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| 001 | 1052296 | ||
| 005 | 20260122203309.0 | ||
| 024 | 7 | _ | |a 10.1016/j.neuroimage.2025.121541 |2 doi |
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| 100 | 1 | _ | |a Li, Yuqin |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a ERP-based interbrain causal model reveals closed-loop information interaction in interpersonal negotiations |
| 260 | _ | _ | |a Orlando, Fla. |c 2025 |b Academic Press |
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| 520 | _ | _ | |a decision-making dynamics in resource allocation. In this study, we used EEG hyperscanning alongside an iteratedultimatum game to investigate interbrain coupling and dyadic exchange behavior during negotiation. Frontalcortex event-related potentials (ERPs) revealed the distinct neural responses driven by partners’ behavioral cues:the proposer’s N200 differed significantly for fair versus unfair offers, and the responder’s feedback-relatednegativity (FRN) showed a trend toward significance for the same contrast, while the proposer’s N500 variedbetween acceptance and rejection feedback. Our analysis introduced a novel causal model based on directionalphase transfer entropy (dPTE) and time-varying ERP amplitudes, illustrating directed neural processes driven bysocial exchange, where the proposer’s brain activity initially exerts a causal impact on the responder’s, whosefeedback in turn influences the proposer, creating a closed-loop interaction that drives adaptive negotiationstrategies. Additionally, our prediction model with autoregression with exogenous input, which incorporatedthese causal links between brains, demonstrated higher accuracy than single-brain or reverse causal models,underscoring the significance of dynamic interbrain coupling in interpersonal coordination. This causal modelprovides a mechanistic explanation of how proposer-responder pairs perceive and adapt to each other’s de-cisions, facilitating shared attention and behavioral coordination in reciprocal, asymmetric negotiations. Thesefindings offer a novel theoretical framework for studying complex social behaviors through interbrain dynamicsand may inspire future applications in enhancing cooperative decision-making processes. |
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| 700 | 1 | _ | |a Sarah, Genon |0 P:(DE-Juel1)161225 |b 1 |
| 700 | 1 | _ | |a Chen, Chunli |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Jiang, Lin |b 3 |
| 700 | 1 | _ | |a Chen, Baodan |b 4 |
| 700 | 1 | _ | |a Li, Rihui |b 5 |
| 700 | 1 | _ | |a Liang, Zhen |b 6 |
| 700 | 1 | _ | |a Yu, Jing |0 0000-0003-2485-2286 |b 7 |
| 700 | 1 | _ | |a Dong, Debo |0 P:(DE-Juel1)190904 |b 8 |
| 700 | 1 | _ | |a Wan, Fen |0 0000-0002-9359-0737 |b 9 |
| 700 | 1 | _ | |a Becker, Benjamin |0 0000-0002-9014-9671 |b 10 |
| 700 | 1 | _ | |a Yao, Dezhong |b 11 |
| 700 | 1 | _ | |a Li, Fali |b 12 |
| 700 | 1 | _ | |a Zhang, Dandan |b 13 |
| 700 | 1 | _ | |a Xu, Peng |0 P:(DE-Juel1)140459 |b 14 |e Corresponding author |
| 773 | _ | _ | |a 10.1016/j.neuroimage.2025.121541 |g Vol. 321, p. 121541 - |0 PERI:(DE-600)1471418-8 |p 121541 - |t NeuroImage |v 321 |y 2025 |x 1053-8119 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/1052296/files/Sarah%20%2B%20Debo25.pdf |y OpenAccess |
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