School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China.
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, 518060, China; Peng Cheng Laboratory, Shenzhen, 518055, China.
Behav Brain Res. 2019 Dec 16;375:112142. doi: 10.1016/j.bbr.2019.112142. Epub 2019 Aug 5.
Dynamic functional connectivity (dFC) analysis based on resting-state functional magnetic resonance imaging (fMRI) has gained popularity in recent years. Despite many studies have linked dFC patterns to various mental diseases and cognitive functions, little research has used dFC in the investigation of low-level sensory perception. The present study is aimed to explore resting-state fMRI dFC patterns correlated with thresholds of two types of perception, pain and touch, on an individual basis. We collected and analyzed resting-state fMRI data and thresholds of pain and touch from 80 healthy participants. dFC states were identified by using independent component analysis, sliding window correlation, and clustering, and then the thresholds of pain and touch are correlated with the occurrence frequencies of dFC states. A new permutation analysis is developed to make identified dFC states more interpretable. We found that the occurrence frequency of a default mode network (DMN)-dominated state was positively correlated with the pain threshold, while the occurrence frequency of a static functional connectivity (sFC)-like state was negatively correlated with the touch threshold. This study showed that the thresholds of pain and touch have distinct dFC correlates, suggesting different influences of baseline brain states on different types of sensory perception. This study also showed that dFC could serve as an indicator of an individual's pain sensitivity, which can be potentially used for pain management.
基于静息态功能磁共振成像(rs-fMRI)的动态功能连接(dFC)分析近年来越来越受到关注。尽管许多研究已经将 dFC 模式与各种精神疾病和认知功能联系起来,但很少有研究将 dFC 用于低水平感官知觉的研究。本研究旨在探索基于个体的静息态 fMRI dFC 模式与两种感知(疼痛和触觉)阈值之间的关系。我们收集并分析了 80 名健康参与者的静息态 fMRI 数据和疼痛与触觉的阈值。通过独立成分分析、滑动窗口相关和聚类来识别 dFC 状态,然后将疼痛和触觉的阈值与 dFC 状态的出现频率相关联。开发了一种新的置换分析方法,使识别出的 dFC 状态更具可解释性。我们发现,默认模式网络(DMN)主导状态的出现频率与疼痛阈值呈正相关,而类似于静态功能连接(sFC)的状态的出现频率与触觉阈值呈负相关。这项研究表明,疼痛和触觉的阈值具有明显的 dFC 相关性,这表明基线脑状态对不同类型的感官知觉有不同的影响。这项研究还表明,dFC 可以作为个体疼痛敏感性的指标,这可能用于疼痛管理。