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      Altered Resting-State Connectivity with Pain-Related Expectation Regions in Female Patients with Severe Knee Osteoarthritis

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          Expectation affects pain experience in humans. Numerous studies have reported that pre-stimulus activity in the anterior insular cortex (aIC), together with prefrontal and limbic regions, integrated pain intensity and expectations. However, it is unclear whether the resting-state functional connectivity (rs-FC) between the aIC and other brain regions affects chronic pain. The purpose of this study was to examine the rs-FC between the aIC and the whole brain regions in female patients with severe knee osteoarthritis (OA).

          Patients and Methods

          Nineteen female patients with chronic severe knee OA and 15 matched controls underwent resting-state functional magnetic resonance imaging. We compared the rs-FC from the aIC seed region between the two groups. A disease-specific measurement of knee OA was performed.


          The aIC showed stronger rs-FC with the right orbitofrontal cortex (OFC), subcallosal area, and bilateral frontal pole compared with controls. The strength of rs-FC between the left aIC and the right OFC was positively correlated with the knee OA pain score ( r = 0.49, p = 0.03). The strength of rs-FC between the right aIC and right OFC was positively correlated with the knee OA total score ( r = 0.48, p = 0.036) and pain score ( r = 0.46, p = 0.049). The OFC, subcallosal area, and frontal pole, together with the aIC, were activated during anticipation of pain stimulus. These areas have been reported as representative pain-related expectation regions.


          This was the first study to show the stronger rs-FCs between the aIC and other pain-related expectation regions in female patients with severe knee OA. Female sex and preoperative pain intensity are risk factors of persistent postoperative pain after total knee arthroplasty. It is suggested that the functional relationship between pain-related expectation regions affects the formation of severe knee OA and persistent postoperative pain following total knee arthroplasty.

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          Most cited references 48

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          Interoceptive predictions in the brain.

          Intuition suggests that perception follows sensation and therefore bodily feelings originate in the body. However, recent evidence goes against this logic: interoceptive experience may largely reflect limbic predictions about the expected state of the body that are constrained by ascending visceral sensations. In this Opinion article, we introduce the Embodied Predictive Interoception Coding model, which integrates an anatomical model of corticocortical connections with Bayesian active inference principles, to propose that agranular visceromotor cortices contribute to interoception by issuing interoceptive predictions. We then discuss how disruptions in interoceptive predictions could function as a common vulnerability for mental and physical illness.
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            Radiological assessment of osteo-arthrosis.

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              Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

              Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.

                Author and article information

                J Pain Res
                J Pain Res
                Journal of Pain Research
                02 December 2020
                : 13
                : 3227-3234
                [1 ]Department of Rehabilitation, Hiroshima University Hospital , Hiroshima, Japan
                [2 ]Sports Medical Center, Hiroshima University Hospital , Hiroshima, Japan
                [3 ]Department of Orthopedic Surgery, Graduate School of Biomedical and Health Sciences, Hiroshima University , Hiroshima, Japan
                [4 ]Department of Orthopedic Surgery, Nihon University School of Medicine, Nihon University , Tokyo, Japan
                [5 ]Department of Rehabilitation Medicine, Wakayama Medical University , Wakayama, Japan
                [6 ]Department of Psychiatry and Neurosciences, Hiroshima University , Hiroshima, Japan
                [7 ]Brain, Mind and KANSEI Sciences Research Center, Hiroshima University , Hiroshima, Japan
                [8 ]Department of Clinical Radiology, Hiroshima University Hospital , Hiroshima, Japan
                Author notes
                Correspondence: Kazuyoshi Nakanishi Department of Orthopedic Surgery, Nihon University School of Medicine, Nihon University , Oyaguchi-Kamimachi 30-1, Itabashi-Ku, Tokyo173-8610, JapanTel +81-3-3972-8111Fax +81-3-3957-6186 Email nakanishi.kazuyoshi@nihon-u.ac.jp
                © 2020 Ushio et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 3, Tables: 9, References: 50, Pages: 8
                Original Research


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