Neumann Lynn, Wulms Niklas, Witte Vanessa, Spisak Tamas, Zunhammer Matthias, Bingel Ulrike, Schmidt-Wilcke Tobias
Medizinische Klinik I, Klinik für Innere Medizin, Nephrologie und Dialyse, Osteologie und Rheumatologie, St. Franziskus-Hospital Münster, Münster, Germany.
Institut für Epidemiologie und Sozialmedizin, Universitätsklinikum Münster, Münster, Germany.
Hum Brain Mapp. 2021 Oct 15;42(15):4896-4908. doi: 10.1002/hbm.25588. Epub 2021 Jul 23.
Pain thresholds vary considerably across individuals and are influenced by a number of behavioral, genetic and neurobiological factors. However, the neurobiological underpinnings that account for individual differences remain to be fully elucidated. In this study, we used voxel-based morphometry (VBM) and graph theory, specifically the local clustering coefficient (CC) based on resting-state connectivity, to identify brain regions, where regional gray matter volume and network properties predicted individual pain thresholds. As a main finding, we identified a cluster in the left posterior insular cortex (IC) reaching into the left parietal operculum, including the secondary somatosensory cortex, where both regional gray matter volume and the local CC correlated with individual pain thresholds. We also performed a resting-state functional connectivity analysis using the left posterior IC as seed region, demonstrating that connectivity to the pre- as well as postcentral gyrus bilaterally; that is, to the motor and primary sensory cortices were correlated with individual pain thresholds. To our knowledge, this is the first study that applied VBM in combination with voxel-based graph theory in the context of pain thresholds. The co-location of the VBM and the local CC cluster provide first evidence that both structure and function map to the same brain region while being correlated with the same behavioral measure; that is, pain thresholds. The study highlights the importance of the posterior IC, not only for pain perception in general, but also for the determination of individual pain thresholds.
疼痛阈值在个体间差异很大,并受多种行为、遗传和神经生物学因素影响。然而,造成个体差异的神经生物学基础仍有待充分阐明。在本研究中,我们使用基于体素的形态测量法(VBM)和图论,特别是基于静息态连接性的局部聚类系数(CC),来识别脑区,其中区域灰质体积和网络属性可预测个体疼痛阈值。作为主要发现,我们在左后岛叶皮质(IC)中识别出一个延伸至左顶叶岛盖的簇,包括次级体感皮层,该区域的灰质体积和局部CC均与个体疼痛阈值相关。我们还以左后IC为种子区域进行了静息态功能连接性分析,结果表明与双侧中央前回和中央后回的连接性,即与运动和初级感觉皮层的连接性与个体疼痛阈值相关。据我们所知,这是第一项在疼痛阈值背景下将VBM与基于体素的图论相结合的研究。VBM和局部CC簇的共定位首次证明,结构和功能映射到同一脑区,同时与同一行为指标(即疼痛阈值)相关。该研究强调了后IC的重要性,不仅对于一般的疼痛感知,而且对于个体疼痛阈值的确定。