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      Affiliative bonding between teachers and students through interpersonal synchronisation in brain activity

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          Abstract

          Human beings organise socially. Theories have posited that interpersonal neural synchronisation might underlie the creation of affiliative bonds. Previous studies tested this hypothesis mainly during a social interaction, making it difficult to determine whether the identified synchronisation is associated with affiliative bonding or with social interaction. This study addressed this issue by focusing on the teacher–student relationship in the resting state both before and after a teaching period. Brain activity was simultaneously measured in both individuals using functional near-infrared spectroscopy. The results showed a significant increase in brain synchronisation at the right sensorimotor cortex between the teacher and student in the resting state after, but not before, the teaching period. Moreover, the synchronisation increased only after a turn-taking mode of teaching but not after a lecturing or video mode of teaching. A chain mediation analysis showed that brain synchronisation during teaching partially mediated the relationship between the brain synchronisation increase in the resting state and strength of the affiliative bond. Finally, both role assignment and social interaction were found to be required for affiliative bonding. Together, these results support the hypothesis that interpersonal synchronisation in brain activity underlies affiliative bonding and that social interaction mechanically mediates the bonding process.

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          Process Analysis: Estimating Mediation in Treatment Evaluations

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            An integrated theory of language production and comprehension.

            Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal.
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              Controlling the familywise error rate in functional neuroimaging: a comparative review.

              Functional neuroimaging data embodies a massive multiple testing problem, where 100,000 correlated test statistics must be assessed. The familywise error rate, the chance of any false positives is the standard measure of Type I errors in multiple testing. In this paper we review and evaluate three approaches to thresholding images of test statistics: Bonferroni, random field and the permutation test. Owing to recent developments, improved Bonferroni procedures, such as Hochberg's methods, are now applicable to dependent data. Continuous random field methods use the smoothness of the image to adapt to the severity of the multiple testing problem. Also, increased computing power has made both permutation and bootstrap methods applicable to functional neuroimaging. We evaluate these approaches on t images using simulations and a collection of real datasets. We find that Bonferroni-related tests offer little improvement over Bonferroni, while the permutation method offers substantial improvement over the random field method for low smoothness and low degrees of freedom. We also show the limitations of trying to find an equivalent number of independent tests for an image of correlated test statistics.
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                Author and article information

                Journal
                Soc Cogn Affect Neurosci
                Soc Cogn Affect Neurosci
                scan
                Social Cognitive and Affective Neuroscience
                Oxford University Press
                1749-5016
                1749-5024
                January 2020
                05 February 2020
                05 February 2020
                : 15
                : 1
                : 97-109
                Affiliations
                [1 ] Center for Teacher Education Research , Faculty of Education, Beijing Normal University, Beijing 100875, China
                [2 ] State Key Laboratory of Cognitive Neuroscience and Learning , Beijing Normal University, Beijing 100875, China
                [3 ] Key Research Base of Humanities and Social Sciences of the Ministry of Education , Academy of Psychology and Behavior, Tianjin Normal University, Tianjin 300074, China
                [4 ] Faculty of Psychology , Tianjin Normal University, Tianjin 300387, China
                [5 ] Center of Collaborative Innovation for Assessment and Promotion of Mental Health , Tianjin 300074, China
                [6 ] IDG/McGovern Institute for Brain Research , Beijing Normal University, Beijing 100875, China
                Author notes
                Correspondence should be addressed to Chunming Lu, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China. E-mail: luchunming@ 123456bnu.edu.cn .

                Lifen Zheng and Wenda Liu contributed equally to this study.

                Article
                nsaa016
                10.1093/scan/nsaa016
                7171379
                32022237
                9422ded5-d40a-48d2-9b83-4c2234ff8998
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 25 September 2019
                : 17 January 2020
                : 20 January 2020
                Page count
                Pages: 13
                Funding
                Funded by: International Joint Research Project of Faculty of Education;
                Award ID: CER201905
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 71974016
                Award ID: 31622030
                Award ID: 61977008
                Categories
                Original Manuscript

                Neurosciences
                affiliative bond,resting state,teaching,teacher,student,fnirs
                Neurosciences
                affiliative bond, resting state, teaching, teacher, student, fnirs

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