The imbalanced anterior and posterior default mode network in the primary insomnia

Yu, Siyi; Guo, Baojun; Shen, Zhifu; Zheng-Yan, Wang; Yu, Kyeong-Nam; Hu, Youping; Feng, Fen

doi:10.1016/j.jpsychires.2018.05.013

Cited by 47 publications

(48 citation statements)

References 45 publications

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“…Neuroimaging studies for insomnia have made substantial effort to understand the neuromechanisms of insomnia. Previous studies found aberrant brain metabolism and connectivity related to the prefrontal cortex, insular cortex, amygdala, precuneus and caudate in primary insomnia [4][5][6][7][8][9][10][11][12][13][14][15][16][17]. For example, using PET, Nofzinger et al [4] found smaller decrease in relative metabolism from waking to non-REM sleep states in the ascending reticular activating system, hypothalamus, thalamus, insular cortex, amygdala, hippocampus, anterior cingulate and medial prefrontal cortices, which supports the CNS hyperarousal hypothesis.…”

Section: Introductionmentioning

confidence: 74%

Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features

Dong

Yin

et al. 2019

Preprint

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Objective: To investigate whether or not functional connectivity (FC) could be used as a potential biomarker for classification of primary insomnia (PI) at the individual level by using multivariate pattern analysis (MVPA). Methods:Thirty-eight drug-naive patients with PI and 44 healthy controls (HC) underwent resting-state functional MR imaging. Three commonly used FC metrics (voxel-wise functional connectivity strength, large-scale functional connectivity and regional homogeneity) were calculated for each participant. We used the MVPA framework using linear support vector machine (SVM) with the three types of metrics as features separately. Subsequently, an unbiased N-fold cross-validation strategy was used to generate a classification system and was then used to evaluate its classification performances. Finally, FC metrics with significant high classification performance were compared between the two groups and were correlated with clinical characteristics, i.e., Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS). Results:The best classifier could reach up to an accuracy of 81.5%, with sensitivity of 84.9%, specificity of 79.1% and area under the receiver operating characteristic curve (AUC) of 83.0% (all P < 0.001). Right fronto-insular cortex, left precuneus and left middle frontal gyrus showed high classification weights. In addition, right fronto-insular cortex and left middle frontal gyrus were the overlapping regions between MVPA and group comparison. Correlation analysis showed that functional connectivity strength (FCS) in left middle frontal gyrus and head of right caudate nucleus were correlated with PSQI and SDS respectively. Conclusion:The current study suggests abnormal FCS might serve as a potential neuromarkers for PI.

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Section: Introductionmentioning

confidence: 74%

Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features

Dong

Yin

et al. 2019

Preprint

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“…In addition, the unique function of these two regions, which is not necessarily AD or neurodegeneration related, may also be involved in explaining this phenomenon. ISTC and precuneus are among the very few regions sensitive to different major stressful life events, including chronic stress exposure ( Calati et al 2018 ), psychiatric disorders (e.g., depression, schizophrenia) ( Szymkowicz et al, 2016 , Whitford et al, 2014 ), head trauma ( Shin et al 2014 ), and insomnia ( Yu et al 2018 ). Together, this connection’s immunity to amyloid deposition, and/or regulatory capacity over stress/homeostatic regulation may explain Supernormals cognitive excellence despite the similarity in overall AD pathology between Supernormals and cognitively normative older adults.…”

Section: Discussionmentioning

confidence: 99%

Cognitively supernormal older adults maintain a unique structural connectome that is resistant to Alzheimer’s pathology

Chen¹,

Baran

Rooks

et al. 2020

NeuroImage: Clinical

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“…Our previous study was a preliminary exploration of the pathogenesis of insomnia (rather than CID with GI disorder) in terms of brain function and structure. [20][21]50] Other research teams have con rmed that insomnia patients have abnormal brain metabolism using MRS technology. [24][25][26] At present, there are no brain imaging studies on patients with CID with GI.…”

Section: Discussionmentioning

confidence: 99%

The Cerebral Mechanism of Acupuncture for Chronic Insomnia with Gastrointestinal Disorder: Protocol for a Randomized Controlled Trial

Peng

Xia

Huangfu

et al. 2020

Preprint

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BackgroundMany patients with chronic insomnia disorder (CID) have gastrointestinal (GI) symptoms. First-line insomnia medications do not treat GI problems. Acupuncture has a comprehensive regulative action on both CID and GI disorder and is receiving increasing attention. Recent studies indicate that both CID and GI diseases may cause abnormal brain activity. However, the neurological mechanism underlying the effect of acupuncture on such diseases is still unclear. The aim of this study is to explore the pathological mechanisms of CID with GI discomfort, as well as the main response characteristics of acupuncture treatment from multiple perspectives using multimodal magnetic resonance imaging (MRI).MethodsA total of 60 participants with CID and GI disorders will be randomly divided into two groups (real acupuncture group and sham acupuncture group; ratio of 1:1). Patients will receive 20 sessions (five sessions per week) of real acupuncture treatment or sham acupuncture treatment. The primary outcome is the aggregate score on the Pittsburgh Sleep Quality Index. Secondary outcomes are scores on the Gastrointestinal Symptom Rating Scale, Self-Rating Anxiety Scale, and Self-Rating Depression Scale. Multimodal MRI scans and clinical assessments will be performed both at baseline and post-treatment. Another 30 age-, sex-, and education-matched healthy subjects will be recruited as controls and will receive MRI scans and clinical evaluations. DiscussionThis study aims to provide scientiﬁc evidence for the mechanism of acupuncture in treating CID with GI disorder using multimodal MRI imaging data on brain structure, function, and metabolism. Trial registrationThe study was registered in the Chinese Clinical Trial Registry on July 11, 2018. (ChiCTR1800017092)

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The imbalanced anterior and posterior default mode network in the primary insomnia

Cited by 47 publications

References 45 publications

Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features

Multivariate Pattern Classification of Primary Insomnia Using Three Types of Functional Connectivity Features

Cognitively supernormal older adults maintain a unique structural connectome that is resistant to Alzheimer’s pathology

The Cerebral Mechanism of Acupuncture for Chronic Insomnia with Gastrointestinal Disorder: Protocol for a Randomized Controlled Trial

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