The brain integrates information from pain-predictive cues and noxious inputs to construct the pain experience. Although previous studies have identified neural encodings of individual pain components, how they are integrated remains elusive. Here, using a cue-induced pain task, we examined temporal functional magnetic resonance imaging activities within the state space, where axes represent individual voxel activities. By analyzing the features of these activities at the large-scale network level, we demonstrated that overall brain networks preserve both cue and stimulus information in their respective subspaces within the state space. However, only higher-order brain networks, including limbic and default mode networks, could reconstruct the pattern of participants’ reported pain by linear summation of subspace activities, providing evidence for the integration of cue and stimulus information. These results suggest a hierarchical organization of the brain for processing pain components and elucidate the mechanism for their integration underlying our pain perception.

中文翻译：

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一种针对大脑疼痛的线索-刺激整合的计算机制


大脑整合来自疼痛预测线索和有害输入的信息来构建疼痛体验。尽管以前的研究已经确定了单个疼痛成分的神经编码，但它们是如何整合的仍然难以捉摸。在这里，使用线索诱导的疼痛任务，我们检查了状态空间内的时间功能磁共振成像活动，其中轴代表单个体素活动。通过在大规模网络水平上分析这些活动的特征，我们证明了整个大脑网络将线索和刺激信息保存在状态空间内各自的子空间中。然而，只有高阶大脑网络，包括边缘和默认模式网络，才能通过子空间活动的线性求和来重建参与者报告的疼痛模式，为线索和刺激信息的整合提供证据。这些结果表明大脑用于处理疼痛成分的分层组织，并阐明了它们整合的机制，构成了我们疼痛感知的基础。