lu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Brain Function Laboratory, Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
| | - Dongqiang Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China; Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, PR China.
| | - Jinsong Wu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Brain Function Laboratory, Neurosurgical Institute of Fudan University, Shanghai, China; Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
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Kitazawa Y, Sonoda M, Sakakura K, Mitsuhashi T, Firestone E, Ueda R, Kambara T, Iwaki H, Luat AF, Marupudi NI, Sood S, Asano E. Intra- and inter-hemispheric network dynamics supporting object recognition and speech production. Neuroimage 2023; 270:119954. [PMID: 36828156 PMCID: PMC10112006 DOI: 10.1016/j.neuroimage.2023.119954] [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: 11/29/2022] [Revised: 02/14/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
We built normative brain atlases that animate millisecond-scale intra- and inter-hemispheric white matter-level connectivity dynamics supporting object recognition and speech production. We quantified electrocorticographic modulations during three naming tasks using event-related high-gamma activity from 1,114 nonepileptogenic intracranial electrodes (i.e., non-lesional areas unaffected by epileptiform discharges). Using this electrocorticography data, we visualized functional connectivity modulations defined as significant naming-related high-gamma modulations occurring simultaneously at two sites connected by direct white matter streamlines on diffusion-weighted imaging tractography. Immediately after stimulus onset, intra- and inter-hemispheric functional connectivity enhancements were confined mainly across modality-specific perceptual regions. During response preparation, left intra-hemispheric connectivity enhancements propagated in a posterior-to-anterior direction, involving the left precentral and prefrontal areas. After overt response onset, inter- and intra-hemispheric connectivity enhancements mainly encompassed precentral, postcentral, and superior-temporal (STG) gyri. We found task-specific connectivity enhancements during response preparation as follows. Picture naming enhanced activity along the left arcuate fasciculus between the inferior-temporal and precentral/posterior inferior-frontal (pIFG) gyri. Nonspeech environmental sound naming augmented functional connectivity via the left inferior longitudinal and fronto-occipital fasciculi between the medial-occipital and STG/pIFG. Auditory descriptive naming task enhanced usage of the left frontal U-fibers, involving the middle-frontal gyrus. Taken together, the commonly observed network enhancements include inter-hemispheric connectivity optimizing perceptual processing exerted in each hemisphere, left intra-hemispheric connectivity supporting semantic and lexical processing, and inter-hemispheric connectivity for symmetric oral movements during overt speech. Our atlases improve the currently available models of object recognition and speech production by adding neural dynamics via direct intra- and inter-hemispheric white matter tracts.
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Affiliation(s)
- Yu Kitazawa
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology and Stroke Medicine, Yokohama City University, Yokohama, 2360004, Japan
| | - Masaki Sonoda
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, Yokohama City University, Yokohama, 2360004, Japan
| | - Kazuki Sakakura
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, University of Tsukuba, Tsukuba, 3058575, Japan
| | - Takumi Mitsuhashi
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, Juntendo University, Tokyo, 1138421, Japan
| | - Ethan Firestone
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Physiology, Wayne State University, Detroit, 48201, USA
| | - Riyo Ueda
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Toshimune Kambara
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Psychology, Hiroshima University, Hiroshima, 7398524, Japan
| | - Hirotaka Iwaki
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Psychiatry, Hachinohe City Hospital, Hachinohe, 0318555, Japan
| | - Aimee F Luat
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Pediatrics, Central Michigan University, Mount Pleasant, 48858, USA
| | - Neena I Marupudi
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA.
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Schell M, Friederici AD, Zaccarella E. Neural classification maps for distinct word combinations in Broca's area. Front Hum Neurosci 2022; 16:930849. [PMID: 36405085 PMCID: PMC9671167 DOI: 10.3389/fnhum.2022.930849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 09/08/2022] [Indexed: 11/16/2023] Open
Abstract
Humans are equipped with the remarkable ability to comprehend an infinite number of utterances. Relations between grammatical categories restrict the way words combine into phrases and sentences. How the brain recognizes different word combinations remains largely unknown, although this is a necessary condition for combinatorial unboundedness in language. Here, we used functional magnetic resonance imaging and multivariate pattern analysis to explore whether distinct neural populations of a known language network hub-Broca's area-are specialized for recognizing distinct simple word combinations. The phrases consisted of a noun (flag) occurring either with a content word, an adjective (green flag), or with a function word, a determiner (that flag). The key result is that the distribution of neural populations classifying word combination in Broca's area seems sensitive to neuroanatomical subdivisions within this area, irrespective of task. The information patterns for adjective + noun were localized in its anterior part (BA45) whereas those for determiner + noun were localized in its posterior part (BA44). Our findings provide preliminary answers to the fundamental question of how lexical and grammatical category information interact during simple word combination, with the observation that Broca's area is sensitive to the recognition of categorical relationships during combinatory processing, based on different demands placed on syntactic and semantic information. This supports the hypothesis that the combinatorial power of language consists of some neural computation capturing phrasal differences when processing linguistic input.
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Affiliation(s)
- Marianne Schell
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Angela D. Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Emiliano Zaccarella
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Maran M, Numssen O, Hartwigsen G, Zaccarella E. Online neurostimulation of Broca's area does not interfere with syntactic predictions: A combined TMS-EEG approach to basic linguistic combination. Front Psychol 2022; 13:968836. [PMID: 36619118 PMCID: PMC9815778 DOI: 10.3389/fpsyg.2022.968836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/13/2022] [Indexed: 01/11/2023] Open
Abstract
Categorical predictions have been proposed as the key mechanism supporting the fast pace of syntactic composition in language. Accordingly, grammar-based expectations are formed-e.g., the determiner "a" triggers the prediction for a noun-and facilitate the analysis of incoming syntactic information, which is then checked against a single or few other word categories. Previous functional neuroimaging studies point towards Broca's area in the left inferior frontal gyrus (IFG) as one fundamental cortical region involved in categorical prediction during incremental language processing. Causal evidence for this hypothesis is however still missing. In this study, we combined Electroencephalography (EEG) and Transcranial Magnetic Stimulation (TMS) to test whether Broca's area is functionally relevant in predictive mechanisms for language. We transiently perturbed Broca's area during the first word in a two-word construction, while simultaneously measuring the Event-Related Potential (ERP) correlates of syntactic composition. We reasoned that if Broca's area is involved in predictive mechanisms for syntax, disruptive TMS during the first word would mitigate the difference in the ERP responses for predicted and unpredicted categories in basic two-word constructions. Contrary to this hypothesis, perturbation of Broca's area at the predictive stage did not affect the ERP correlates of basic composition. The correlation strength between the electrical field induced by TMS and the ERP responses further confirmed this pattern. We discuss the present results considering an alternative account of the role of Broca's area in syntactic composition, namely the bottom-up integration of words into constituents, and of compensatory mechanisms within the language predictive network.
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Affiliation(s)
- Matteo Maran
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany,International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany,*Correspondence: Matteo Maran,
| | - Ole Numssen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Emiliano Zaccarella
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Chen Y, Li L, Wang M, Wang R. Which Cognitive Factors Predict L2 Grammar Learning: Cognitive Control, Statistical Learning, Working Memory, or Attention? Front Psychol 2022; 13:943988. [PMID: 35910975 PMCID: PMC9333089 DOI: 10.3389/fpsyg.2022.943988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 06/23/2022] [Indexed: 11/13/2022] Open
Abstract
Individual variability of cognitive factors in second language (L2) grammar learning has long been the focus in the field of L2 acquisition. Most explored the issue by focusing on one factor like cognitive control, working memory, statistical learning (SL), or attention. Few investigated the topic by taking all these factors into consideration. However, different factors might interact and collaboratively contribute to the learning process. Examining the issue by considering all the factors might yield different results and facilitate our understanding of the mechanism subserving L2 grammar learning. Therefore, this study explored whether and how these factors predicted L2 grammar learning. A total of 34 college students completed a set of cognitive measurements on these cognitive factors, after which they were trained with artificial grammar over 5 consecutive days. Using multiple regression analysis and machine learning algorithms, we found that in the initial phase, SL was the more significant predictor, whereas in the intermediate and the last phases, cognitive control served as the more significant predictor. In other words, in the initial phase of L2 grammar learning, SL might play an important role, whereas in the intermediate and proficient phase, the updating component of cognitive control might play a more significant role. The findings provided empirical evidence to the neurocognitive account of grammar learning, shedding light on the mechanism of L2 grammar learning.
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Wu J, Zhang M, Dang Q, Chang Q, Yuan Q, Zhang Z, Ding G, Lu C, Guo T. Nonverbal cognitive control training increases the efficiency of frontal-subcortical collaboration for bilingual language control. Neuropsychologia 2022; 169:108204. [DOI: 10.1016/j.neuropsychologia.2022.108204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/21/2022] [Accepted: 03/03/2022] [Indexed: 10/18/2022]
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9
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Neural segregation in left inferior frontal gyrus of semantic processes at different levels of syntactic hierarchy. Neuropsychologia 2022; 171:108254. [DOI: 10.1016/j.neuropsychologia.2022.108254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 03/07/2022] [Accepted: 04/26/2022] [Indexed: 11/17/2022]
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10
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Chen L, Goucha T, Männel C, Friederici AD, Zaccarella E. Hierarchical syntactic processing is beyond mere associating: Functional magnetic resonance imaging evidence from a novel artificial grammar. Hum Brain Mapp 2021; 42:3253-3268. [PMID: 33822433 PMCID: PMC8193521 DOI: 10.1002/hbm.25432] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/02/2021] [Accepted: 03/24/2021] [Indexed: 01/31/2023] Open
Abstract
Grammar is central to any natural language. In the past decades, the artificial grammar of the AnBn type in which a pair of associated elements can be nested in the other pair was considered as a desirable model to mimic human language syntax without semantic interference. However, such a grammar relies on mere associating mechanisms, thus insufficient to reflect the hierarchical nature of human syntax. Here, we test how the brain imposes syntactic hierarchies according to the category relations on linearized sequences by designing a novel artificial “Hierarchical syntactic structure‐building Grammar” (HG), and compare this to the AnBn grammar as a “Nested associating Grammar” (NG) based on multilevel associations. Thirty‐six healthy German native speakers were randomly assigned to one of the two grammars. Both groups performed a grammaticality judgment task on auditorily presented word sequences generated by the corresponding grammar in the scanner after a successful explicit behavioral learning session. Compared to the NG group, we found that the HG group showed a (a) significantly higher involvement of Brodmann area (BA) 44 in Broca's area and the posterior superior temporal gyrus (pSTG); and (b) qualitatively distinct connectivity between the two regions. Thus, the present study demonstrates that the build‐up process of syntactic hierarchies on the basis of category relations critically relies on a distinctive left‐hemispheric syntactic network involving BA 44 and pSTG. This indicates that our novel artificial grammar can constitute a suitable experimental tool to investigate syntax‐specific processes in the human brain.
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Affiliation(s)
- Luyao Chen
- College of Chinese Language and Culture, Beijing Normal University, Beijing.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tomás Goucha
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Claudia Männel
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Department of Audiology and Phoniatrics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Emiliano Zaccarella
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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