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Li M, Wang Z, Yu X, Zhou X. Single-trial interindividual correlation shows semantic and visuospatial networks are fundamental for advanced mathematical learning. Eur J Neurosci 2024. [PMID: 39138595 DOI: 10.1111/ejn.16494] [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: 02/28/2024] [Revised: 07/06/2024] [Accepted: 07/22/2024] [Indexed: 08/15/2024]
Abstract
Mathematical learning and ability are crucial for individual and national economic and technological development, but the neural mechanisms underlying advanced mathematical learning remain unclear. The current study used functional magnetic resonance imaging (fMRI) to investigate how brain networks were involved in advanced mathematical learning and transfer. We recorded fMRI data from 24 undergraduate students as they learned the advanced mathematical concept of a commutative mathematical group. After learning, participants were required to complete learning and transfer behavioural tests. Results of single-trial interindividual brain-behaviour correlation analysis found that brain activity in the semantic and visuospatial networks, and the functional connectivity within the semantic network during advanced mathematical learning were positively correlated with learning and transfer effects. Additionally, the functional connectivity between the semantic and visuospatial networks was negatively correlated with the learning and transfer effects. These findings suggest that advanced mathematical learning relies on both semantic and visuospatial networks.
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Affiliation(s)
- Mengyi Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, China
- Faculty of Psychology, Tianjin Normal University, Tianjin, China
| | - Zilong Wang
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, China
- Department of Education, Ocean University of China, Qingdao, Shandong, China
- Information Technology Department, Qingdao Vocational and Technical College of Hotel Management, Qingdao, Shandong, China
| | - Xiaodan Yu
- Department of Education, Ocean University of China, Qingdao, Shandong, China
| | - Xinlin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, China
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Cui J, Wang L, Li D, Zhou X. Verbalized arithmetic principles correlate with mathematics achievement. BRITISH JOURNAL OF EDUCATIONAL PSYCHOLOGY 2024; 94:41-57. [PMID: 37574834 DOI: 10.1111/bjep.12632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 07/14/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND When mathematical knowledge is expressed in general language, it is called verbalized mathematics. Previous studies on verbalized mathematics typically paid attention to mathematical vocabulary or educational practice. However, these studies did not exclude the role of symbolic mathematics ability, and almost no research has focused on verbalized mathematical principles. AIMS This study is aimed to investigate whether verbalized mathematics ability independently predicts mathematics achievement. The current study hypothesized that verbalized mathematics ability supports mathematics achievement independent of general language, related cognitive abilities and even symbolic mathematical ability. SAMPLE A sample of 241 undergraduates (136 males, 105 females, mean age = 21.95, SD = 2.38) in Beijing, China. METHODS A total of 12 tests were used, including a verbalized arithmetic principle test, a mathematics achievement test, and tests on general language (sentence completion test), symbolic mathematical ability (including symbolic arithmetic principles test, simple arithmetic computation and complex arithmetic computation), approximate number sense ability (numerosity comparison test) and several related cognitive covariates (including the non-verbal matrix reasoning, the syllogism reasoning, mental rotation, figure matching and choice reaction time). RESULTS Results showed that the processing of verbalized arithmetic principles displayed a significant role in mathematics achievement after controlling for general language, related cognitive abilities, approximate number sense ability and symbolic mathematics ability. CONCLUSIONS The results suggest that verbalized mathematics ability was an independent predictor and provided empirical evidence supporting the verbalized mathematics role on achievement as an independent component in three-component mathematics model.
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Affiliation(s)
- Jiaxin Cui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Advanced Innovation Center for Future Education, Beijing Normal University, Beijing, China
- College of Education, Hebei Normal University, Shijiazhuang, China
| | - Li Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Advanced Innovation Center for Future Education, Beijing Normal University, Beijing, China
- Faculty of Education, Beijing Normal University, Beijing, China
| | - Dawei Li
- Center for Cognitive Neuroscience, Duke University, Durham, North Carolina, USA
| | - Xinlin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Advanced Innovation Center for Future Education, Beijing Normal University, Beijing, China
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Poikonen H, Tobler S, Trninić D, Formaz C, Gashaj V, Kapur M. Math on cortex-enhanced delta phase synchrony in math experts during long and complex math demonstrations. Cereb Cortex 2024; 34:bhae025. [PMID: 38365270 DOI: 10.1093/cercor/bhae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/18/2024] Open
Abstract
Neural oscillations are important for working memory and reasoning and they are modulated during cognitively challenging tasks, like mathematics. Previous work has examined local cortical synchrony on theta (4-8 Hz) and alpha (8-13 Hz) bands over frontal and parietal electrodes during short mathematical tasks when sitting. However, it is unknown whether processing of long and complex math stimuli evokes inter-regional functional connectivity. We recorded cortical activity with EEG while math experts and novices watched long (13-68 seconds) and complex (bachelor-level) math demonstrations when sitting and standing. Fronto-parietal connectivity over the left hemisphere was stronger in math experts than novices reflected by enhanced delta (0.5-4 Hz) phase synchrony in experts. Processing of complex math tasks when standing extended the difference to right hemisphere, suggesting that other cognitive processes, such as maintenance of body balance when standing, may interfere with novice's internal concentration required during complex math tasks more than in experts. There were no groups differences in phase synchrony over theta or alpha frequencies. These results suggest that low-frequency oscillations modulate inter-regional connectivity during long and complex mathematical cognition and demonstrate one way in which the brain functions of math experts differ from those of novices: through enhanced fronto-parietal functional connectivity.
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Affiliation(s)
- Hanna Poikonen
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
- Centre of Excellence in Music, Mind, Body and Brain, Faculty of Educational Sciences, University of Helsinki, Helsinki 00014, Finland
| | - Samuel Tobler
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
| | - Dragan Trninić
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
| | - Cléa Formaz
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
| | - Venera Gashaj
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
- Department of Psychology, University of Tuebingen, Tuebingen 72076, Germany
| | - Manu Kapur
- Professorship for Learning Sciences and Higher Education, Department of Humanities, Social and Political Sciences, Swiss Federal Institute of Technology (ETH) Zurich, Zurich 8092, Switzerland
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Li M, Cheng D, Chen C, Zhou X. High-definition transcranial direct current stimulation (HD-tDCS) of the left middle temporal gyrus (LMTG) improves mathematical reasoning. Brain Topogr 2023; 36:890-900. [PMID: 37540333 DOI: 10.1007/s10548-023-00996-3] [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: 03/06/2023] [Accepted: 07/24/2023] [Indexed: 08/05/2023]
Abstract
The role of the visuospatial network in mathematical processing has been established, but the role of the semantic neural network in mathematical processing is still poorly understood. The current study used high-definition transcranial direct current stimulation (HD-tDCS) to examine whether the semantic network supports mathematical processing. Using a single-blind, randomized, sham-controlled experimental design, 48 participants were randomly assigned to receive either anodal or sham HD-tDCS on the left middle temporal gyrus (LMTG), a core region of the semantic network. A number series completion task was used to measure mathematical reasoning and an arithmetical computation task was used as a control condition. Both tasks were administered before and after the 20 min HD-tDCS. The results showed that anodal HD-tDCS on the LMTG enhanced performance on the number series completion task, but not on the arithmetical computation task. Trial-level analysis further showed greater improvement at the more difficult problems of the number series completion task. These results demonstrate that the semantic network plays an important role in mathematical processing.
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Affiliation(s)
- Mengyi Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, 100875, China
| | - Dazhi Cheng
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, 100875, China
- School of Psychology, Capital Normal University, Beijing, 100073, China
| | - Chuansheng Chen
- Department of Psychological Science, University of California, Irvine, CA, 92697-7085, USA
| | - Xinlin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Research association for brain and mathematical learning, Beijing Normal University, Beijing, 100875, China.
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Chen J, Qian P, Gao X, Li B, Zhang Y, Zhang D. Inter-brain coupling reflects disciplinary differences in real-world classroom learning. NPJ SCIENCE OF LEARNING 2023; 8:11. [PMID: 37130852 PMCID: PMC10154329 DOI: 10.1038/s41539-023-00162-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 04/06/2023] [Indexed: 05/04/2023]
Abstract
The classroom is the primary site for learning. A vital feature of classroom learning is the division of educational content into various disciplines. While disciplinary differences could substantially influence the learning process toward success, little is known about the neural mechanism underlying successful disciplinary learning. In the present study, wearable EEG devices were used to record a group of high school students during their classes of a soft (Chinese) and a hard (Math) discipline throughout one semester. Inter-brain coupling analysis was conducted to characterize students' classroom learning process. The students with higher scores in the Math final exam were found to have stronger inter-brain couplings to the class (i.e., all the other classmates), whereas the students with higher scores in Chinese were found to have stronger inter-brain couplings to the top students in the class. These differences in inter-brain couplings were also reflected in distinct dominant frequencies for the two disciplines. Our results illustrate disciplinary differences in the classroom learning from an inter-brain perspective, suggesting that an individual's inter-brain coupling to the class and to the top students could serve as potential neural correlates for successful learning in hard and soft disciplines correspondingly.
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Affiliation(s)
- Jingjing Chen
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China
| | - Penghao Qian
- College of Information and Electrical Engineering, China Agricultural University, Beijing, China
| | | | - Baosong Li
- Beijing No. 19 High School, Beijing, China
- College of Education, Zhejiang Normal University, Jinhua, China
| | - Yu Zhang
- Institution of Education, Tsinghua University, Beijing, China.
| | - Dan Zhang
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing, China.
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China.
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Li M, Lu Y, Zhou X. The involvement of the semantic neural network in rule identification of mathematical processing. Cortex 2023; 164:11-20. [PMID: 37148824 DOI: 10.1016/j.cortex.2023.03.010] [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: 04/28/2022] [Revised: 02/15/2023] [Accepted: 03/30/2023] [Indexed: 05/08/2023]
Abstract
The role of the visuospatial network in mathematical processing has been established, but the involvement of the semantic network in mathematical processing is still poorly understood. The current study utilized a number series completion paradigm with the event-related potential (ERP) technique to examine whether the semantic network supports mathematical processing and to find the corresponding spatiotemporal neural marker. In total, 32 right-handed undergraduate students were recruited and asked to complete the number series completion as well as the arithmetical computation task in which numbers were presented in sequence. The event-related potential and multi-voxel pattern analysis showed that the rule identification process involves more semantic processing when compared with the arithmetical computation processes, and it elicited higher amplitudes for the late negative component (LNC) in left frontal and temporal lobes. These results demonstrated that the semantic network supports the rule identification in mathematical processing, with the LNC acting as the neural marker.
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Affiliation(s)
- Mengyi Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Research Association for Brain and Mathematical Learning, Beijing Normal University, Beijing, China
| | - Yujie Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Research Association for Brain and Mathematical Learning, Beijing Normal University, Beijing, China
| | - Xinlin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Research Association for Brain and Mathematical Learning, Beijing Normal University, Beijing, China.
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Associations between digital media use and brain surface structural measures in preschool-aged children. Sci Rep 2022; 12:19095. [PMID: 36351968 PMCID: PMC9645312 DOI: 10.1038/s41598-022-20922-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 09/20/2022] [Indexed: 11/10/2022] Open
Abstract
The American Academy of Pediatrics recommends limits on digital media use ("screen time"), citing cognitive-behavioral risks. Media use in early childhood is ubiquitous, though few imaging-based studies have been conducted to quantify impacts on brain development. Cortical morphology changes dynamically from infancy through adulthood and is associated with cognitive-behavioral abilities. The current study involved 52 children who completed MRI and cognitive testing at a single visit. The MRI protocol included a high-resolution T1-weighted anatomical scan. The child's parent completed the ScreenQ composite measure of media use. MRI measures included cortical thickness (CT) and sulcal depth (SD) across the cerebrum. ScreenQ was applied as a predictor of CT and SD first in whole-brain regression analyses and then for regions of interest (ROIs) identified in a prior study of screen time involving adolescents, controlling for sex, age and maternal education. Higher ScreenQ scores were correlated with lower CT in right-lateralized occipital, parietal, temporal and fusiform areas, and also lower SD in right-lateralized inferior temporal/fusiform areas, with substantially greater statistical significance in ROI-based analyses. These areas support primary visual and higher-order processing and align with prior findings in adolescents. While differences in visual areas likely reflect maturation, those in higher-order areas may suggest under-development, though further studies are needed.
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Li L, Shi J, Zhong B. Good in arts, good in computer? Rural students’ computer skills are bolstered by arts and science literacies. COMPUTERS IN HUMAN BEHAVIOR 2022. [DOI: 10.1016/j.chb.2022.107573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Affiliation(s)
- Xinlin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University Beijing China
- Advanced Innovation Center for Future Education Beijing Normal University Beijing China
- Research Center for Brain and Mathematics Learning Beijing Normal University Beijing China
| | - Jieying Zeng
- Business School Beijing Wuzi University Beijing China
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