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Interbrain Neural Correlates of Self and Other Integration in Joint Statistical Learning

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Bibliographic Details
Title: Interbrain Neural Correlates of Self and Other Integration in Joint Statistical Learning
Language: English
Authors: Zheng Zheng, Jun Wang (ORCID 0000-0001-8560-3203)
Source: npj Science of Learning. 2024 9.
Availability: Nature Portfolio. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://www.nature.com/npjscilearn/
Peer Reviewed: Y
Page Count: 11
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Statistics Education, Cooperative Learning, Observational Learning, Learning Processes, Interference (Learning), Reaction Time, Brain
DOI: 10.1038/s41539-024-00280-4
ISSN: 2056-7936
Abstract: While statistical learning is often studied individually, its collective representation through self-other integration remains unclear. This study examines dynamic self-other integration and its multi-brain mechanism using simultaneous recordings from dyads. Participants (N = 112) each repeatedly responded to half of a fixed stimulus sequence with either an active partner (joint context) or a passive observer (baseline context). Significant individual statistical learning was evident in the joint context, characterized by decreased reaction time (RT) and intra-brain neural responses, followed by a quadratic trend (i.e., first increasing and then decreasing) upon insertion of an interference sequence. More importantly, Brain-to-Brain Coupling (BtBC) in the theta band also showed learning and modulation-related trends, with its slope negatively and positively correlating with the slopes of RT and intra-brain functional connectivity, respectively. These results highlight the dynamic nature of self-other integration in joint statistical learning, with statistical regularities implicitly and spontaneously modulating this process. Notably, the BtBC serves as a key neural correlate underlying the dynamics of self-other integration.
Abstractor: As Provided
Notes: https://osf.io/wdctr
Entry Date: 2024
Accession Number: EJ1450107
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Zheng+Zheng%22">Zheng Zheng</searchLink><br /><searchLink fieldCode="AR" term="%22Jun+Wang%22">Jun Wang</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-8560-3203">0000-0001-8560-3203</externalLink>)
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  Data: While statistical learning is often studied individually, its collective representation through self-other integration remains unclear. This study examines dynamic self-other integration and its multi-brain mechanism using simultaneous recordings from dyads. Participants (N = 112) each repeatedly responded to half of a fixed stimulus sequence with either an active partner (joint context) or a passive observer (baseline context). Significant individual statistical learning was evident in the joint context, characterized by decreased reaction time (RT) and intra-brain neural responses, followed by a quadratic trend (i.e., first increasing and then decreasing) upon insertion of an interference sequence. More importantly, Brain-to-Brain Coupling (BtBC) in the theta band also showed learning and modulation-related trends, with its slope negatively and positively correlating with the slopes of RT and intra-brain functional connectivity, respectively. These results highlight the dynamic nature of self-other integration in joint statistical learning, with statistical regularities implicitly and spontaneously modulating this process. Notably, the BtBC serves as a key neural correlate underlying the dynamics of self-other integration.
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  Data: https://osf.io/wdctr
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