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  • 标题:Ultrafast ultrasound imaging pattern analysis reveals distinctive dynamic brain states and potent sub-network alterations in arthritic animals
  • 本地全文:下载
  • 作者:Line Rahal ; Miguel Thibaut ; Isabelle Rivals
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • 页码:1-17
  • DOI:10.1038/s41598-020-66967-x
  • 出版社:Springer Nature
  • 摘要:Chronic pain pathologies, which are due to maladaptive changes in the peripheral and/or central nervous systems, are debilitating diseases that affect 20% of the European adult population. A better understanding of the mechanisms underlying this pathogenesis would facilitate the identification of novel therapeutic targets. Functional connectivity (FC) extracted from coherent low-frequency hemodynamic fluctuations among cerebral networks has recently brought light on a powerful approach to study large scale brain networks and their disruptions in neurological/psychiatric disorders. Analysis of FC is classically performed on averaged signals over time, but recently, the analysis of the dynamics of FC has also provided new promising information. Keeping in mind the limitations of animal models of persistent pain but also the powerful tool they represent to improve our understanding of the neurobiological basis of chronic pain pathogenicity, this study aimed at defining the alterations in functional connectivity, in a clinically relevant animal model of sustained inflammatory pain (Adjuvant-induced Arthritis) in rats by using functional ultrasound imaging, a neuroimaging technique with a unique spatiotemporal resolution (100 μm and 2 ms) and sensitivity. Our results show profound alterations of FC in arthritic animals, such as a subpart of the somatomotor (SM) network, occurring several weeks after the beginning of the disease. Also, we demonstrate for the first time that dynamic functional connectivity assessed by ultrasound can provide quantitative and robust information on the dynamic pattern that we define as brain states. While the main state consists of an overall synchrony of hemodynamic fluctuations in the SM network, arthritic animal spend statistically more time in two other states, where the fluctuations of the primary sensory cortex of the inflamed hind paws show asynchrony with the rest of the SM network. Finally, correlating FC changes with pain behavior in individual animals suggest links between FC alterations and either the cognitive or the emotional aspects of pain. Our study introduces fUS as a new translational tool for the enhanced understanding of the dynamic pain connectome and brain plasticity in a major preclinical model of chronic pain.
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