Tu Yiheng, Zhang Binlong, Cao Jin, Wilson Georgia, Zhang Zhiguo, Kong Jian
Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
Neuroimage. 2019 Nov 15;202:116049. doi: 10.1016/j.neuroimage.2019.116049. Epub 2019 Jul 23.
Individuals are unique in terms of brain and behavior. Some are very sensitive to pain, while others have a high tolerance. However, how inter-individual intrinsic differences in the brain are related to pain is unknown. Here, we performed longitudinal test-retest analyses to investigate pain threshold variability among individuals using a resting-state fMRI brain connectome. Twenty-four healthy subjects who received four MRI sessions separated by at least 7 days were included in the data analysis. Subjects' pain thresholds were measured using two modalities of experimental pain (heat and pressure) on two different locations (heat pain: leg and arm; pressure pain: leg and thumbnail). Behavioral results showed strong inter-individual variability and strong within-individual stability in pain threshold. Resting state fMRI data analyses showed that functional connectivity profiles can accurately identify subjects across four sessions, indicating that an individual's connectivity profile may be intrinsic and unique. By using multivariate pattern analyses, we found that connectivity profiles could be used to predict an individual's pain threshold at both within-session and between-session levels, with the most predictive contribution from medial-frontal and frontal-parietal networks. These results demonstrate the potential of using a resting-state fMRI brain connectome to build a 'neural trait' for characterizing an individual's pain-related behavior, and such a 'neural trait' may eventually be used to personalize clinical assessments.
个体在大脑和行为方面是独特的。有些人对疼痛非常敏感,而另一些人则具有较高的耐受性。然而,大脑中个体间的内在差异与疼痛之间的关系尚不清楚。在这里,我们进行了纵向重测分析,以使用静息态功能磁共振成像(fMRI)脑连接组来研究个体之间的疼痛阈值变异性。数据分析纳入了24名健康受试者,他们接受了四次MRI检查,每次检查间隔至少7天。使用两种实验性疼痛模式(热和压力)在两个不同位置(热痛:腿部和手臂;压力痛:腿部和拇指指甲)测量受试者的疼痛阈值。行为结果显示,疼痛阈值存在强烈的个体间变异性和强烈的个体内稳定性。静息态fMRI数据分析表明,功能连接图谱可以准确地在四个检查阶段识别受试者,这表明个体的连接图谱可能是内在的且独特的。通过使用多变量模式分析,我们发现连接图谱可用于在检查阶段内和检查阶段之间预测个体的疼痛阈值,其中内侧额叶和额顶网络的预测贡献最大。这些结果证明了使用静息态fMRI脑连接组来构建用于表征个体疼痛相关行为的“神经特征”的潜力,并且这样的“神经特征”最终可能用于个性化临床评估。