In August 2018, the research paper Interpersonal synchronization of inferior frontal cortices tracks social interactive learning of a song by Hu Yi's research group was accepted by the authoritative international neuroimaging journal "NeuroImage". The research uses a technology based on the combination of functional near-infrared brain imaging (fNIRS) and multiple simultaneous scanning (hyperscanning) to explore the mechanism of interpersonal brain synchronization in social interactive learning.
Most human learning is done in interactive form; this includes observation and imitation, teacher-student interaction, and so on. As early as two thousand years ago, educators proposed to spread knowledge through interaction (such as "Socratic Dialogue", etc.). However, the neural mechanism of this social interaction learning is still unclear. Interestingly, recent studies have found (such as Cheng et al., 2015; Hu et al., 2017; Hu et al., 2018; Pan et al., 2017) that humans will generate inter-brain signals during interaction Synchronization phenomenon, this synchronization mechanism is closely related to the process and result of interaction. The interpersonal brain synchronization model is believed to support human social cognitive processing. Does it also play an important role in social interaction learning?
In order to answer the above questions, the research group cooperated with researchers from University College London, taking 24 pairs of teacher-student combinations as the research object, and collected the brain function imaging data of teachers during the teaching of music songs to students (Figure 1A). In the process of interactive learning, teachers can use two teaching methods: "part learning" (PL; teaching singing sentence by sentence) or "whole learning" (WL; teaching singing the whole song) (Figure 1B). The brain activities of the frontotemporal and parietal cortex were recorded simultaneously (Figure 1C). After the interactive learning, the students complete the song singing independently (to evaluate the learning effect afterwards). The relationship between teacher and student brain activity changes over time is calculated as an indicator of interpersonal brain synchronization. The whole experiment process was recorded by the camera to encode the behavior afterwards (Figure 2).
(Figure 1. (A) Social interaction learning paradigm. (B) Partial learning and overall learning strategies. (C) Brain area of ​​interest.)
(Figure 2. Analysis of the combination of interpersonal brain synchronization and interactive behavior. (A) Time series of interpersonal brain synchronization in the "partial learning" group. Blue dots indicate non-singing interactive behaviors; red dots indicate singing interactive behaviors (student observation stage); green dots Represents singing interactive behavior (student imitation stage). (B) Corresponding interactive learning behavior extracted from the video.)
The research mainly found that "partial learning" has more interactions than "overall learning" (Figure 3B), which brings better learning results (Figure 3A), and triggers inferior frontal cortex (IFC) between teachers and students. ) Synchronization occurs (Figure 4A-C). Through further analysis in combination with the interactive behavior of video coding [including singing interactive behavior (further subdivided into student observation stage and student imitation stage), non-singing interactive behavior and non-interactive behavior], it is found that this kind of interpersonal brain synchronization (interpersonal brain synchronization, The IBS phenomenon has the strongest effect during the vocal interaction (VI, Figure 5A), especially the student observation period (OBSERVATION, that is, the teacher’s demonstration period, Figure 6A), and it is significantly related to the student’s learning results (Figure 4D, 5B, 6B). It is worth noting that through Granger causality analysis, the study found that during the student's observation period, the teacher's brain activity has a higher predictive power for the student (Figure 6C). These findings have important theoretical significance for our understanding of the cognitive and neural processes of social interactive learning, and also provide important references for teaching and clinical practice.
(Figure 3. Learning performance and interactive learning behavior. (A) Student learning performance. (B) Number of interactive learning behaviors. (C) Percentage of interactive learning behavior duration.)
(Figure 4. Interpersonal brain synchronization results. (A) Frequency band of interest. (B) One-sample t-test of interpersonal brain synchronization. (C) Differences in interpersonal brain synchronization. (D) Between interpersonal brain synchronization and learning performance Related.)
(Figure 5. Interpersonal brain synchronization and interactive learning behavior. (A) Interpersonal brain synchronization during singing interaction (VI), non-singing interaction (NVI), and non-interaction (NI). (B) Interpersonal brain synchronization and interactive learning behavior relationship.)
(Figure 6. Interpersonal brain synchronization during the singing interaction. (A) During the singing interaction, the interpersonal brain synchronization during the student observation (OBSERVATION) and imitation (IMITATION) phases. (B) The interpersonal brain synchronization during the student observation period and the student's pitch Performance-related. (C) Granger causality analysis during student observation. Teachers have higher predictive power for students’ brain signals.)
The cognitive neural process of human-human high-level social interaction is a hot spot in the field of psychology and neuroscience research. In recent years, the research group has used EEG, near-infrared imaging technology, combined with multiple simultaneous scanning methods, revealing human cooperation (Cheng et al., 2015; Pan et al., 2017), decision-making (Hu et al., 2018), pro-social behavior (Hu et al., 2017) and a series of interpersonal brain synchronization patterns in the process of social interaction.
The research paper was mainly completed by Pan Yafeng, a PhD student in the research group of Professor Hu Yi (now co-trained by East China Normal University and the Free University of Brussels) and Giacomo Novembre, an assistant researcher at University College London, UK. The corresponding author is Professor Hu Yi. The research was funded by the National Natural Science Foundation of China. Doctoral student Pan Yafeng has received funding from the China Scholarship Council and East China Normal University's Excellent Doctoral Dissertation Cultivation Program. The phased results of this research were presented orally at the “Social Brain Interaction Brain Health Brain†academic seminar (2017); the complete data results were presented at the 4th Annual Meeting of The French Community of Functional NIRS (4th Annual Meeting of The French Community of Functional NIRS). , 2017) conducted an oral presentation.
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