# Electrophysiological Hyperscanning of Negotiation During Group-Oriented Decision-Making
## 4 Discussion
As a result, lower coherence in frontal delta activity may indicate asymmetric cognitive control processes, where interactants independently regulate uncertainty, strategic shifts, and fairness perceptions [59]. This neural dissociation is consistent with the behavioral profile reported by participants, characterized by low conflict and moderate influence. Rather than reflecting interpersonal discord, frontal inter-brain dissimilarity may index self-regulated cognitive engagement within a shared, non-adversarial task structure. Hyperscanning research suggests that inter-brain synchronization does not necessarily reflect functional alignment but may arise from cooperative or adversarial neural dynamics [60,61]. The observed lower delta synchronization in the frontal regions of the dyads may thus signal increased cognitive effort in conflict resolution, suppression of competing responses, or the negotiation of divergent interpretations. Despite the study's contributions to understanding the neural dynamics of negotiation, several methodological limitations should be acknowledged to guide future research. Firstly, the interpretation of frontal delta dissimilarity as an index of cognitive conflict regulation is supported by research on low-frequency frontal oscillations and executive control. However, the current study did not include time-locked behavioral markers of conflict dynamics or parametric measures of decisional divergence, and the sample size limited the ability to test direct neuro-behavioral correlations. Future research should integrate continuous measures of negotiation dynamics, synchronized behavioral annotations, and temporally resolved EEG analyses to better understand the neural mechanisms of conflict regulation during negotiation. Secondly, although the study was adequately powered for detecting medium within-subject effects, the relatively small sample limits broader generalization and the exploration of interaction-level variability. Thirdly, although gender was not a variable of interest in the present study, the sample's imbalance (20 females, 6 males) may limit generalizability, particularly given documented sex differences in negotiation styles, emotional regulation, and neural synchrony patterns. Future studies should implement stratified dyadic designs or include gender as a planned covariate to test its specific impact. Finally, while designed to simulate a realistic group decision, the absence of real-world stakes may have limited affective arousal, potentially influencing the magnitude of neural activation during negotiation. An interesting avenue for future research would be to examine how individual differences, such as personality traits, empathy levels, or prior negotiation experience, influence the observed neural patterns. It is possible that more experienced negotiators exhibit different frontal delta dynamics, reflecting more efficient strategic adaptation. Similarly, individuals with higher trait empathy may show reduced inter-brain dissimilarity, indicating a greater tendency to align with their partner's cognitive and emotional states. Investigating these moderating factors could provide a more nuanced understanding of how neural mechanisms underpin real-world negotiation behavior. In addition, future studies could benefit from incorporating a time-resolved analysis of the negotiation process. Segmenting interactions into distinct phases--such as initial disagreement, deadlock, and resolution--could help uncover more detailed temporal dynamics of neural engagement and clarify how cognitive and affective processes evolve throughout the negotiation.