Decision response and feedback in gambling are interrelated. Different decisions lead to different ranges of feedback, which in turn influences subsequent decisions. However, the mechanism underlying the continuous decision-feedback process is still left unveiled. To fulfill this gap, we applied the hidden Markov model (HMM) to the gambling electroencephalogram (EEG) data to characterize the dynamics of this process. Furthermore, we explored the differences between distinct decision responses (i.e. choose large or small bets) or distinct feedback (i.e. win or loss outcomes) in corresponding phases. We demonstrated that the processing stages in decision-feedback process including strategy adjustment and visual information processing can be characterized by distinct brain networks. Moreover, time-varying networks showed, after decision response, large bet recruited more resources from right frontal and right center cortices while small bet was more related to the activation of the left frontal lobe. Concerning feedback, networks of win feedback showed a strong right frontal and right center pattern, while an information flow originating from the left frontal lobe to the middle frontal lobe was observed in loss feedback. Taken together, these findings shed light on general principles of natural decision-feedback and may contribute to the design of biologically inspired, participant-independent decision-feedback systems.

中文翻译：

---

脑电图隐马尔可夫模型揭示的决策反馈阶段

赌博中的决策响应和反馈是相互关联的。不同的决策会导致不同范围的反馈，进而影响后续决策。然而，持续决策反馈过程背后的机制仍未揭开。为了弥补这一差距，我们将隐马尔可夫模型 (HMM) 应用于赌博脑电图 (EEG) 数据，以表征这一过程的动态。此外，我们探讨了相应阶段不同决策响应（即选择大赌注或小赌注）或不同反馈（即输赢结果）之间的差异。我们证明了决策反馈过程中的处理阶段，包括策略调整和视觉信息处理，可以通过不同的大脑网络来表征。此外，时变网络显示，在决策响应之后，大赌注从右额叶和右中央皮质招募更多资源，而小赌注与左额叶的激活更相关。关于反馈，获胜反馈网络显示出强烈的右额和右中心模式，而在损失反馈中观察到从左额叶到中额叶的信息流。总之，这些发现阐明了自然决策反馈的一般原则，并可能有助于设计受生物学启发的、独立于参与者的决策反馈系统。而在损失反馈中观察到从左额叶到中额叶的信息流。总之，这些发现阐明了自然决策反馈的一般原则，并可能有助于设计受生物学启发的、独立于参与者的决策反馈系统。而在损失反馈中观察到从左额叶到中额叶的信息流。总之，这些发现阐明了自然决策反馈的一般原则，并可能有助于设计受生物学启发的、独立于参与者的决策反馈系统。