The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain

作者：Kun Zhu, Jianchao Chang, Siya Zhang, Yan Li, Junxun Zuo, Haoyu Ni, Bing Xie, Jiyuan Yao, Zhibin Xu, Sicheng Bian, Tingfei Yan, Xianyong Wu, Senlin Chen, Weiming Jin, Ying Wang, Peng Xu, Peiwen Song, Yuanyuan Wu, Cailiang Shen, Jiajia Zhu, Yongqiang Yu, Fulong Dong · 发表于：NeuroImage · 年份：2024 · DOI：10.1016/j.neuroimage.2024.120558 · 被引用次数：31 · 研究领域：Functional Brain Connectivity Studies、Heart Rate Variability and Autonomic Control、Musculoskeletal pain and rehabilitation

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classi...