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ImportanceAlthough researchers have devoted substantial efforts, money, and time to studying the causes of dementia and the means to prevent it, no effective treatment exists yet. Identifying preclinical risk factors of dementia could help prevent or delay its progression.ObjectiveTo develop a point risk score prediction model of dementia.Design, Setting, and ParticipantsThis study used a large UK population-based prospective cohort study conducted between March 13, 2006, and October 1, 2010. Data analysis was performed from June 7 to September 15, 2021. Individual analyses of time end points were concluded at the first dementia diagnosis during the follow-up period. The data were split into training and testing data sets to separately establish and validate a prediction model.Main Outcomes and MeasuresOutcomes of interest included 5-, 9-, and 13-year dementia risk. Least absolute shrinkage and selection operator and multivariate Cox proportional hazards regression models were used to identify available and practical dementia predictors. A point risk score model was developed for the individual prediction of 5-, 9-, and 13-year dementia risk.ResultsA total of 502 505 participants were selected; the population after exclusions for missing data and dementia diagnosis at baseline was 444 695 (205 187 men; mean [SD] age, 56.74 [8.18] years; 239 508 women; mean [SD] age, 56.20 [8.01] years). Dementia occurrence during the 13 years of follow-up was 0.7% for men and 0.5% for women. The C statistic of the final multivariate Cox proportional hazards regression model was 0.86 for men and 0.85 for women in the training data set, and 0.85 for men and 0.87 for women in the testing data set. Men and women shared some modifiable risk and protective factors, but they also presented independent risk factors that accounted for 31.7% of men developing dementia and 53.35% of women developing dementia according to the weighted population-attributable fraction. The total point score of the risk score model ranged from −18 to 30 in men and −17 to 30 in women. The risk score model yielded nearly 100% prediction accuracy of 13-year dementia risk both in men and women.Conclusions and RelevanceIn this diagnostic study, a practical risk score tool was developed for individual prediction of dementia risk, which may help individuals identify their potential risk profile and provide guidance on precise and timely actions to promote dementia delay or prevention.

Background Subjects with mental disorders are at a higher risk of various pandemic, but no specific studies concerning on screening and comparing the risk factors of COVID-19 for subjects with and without mental disorders, and the role of different classes of mental disorders with respect to the COVID-19. Methods This study comprised 42,264 subjects with mental disorders and 431,694 subjects without. Logistic regression was used to evaluate the associations of exposure factors with COVID-19 risk. Interaction terms were employed to explore the potential interaction effect between mental disorders and each exposure factor on COVID-19 risk. Results Mental disorders increased 1.45-fold risk of COVID-19 compared with non-mental disorders. There were significant interaction effects between mental disorders and age, sex, ethnicity, health ratings, socioeconomic adversity, lifestyle habits or comorbidities on COVID-19 risk. Subjects with and without mental disorders shared some overlapping risk factors of COVID-19, including the non-white ethnicity, socioeconomic adversity and comorbidities. Subjects without mental disorders carry some specific risk and protective factors. Among subjects with mental disorders, the COVID-19 risk was higher in subjects with a diagnosis of organic/symptomatic mental disorders, mood disorders, and neurotic, stress-related and somatoform disorders than that of their counterparts. Age, amount of alcohol consumption, BMI and Townsend deprivation showed non-linear increase with COVID-19 risk. Limitations Absence of replication. Conclusions Subjects with mental disorders are vulnerable populations to whom more attention should be paid. Public health guidance should focus on reducing the COVID-19 risk by advocating healthy lifestyle habits and preferential policies in populations with comorbidities.

Background A diagnosis of dementia in middle-aged and elder people is often complicated by physical frailty and comorbid neuropsychiatric symptoms (NPSs). Previous studies have identified NPSs as a risk factor for dementia. The aim of this study was to figure out to what extent individual NPS and certain demographic factors increased the risk of dementia in middle-aged and senior psychiatric inpatients. Methods One hundred twenty-seven middle-aged and senior patients admitted to psychiatric wards for late-onset (age ≥ 50 years) psychiatric symptoms were included and categorized into dementia or non-demented psychiatric disorders (NDPD). The patients’ demographic information and medical records were collected during the first hospitalization and subjected to statistical analyses. Results 41.73% of the registered psychiatric inpatients were diagnosed as dementia in which Alzheimer’s disease (AD) was the dominant subtype. The NDPD group consisted of nine individual diagnoses, except for schizophrenia. The frequencies of dementia inpatients increased with first episode age while that of NDPD inpatients decreased with first episode age. In the enrolled inpatients, most of dementia patients were males while females accounted for a higher proportion of NDPD patients. 58.49% of enrolled dementia inpatients presented cognitive deficit (CD) as the initial symptom while the remaining 41.51% showed NPS as initial symptom. Of the 12 NPSs, agitation and apathy greatly and significantly increased risk of dementia in psychiatric inpatients with late-onset psychiatric symptoms. Conclusions These results added evidence that the demented patients admitted to psychiatric ward are more likely to be male, older first episode age, and have characteristic NPS including aberrant motor behavior (AMB), hallucinations, agitation, irritability and apathy. Further, this study emphasized the importance of agitation and apathy of NPSs functioning as risk factors of dementia in these inpatients.

A new method, called granger causality density (GCD), could reflect the directed information flow of the epileptiform activity, which is much closely match with excitatory and inhibitory imbalance theory of epilepsy. Here, we investigated if GCD could effectively localize the Rolandic focus in 50 patients with benign childhood epilepsy with central-temporal spikes (BECTS) from 27 normal children. The BECTS were classified into ictal epileptiform discharges (IEDs; 12 females, 15 males;age, 8.15 ± 1.68 years) and non-IEDs (10 females, 13 males; age, 9.09 ± 1.98 years) subgroups depending on the presence of central-temporal spikes. Multiple correlation-modality analyses (Pearson, across-voxel and across-subject correlations) were used to calculate the couplings between the GCD maps and IEDs-related brain activation map. The individual lateralization coefficient of localize IEDs and multiple regression analysis were used to identify the reliability of the GCD method in localizing the Rolandic focus. In this study, multiple correlation-modality analyses showed that the IEDs-related brain activation map and the GCD maps had highly temporal (coefficient ׀r\= 0.56 ~ 0.65) and spatial (\r\=0.53~0.91) (r\=~ couplings. The proposed GCD method and multiple regression analyses showed consistent findings with the clinical EEG recordings in lateralization of Rolandic focus. Furthermore, the GCD method could reflect the epilepsy-related brain activity during non-IEDs substate. Therefore, the proposed GCD method has the potential to be served as an effective and reliable neuroimaging biomarker to localize the Rolandic focus of BECTS. These findings are critical for clinical early diagnosis, and may promote the progression of treatment and management of pediatric epilepsy.

Sleep-related attentional bias and instinctual craving-sleep status may be associated with value-driven selective attention network and SEEKING system. We hypothesized that the two networks might be important components and underlie etiology of inability to initiate or/and maintain sleep in patients with chronic insomnia (PIs). Our aim is to investigate whether frequency-frequency couplings(temporal and spatial coupling, and differences of a set of imaging parameters) could elevate the sensibility to characterize the two insomnia-related networks in studying their relationships with sleep parameters and post-insomnia emotions. Forty-eight PIs and 48 status-matched good sleepers were requested to complete sleep and emotion-related questionnaires. Receiver operating characteristic curve was used to calculate the discriminatory power of a set of parameters. Granger causality and mediating causality analysis were used to address the causal relationships between the two networks and sleep/emotion-related parameters. Frequency-frequency couplings could characterize the two networks with high discriminatory power (AUC, 0.951; sensitivity, 87.5%; specificity, 95.8%), which suggested that the frequency-frequency couplings could be served as a useful biomarker to address the insomnia-related brain networks. Functional deficits of the SEEKING system played decreased mediator acting in post-insomnia negative emotions (decreased frequency-frequency coupling). Functional hyperarousal of the value-driven attention network played decreased mediator acting in sleep regulation (increased frequency-frequency coupling). Granger causality analysis showed decreased causal effect connectivity between and within the two networks. The between-network causal effect connectivity segregation played decreased mediator acting in sleep regulation (decreased connectivity). These findings suggest that the functional deficits and segregation of the two systems may underlie etiology of PIs.

Subjects with mental disorders are at a higher risk of various pandemic, but no specific studies concerning on screening and comparing the risk factors of COVID-19 for subjects with and without mental disorders, and the role of different classes of mental disorders with respect to the COVID-19.This study comprised 42,264 subjects with mental disorders and 431,694 subjects without. Logistic regression was used to evaluate the associations of exposure factors with COVID-19 risk. Interaction terms were employed to explore the potential interaction effect between mental disorders and each exposure factor on COVID-19 risk.Mental disorders increased 1.45-fold risk of COVID-19 compared with non-mental disorders. There were significant interaction effects between mental disorders and age, sex, ethnicity, health ratings, socioeconomic adversity, lifestyle habits or comorbidities on COVID-19 risk. Subjects with and without mental disorders shared some overlapping risk factors of COVID-19, including the non-white ethnicity, socioeconomic adversity and comorbidities. Subjects without mental disorders carry some specific risk and protective factors. Among subjects with mental disorders, the COVID-19 risk was higher in subjects with a diagnosis of organic/symptomatic mental disorders, mood disorders, and neurotic, stress-related and somatoform disorders than that of their counterparts. Age, amount of alcohol consumption, BMI and Townsend deprivation showed non-linear increase with COVID-19 risk.Absence of replication.Subjects with mental disorders are vulnerable populations to whom more attention should be paid. Public health guidance should focus on reducing the COVID-19 risk by advocating healthy lifestyle habits and preferential policies in populations with comorbidities.

To investigate directed information flow of epileptiform activity in benign epilepsy with centrotemporal spikes (BECTS) during ictal epileptiform discharges (IEDs) and non-IEDs periods. In this multi-center study, a total of 188 subjects, including 50 BECTS and 138 normal children’s controls (NCs) from three different centers (Center 1: females/males, 38/55; mean age, 9.33 ± 2.6 years; Center 2: females/males,7/10; mean age, 8.59 ± 2.32 years; Center 3: females/males, 14/14; mean age, 13 ± 3.42 years) were recruited. The BECTS were classified into IEDs (females/males, 12/15; mean age, 8.15 ± 1.68 years) and non-IEDs (females/males, 10/13; mean age, 9.09 ± 1.98 years) subgroups depending on presence of central-temporal spikes from an EEG-fMRI examination. Three new methods, structural equation parametric modeling, dynamic causal modeling and granger causality density (GCD) were used to determine optimal network architectures for BECTS. Three multicentric NCs determined a reliable and consistent network architecture by structural equation parametric modeling method. Further analyses were used for IEDs and non-IEDs to determine the brain network architecture by structural equation parametric modeling, dynamic causal modeling and GCD, respectively. The brain network architecture of IEDs substate, non-IEDs substate and NCs are different. IEDs promoted the driving effect of the Rolandic areas with more output information flows, and increased the targeted effect of the top of pre-/post-central gyrus with more input information flows. The information flow arises from the Rolandic areas, and subsequently propagates to the top of pre-/post-central gyrus and thalamus. From non-IEDs status to IEDs status, the thalamus load may play an important role in the modulation and regulation of epileptiform activity. These findings shed new light on pathophysiological mechanism of directed localization of epileptiform activity in BECTS.

Coronavirus disease 2019 (COVID-19), a respiratory disease of unknown origin, has a high rate of morbidity and mortality. Individuals with mental disorders may have a higher risk of infection and worse clinical outcomes because of a variety of factors such as poorer general resilience and lower immune function. However, there have been no studies to date specifically investigating the risk of COVID-19 and associated mortality in these patients. This was addressed in the present study by analyzing the data of 473,958 subjects included in the UK Biobank, 14,877 of whom tested positive for COVID-19 infection. Logistic regression analysis was performed to evaluate the associations between mental disorders and risks of COVID-19 infection and associated mortality. The results showed that subjects who were diagnosed with a mental disorder had a significantly higher risk of developing COVID-19 and a worse outcome as evidenced by higher rates of COVID-19-related mortality, with the strongest effects observed for dementia. Among dementia subtypes, Alzheimer disease patients had the highest risks of COVID-19 infection (7.39-fold increase) and associated mortality (2.13-fold increase). Late-life anxiety only increased the risk of developing COVID-19 while late-life depression not only was associated with a higher risk of infection but also a worse outcome. These findings highlight the need to prioritize patients with mental disorders-especially those who experience these disorders later in life—when implementing preventive strategies such as vaccinations.

To identify altered inter-hemispheric communication between patients with primary insomnia (PIs) and good sleepers (GSs), and their relationships with sleep and emotion-related parameters. Forty-eight PIs and 48 status-matched GSs were asked to complete a number of sleep and emotion-related questionnaires. Voxel-mirrored homotopic connectivity(VMHC) and seed-based functional connectivity were used to characterize the inter-hemispheric coordination. Seven PIs were examined twice to evaluate the test-retest reliability. Support vector machine and ROC curve were applied to discriminate the two groups. Pearson correlation and mediating causality analysis were used to describe the relationships between insomnia-related brain networks and sleep/emotion-related parameters. High test-retest stability (intraclass correlation coefficient ≥ 0.8) of the VMHC maps was observed. Intra-, and inter-hemispheric coordination dysfunctions of the default mode network, visual pathways and executive control network were found. These differences received good discriminatory power to distinguish the two groups (AUC, 0.887; sensitivity, 81.3%; specificity, 87.5%). Intra-, and inter-hemispheric communication within the default mode network and visual pathways correlated with and partially mediated the insomnia-related parameters, while the executive control network correlated with post-insomnia negative emotions. Altered inter-hemispheric coordination within the default mode network and visual pathway may be identified as core predisposing or perpetuating factors in the etiology of PIs, while the executive control network may underlie the post-insomnia negative emotional symptoms. These findings may suggest that the inter-hemispheric communication might be potential neuroimaging markers to discribe underlie neurobiological mechanism of PIs and expand our understanding of the etiology of PIs.

Objective Seizure occurs when the balance between excitatory and inhibitory (E/I) inputs to neurons is perturbed, resulting in abnormal electrical activity. This study investigated whether an existing E/I imbalance in neural networks is a useful diagnostic biomarker for Rolandic epilepsy by a resting-state dynamic causal modeling-based support vector machine (rs-DCM-SVM) algorithm. Methods This multicenter study enrolled a discovery cohort (76 children with Rolandic epilepsy and 76 normal controls [NCs]) and a replication cohort (59 children with Rolandic epilepsy and 60 NCs). Spatial independent component analysis was used to seven canonical neural networks, and a total of 25 regions of interest were selected from these networks. The rs-DCM-SVM classifier was used for individual classification, consensus feature selection, and feature ranking. Results The rs-DCM-SVM classifier showed that the E/I imbalance in brain networks is a useful neuroimaging biomarker for Rolandic epilepsy, with an accuracy of 88.2% and 81.5% and an area under curve of .92 and .83 in the discovery and the replication cohorts, respectively. Consensus brain regions with the highest contributions to the classification were located within the epilepsy-related networks, indicating that this classifier was suitable. Consensus functional connection pairs with the highest contributions to the classification were associated with an excitation network loop and an inhibition network loop. The excitation loop mediated the integration of advanced cognitive networks (subcortex, dorsal attention, default mode, executive control, and salience networks), whereas the inhibition loop was involved in the segregation of sensorimotor and language networks. The two loops showed functional segregation. Significance Brain E/I imbalance has potential to serve as a biomarker for individual classification in children with Rolandic epilepsy, and might be an important mechanism for causing seizures and cognitive impairment in children with Rolandic epilepsy.

Study objectives We aimed to investigate the prospective associations of sleep phenotypes with severe intentional self-harm (ISH) in middle-aged and older adults. Methods A total of 499,159 participants (mean age: 56.55 ± 8.09 years; female: 54.4%) were recruited from the UK Biobank between 2006 and 2010 with follow-up until February 2016 in this population-based prospective study. Severe ISH was based on hospital inpatient records or a death cause of ICD-10 codes X60-X84. Patients with hospitalized diagnosis of severe ISH before the initial assessment were excluded. Sleep phenotypes, including sleep duration, chronotype, insomnia, sleepiness, and napping, were assessed at the initial assessments. Cox regression analysis was used to estimate temporal associations between sleep phenotypes and future risk of severe ISH. Results During a follow-up period of 7.04 years (SD: 0.88), 1,219 participants experienced the first hospitalization or death related to severe ISH. After adjusting for demographics, substance use, medical diseases, mental disorders, and other sleep phenotypes, short sleep duration (HR: 1.50, 95% CI: 1.23–1.83, p < .001), long sleep duration (HR: 1.56, 95% CI: 1.15–2.12, p = .004), and insomnia (usually: HR: 1.57, 95% CI: 1.31–1.89, p < .001) were significantly associated with severe ISH. Sensitivity analyses excluding participants with mental disorders preceding severe ISH yielded similar results. Conclusion The current study provides the empirical evidence of the independent prediction of sleep phenotypes, mainly insomnia, short- and long-sleep duration, for the future risk of severe ISH among middle-aged and older adults.

Primary insomnia (PIs) is highly prevalent and can lead to adverse socioeconomic impacts, but the underlying mechanism of its complex brain network impairment remains largely unknown. Functional studies are too few and diverse in methodology, which makes it difficult to glean general conclusions. To answer this question, we first used graph theory-based network analyse, together with seed-based functional connectivity approach, to characterize the topology architecture of whole-brain functional networks associated with PIs. Forty-eight subjects with PIs and 48 age/sex/education-matched good sleepers were recruited. We found PIs is associated with altered connection properties of intra-networks within the executive control network, default mode network and salience network, and inter-network between auditory language comprehension center and executive control network. These complex networks were correlated with negative emotions and insomnia severity in the PIs group. Altered connection properties of these network hubs appeared to be neural risk factors for neuropsychological changes of PIs, and might be used as potential neuroimaging markers to distinguish the PIs from the good sleepers. These findings highlight the role of functional connectivity in the pathophysiology of PIs, and may underlie the neural mechanisms of etiology of PIs.

Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke.

Psychophysiological insomnia (PI) includes arousal to sleep-related stimuli (SS), which can be treated by cognitive behavioral therapy for insomnia (CBT-I). The present study was an exploratory, prospective intervention study that aimed to explore brain response to visual SS in PI before and after CBT-I. Blood oxygen level dependent (BOLD) signal differences in response to SS and neutral stimuli (NS) were compared between 14 drug-free PI patients and 18 good sleepers (GS) using functional magnetic resonance imaging (fMRI). BOLD changes after CBT-I in patients were also examined. PI patients showed higher BOLD activation to SS in the precentral, prefrontal, fusiform, and posterior cingulate cortices before CBT-I. The increased responses to SS were reduced after CBT-I. The increased response to SS in the precentral cortex was associated with longer wake time after sleep onset (WASO), and its reduction after CBT-I was associated with improvements in WASO. Clinical improvements after CBT-I were correlated with BOLD reduction in the right insula and left paracentral cortex in response to SS. PI showed hyper-responses to SS in the precentral cortex, prefrontal cortex, and default mode network and these brain hyper-responses were normalized after CBT-I. CBT-I may exert its treatment effects on PI by reducing hyper-responses to SS in the precentral cortex and insula.

Sleep has a profound impact on memory consolidation. In this study, human participants underwent Pavlovian conditioning and extinction before we manipulated nocturnal memory consolidation by a split-night protocol with 80 healthy male participants in four groups. Recall after a second (recovery) night of sleep revealed that sleeping the first half of the night, which is dominated by slow-wave sleep, did not improve recall. Conversely, sleeping the second half of the night, which is dominated by rapid eye movement (REM) sleep, led to better discrimination between fear-relevant and neutral stimuli in behavioral and autonomic measures. Meanwhile, staying awake in the second half of the night led to an increase of discrimination between extinguished and neutral stimuli, which was paralleled by an activation of the ventromedial prefrontal cortex and amygdala. We conclude that sleep, especially REM sleep, is causal to successful consolidation of dangerous and safety stimuli and reduces return of fear after extinction. SIGNIFICANCE STATEMENT We use a split-night protocol to investigate the influence of different sleep phases on successful consolidation of conditioned fear and extinction. Such a protocol uses the fact that in humans the first half of the night is dominated by slow-wave sleep, whereas during the second half, rapid eye movement (REM) sleep is more predominant. Our data show that only REM-rich sleep during the second half of the night promoted good discrimination between fear-relevant and neutral stimuli during recall, while staying awake led to a recovery of discrimination between extinguished and neutral stimuli. This suggests that sleep following extinction contributes independently to successful extinction memory consolidation.

Objective: To identify the underlying intrinsic functional connectome changes in patients with alcohol dependence.Methods: A functional connectivity density (FCD) analysis was used to report on the functional connectivity changes in 24 male patients with alcohol dependence (age, 47.83 ± 6.93 years) and 24 healthy male subjects (age, 47.67 ± 6.99 years). We defined the voxels with a correlated threshold of r > 0.25 inside their neighborhood (radius sphere ≤ 6 mm) as shortFCD, and radius sphere > 6 mm as longFCD. We repeated the network analysis using a range of correlation r thresholds (r = 0.30, 0.35, 0.40, 0.45, 0.50, 0.6, and 0.75) to determine whether between-group differences were substantially affected by the selection of the different R-value thresholds used. A ROC curve was used to test the ability of the FCD in discriminating between the two groups. Pearson's correlation was used to evaluate the relationships between the FCD differences in brain areas and demographic characteristics.Results: The covered differences in brain areas in binarized shortFCD were larger than binarized longFCD in both groups. The intra-group FCD differences did not depend on the selection of different thresholds used. Patients with alcohol dependence were associated with the longFCD deficit in the cerebellum posterior lobe, and shortFCD deficit in the ventral system of the visual pathway and increased shortFCD in the left precentral gyrus, right salience network and right cingulate gyrus. A ROC curve demonstrated that these specific brain areas alone discriminated between the two groups with a high degree of sensitivity and specificity. In the alcohol dependence group, the cerebellum posterior lobe, visual association cortex and the salience network displayed significant correlations with demographic characteristics.Conclusions: The shortFCD analysis was more sensitive than the longFCD analysis in finding differences in the brain areas. The ventral visual pathway-cerebellar circuit deficit appeared to be altered in patients with alcohol dependence.

Xi-Jian Dai,1,2* Chun-Lei Liu,3,4* Ren-Lai Zhou,3 Hong-Han Gong,1 Bin Wu,5 Lei Gao,1 Yi-Xiang J Wang2 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 2Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, People’s Republic of China; 3Beijing Key Lab of Applied Experimental Psychology, School of Psychology, and National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China; 4School of Education, Qufu Normal University, Qufu, Shandong, People’s Republic of China; 5National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, People’s Republic of China *These authors have contributed equally to this work Objective: The aim of this study is to use resting-state functional connectivity (rsFC) and amplitude of low-frequency fluctuation (ALFF) methods to explore intrinsic default-mode network (DMN) impairment after sleep deprivation (SD) and its relationships with clinical features. Methods: Twelve healthy male subjects underwent resting-state functional magnetic resonance imaging twice: once following rested wakefulness (RW) and the other following 72 hours of total SD. Before the scans, all subjects underwent the attention network test (ANT). The independent component analysis (ICA), rsFC, and ALFF methods were used to examine intrinsic DMN impairment. Receiver operating characteristic (ROC) curve was used to distinguish SD status from RW status. Results: Compared with RW subjects, SD subjects showed a lower accuracy rate (RW =96.83%, SD =77.67%; P

Sleep-related attentional bias has been suggested to represent an important factor for the maintenance of chronic insomnia. However, little is known about potentially underlying psychological mechanisms such as threat or craving. As these are associated with distinguishable brain activation patterns, we performed a functional neuroimaging study.Functional magnetic resonance imaging was used to investigate brain reactivity to sleep-related words in 20 patients with primary insomnia according to DSM-IV criteria and 35 good sleeper controls according to Research Diagnostic Criteria. In addition, an emotional Stroop task was performed in all participants outside the scanner to investigate sleep-related attentional bias.Contrary to the hypotheses, patients with chronic insomnia did not differ from good sleeper controls in terms of threat- or craving-related brain reactivity to sleep-related words. In addition, the emotional Stroop task did not reveal any significant group difference in sleep-related attentional bias. Exploratory analyses did not show any significant correlations between brain reactivity/selective attention to sleep-related words and questionnaire scores/PSG parameters.The results from the present study call into question that attentional bias to sleep-related stimuli is a core feature of chronic insomnia. Future studies may use pictorial stimuli and larger sample sizes for investigating sleep-related information processing in insomnia.

Background Duplex kidney is a common anomaly that is frequently associated with multiple complications. Typical computed tomography urography (CTU) includes four phases (unenhanced, arterial, parenchymal and excretory) and has been suggested to considerably aid in the duplex kidney diagnosi. Unfortunately, regarding duplex kidney with prolonged dilatation, the affected parenchyma and tortuous ureters demonstrate a lack of or delayed excretory opacification. We used prolonged-delay CTU, which consists of another prolonged-delay phase (1- to 72-h delay; mean delay: 24 h) to opacify the duplicated ureters and affected parenchyma. Methods Seventeen patients (9 males and 8 females; age range: 2.5–56 y; mean age: 40.4 y) with duplex kidney were included in this study. Unenhanced scans did not find typical characteristics of duplex kidney, except for irregular perirenal morphology. Duplex kidney could not be confirmed on typical four-phase CTU, whereas it could be easily diagnosed in axial and CT-3D reconstruction using prolonged CTU (prolonged-delay phase). Results Between January 2005 and October 2010, in this review board-approved study (with waived informed consent), 17 patients (9 males and 8 females; age range: 2.5 ~ 56 y; mean age: 40.4 y) with suspicious duplex kidney underwent prolonged CTU to opacify the duplicated ureters and confirm the diagnosis. Conclusion Our results suggest the validity of prolonged CTU to aid in the evaluation of the function of the affected parenchyma and in the demonstration of urinary tract malformations.

Xiao Nie,1,* Yi Shao,2,* Si-yu Liu,3 Hai-jun Li,1 Ai-lan Wan,4 Si Nie,1 De-chang Peng,1 Xi-jian Dai1,5 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology,The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 3Medical College of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 4Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 5Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, People’s Republic of China *These authors contributed equally tothis work Objective: The aim of this study is to explore the resting-state functional connectivity (FC) differences between the paired default mode network (DMN) subregions in patients with primary insomnia (PIs).Methods: Forty-two PIs and forty-two age- and sex-matched good sleepers (GSs) were recruited. All subjects underwent the resting-state functional magnetic resonance imaging scans. The seed-based region-to-region FC method was used to evaluate the abnormal connectivity within the DMN subregions between the PIs and the GSs. Pearson correlation analysis was used to investigate the relationships between the abnormal FC strength within the paired DMN subregions and the clinical features in PIs.Results: Compared with the GSs, the PIs showed higher Pittsburgh Sleep Quality Index score, Hamilton Anxiety Rating Scale score, Hamilton Depression Rating Scale score, Self-Rating Depression Scale score, Self Rating Anxiety Scale score, Self-Rating Scale of Sleep score, and Profile of Mood States score (P

To explore the regional brain activities in patients with chronic primary insomnia (PCPIs) and their sex differences.Forty-two PCPIs (27 females, 15 males) and 42 good sleepers (GSs; 24 females, 18 males) were recruited. Six PCPIs (3 males, 3 females) were scanned twice by MRI to examine the test-retest reliability. Amplitude of low frequency fluctuation (ALFF) method was used to assess the local brain features. The mean signal values of the different ALFF areas were analyzed with a receiver operating characteristic (ROC) curve. Simple linear regression analysis was performed to investigate the relationships between clinical features and different brain areas.Both female and male PCPIs showed higher ALFF in the temporal lobe and occipital lobe, especially in female PCPIs. Female PCPIs had lower ALFF in the bilateral cerebellum posterior lobe, left dorsolateral prefrontal cortex, and bilateral limbic lobe; however, male PCPIs showed lower ALFF in the left occipital gyrus. The mean signal value of the cerebellum in female PCPIs showed negative correlations with negative emotions. Compared with male PCPIs, female PCPIs showed higher ALFF in the bilateral middle temporal gyrus and lower ALFF in the left limbic lobe. The different areas showed high test-retest stability (Clusters of contiguous volumes ≥ 1080 mm(3) with an intraclass correlation coefficient ≥ 0.80) and high degree of sensitivity and specificity.Female PCPIs showed more regional brain differences with higher and lower ALFF responses than male PCPIs. However, they shared analogous excessive hyperarousal mechanism and wide variations in aberrant brain areas.

Xi-Jian Dai,1,2 De-Chang Peng,1 Hong-Han Gong,1 Ai-Lan Wan,3 Xiao Nie,1 Hai-Jun Li,1 Yi-Xiang J Wang2 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nangchang, Jiangxi, People’s Republic of China; 2Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong; 3Department of Psychosomatic Medicine, the First Affiliated Hospital of Nangchang University, Nangchang, Jiangxi, People’s Republic of China Study objective: To prospectively explore the underlying regional homogeneity (ReHo) brain-activity deficit in patients with chronic primary insomnia (PCPIs) and its relationship with clinical features.Design: The ReHo method and Statistical Parametric Mapping 8 software were used to evaluate whether resting-state localized brain activity was modulated between PCPIs and good sleepers (GSs), and correlation analysis between altered regional brain areas and clinical features was calculated. Patients and participants: Twenty-four PCPIs (17 females, seven males) and 24 (12 females, 12 males) age-, sex-, and education-matched GSs.Measurements and results: PCPIs disturbed subjective sleep quality, split positive mood, and exacerbated negative moods. Compared with GSs, PCPIs showed higher ReHo in left fusiform gyrus, and lower ReHo in bilateral cingulate gyrus and right cerebellum anterior lobe. Compared with female GSs, female PCPIs showed higher ReHo in the left fusiform gyrus and right posterior cingulate, and lower ReHo in the left cerebellum anterior lobe and left superior frontal gyrus. Compared with male GSs, male PCPIs showed higher ReHo in the right temporal lobe and lower ReHo in the bilateral frontal lobe. The fusiform gyrus showed strong positive correlations and the frontal lobe showed negative correlations with the clinical measurements.Conclusion: The ReHo analysis is a useful noninvasive imaging tool for the detection of cerebral changes and the indexing of clinical features. The abnormal spontaneous activity areas provided important information on the neural mechanisms underlying emotion and sleep-quality impairment in PCPIs. Keywords: insomnia, regional homogeneity, functional magnetic resonance imaging, sex difference, sleep disorder, blood oxygen level-dependent, mood disorder

Previous studies suggested a remediation role of acupuncture in insomnia, and acupuncture also has been used in insomnia empirically and clinically. In this study, we employed fMRI to test the role of acupuncture in sleep deprivation (SD). Sixteen healthy volunteers (8 males) were recruited and scheduled for three fMRI scanning procedures, one following the individual’s normal sleep and received acupuncture SP6 (NOR group) and the other two after 24 h of total SD with acupuncture on SP6 (SD group) or sham (Sham group). The sessions were counterbalanced approximately two weeks apart. Acupuncture stimuli elicited significantly different activation patterns of three groups. In NOR group, the right superior temporal lobe, left inferior parietal lobule, and left postcentral gyrus were activated; in SD group, the anterior cingulate cortex, bilateral insula, left basal ganglia, and thalamus were significantly activated while, in Sham group, the bilateral thalamus and left cerebellum were activated. Different activation patterns suggest a unique role of acupuncture on SP6 in remediation of SD. SP6 elicits greater and anatomically different activations than those of sham stimuli; that is, the salience network, a unique interoceptive autonomic circuit, may indicate the mechanism underlying acupuncture in restoring sleep deprivation.

To discuss the central modulating mechanism of Sanyinjiao (SP 6) and the amplitude of low-frequency fluctuation (ALFF) differences of the functional brain regions between SP 6 and sham acupoint.Sixteen volunteers accepted right Sanyinjiao (SP 6) (SP 6 group) or right sham (sham group) acupuncture for two times after 24 h sleep deprivation (SD), there was two weeks between two acupunctures. The needle was retained for 4 minutes and the brain fMRI scanning was performed by 3.0 TMR every time. The ALFF consequent data was processed by REST. One-sample t-test and two-pair t-test were performed by SPM5.SP 6 group mainly caused ALFF change in inferior parietal lobule, posterior cingulated while sham group in precuneus, posterior cingulated. SP 6 group increased ALFF in left fusiform temporal gyrus, medial frontal gyrus with no decreased regions compared with sham group.Retaining needle dose influence the activity of the brain region during resting-state in both group, especially the mood-related regions. And its mechanism is probably that the relevant effect is carried out by regulating function to target organs of complex brain network comprised of relevant functional center and related brain region. There are differences between SP 6 and Sham acupoint.

Objective To explore the gender differences of brain regional homogeneity (ReHo) in healthy subjects during the resting-state, after normal sleep, and after sleep deprivation (SD) using functional magnetic resonance imaging (fMRI) and the ReHo method. Methods Sixteen healthy subjects (eight males and eight females) each underwent the resting-state fMRI exams twice, i.e., once after normal sleep and again after 24h's SD. According to the gender and sleep, 16 subjects were all measured twice and divided into four groups: the male control group (MC), female control group (FC), male SD group (MSD), and female SD group (FSD). The ReHo method was used to calculate and analyze the data, SPM5 software was used to perform a two-sample T -test and a two-pair T -test with a P value 3 was used to determine statistical significance. Results Compared with the MC, the MSD showed significantly higher ReHo in the right paracentral lobule (BA3/6), but in no obviously lower regions. Compared with the FC, the FSD showed significantly higher ReHo in bilateral parietal lobes (BA2/3), bilateral vision-related regions of occipital lobes (BA17/18/19), right frontal lobe (BA4/6), and lower ReHo in the right frontal lobe. Compared with the FC, the MC showed significantly higher ReHo in the left occipital lobe (BA18/19), and left temporal lobe (BA21), left frontal lobe, and lower ReHo in the right insula and in the left parietal lobe. Compared with the FSD, the MSD showed significantly higher ReHo in the left cerebellum posterior lobe (uvula/declive of vermis), left parietal lobe, and bilateral frontal lobes, and lower ReHo in the right occipital lobe (BA17) and right frontal lobe (BA4). Conclusions The differences of brain activity in the resting state can be widely found not only between the control and SD group in a same gender group, but also between the male group and female group. Thus, we should take the gender differences into consideration in future fMRI studies, especially the treatment of brain-related diseases (e.g., depression).

Sleep deprivation (SD) adversely affects brain function and is accompanied by frequency dependent changes in EEG. Recent studies have suggested that BOLD fluctuations pertain to a spatiotemporal organization with different frequencies. The present study aimed to investigate the frequency-dependent SD-related brain oscillatory activity by using the amplitude of low-frequency fluctuation (ALFF) analysis. The ALFF changes were measured across different frequencies (Slow-4: 0.027–0.073 Hz; Slow-5: 0.01–0.027 Hz; and Typical band: 0.01–0.08 Hz) in 24 h SD as compared to rested wakeful during resting-state fMRI. Sixteen volunteers underwent two fMRI sessions, once during rested wakefulness and once after 24 h of SD. SD showed prominently decreased ALFF in the right inferior parietal lobule (IPL), bilateral orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC), while increased ALFF in the visual cortex, left sensorimotor cortex and fusiform gyrus. Across the Slow-4 and Slow-5, results differed significantly in the OFC, DLPFC, thalamus and caudate in comparison to typical frequency band; and Slow-4 showed greater differences. In addition, negative correlations of behavior performance and ALFF patterns were found mainly in the right IPL across the typical frequency band. These observations provided novel insights about the physiological responses of SD, identified how it disturbs the brain rhythms, and linked SD with frequency-dependent alterations in amplitude patterns.

Hai-Jun Li,1,* Xi-Jian Dai,1,2,* Hong-Han Gong,1 Xiao Nie,1 Wei Zhang,3 De-Chang Peng1 1Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 2Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong Special Administrative Region, People’s Republic of China; 3Department of Pneumology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China *These authors contributed equally to this work Background: The majority of previous neuroimaging studies have demonstrated both structural and functional abnormalities in obstructive sleep apnea (OSA). However, few studies have focused on the regional intensity of spontaneous fluctuations during the resting state and the relationship between the abnormal properties and the behavioral performances. In the present study, we employed the amplitude of low-frequency fluctuation (ALFF) method to explore the local features of spontaneous brain activity in OSA patients (OSAs).Methods: Twenty-five untreated male severe OSAs and 25 age-matched and years-of-education-matched male good sleepers (GSs) were included in this study. The ALFF method was used to assess the local features of spontaneous brain activity. The mean signal values of the altered ALFF areas were analyzed with receiver operating characteristic curve. Partial correlation analysis was used to explore the relationship between the observed mean ALFF values of the different areas and the behavioral performances.Results: Compared with GSs, OSAs had significantly higher scores for body mass index, apnea–hypopnea index, arterial oxygen saturation

Central nervous system (CNS) cryptococcosis is an opportunistic fungal infection that typically occurs in patients with reduced immunological function, such as patients with AIDS, patients receiving organ transplants, or patients receiving corticosteroid and immunosuppressive therapy. CNS cryptococcosis rarely occurs in immunocompetent patients. CNS cryptococcosis is characterized by meningitis and encephalitis and occasionally forms isolated granulomas. Isolated cerebellar cryptococcoma is a rare condition, especially in immunocompetent patients, and the misdiagnosis rate is high. A definite diagnosis must be based on pathology. To raise awareness of this disease, the clinical data of a patient with cryptococcomas in the right side of the cerebellum are reported.