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      Temporal regularity of intrinsic cerebral activity in patients with chronic primary insomnia: a brain entropy study using resting‐state fMRI

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          Abstract

          Introduction

          Several neuroimaging studies have suggested that patients with chronic primary insomnia ( CPI) exhibit anatomical and functional alterations of the brain, but the temporal regularity in spontaneous neuronal activity remains unknown. Here, brain entropy ( BEN), a data‐driven method used to measure the signal regularity of a time series, was applied for the first time to investigate changes in the entire brain at the voxel level.

          Methods

          Resting‐state functional MRI data were used to investigate insomnia‐related BEN alterations and the resting‐state functional connectivity (rs FC) pattern in seed regions with altered BEN in 29 patients with identified and untreated CPI and 29 matched healthy controls. Subsequently, within the CPI group, correlation analysis was conducted to evaluate the relationship between the clinical variables and the BEN and rs FC of the abnormal regions.

          Results

          Chronic primary insomnia patients showed significant increase in BEN in the central part of the default‐mode network ( DMN), the anterior regions of the task‐positive network ( TPN), the hippocampus (Hipp), and basal ganglia ( BG), and decreases in BEN in the right postcentral gyrus (Po CG) and right temporal–occipital junction ( TOJ). We also demonstrated that three altered resting‐state functional connectivity (rs FC) patterns were associated with abnormal BEN regions in CPI patients. Correlation analysis identified an association between the altered rs FC and clinical variables, such as the Pittsburgh Sleep Quality Index ( PSQI), in CPI patients.

          Conclusions

          Together, these findings suggest that abnormal BEN‐related intrinsic functional plasticity in CPI patients corresponds to poor sleep quality during chronic insomnia. Alterations in both BEN and its affected connectivity may improve our understanding of treatment‐naïve CPI patients and promote the future development of new therapeutic strategies.

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          Most cited references27

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          Sleep and emotions: a focus on insomnia.

          Insomnia disorder is defined as difficulties in initiating/maintaining sleep and/or non-restorative sleep accompanied by decreased daytime functioning, persisting for at least four weeks. For many patients suffering from depression and anxiety, insomnia is a pervasive problem. Many of the aetiological theories of insomnia postulate that heightened emotional reactivity contributes to the maintenance of symptoms. This review focuses on the role of emotional reactivity in insomnia, and how the relationship between insomnia and depression and anxiety may be mediated by emotional reactivity. Furthermore, studies investigating the valence of emotions in insomnia are reviewed. Overall, there is empirical evidence that dysfunctional emotional reactivity might mediate the interaction between cognitive and autonomic hyperarousal, thus contributing to the maintenance of insomnia. Moreover, dysfunctions in sleep-wake regulating neural circuitries seem to be able to reinforce emotional disturbances. It seems plausible that dysfunctional emotional reactivity modulates the relationship between insomnia and depression and anxiety. Considering the interaction between sleep and emotional valence, poor sleep quality seems to correlate with high negative and low positive emotions, both in clinical and subclinical samples. Good sleep seems to be associated with high positive emotions, but not necessarily with low negative emotions. This review underlines the need for future research on emotions in insomnia. (c) 2009 Elsevier Ltd. All rights reserved.
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            Evidence for the default network's role in spontaneous cognition.

            A set of brain regions known as the default network increases its activity when focus on the external world is relaxed. During such moments, participants change their focus of external attention and engage in spontaneous cognitive processes including remembering the past and imagining the future. However, the functional contributions of the default network to shifts in external attention versus internal mentation have been difficult to disentangle because the two processes are correlated under typical circumstances. To address this issue, the present study manipulated factors that promote spontaneous cognition separately from those that change the scope of external attention. Results revealed that the default network increased its activity when spontaneous cognition was maximized but not when participants increased their attention to unpredictable foveal or peripheral stimuli. To examine the nature of participants' spontaneous thoughts, a second experiment used self-report questionnaires to quantify spontaneous thoughts during extended fixation epochs. Thoughts about one's personal past and future comprised a major focus of spontaneous cognition with considerable variability. Activity correlations between the medial temporal lobe and distributed cortical regions within the default network predicted a small, but significant, portion of the observed variability. Collectively, these results suggest that during passive states, activity within the default network reflects spontaneous, internally directed cognitive processes.
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              Altered resting state complexity in schizophrenia.

              The complexity of the human brain's activity and connectivity varies over temporal scales and is altered in disease states such as schizophrenia. Using a multi-level analysis of spontaneous low-frequency fMRI data stretching from the activity of individual brain regions to the coordinated connectivity pattern of the whole brain, we investigate the role of brain signal complexity in schizophrenia. Specifically, we quantitatively characterize the univariate wavelet entropy of regional activity, the bivariate pairwise functional connectivity between regions, and the multivariate network organization of connectivity patterns. Our results indicate that univariate measures of complexity are less sensitive to disease state than higher level bivariate and multivariate measures. While wavelet entropy is unaffected by disease state, the magnitude of pairwise functional connectivity is significantly decreased in schizophrenia and the variance is increased. Furthermore, by considering the network structure as a function of correlation strength, we find that network organization specifically of weak connections is strongly correlated with attention, memory, and negative symptom scores and displays potential as a clinical biomarker, providing up to 75% classification accuracy and 85% sensitivity. We also develop a general statistical framework for the testing of group differences in network properties, which is broadly applicable to studies where changes in network organization are crucial to the understanding of brain function. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                fq.chou@yahoo.com
                honghan_gong@sina.com
                Journal
                Brain Behav
                Brain Behav
                10.1002/(ISSN)2157-9032
                BRB3
                Brain and Behavior
                John Wiley and Sons Inc. (Hoboken )
                2162-3279
                14 July 2016
                October 2016
                : 6
                : 10 ( doiID: 10.1002/brb3.2016.6.issue-10 )
                : e00529
                Affiliations
                [ 1 ] Department of Radiology the First Affiliated HospitalNanchang University NanchangChina
                [ 2 ]Jiangxi Province Medical Imaging Research Institute NanchangChina
                [ 3 ] Department of RadiologyJiangxi Province Children's Hospital NanchangChina
                [ 4 ] Department of OncologyThe Second Hospital of Nanchang NanchangChina
                Author notes
                [*] [* ] Correspondence

                Fuqing Zhou and Honghan Gong, Department of Radiology, the First Affiliated Hospital, Nanchang University, Nanchang, China.

                Emails: fq.chou@ 123456yahoo.com and honghan_gong@ 123456sina.com

                Article
                BRB3529
                10.1002/brb3.529
                5064341
                27781143
                463b09ba-ad66-43ad-8dfa-dee2ae3c09c5
                © 2016 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 December 2015
                : 06 May 2016
                : 03 June 2016
                Page count
                Figures: 6, Tables: 2, Pages: 12, Words: 8243
                Funding
                Funded by: National Science Foundation of China
                Award ID: 81101041
                Award ID: 81560284
                Award ID: 81260217
                Award ID: 81460263
                Funded by: Science and Technology Project of Jiangxi Provincial Education Department, China
                Award ID: GJJ13136
                Funded by: Natural Science Foundation of Jiangxi, China
                Award ID: 2013BAB215008
                Funded by: Science and Technology Support Program of Jiangxi, China
                Award ID: 20151BBG70224
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                brb3529
                October 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:14.10.2016

                Neurosciences
                chronic primary insomnia,functional connectivity,functional plasticity,resting‐state functional mri,sample entropy

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