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Background: The neuropathologic mechanism of primary insomnia (PI) of females remains unclear. This study aims to investigate the features of amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) in females with PI using functional magnetic resonance imaging (fMRI), and then explore the abnormalities of functional connectivity (FC). Materials and methods: A total of 39 female PI patients and 31 female healthy controls (HC) were enrolled in the study. The sleep condition was assessed using the Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI), and their depressive symptom was evaluated using the Hamilton Depression Scale (HAMD-24). The rs-fMRI was once conducted for every subject. ReHo, ALFF, and ROI-based FC were used to analyze the changes of brain function. Results: ALFF values were increased in the Cerebelum_4_5_L, as well as decreased ALFF in the bilateral Frontal_Sup_Medial (SFGmed), Angular_L (ANG.L), Parietal_ Inf_R (IPL.R), SupraMarginal_R (SMG.R), and Postcentral_R (PoCG.R). ReHo values were increased in the Temporal_Pole_Mid_R (TPOsup.R), as well as decreased ReHo in the Insula_R (INS.R), Frontal_Inf_Oper_R (ORBinf.R), Putamen_R (PUT.R), Rolandic_Oper_R (ROL.R), bilateral Cingulum_Post (PCG), bilateral Frontal_Sup_ Medial (SFGmed), bilateral anterior cingulate and paracingulate gyri (ACG), and the bilateral precuneus (PCUN). Across the entire brain, there was a decline in the FC between Angular_R and Frontal_Sup_Medial_L. Conclusion: Alterations in brain regions of female patients with PI involved multiple functional networks, including the default mode network, the salience network, the central executive network, and the limbic network. Reduced coordination between functional networks may be an important mechanism for insomnia and may lead to reduced cognitive function and decision-making ability. [ABSTRACT FROM AUTHOR]

Chronic insomnia has the potential to significantly impact physical well-being, occupational performance, and overall quality of life. This review summarizes the clinical and basic research on the central regulatory mechanism of acupuncture in treating primary insomnia (PI), aiming to explore the clinical effectiveness and possible mechanism of acupuncture in treating PI. The currently available drugs for insomnia exhibit notable adverse effects and tend to induce dependence. Empirical evidence from clinical investigations has demonstrated that acupuncture has a favorable safety profile while substantially enhancing the sleep quality of individuals diagnosed with PI. The combination of acupuncture and medication has been shown to augment the therapeutic efficacy of medication while reducing the dosage and mitigating the occurrence of unwanted effects. A review of the current clinical and basic research on the effects of acupuncture on central alterations in PI patients revealed that acupuncture exerts a regulatory influence on the functional activity of brain regions implicated in cognitive and emotional processes. Additionally, acupuncture has been found to impact metabolite levels and circadian clock gene expression and enhance inflammatory responses and energy metabolism. Notably, a single acupuncture intervention had a modulatory effect on functional brain regions similar to that of cumulative acupuncture. The current clinical trials on acupuncture have been limited in scale, and basic research has focused on a single objective. With the continuous progress of brain research, extensive clinical randomized controlled trials of high quality can be combined with various neuroimaging technology modalities. Moreover, different targets and pathways can be explored through basic research. This may serve to enhance the understanding of the fundamental central nervous system mechanisms involved in the efficacy of acupuncture in treating PI.

Objectives: To quantitatively measure the T1 value, T2 value, proton density (PD) value, and cerebral blood flow (CBF) in young and middle-aged primary insomnia (PI) patients, and analyze the correlations between relaxation times, PD, and CBF to explore potential brain changes. Methods: Cranial magnetic resonance (MR) images of 44 PI patients and 30 healthy subjects were prospectively collected for analysis. The T1, T2, PD, and CBF values of the frontal lobe, parietal lobe, temporal lobe, and occipital lobe were independently measured using three-dimensional arterial spin labeling (3D-ASL), synthetic magnetic resonance imaging (syMRI) and a whole-brain automatic segmentation method. The differences of these imaging indices were compared between PI patients and healthy subjects. Follow-up MR images were obtained from PI patients after 6 months to compare with pre-treatment images. The Wilcoxon signed rank test and Spearman rank were used for statistical analysis. Results: Bilateral CBF asymmetry was observed in 38 patients, with significant differences in both the T2 value and CBF between the four lobes of the brain (p < 0.01). However, no significant difference was found in the T1 and PD values between the bilateral lobes. A negative correlation was found between CBF and T2 values in the right four lobes of patients with primary insomnia (PI). During follow-up examinations, five PI patients showed a disappearance of insomnia symptoms and a decrease in CBF in both brain lobes. Conclusion: Insomnia symptoms may be associated with high CBF, and most PI patients have higher CBF and lower T2 values in the right cerebral hemispheres. The right hemisphere appears to play a critical role in the pathophysiology of PI. The 3D-ASL and syMRI technologies can provide a quantitative imaging basis for investigating the brain conditions and changes in young and middle-aged PI patients. [ABSTRACT FROM AUTHOR]

Primary insomnia (PI) is among the most prevalent sleep-related disorders and has a far-reaching impact on daytime functioning. Repetitive transcranial magnetic stimulation (rTMS) has drawn attention because of its effectiveness and safety. The purpose of the current study was to detect changes in the topological organization of whole-brain functional networks and to determine their associations with the clinical treatment effects of rTMS. Resting-state functional magnetic resonance imaging (rsfMRI) data from 32 patients with PI were collected and compared with findings from 32 age- and gender-matched healthy controls (HCs). The patients were treated with Stanford accelerated intelligent neuromodulation therapy, which is a recently validated neuroscience-informed accelerated intermittent theta-burst stimulation protocol. Graph theoretical analysis was used to construct functional connectivity matrices and to extract the attribute features of small-world networks in insomnia. Scores on the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and the associations between these clinical characteristics and functional metrics, were the primary outcomes. At baseline, the patients with PI showed inefficient small-world property and aberrant functional segregation and functional integration compared with the HCs. These properties showed renormalization after individualized rTMS treatment. Furthermore, low functional connectivity between the right insula and left medial frontal gyrus correlated with improvement in ISI scores. We highlight functional network dysfunctions in PI patients and provide evidence into the pathophysiological mechanisms involved and the possible mode of action of rTMS. [ABSTRACT FROM AUTHOR]

Primary insomnia (PI) is among the most prevalent sleep-related disorders and has a far-reaching impact on daytime functioning. Repetitive transcranial magnetic stimulation (rTMS) has drawn attention because of its effectiveness and safety. The purpose of the current study was to detect changes in the topological organization of whole-brain functional networks and to determine their associations with the clinical treatment effects of rTMS. Resting-state functional magnetic resonance imaging (rsfMRI) data from 32 patients with PI were collected and compared with findings from 32 age- and gender-matched healthy controls (HCs). The patients were treated with Stanford accelerated intelligent neuromodulation therapy, which is a recently validated neuroscience-informed accelerated intermittent theta-burst stimulation protocol. Graph theoretical analysis was used to construct functional connectivity matrices and to extract the attribute features of small-world networks in insomnia. Scores on the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and the associations between these clinical characteristics and functional metrics, were the primary outcomes. At baseline, the patients with PI showed inefficient small-world property and aberrant functional segregation and functional integration compared with the HCs. These properties showed renormalization after individualized rTMS treatment. Furthermore, low functional connectivity between the right insula and left medial frontal gyrus correlated with improvement in ISI scores. We highlight functional network dysfunctions in PI patients and provide evidence into the pathophysiological mechanisms involved and the possible mode of action of rTMS.

Transcutaneous auricular vagus nerve stimulation (taVNS) has been reported to be effective in the treatment of primary insomnia (PI); however, its efficacy varies considerably across individuals for reasons that are unclear. In order to clarify the underlying mechanisms, this study investigated the effects of taVNS on spontaneous neuronal activity and autonomic nervous system function by functional magnetic resonance imaging (fMRI) and measurement of heart rate variability (HRV), respectively, in patients with PI. Forty patients with PI were divided into effective (group A) and ineffective (group B) groups based on their response to taVNS as determined by Pittsburgh Sleep Quality Index score reduction rate (group A ≥ 25% and group B < 25%). Spontaneous neuronal activity was measured by fractional amplitude of low-frequency fluctuations (fALFF) and HRV values and was compared between the two groups as well as before vs after taVNS. We then analyzed the correlations among efficacy of taVNS for 4 weeks, the fALFF and HRV values during continuous taVNS state. The results showed that the HRV parameter values (i.e., root mean square of successive differences, percentage of adjacent NN intervals differing by >50 ms, and high frequency) of group A were higher than those of group B during continuous taVNS state. In the fMRI scan, the fALFF values of the right cerebellum, right medial superior frontal gyrus, and bilateral supplementary motor area—which belong to the sensorimotor network (SMN)—were lower in group A than in group B during continuous taVNS state. The correlation analysis revealed that the efficacy of continuous taVNS and HRV and fALFF values were interrelated. These findings demonstrate that differential regulation of the SMN by the autonomic nervous system may be responsible for inter-individual variations in the efficacy of taVNS and suggest that HRV and fALFF are potential biomarkers for predicting PI patients’ response to taVNS treatment.

Transcutaneous auricular vagus nerve stimulation (taVNS) has been reported to be effective in the treatment of primary insomnia (PI); however, its efficacy varies considerably across individuals for reasons that are unclear. In order to clarify the underlying mechanisms, this study investigated the effects of taVNS on spontaneous neuronal activity and autonomic nervous system function by functional magnetic resonance imaging (fMRI) and measurement of heart rate variability (HRV), respectively, in patients with PI. Forty patients with PI were divided into effective (group A) and ineffective (group B) groups based on their response to taVNS as determined by Pittsburgh Sleep Quality Index score reduction rate (group A ≥ 25% and group B < 25%). Spontaneous neuronal activity was measured by fractional amplitude of low-frequency fluctuations (fALFF) and HRV values and was compared between the two groups as well as before vs after taVNS. We then analyzed the correlations among efficacy of taVNS for 4 weeks, the fALFF and HRV values during continuous taVNS state. The results showed that the HRV parameter values (i.e., root mean square of successive differences, percentage of adjacent NN intervals differing by >50 ms, and high frequency) of group A were higher than those of group B during continuous taVNS state. In the fMRI scan, the fALFF values of the right cerebellum, right medial superior frontal gyrus, and bilateral supplementary motor area—which belong to the sensorimotor network (SMN)—were lower in group A than in group B during continuous taVNS state. The correlation analysis revealed that the efficacy of continuous taVNS and HRV and fALFF values were interrelated. These findings demonstrate that differential regulation of the SMN by the autonomic nervous system may be responsible for inter-individual variations in the efficacy of taVNS and suggest that HRV and fALFF are potential biomarkers for predicting PI patients' response to taVNS treatment. [ABSTRACT FROM AUTHOR]

ObjectivesThe present study examined the abnormal resting state functional connections (RSFCs) in structural deficit brain regions of primary insomnia (PI) patients.MethodsThirty-three PI patients and 38 well-matched healthy controls participated in our study. We used voxel-based morphometry and RSFC to study functional connectivity abnormalities of brain regions with structural deficits in PI patients.ResultsPI patients showed decreased gray matter (GM) volume in the left dorsolateral prefrontal cortex, left orbitofrontal cortex (OFC), bilateral middle frontal gyrus (MFC), right inferior frontal gyrus (IFG), and left inferior temporal gyrus. Gray matter volume in the right MFC negatively correlated with Self-Rating Scale of Sleep (SRSS) scores, and GM volume in the right IFG negatively correlated with SRSS and Insomnia Severity Index (ISI) scores. Therefore, the right MFC and right IFG were selected as regions of interest for RSFC analysis. PI patients had weakened RSFC between the right inferior parietal gyrus (IPC) and the right MFC compared to the healthy controls and between the left OFC and right IFG. The RSFC between the right MFC and right IPC negatively correlated with SRSS scores. The RSFC between the right IFG and left OFC negatively correlated with SRSS, ISI, SAS, and SDS scores.ConclusionsThe present study found structural changes in the right MFC and right IFG accompanied by RSFC changes. This finding may provide novel insights into the neural mechanisms of PI via combining structural and functional modality information.

The physiological mechanism underlying primary insomnia (PI) is poorly understood. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a powerful tool to explore PI. However, previous studies ignore the dynamics of the brain activity. In the current study, we aimed to explore altered dynamic intrinsic brain activity in PI. Fifty-nine patients with PI and 47 matched healthy controls (HCs) were recruited and underwent resting-state fMRI. The variance of dynamic amplitude of low frequency fluctuation (dALFF) maps across time was calculated to measure the temporal variability of intrinsic brain activity and then compared between patients with PI and HCs. As a result, patients with PI presented increased variance of dALFF in the bilateral hippocampus extending to the parahippocampus, the right putamen and the right anterior insula cortex. In addition, the variance of dALFF in the right putamen was positively correlated with Self-rating Anxiety Scale (SAS) score in PI. Our results revealed increased instability of intrinsic activity in PI.

PurposeInsomnia is the most prevalent sleep complaint in the general population but is often intractable due to uncertainty regarding the underlying pathomechanisms. Sleep is regulated by a network of neural structures interconnected with the core nodes of the brain connectome referred to as the “rich club”. We examined alterations in brain rich-club organization as revealed by diffusion tensor imaging (DTI) and the statistical relationships between abnormalities in rich-club metrics and the clinical features of primary insomnia (PI).MethodsThis study recruited 43 primary insomnia (PI) patients and 42 age-, sex-, and education level-matched healthy controls (HCs). Differences in global and regional network parameters between PI and healthy control groups were compared by nonparametric tests, and Spearman's correlations were calculated to assess associations of these network metrics with PI-related clinical features, including disease duration and scores on the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Self-Rating Anxiety Scale, and Self-Rating Depression Scale.ResultsWeighted white matter networks exhibited weaker rich-club organization in PI patients than HCs across different thresholds (50%, 75%, and 90%) and parcellation schemes [automated anatomical labeling (AAL)-90 and AAL-1024]. Aberrant rich-club organization was found mainly in limbic-cortical-basal ganglia circuits and the default-mode network.ConclusionsAbnormal rich-club metrics are a characteristic feature of PI-related to disease severity. These metrics provide potential clues to PI pathogenesis and may be useful as diagnostic markers and for assessment of treatment response.

Primary insomnia (PI) is associated with increased spontaneous neuronal activity. Transcutaneous auricular vagus nerve stimulation (taVNS) modulates brain function, and it is an effective treatment for primary insomnia. However, whether taVNS alleviates insomnia through modulating spontaneous neuronal activity is not fully clarified. This study aims to investigate the instant effect of taVNS in modulating spontaneous neuronal activity in PI patients using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-two PI subjects underwent rs-fMRI scanning prior and immediately after 30 min treatment of taVNS controlled by twenty healthy adults. Amplitude of low frequency fluctuations (ALFF) analysis was employed to assess the difference in spontaneous neuronal activity between PI patients and healthy adults, as well as between pre-treatment and post-treatment of taVNS. The taVNS-induced altered ALFF brain areas were then selected as regions of interest to perform the resting state functional connectivity (RSFC) analysis in PI patients. The right precuneus showed significantly increased ALFF in PI patients. After immediate taVNS treatment, the ALFF was significantly decreased in the right precuneus and increased in the left middle occipital gyrus. The RSFC in right precuneus with right angular, right superior frontal gyrus, and right middle frontal gyrus was significantly decreased. This study provides insights into the instant brain effects of taVNS on PI patients.

The physiological mechanism underlying primary insomnia (PI) is poorly understood. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a powerful tool to explore PI. However, previous studies ignore the dynamics of the brain activity. In the current study, we aimed to explore altered dynamic intrinsic brain activity in PI. Fifty-nine patients with PI and 47 matched healthy controls (HCs) were recruited and underwent resting-state fMRI. The variance of dynamic amplitude of low frequency fluctuation (dALFF) maps across time was calculated to measure the temporal variability of intrinsic brain activity and then compared between patients with PI and HCs. As a result, patients with PI presented increased variance of dALFF in the bilateral hippocampus extending to the parahippocampus, the right putamen and the right anterior insula cortex. In addition, the variance of dALFF in the right putamen was positively correlated with Self-rating Anxiety Scale (SAS) score in PI. Our results revealed increased instability of intrinsic activity in PI. [ABSTRACT FROM AUTHOR]

Objectives: The present study examined the abnormal resting state functional connections (RSFCs) in structural deficit brain regions of primary insomnia (PI) patients. Methods: Thirty-three PI patients and 38 well-matched healthy controls participated in our study. We used voxel-based morphometry and RSFC to study functional connectivity abnormalities of brain regions with structural deficits in PI patients. Results: PI patients showed decreased gray matter (GM) volume in the left dorsolateral prefrontal cortex, left orbitofrontal cortex (OFC), bilateral middle frontal gyrus (MFC), right inferior frontal gyrus (IFG), and left inferior temporal gyrus. Gray matter volume in the right MFC negatively correlated with Self-Rating Scale of Sleep (SRSS) scores, and GM volume in the right IFG negatively correlated with SRSS and Insomnia Severity Index (ISI) scores. Therefore, the right MFC and right IFG were selected as regions of interest for RSFC analysis. PI patients had weakened RSFC between the right inferior parietal gyrus (IPC) and the right MFC compared to the healthy controls and between the left OFC and right IFG. The RSFC between the right MFC and right IPC negatively correlated with SRSS scores. The RSFC between the right IFG and left OFC negatively correlated with SRSS, ISI, SAS, and SDS scores. Conclusions: The present study found structural changes in the right MFC and right IFG accompanied by RSFC changes. This finding may provide novel insights into the neural mechanisms of PI via combining structural and functional modality information. [ABSTRACT FROM AUTHOR]

Purpose: Insomnia is the most prevalent sleep complaint in the general population but is often intractable due to uncertainty regarding the underlying pathomechanisms. Sleep is regulated by a network of neural structures interconnected with the core nodes of the brain connectome referred to as the "rich club". We examined alterations in brain rich-club organization as revealed by diffusion tensor imaging (DTI) and the statistical relationships between abnormalities in rich-club metrics and the clinical features of primary insomnia (PI). Methods: This study recruited 43 primary insomnia (PI) patients and 42 age-, sex-, and education level-matched healthy controls (HCs). Differences in global and regional network parameters between PI and healthy control groups were compared by nonparametric tests, and Spearman's correlations were calculated to assess associations of these network metrics with PI-related clinical features, including disease duration and scores on the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Self-Rating Anxiety Scale, and Self-Rating Depression Scale. Results: Weighted white matter networks exhibited weaker rich-club organization in PI patients than HCs across different thresholds (50%, 75%, and 90%) and parcellation schemes [automated anatomical labeling (AAL)-90 and AAL-1024]. Aberrant rich-club organization was found mainly in limbic-cortical-basal ganglia circuits and the default-mode network. Conclusions: Abnormal rich-club metrics are a characteristic feature of PI-related to disease severity. These metrics provide potential clues to PI pathogenesis and may be useful as diagnostic markers and for assessment of treatment response. [ABSTRACT FROM AUTHOR]

Primary insomnia (PI) is associated with increased spontaneous neuronal activity. Transcutaneous auricular vagus nerve stimulation (taVNS) modulates brain function, and it is an effective treatment for primary insomnia. However, whether taVNS alleviates insomnia through modulating spontaneous neuronal activity is not fully clarified. This study aims to investigate the instant effect of taVNS in modulating spontaneous neuronal activity in PI patients using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-two PI subjects underwent rs-fMRI scanning prior and immediately after 30 min treatment of taVNS controlled by twenty healthy adults. Amplitude of low frequency fluctuations (ALFF) analysis was employed to assess the difference in spontaneous neuronal activity between PI patients and healthy adults, as well as between pre-treatment and post-treatment of taVNS. The taVNS-induced altered ALFF brain areas were then selected as regions of interest to perform the resting state functional connectivity (RSFC) analysis in PI patients. The right precuneus showed significantly increased ALFF in PI patients. After immediate taVNS treatment, the ALFF was significantly decreased in the right precuneus and increased in the left middle occipital gyrus. The RSFC in right precuneus with right angular, right superior frontal gyrus, and right middle frontal gyrus was significantly decreased. This study provides insights into the instant brain effects of taVNS on PI patients. [ABSTRACT FROM AUTHOR]

Objective: To explore 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. Voxel-wise functional connectivity strength (FCS), large-scale functional connectivity (large-scale FC) and regional homogeneity (ReHo) were calculated for each participant. We used support vector machine (SVM) with the three types of metrics as features separately to classify patients from healthy controls. Then we evaluated 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) in the patients' group.Results: The best classifier could reach up to an accuracy of 81.5%, with a 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 anterior insular cortex (BA48), left precuneus (BA7), and left middle frontal gyrus (BA8) showed high classification weights. In addition, the right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) were the overlapping regions between MVPA and group comparison. Correlation analysis showed that 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 in right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) might serve as a potential neuromarkers for PI.

Objective: To explore 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. Voxel-wise functional connectivity strength (FCS), large-scale functional connectivity (large-scale FC) and regional homogeneity (ReHo) were calculated for each participant. We used support vector machine (SVM) with the three types of metrics as features separately to classify patients from healthy controls. Then we evaluated 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) in the patients' group. Results: The best classifier could reach up to an accuracy of 81.5%, with a 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 anterior insular cortex (BA48), left precuneus (BA7), and left middle frontal gyrus (BA8) showed high classification weights. In addition, the right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) were the overlapping regions between MVPA and group comparison. Correlation analysis showed that 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 in right anterior insular cortex (BA48) and left middle frontal gyrus (BA8) might serve as a potential neuromarkers for PI. [ABSTRACT FROM AUTHOR]

Background: Primary insomnia is a high prevalent sleep disorder. Disturbed brain activity during reward, emotional, and cognitive processing have been observed in insomnia patients. Studies have implicated a critical role of the striatum in these dysfunctions. However, there have been no direct investigations on the whole-brain functional connectivity (FC) of the striatum in insomnia.Methods: We analyzed the group differences in the FC images of 6 predefined striatal subregions based on the multi-band resting-state fMRI data of 18 insomnia patients and 16 healthy controls.Results: We found increased positive FC in the bilateral medial frontal gyrus for bilateral dorsal caudate (DC) and left inferior ventral striatum (VS) subregions, but increased negative FC in the bilateral inferior parietal lobe for the left inferior VSi and right dorsal caudal putamen (DCP) subregions, and in the lateral temporal, occipital, and primary sensorimotor areas for the bilateral DC and left superior VS subregions. The FC between the right DCP and right inferior parietal lobe showed significant positive correlation with Pittsburgh Sleep Quality Index (PSQI).Conclusion: The findings indicate disturbed striatal FC with the default mode network (DMN), the visual and somatosensory areas in insomnia, which likely reflects an inappropriate reward or emotional significance attribute to self-reflection, episodic memory, sensory-perception processes. The altered striatal FC might increase the risk of insomnia patients to develop depression and anxiety.

Purpose: Primary insomnia (PI) is the second most common mental disorder. However, the topologic alterations in structural brain connectome in patients with PI remain largely unknown.Methods: A total of 44 PI patients and 46 age-, gender-, and education level matched healthy control (HC) participants were recruited in this study. Diffusion tensor imaging (DTI) and resting state MRI were used to construct structural connectome for each participant, and the network parameters were employed by non-parametric permutations to evaluate the significant differences between the two groups. Relationships between abnormal network metrics and clinical characteristics, including the disease duration, the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS), were investigated with Spearman’s correlation analysis in PI patients.Results: PI patients demonstrated small-world architecture with lower global (P = 0.005) and local (P = 0.035) efficiencies compared with the HC group. The unique hub nodal properties in PI patients were mainly in the right limbic cortico-basal-ganglia circuit. Five disrupted subnetworks in PI patients were observed in the limbic cortico-basal-ganglia circuit and left default-mode networks (DMN) (P < 0.05, NBS corrected). Moreover, most unique hub nodal properties in the right limbic cortico-basal-ganglia circuit were significantly correlated with disease duration, and clinical characteristics (SAS, SDS, ISI scores) in PI processing.Conclusion: These findings suggested the abnormal anatomical network architecture may be closely linked to clinical characteristics in PI. The study provided novel insights into the neural substrates underlying symptoms and neurophysiologic mechanisms of PI.

Background: Resting-state functional magnetic resonance imaging (fMRI) studies have uncovered the disruptions of functional brain networks in primary insomnia (PI) patients. However, the etiology and pathogenesis underlying this disorder remains ambiguous, and the insomnia related symptoms are influenced by a complex network organization in the brain. The purpose of this study was to explore the abnormal intrinsic functional hubs in PI patients using a voxel-wise degree centrality (DC) analysis and seed-based functional connectivity (FC) approach.Methods: A total of 26 PI patients and 28 healthy controls were enrolled, and they underwent resting-state fMRI. Degree centrality was measured across the whole brain, and group differences in DC were compared. The peak points, which significantly altered DC between the two groups, were defined as the seed regions and were further used to calculate FC of the whole brain. Later, correlation analyses were performed between the changes in brain function and clinical features.Results: Primary insomnia patients showed DC values lower than healthy controls in the left inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) and showed a higher DC value in the right precuneus. The seed-based analyses demonstrated decreased FC between the left MTG and the left posterior cingulate cortex (PCC), and decreased FC was observed between the right precuneus and the right lateral occipital cortex. Reduced DC in the left IFG and decreased FC in the left PCC were positively correlated with the Pittsburgh sleep quality index and the insomnia severity index.Conclusions: This study revealed that PI patients exhibited abnormal intrinsic functional hubs in the left IFG, MTG, and the right precuneus, as well as abnormal seed-based FC in these hubs. These results contribute to better understanding of how brain function influences the symptoms of PI.

Background: Recently, there have been many reports about abnormalities regarding structural and functional brain connectivity of the patients with primary insomnia. However, the alterations in functional interaction between the left and right cerebral hemispheres have not been well understood. The resting-state fMRI approach, which reveals spontaneous neural fluctuations in blood-oxygen-level-dependent signals, offers a method to quantify functional interactions between the hemispheres directly.Methods: We compared interhemispheric functional connectivity (FC) between 26 patients with primary insomnia (48.85 ± 12.02 years) and 28 healthy controls (49.07 ± 11.81 years) using a voxel-mirrored homotopic connectivity (VMHC) method. The patients with primary insomnia and healthy controls were matched for age, gender, and education. Brain regions, which had significant differences in VMHC maps between the primary insomnia and healthy control groups, were defined as seed region of interests. A seed-based approach was further used to reveal significant differences of FC between the seeds and the whole contralateral hemisphere.Results: The patients with primary insomnia showed higher VMHC than healthy controls in the anterior cingulate cortex (ACC) bilaterally. The seed-based analyses demonstrated increased FC between the left ACC and right thalamus (and the right ACC and left orbitofrontal cortex) in patients with primary insomnia, revealing abnormal connectivity between the two cerebral hemispheres. The VMHC values in the ACC were positively correlated with the time to fall asleep and Self-Rating Depression Scale scores (SDS).Conclusions: The results demonstrate that there is abnormal interhemispheric resting-state FC in the brain regions of patients with primary insomnia, especially in the ACC. Our finding demonstrates valid evidence that the ACC is an area of interest in the neurobiology of primary insomnia.

ObjectiveDaytime cognitive impairment is an essential symptom of primary insomnia (PI). However, the underlying neural substrate remains largely unknown. Many studies have shown that the right anterior insula (rAI) as a key node of salience network (SN) plays a critical role in switching between the executive control network (ECN) and the default mode network (DMN) for better performance of cognitively demanding tasks. Aberrant effective connectivity (directional functional connectivity) of rAI with ECN or DMN may be one reason for daytime cognitive impairment in PI patients. Up to now, no effective connectivity study has been conducted on patients with PI during resting state. Our aim is to investigate the effective connectivity between the rAI and the other voxels in the whole brain in PI.Materials and methodsFifty drug-naive patients with PI and forty age- and sex-matched healthy controls were scanned using resting-state functional MRI. Seed-based Granger causality analysis was used to examine effective connectivity between the rAI, including ventral and dorsal part, and the whole brain. The effective connectivity was compared between the two groups and was correlated with clinical characteristics.ResultsCompared with controls, patients showed decreased effective connectivity from the rAI to the bilateral precuneus, the left postcentral gyrus (extending to bilateral precuneus) and the bilateral cerebellum posterior lobe, and decreased effective connectivity from the bilateral orbitofrontal cortex (OFC) to the rAI (single voxel P

Accumulating evidence from neuroimaging studies suggests that primary insomnia (PI) affects interregional neural coordination of multiple interacting functional brain networks. However, a complete understanding of the whole-brain network organization from a system-level perspective in PI is still lacking. To this end, we investigated in topological organization changes in brain functional networks in PI. 36 PI patients and 38 age-, sex-, and education-matched healthy controls were recruited. All participants underwent a series of neuropsychological assessments and resting-state functional magnetic resonance imaging scans. Individual whole-brain functional network were constructed and analyzed using graph theory-based network approaches. There were no significant differences with respect to age, sex, or education between groups (P > 0.05). Graph-based analyses revealed that participants with PI had a significantly higher total number of edges (P = 0.022), global efficiency (P = 0.014), and normalized global efficiency (P = 0.002), and a significantly lower normalized local efficiency (P = 0.042) compared with controls. Locally, several prefrontal and parietal regions, the superior temporal gyrus, and the thalamus exhibited higher nodal efficiency in participants with PI (P

Purpose: Primary insomnia (PI) is the second most common mental disorder. However, the topologic alterations in structural brain connectome in patients with PI remain largely unknown. Methods: A total of 44 PI patients and 46 age-, gender-, and education level matched healthy control (HC) participants were recruited in this study. Diffusion tensor imaging (DTI) and resting state MRI were used to construct structural connectome for each participant, and the network parameters were employed by non-parametric permutations to evaluate the significant differences between the two groups. Relationships between abnormal network metrics and clinical characteristics, including the disease duration, the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS), were investigated with Spearman's correlation analysis in PI patients. Results: PI patients demonstrated small-world architecture with lower global (P = 0.005) and local (P = 0.035) efficiencies compared with the HC group. The unique hub nodal properties in PI patients were mainly in the right limbic cortico-basal-ganglia circuit. Five disrupted subnetworks in PI patients were observed in the limbic cortico-basal-ganglia circuit and left default-mode networks (DMN) (P < 0.05, NBS corrected). Moreover, most unique hub nodal properties in the right limbic cortico-basal-ganglia circuit were significantly correlated with disease duration, and clinical characteristics (SAS, SDS, ISI scores) in PI processing. Conclusion: These findings suggested the abnormal anatomical network architecture may be closely linked to clinical characteristics in PI. The study provided novel insights into the neural substrates underlying symptoms and neurophysiologic mechanisms of PI. [ABSTRACT FROM AUTHOR]

Background: Resting-state functional magnetic resonance imaging (fMRI) studies have uncovered the disruptions of functional brain networks in primary insomnia (PI) patients. However, the etiology and pathogenesis underlying this disorder remains ambiguous, and the insomnia related symptoms are influenced by a complex network organization in the brain. The purpose of this study was to explore the abnormal intrinsic functional hubs in PI patients using a voxel-wise degree centrality (DC) analysis and seed-based functional connectivity (FC) approach. Methods: A total of 26 PI patients and 28 healthy controls were enrolled, and they underwent resting-state fMRI. Degree centrality was measured across the whole brain, and group differences in DC were compared. The peak points, which significantly altered DC between the two groups, were defined as the seed regions and were further used to calculate FC of the whole brain. Later, correlation analyses were performed between the changes in brain function and clinical features. Results: Primary insomnia patients showed DC values lower than healthy controls in the left inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) and showed a higher DC value in the right precuneus. The seed-based analyses demonstrated decreased FC between the left MTG and the left posterior cingulate cortex (PCC), and decreased FC was observed between the right precuneus and the right lateral occipital cortex. Reduced DC in the left IFG and decreased FC in the left PCC were positively correlated with the Pittsburgh sleep quality index and the insomnia severity index. Conclusions: This study revealed that PI patients exhibited abnormal intrinsic functional hubs in the left IFG, MTG, and the right precuneus, as well as abnormal seed-based FC in these hubs. These results contribute to better understanding of how brain function influences the symptoms of PI. [ABSTRACT FROM AUTHOR]

Objective: Daytime cognitive impairment is an essential symptom of primary insomnia (PI). However, the underlying neural substrate remains largely unknown. Many studies have shown that the right anterior insula (rAI) as a key node of salience network (SN) plays a critical role in switching between the executive control network (ECN) and the default mode network (DMN) for better performance of cognitively demanding tasks. Aberrant effective connectivity (directional functional connectivity) of rAI with ECN or DMN may be one reason for daytime cognitive impairment in PI patients. Up to now, no effective connectivity study has been conducted on patients with PI during resting state. Our aim is to investigate the effective connectivity between the rAI and the other voxels in the whole brain in PI. Materials and methods: Fifty drug-naive patients with PI and forty age- and sexmatched healthy controls were scanned using resting-state functional MRI. Seed-based Granger causality analysis was used to examine effective connectivity between the rAI, including ventral and dorsal part, and the whole brain. The effective connectivity was compared between the two groups and was correlated with clinical characteristics. Results: Compared with controls, patients showed decreased effective connectivity from the rAI to the bilateral precuneus, the left postcentral gyrus (extending to bilateral precuneus) and the bilateral cerebellum posterior lobe, and decreased effective connectivity from the bilateral orbitofrontal cortex (OFC) to the rAI (single voxel P < 0.001, AlphaSim corrected with P < 0.01). In addition, effective connectivity from the ventral rAI to the left postcentral gyrus and from the left OFC to the ventral rAI were significantly negatively correlated with Insomnia Severity Index scores (r = -0.28/P = 0.046 and r = -0.29/P = 0.038, respectively). Conclusion: The present study is the first to reveal aberrant effective connectivity between the SN hub (rAI) and the posterior DMN hub (precuneus) as well as decisionmaking region (OFC) and sensori-motor region in PI. These findings suggest an aberrant salience processing system of the rAI in PI patients. [ABSTRACT FROM AUTHOR]

Accumulating evidence from neuroimaging studies suggests that primary insomnia (PI) affects interregional neural coordination of multiple interacting functional brain networks. However, a complete understanding of the whole-brain network organization from a system-level perspective in PI is still lacking. To this end, we investigated in topological organization changes in brain functional networks in PI. 36 PI patients and 38 age-, sex-, and education-matched healthy controls were recruited. All participants underwent a series of neuropsychological assessments and resting-state functional magnetic resonance imaging scans. Individual whole-brain functional network were constructed and analyzed using graph theory-based network approaches. There were no significant differences with respect to age, sex, or education between groups (P > 0.05). Graphbased analyses revealed that participants with PI had a significantly higher total number of edges (P = 0.022), global efficiency (P = 0.014), and normalized global efficiency (P = 0.002), and a significantly lower normalized local efficiency (P = 0.042) compared with controls. Locally, several prefrontal and parietal regions, the superior temporal gyrus, and the thalamus exhibited higher nodal efficiency in participants with PI (P < 0.05, false discovery rate corrected). In addition, most of these regions showed increased functional connectivity in PI patients (P < 0.05, corrected). Finally, altered network efficiency was correlated with neuropsychological variables of the Epworth Sleepiness Scale and Insomnia Severity Index in patients with PI. PI is associated with abnormal organization of large-scale functional brain networks, which may account for memory and emotional dysfunction in people with PI. These findings provide novel implications for neural substrates associated with PI. [ABSTRACT FROM AUTHOR]