Abnormal intrinsic functional hubs in alcohol dependence: evidence from a voxelwise degree centrality analysis

Substance use disorders are characterised by increased voxel-wise intrinsic measures in sensorimotor cortices: An ALE meta-analysis

Substance use disorders (SUDs) are severe psychiatric illnesses. Seed region and independent component analyses are currently the dominant connectivity measures but carry the risk of false negatives due to selection. They can be complemented by a data-driven and whole-brain usage of voxel-wise intrinsic measures (VIMs). We meta-analytically integrated VIMs, namely regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), voxel-mirrored homotopy connectivity (VMHC) and degree centrality (DC) across different SUDs using the Activation Likelihood Estimation (ALE) algorithm, functionally decoded emerging clusters, and analysed their connectivity profiles. Our systematic search identified 51 studies including 1439 SUD participants. Although no overall convergent pattern of alterations across VIMs in SUDs was found, sensitivity analyses demonstrated two ALE-derived clusters of increased ReHo and ALFF in SUDs, which peaked in the left pre- and postcentral cortices. Subsequent analyses showed their involvement in action execution, somesthesis, finger tapping and vibrotactile monitoring/discrimination. Their numerous clinical correlates across included studies highlight the under-discussed role of sensorimotor cortices in SUD, urging a more attentive exploration of their clinical significance.

Resting-state brain plasticity is associated with the severity in cervical spondylotic myelopathy

OBJECTIVE

To investigate the brain mechanism of non-correspondence between imaging presentations and clinical symptoms in cervical spondylotic myelopathy (CSM) patients and to test the utility of brain imaging biomarkers for predicting prognosis of CSM.

METHODS

Forty patients with CSM (22 mild-moderate CSM, 18 severe CSM) and 25 healthy controls (HCs) were recruited for rs-fMRI and cervical spinal cord diffusion tensor imaging (DTI) scans. DTI at the spinal cord (level C2/3) with fractional anisotropy (FA) and degree centrality (DC) were recorded. Then one-way analysis of covariance (ANCOVA) was conducted to detect the group differences in the DC and FA values across the three groups. Pearson correlation analysis was then separately performed between JOA with FA and DC.

RESULTS

Among them, degree centrality value of left middle temporal gyrus exhibited a progressive increase in CSM groups compared with HCs, the DC value in severe CSM group was higher compared with mild-moderate CSM group. (P < 0.05), and the DC values of the right superior temporal gyrus and precuneus showed a decrease after increase. Among them, DC values in the area of precuneus in severe CSM group were significantly lower than those in mild-moderate CSM and HCs. (P < 0.05). The fractional anisotropy (FA) values of the level C2/3 showed a progressive decrease in different clinical stages, that severe CSM group was the lowest, significantly lower than those in mild-moderate CSM and HCs (P < 0.05). There was negative correlation between DC value of left middle temporal gyrus and JOA scores (P < 0.001), and the FA values of dorsal column in the level C2/3 positively correlated with the JOA scores (P < 0.001).

CONCLUSION

Structural and functional changes have taken place in the cervical spinal cord and brain of CSM patients. The Brain reorganization plays an important role in maintaining the symptoms and signs of CSM, aberrant DC values in the left middle temporal gyrus may be the possible mechanism of inconsistency between imaging findings and clinical symptoms. Degree centrality is a potentially useful prognostic functional biomarker in cervical spondylotic myelopathy.

Alterations in degree centrality and functional connectivity in tension-type headache: a resting-state fMRI study

Previous studies have provided evidence of structural and functional changes in the brains of patients with tension-type headache (TTH). However, investigations of functional connectivity alterations in TTH have been inconclusive. The present study aimed to investigate abnormal intrinsic functional connectivity patterns in patients with TTH through the voxel-wise degree centrality (DC) method as well as functional connectivity (FC) analysis. A total of 33 patients with TTH and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and were enrolled in the final study. The voxel-wise DC method was performed to quantify abnormalities in the local functional connectivity hubs. Nodes with abnormal DC were used as seeds for further FC analysis to evaluate alterations in functional connectivity patterns. In addition, correlational analyses were performed between abnormal DC and FC values and clinical features. Compared with HCs, patients with TTH had higher DC values in the left middle temporal gyrus (MTG.L) and lower DC values in the left anterior cingulate and paracingulate gyri (ACG.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Seed-based FC analyses revealed that patients with TTH showed greater connections between ACG.L and the right cerebellum lobule IX (CR-IX.R), and smaller connections between ACG.L and ACG.L. The MTG.L showed increased FC with the ACG.L, and decreased FC with the right caudate nucleus (CAU.R) and left precuneus (PCUN.L) (GRF, voxel-wise p < 0.05, cluster-wise p < 0.05, two-tailed). Additionally, the DC value of the MTG.L was negatively correlated with the DASS-depression score (p = 0.046, r=-0.350). This preliminary study provides important insights into the pathophysiological mechanisms of TTH.

Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders

BACKGROUND

Magnetic resonance imaging provides noninvasive tools to investigate alcohol use disorder (AUD) and nicotine use disorder (NUD) and neural phenotypes for genetic studies. A data-driven transdiagnostic approach could provide a new perspective on the neurobiology of AUD and NUD.

METHODS

Using samples of individuals with AUD (n = 140), individuals with NUD (n = 249), and healthy control participants (n = 461) from the UK Biobank, we integrated clinical, neuroimaging, and genetic markers to identify biotypes of AUD and NUD. We partitioned participants with AUD and NUD based on resting-state functional connectivity (FC) features associated with clinical metrics. A multitask artificial neural network was trained to evaluate the cluster-defined biotypes and jointly infer AUD and NUD diagnoses.

RESULTS

Three biotypes-primary NUD, mixed NUD/AUD with depression and anxiety, and mixed AUD/NUD-were identified. Multitask classifiers incorporating biotype knowledge achieved higher area under the curve (AUD: 0.76, NUD: 0.74) than single-task classifiers without biotype differentiation (AUD: 0.61, NUD: 0.64). Cerebellar FC features were important in distinguishing the 3 biotypes. The biotype of mixed NUD/AUD with depression and anxiety demonstrated the largest number of FC features (n = 5), all related to the visual cortex, that significantly differed from healthy control participants and were validated in a replication sample (p < .05). A polymorphism in TNRC6A was associated with the mixed AUD/NUD biotype in both the discovery (p = 7.3 × 10-5) and replication (p = 4.2 × 10-2) sets.

CONCLUSIONS

Biotyping and multitask learning using FC features can characterize the clinical and genetic profiles of AUD and NUD and help identify cerebellar and visual circuit markers to differentiate the AUD/NUD group from the healthy control group. These markers support a new growing body of literature.

A voxel-level resting-state fMRI study on patients with alcohol use disorders based on a power spectrum slope analysis method

Background

Earlier neuroimaging investigations showed that abnormal brain activity in patients with alcohol use disorder (AUD) was frequency dependent. However, there is lacking of a comprehensive method to capture the amplitude of multi-frequency bands directly. Here, we used a new method, the power spectrum slope (PSS) to explore abnormal spontaneous activity of brain in patients with AUD.

Methods

Thirty-three AUD patients and 29 healthy controls (HCs) enrolled in this study. The coefficient b and the power-law slope b' were calculated and compared between two groups. We also used the receiver operating characteristic (ROC) curve to examine the ability of the PSS analysis to distinguish between AUD and HCs. We next examined the correlation between PSS difference in the brain areas and the severity of alcohol dependence.

Results

Thirty AUD patients and 26 HCs were retained after head motion correction. The two metrics of PSS values increased in the left precentral gyrus in AUD patients. The area under the curve values of PSS differences in the specific brain area were respectively 0.836 and 0.844, with sensitivities of 86.7% and 83.3% and specificities of 73.1% and 76.9%. The Michigan Alcoholism Screening Test (MAST) and Alcohol drinking scale (ADS) scores were not significantly correlated with the PSS values in the specific brain area.

Conclusion

As a novel method, the PSS can well detect abnormal local brain activity in the AUD patients and may offer new insights for future fMRI studies.

Alterations of brain activity in patients with alcohol use disorder: a resting-state fMRI study

BACKGROUND

Alcohol use disorder (AUD) has a negative impact on one's health and wastes a lot of societal resources since it damages one's brain tissue. Yet the knowledge of the neural mechanisms underlying alcohol addiction still remains limited. This study aims to investigate the neural mechanisms underlying alcohol addiction by using voxel-wise binarized degree centrality (DC), weighted DC and functional connectivity (FC) methods to analyze brain network activity in individuals with AUD.

METHODS

Thirty-three AUD patients and 29 healthy controls (HC) participated in this study. Binarized and weighted DC approach coupled with a second seed-based FC algorithm was used to assess the abnormal intrinsic hub features in AUD. We also examined the correlation between changes in functional network nodes and the severity of alcohol dependence.

RESULTS

Thirty AUD patients and 26 HC were retained after head motion correction. The spatial distribution maps of the binarized DC and weighted DC for the AUD and HC groups were roughly similar. In comparison to HC, the AUD group had decreased binarized DC and decreased weighted DC in the left precentral gyrus (PreCG) and the left inferior parietal lobule (IPL). Significantly different brain regions in the DC analysis were defined as seed points in the FC analysis. Compared with HC, changes in FC within the right inferior temporal gyrus (ITG), right middle temporal gyrus (MTG), left dorsolateral superior frontal gyrus (SFGdor), bilateral IPL, left precuneus (PCUN), left lingual gyrus (LING), right cerebellum_crus1/ITG/inferior occipital gyrus (IOG) and right superior parietal gyrus (SPG) were observed. The correlation analysis revealed that FC of right MTG-right PreCG was negatively correlated with MAST scores, and FC of right IPL-left IPL was positively correlated with ADS scores.

CONCLUSIONS

Alcohol use disorder is associated with aberrant regional activities in multiple brain areas. Binarized DC, weighted DC and FC analyses may be useful biological indicators for the detection of regional brain activities in patients with AUD. Intergroup differences in FC have also been observed in AUD patients, and these variations were connected to the severity of the symptoms. The AUD patients with lower FC value of the right IPL - left IPL has a lighter dependence on alcohol. This difference in symptom severity may be a compensation for cognitive impairment, indicating a difference in pathological pathways. Future AUD research will now have a fresh path thanks to these discoveries.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Relapse risk revealed by degree centrality and cluster analysis in heroin addicts undergoing methadone maintenance treatment

BACKGROUND

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

METHODS

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

RESULTS

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical-striatal-thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

CONCLUSION

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients’ cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

Altered brain connectivity during visual stimulation in schizophrenia

Schizophrenia (SCZ) can be described as a functional dysconnectivity syndrome that affects brain connectivity and circuitry. However, little is known about how sensory stimulation modulates network parameters in schizophrenia, such as their small-worldness (SW) during visual processing. To address this question, we applied graph theory algorithms to multi-electrode EEG recordings obtained during visual stimulation with a checkerboard pattern-reversal stimulus. Twenty-six volunteers participated in the study, 13 diagnosed with schizophrenia (SCZ; mean age = 38.3 years; SD = 9.61 years) and 13 healthy controls (HC; mean age = 28.92 years; SD = 12.92 years). The visually evoked potential (VEP) showed a global amplitude decrease (p < 0.05) for SCZ patients as opposed to HC but no differences in latency (p > 0.05). As a signature of functional connectivity, graph measures were obtained from the Magnitude-Squared Coherence between signals from pairs of occipital electrodes, separately for the alpha (8-13 Hz) and low-gamma (36-55 Hz) bands. For the alpha band, there was a significant effect of the visual stimulus on all measures (p < 0.05) but no group interaction between SCZ and HZ (p > 0.05). For the low-gamma spectrum, both groups showed a decrease of Characteristic Path Length (L) during visual stimulation (p < 0.05), but, contrary to the HC group, only SCZ significantly lowered their small-world (SW) connectivity index during visual stimulation (SCZ p < 0.05; HC p > 0.05). This indicates dysconnectivity of the functional network in the low-gamma band of SCZ during stimulation, which might indirectly reflect an altered ability to react to new sensory input in patients. These results provide novel evidence about a possible electrophysiological signature of the global deficits revealed by the application of graph theory onto electroencephalography in schizophrenia.

Predicting the severity of internet gaming disorder with resting-state brain features: A multi-voxel pattern analysis

BACKGROUND

Internet gaming disorder (IGD) has become a worldwide mental health concern; however, the neural mechanism underlying this disorder remains unclear. Multivoxel pattern analysis (MVPA), a newly developed data-driven approach, can be used to investigate the neural features of IGD based on massive neural data.

METHODS

Resting-state fMRI data from four hundred and two participants with varying levels of IGD severity were recruited. Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF) were calculated and subsequently decoded by applying MVPA. The highly weighted regions in both predictive models were selected as regions of interest for further graph theory and Granger causality analysis (GCA) to explore how they affect IGD severity.

RESULTS

The results revealed that the neural patterns of ReHo and ALFF can independently and significantly predict IGD severity. The highly weighted regions that contributed to both predictive models were the right precentral gyrus and left postcentral gyrus. Moreover, topological properties of the right precentral gyrus were significantly correlated with IGD severity; further GCA revealed effective connectivity from the right precentral gyrus to left precentral gyrus and dorsal anterior cingulate cortex, both of which were significantly associated with IGD severity.

CONCLUSIONS

The present study demonstrated that IGD has distinctive neural patterns, and this pattern could be found by machine learning. In addition, the neural features in the right precentral gyrus play a key role in predicting IGD severity. The current study revealed the neural features of IGD and provided a potential target for IGD interventions using brain modulation.

Alcohol-induced brain deficit in alcohol dependence

Although numerous adverse effects of alcohol addiction on health, behavior, and brain function were widely reported, the neurobiological mechanism of alcohol dependence remains largely unknown. In this study, a total of twenty-nine patients with alcohol dependence and twenty-nine status-matched normal controls (NCs) were recruited. Percent amplitude of fluctuation (PerAF) was applied to identify alcohol-related brain activity deficits. We found that alcohol dependence was associated with widespread differences in the left orbitofrontal cortex, right higher visual cortex, right supramarginal gyrus, right postcentral gyrus, and bilateral cerebellum posterior lobe with decreased PerAF, but no brain areas with increased PerAF differences were found. ROC curve showed that decreased PerAF revealed extremely high discriminatory power with a high AUC value of 0.953, as well as a high degree of sensitivity (96.6%) and specificity (86.2%), in distinguishing patients with alcohol dependence from NCs. In the alcohol dependence group, the amount of daily alcohol consumption showed significant negative correlations with the right cerebellum posterior lobe and right higher visual cortex. These findings suggest that the cerebellar-visual-orbitofrontal circuit was disturbed by alcohol dependence. The proposed new method of PerAF may be served as a potential biomarker to identify the regional brain activity deficits of alcohol dependence.

Altered dynamic brain activity and its association with memory decline after night shift-related sleep deprivation in nurses

AIMS AND OBJECTIVES

To investigate, for the first time, aberrant time-varying local brain activity in nurses following night shift-related sleep deprivation (SD) and its association with memory decline.

BACKGROUND

Prior studies have elucidated alterations in static local brain activity resulting from SD in the occupations outside medical profession.

DESIGN

A longitudinal study followed the STROBE recommendations.

METHODS

Twenty female nurses underwent resting-state functional magnetic resonance imaging and memory function assessment (by Complex Figure Test (CFT) and the California Verbal Learning Test, Second Edition (CVLT-II)) twice, once in a rested wakefulness (RW) state and another after SD. By combining the sliding-window approach and amplitude of low-frequency fluctuation (ALFF) analysis, the dynamic ALFF (dALFF) variability was calculated to reflect the characteristics of dynamic local brain activity.

RESULTS

Poor performance on the CFT and CVLT-II was observed in nurses with night shift-related SD. Reduced dALFF variability was found in a set of cognition-related brain regions (including the medial/middle/superior frontal gyrus, anterior/posterior cingulate gyrus, precuneus, angular gyrus, orbitofrontal and subgenual areas, and posterior cerebellum lobe), while increased dALFF variability was observed in the somatosensory-related, visual and auditory regions. SD-related dALFF variability alterations correlated with changes in subjects' performance on the CFT and CVLT-II.

CONCLUSIONS

Night shift-related SD disturbed dynamic brain activity in high cognitive regions and induced compensatory reactions in primary perceptual cortex. Identifying dALFF variability abnormalities may broaden our understanding of neural substrates underlying SD-related cognitive alterations, especially memory dysfunction.

RELEVANCE TO CLINICAL PRACTICE

Night shift-related SD is as an important occupational hazard affecting brain function in nurses. The effective countermeasure addressing the adverse outcomes of SD should be advocated for nurses.

PATIENT OR PUBLIC CONTRIBUTION

Patients or public were not involved in the design and implementation of the study or the analysis and interpretation of the data.

Identification of key genes with prognostic value in gastric cancer by bioinformatics analysis

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis.

Methods: The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein–protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets.

Results: In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (MYLK, MYL9, LUM, and CAV1) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients.

Conclusion: We found that MYLK, MYL9, LUM, and CAV1 are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.

Molecular mechanism by which CDCP1 promotes proneural-mesenchymal transformation in primary glioblastoma

Background

Compared with the proneural (PN) subtype of glioblastoma (GBM), the mesenchymal (MES) subtype is more invasive and immune evasive and is closely related to poor prognosis. Here, we used transcriptome data and experimental evidence to indicate that CUB domain-containing protein 1 (CDCP1) is a novel regulator that facilitates the transformation of PN-GBM to MES-GBM.

Methods

The mRNA expression data of CDCP1 in glioma were collected from the TCGA, CGGA and GEO databases, and in vitro experiments verified CDCP1 expression in glioma tissue samples. Independent prognostic analysis revealed the correlation of the CDCP1 expression level and patient survival. Bioinformatics analysis and experiments verified the biological function of CDCP1. Multivariate proportional hazards models and a PPI network were used to select key genes. A prognostic risk model for predicting the survival of glioma patients was constructed based on the selected genes.

Results

The results showed that the expression of CDCP1 increased with increasing tumor grade and that the overexpression of CDCP1 correlated with a poor prognosis. CDCP1 was highly expressed in MES-GBM but weakly expressed in PN-GBM. The risk model (considering CDCP1 combined with CD44 and ITGAM expression) could represent a tool for predicting survival and prognosis in glioma patients.

Conclusions

Our study indicates that CDCP1 plays an important role in facilitating the transformation of PN-GBM to MES-GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02373-1.

Anomalies in global network connectivity associated with early recovery from alcohol dependence: A network transcranial magnetic stimulation and electroencephalography study

Although previous research in alcohol dependent populations identified alterations within local structures of the addiction ‘reward’ circuitry, there is limited research into global features of this network, especially in early recovery. Transcranial magnetic stimulation (TMS) is capable of non‐invasively perturbing the brain network while electroencephalography (EEG) measures the network response. The current study is the first to apply a TMS inhibitory paradigm while utilising network science (graph theory) to quantify network anomalies associated with alcohol dependence. Eleven individuals with alcohol‐dependence (ALD) in early recovery and 16 healthy controls (HC) were administered 75 single pulses and 75 paired‐pulses (inhibitory paradigm) to both the left and right prefrontal cortex (PFC). For each participant, Pearson cross‐correlation was applied to the EEG data and correlation matrices constructed. Global network measures (mean degree, clustering coefficient, local efficiency and global efficiency) were extracted for comparison between groups. Following administration of the inhibitory paired‐pulse TMS to the left PFC, the ALD group exhibited altered mean degree, clustering coefficient, local efficiency and global efficiency compared to HC. Decreases in local efficiency increased the prediction of being in the ALD group, while all network metrics (following paired‐pulse left TMS) were able to adequately discriminate between the groups. In the ALD group, reduced mean degree and global clustering was associated with increased severity of past alcohol use. Our study provides preliminary evidence of altered network topology in patients with alcohol dependence in early recovery. Network anomalies were predictive of high alcohol use and correlated with clinical features of alcohol dependence. Further research using this novel brain mapping technique may identify useful network biomarkers of alcohol dependence and recovery.

Glucose Fluctuations Are Linked to Disrupted Brain Functional Architecture and Cognitive Impairment

BACKGROUND

Type 2 diabetes mellitus (T2DM) accelerates cognitive decline, which is believed to be triggered by aberrant neural activity.

OBJECTIVE

To explore how glucose fluctuations impact brain functional architecture and cognition in T2DM patients.

METHODS

T2DM patients were divided according to glycemic variability, forming two categories: patients with fluctuating glucose levels and patients with stable glucose levels. Degree centrality (DC) was calculated within the cerebral gray matter of each participant and was compared among the two patient groups and a healthy control group. The relationships between glucose fluctuations and aberrant DC and cognitive performance, as well as the relationship between aberrant DC and cognitive performance, were further explored.

RESULTS

Compared with T2DM patients with stable glucose levels, T2DM patients with fluctuating glucose levels exhibited significantly worse performance on the Montreal Cognitive Assessment, Trail Making Test-B (TMT-B), and verbal fluency test (VFT), as well as significant decreases in DC in certain regions, most of which were within the default mode network. In the combined T2DM group, the mean amplitude of glycemic excursions (MAGE) was positively correlated with TMT-B scores and negatively correlated with VFT scores. Moreover, the MAGE was negatively correlated with DC in the left medial prefrontal cortex (mPFC). In addition, TMT-B scores were negatively correlated with reduced DC in the left mPFC.

CONCLUSION

These findings further contribute to the mounting evidence of the effects of glycemic variability on the diabetic brain. Tightened control of glucose fluctuations might prevent cognitive decline and changes in brain functional architecture in T2DM individuals.

Altered Functional Brain Network in Systemic Lupus Erythematosus Patients Without Overt Neuropsychiatric Symptoms Based on Resting-State Functional Magnetic Resonance Imaging and Multivariate Pattern Analysis

Objective: This study aims to investigate the alterations in functional brain network in systemic lupus erythematosus patients without overt neuropsychiatric symptoms [neuropsychiatric systemic lupus erythematosus (non-NPSLE)] from the perspective of degree centrality (DC) and functional connectivity (FC) using resting-state functional magnetic resonance imaging (MRI) and multivariate pattern analysis (MVPA) approach.

Methods: DC analysis was performed based on the resting-state functional MRI data derived from 47 non-NPSLE patients and 47 healthy controls (HCs). Nodes with abnormal DC were utilized as seeds for further FC analysis. The correlation between MRI variables and clinical or neuropsychological data was analyzed using Pearson correlation analysis. Finally, MVPA classification based on DC was performed.

Results: When compared with the HCs, the non-NPSLE patients exhibited remarkably higher DC in the bilateral hippocampus (HIP), right insula (INS), and lower DC in the left superior parietal gyrus. Furthermore, the patients displayed significantly higher FC between the left HIP and the left INS/left dorsolateral middle frontal gyrus/left supramarginal gyrus and higher FC between the right HIP and the right middle temporal gyrus/right dorsolateral middle frontal gyrus/right dorsolateral inferior frontal gyrus/right supramarginal gyrus (all imaging variables mentioned earlier underwent cluster-level false discovery rate corrections, the voxel threshold was p < 0.001, cluster threshold was p < 0.05). Correlation analysis revealed significantly negative correlations between DC values of the right INS and disease activity and the DC values of the right HIP and the Montreal Cognitive Assessment scores. The accuracy, sensitivity, and specificity of MVPA classification based on DC were 72.34, 63.83, and 80.85%, respectively. The most discriminative power brain regions were chiefly located within the temporal, parietal, and frontal regions.

Conclusion: Patients with non-NPSLE exhibited abnormal DC and FC in the brain network. MVPA based on DC possessed commendable classification ability. Our study may provide a novel perspective on the neuropathological mechanisms underlying subclinical brain damage in non-NPSLE.

Abnormal degree centrality in lifelong premature ejaculation patients: an fMRI study

Lifelong premature ejaculation (PE) is one of the most prevalent male sexual dysfunctions. It is still not well known about the possible neural mechanisms of lifelong PE. This study tried to investigate the abnormal characteristics of brain functional networks of lifelong PE and to assess relationships of PE-related functional abnormalities with clinical symptoms. Functional magnetic resonance imaging (fMRI) data and clinical symptoms were collected from 45 lifelong PE patients and 37 healthy controls (HCs) since 2016, including disease and sexual life history, intravaginal ejaculatory latency time measured by stopwatch and other scales. The degree centrality (DC) approach were applied to distinguish altered brain functions between the two groups (p < 0.05, false discovery rate corrected). Correlation analysis was then performed to examine relationships between the imaging findings and clinical symptoms (p < 0.05, Bonferroni corrected). Results showed that compared with HCs, lifelong PE patients had increased DC value in the medial prefrontal cortex (mPFC), precuneus and primary somatosensory cortex (SI) as well as decreased DC value in the insula and orbitofrontal cortex. After controlling for anxiety and depression levels, the significant difference in the mPFC was not found. The DC value in the SI positively correlated with premature ejaculation diagnostic tool (PEDT) score in the patients. The present findings indicate that lifelong PE patients have altered DC in brain regions involved in sensation, motivation and inhibitory control processing. Our study may improve our understanding and provide a new sight into the further research of lifelong PE.

Neural correlates of alcohol use disorder severity among nontreatment-seeking heavy drinkers: An examination of the incentive salience and negative emotionality domains of the alcohol and addiction research domain criteria

BACKGROUND

The Alcohol and Addiction Research Domain Criteria (AARDoC) propose that alcohol use disorder is associated with neural dysfunction in three primary domains: incentive salience, negative emotionality, and executive function. Prior studies in heavy drinking samples have examined brain activation changes associated with alcohol and negative affect cues, representing the incentive salience and negative emotionality domains, respectively. Yet studies examining such cue-induced changes in functional connectivity (FC) are relatively sparse.

METHODS

Nontreatment-seeking heavy drinking adults (N = 149, 56.0% male, 48.6% non-white, mean age 34.8 years (SD = 10.0)) underwent functional magnetic resonance imaging during presentation of alcohol, negative, and neutral pictures. We focused on FC changes involving the nucleus accumbens and amygdala in addition to activation and FC correlations with self-reported AUD severity.

RESULTS

For alcohol cues versus neutral cues, we observed accumbens FC changes in the cerebellum and prefrontal cortex (PFC), and amygdala FC changes with occipital, parietal, and hippocampal regions. AUD severity correlated positively with activation in the cerebellum (p < 0.05), accumbens FC in the cingulate gyri, somatosensory gyri, and cerebellum (p < 0.05), and with amygdala FC in the PFC and inferior parietal lobule (p < 0.05) for alcohol cues versus neutral cues. For negative cues versus neutral cues, we observed accumbens FC changes in the lateral temporal, occipital, and parietal regions, and amygdala FC changes in the fusiform and lingual gyri (p < 0.05).

CONCLUSIONS

The present findings provide empirical support for the AARDoC domains of incentive salience and negative emotionality and indicate that AUD severity is associated with salience and response control for reward cues. When covarying for differences in nonalcohol substance use and mood disorder diagnoses, AUD severity was also associated with emotional reactivity for negative cues.

Altered brain intrinsic functional hubs and connectivity associated with relapse risk in heroin dependents undergoing methadone maintenance treatment: A resting-state fMRI study

BACKGROUND

The neural substrates underlying the relapse behavior of heroin dependents (HD) who received long-term methadone maintenance treatment (MMT) have yet to be thoroughly expounded. This study investigated the relapse-related intrinsic functional hubs of HD and their functional integration feature at whole brain network level.

METHODS

57 male HD receiving MMT and 49 matched healthy controls (HC) were enrolled. All of the subjects received resting-state functional magnetic resonance imaging scan. And the 57 patients were assigned a 26-month follow-up for collecting illegal drug use information. Of them, 11 were non-relapsers and 46 relapsers. We analyzed the voxel-based degree centrality (DC) to reveal the differences in nodule centrality between HD and HC, conducted Pearson partial-correlation analysis to confirm the relationship between relapse frequency and DC value of the nodes with significant intergroup differences, and finally compared the functional connectivity (FC) of the relapse-related hubs between non-relapsers and relapsers.

RESULTS

We found the DC values of right insula and left nucleus accumbens (NAc) were negatively correlated with relapse frequency. Compared with the non-relapsers, the relapsers had a significant decreased FC between left NAc and inhibitory control circuitry, including left dorsolateral prefrontal cortex, left inferior frontal gyrus and motor regions.

CONCLUSIONS

These findings suggest that the neural substrates of relapse vulnerability in HD undergoing MMT are the intrinsic functional hubs of introceptive and reward systems and the latter modulates relapse behavior via interaction with inhibitory control circuit.

A whole-brain modeling approach to identify individual and group variations in functional connectivity

Resting-state functional connectivity is an important and widely used measure of individual and group differences. Yet, extant statistical methods are limited to linking covariates with variations in functional connectivity across subjects, especially at the voxel-wise level of the whole brain. This paper introduces a modeling approach that regresses whole-brain functional connectivity on covariates. Our approach is a mesoscale approach that enables identification of brain subnetworks. These subnetworks are composite of spatially independent components discovered by a dimension reduction approach (such as whole-brain group ICA) and covariate-related projections determined by the covariate-assisted principal regression, a recently introduced covariance matrix regression method. We demonstrate the efficacy of this approach using a resting-state fMRI dataset of a medium-sized cohort of subjects obtained from the Human Connectome Project. The results suggest that the approach may improve statistical power in detecting interaction effects of gender and alcohol on whole-brain functional connectivity, and in identifying the brain areas contributing significantly to the covariate-related differences in functional connectivity.

Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis

Gastric cancer (GC) is one of the most common malignancies of the digestive system with few genetic markers for its early detection and prevention. In this study, differentially expressed genes (DEGs) were analyzed using GEO2R from GSE54129 and GSE13911 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, STRING, and Cytoscape. Finally, we performed survival analysis of key genes through the Kaplan-Meier plotter. A total of 1034 DEGs were identified in GC. GO and KEGG results showed that DEGs mainly enriched in plasma membrane, cell adhesion, and PI3K-Akt signaling pathway. Subsequently, the PPI network with 44 nodes and 333 edges was constructed, and 18 candidate genes in the network were focused on by centrality analysis and module analysis. Furthermore, data showed that high expressions of fibronectin 1(FN1), the tissue inhibitor of metalloproteinases 1 (TIMP1), secreted phosphoprotein 1 (SPP1), apolipoprotein E (APOE), and versican (VCAN) were related to poor overall survivals in GC patients. In summary, this study suggests that FN1, TIMP1, SPP1, APOE, and VCAN may act as the key genes in GC.

Behavioural cue reactivity to alcohol-related and non-alcohol-related stimuli among individuals with alcohol use disorder: An fMRI study with a visual task

Patients with alcohol use disorder (AUD) have difficulty controlling their alcohol cravings and thus exhibit increased use and early relapse. Although patients tend to respond more strongly to alcohol-related images than to non-alcohol-related images, few researchers have examined the factors that modulate cravings. Here, we examined whole-brain blood oxygen level-dependent (BOLD) responses to behavioural cues in individuals with AUD and in healthy controls (HCs). The participants included 24 patients with AUD and 15 HCs. We presented visual cues consisting of four beverage-related images (juice, drinking juice, sake, and drinking sake), and the cue reactivity of AUD participants was contrasted with that of HC participants. Multiple comparisons revealed that the AUD group had lower BOLD responses than the HC group in the left precuneus (p = 0.036) and the left posterior cingulate cortex (PCC) (p = 0.044) to images of drinking juice and higher BOLD responses than the HC group in the left PCC (p = 0.044) to images of drinking sake. Furthermore, compared to the HCs, the AUD patients had decreased BOLD responses associated with cue reactivity to drinking juice in the left precuneus during the periods from 15 to 18 s (p = 0.004, df = 37) and 18 to 21 s (p = 0.002, df = 37). Our findings suggest that HCs and AUD patients differ in their responses not to images of alcoholic beverages but to images related to alcohol-drinking behaviour. Thus, these patients appear to have different patterns of brain activity. This information may aid clinicians in developing treatments for patients with AUD.

Abnormal degree centrality in delayed encephalopathy after carbon monoxide poisoning: a resting-state fMRI study

Purpose

To explore neuropathologic mechanisms in functional brain regions in patients with delayed encephalopathy after carbon monoxide poisoning (DEACMP) from the perspective of the brain network nodes by resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

The fMRI and cognitive assessments were performed in 25 patients with DEACMP and 25 age-, sex- and education-matched healthy controls (HCs). Data analysis was performed via the degree centrality (DC) method. Then, the associations between the cognitive assessments and DC in the identified abnormal brain regions were assessed by using a correlation analysis.

Results

Compared with the HCs, the DEACMP patients displayed significantly decreased DC values in the right superior frontal gyrus, right precentral gyrus, right angular gyrus, right marginal gyrus, right hippocampus, and left thalamus but increased DC values in the right inferior frontal gyrus, right cingulate gyrus, left superior temporal gyrus, left medial temporal gyrus, right lingual gyrus, and right posterior cerebellar lobe, pons, and midbrain (GRF correction, voxel P value < 0.001, cluster P value < 0.01). The correlation analysis in the DEACMP group revealed that there was a negative correlation between the DC values in the right hippocampus and MMSE scores, whereas a positive correlation was observed in the right cingulate gyrus.

Conclusions

Patients with DEACMP exhibited abnormal degree centrality in the brain network. This finding may provide a new approach for examining the neuropathologic mechanisms underlying DEACMP.

Relapsing-Remitting Multiple Sclerosis Is Associated With Regional Brain Activity Deficits in Motor- and Cognitive-Related Brain Areas

Objective: To identify the abnormal regional spontaneous brain activity associated with relapsing-remitting multiple sclerosis (RRMS) using fractional amplitude of low-frequency fluctuation (fALFF) analysis and their relationships with clinical features.

Methods: A total of 26 RRMS (11 males, 15 females; age, 36.58 ± 10.82 years) and 27 status-matched healthy group (HGs; 12 males, 15 females; age, 35.85 ± 12.05 years) underwent an Expanded Disability Status Scale (EDSS) examination. fALFF was applied to evaluate the abnormal regional brain activity associated with RRMS. Pearson's correlation analysis was applied to calculate the correlations between the signal values of brain areas that exhibited abnormal fALFF values and clinical features. Receiver operating characteristic (ROC) curve was performed to evaluate the sensitivity and specificity of those altered brain areas to distinguish between RRMS and HGs.

Results: Compared with HGs, RRMS exhibited higher fALFF in the right cerebellum posterior lobe, left orbitofrontal cortex, left dorsolateral prefrontal cortex, bilateral supplementary motor area, and right fusiform gyrus and lower fALFF values in the left hippocampus and right precuneus. ROC revealed that these areas showed two good and five fair AUC values (0.77 ± 0.03, 0.729~0.822). However, four combinations with more than five brain regions received the same best discriminatory power with a sensitivity of 96.3% and a specificity of 88.5%. EDSS revealed a negative correlation with supplementary motor area (r = −0.395, p = 0.046).

Conclusions: RRMS is associated with abnormal regional brain activity deficits of motor- and cognitive-related areas. The fALFF parameter may serve as a potential biological marker to discriminate between the two groups.

Altered Intra- and Inter-regional Functional Connectivity of the Anterior Cingulate Gyrus in Patients With Tremor-Dominant Parkinson's Disease Complicated With Sleep Disorder

Objective: To investigate changes in brain function at the regional and whole-brain levels in patients with tremor-dominant Parkinson's disease (TDPD) complicated by sleep disorder (SD) by regional homogeneity (ReHo) and functional connectivity (FC) analysis of whole-brain resting-state functional magnetic resonance images. Materials and Methods: ReHo and seed-based FC analyses were conducted among 32 patients with TDPD and SD (TDPD-SD), 24 with TDPD and no SD (TDPD-NSD), and 23 healthy controls (HCs) to assess spontaneous brain activity and network-level brain function. Correlation analyses were used to examine the associations between brain activity and the clinical data. Results: Anterior cingulate gyrus (ACC) ReHo values differed significantly among the groups. ACC ReHo values were increased in TDPD-SD vs. HC and TDPD-SD vs. TDPD-NSD. ACC ReHo values were reduced in TDPD-NSD vs. HC. TDPD-SD ReHo values were positively correlated with Pittsburgh Sleep Quality Index (PSQI) scores (r = 0.41, p = 0.020) but negatively correlated with Parkinson's Disease Sleep Scale (PDSS) scores (r = -0.38, p = 0.030). FC analysis using ACC as a mask showed that FC of the left olfactory cortex (L-OC), right straight gyrus (R-SG), right superior parietal gyrus (R-SPG), and right precuneus differed significantly among the groups. FC values between R-SG and ACC were significantly lower in TDPD-SD than in TDPD-NSD, while the FC of L-OC and R-OC with ACC was significantly lower in TDPD-SD than in HC. FC between ACC and L-OC, R-SPG, and the right precuneus was lower in TDPD-NSD than in HC. There was no correlation between the FC values and other clinical data in any of the groups. Conclusion: Localized abnormal activity in TDPD-SD was chiefly triggered by ACC. The change in the ReHo of ACC is closely related to the severity of TDPD-associated SD, revealing the role of this region as a regulator of the sleep mechanism in TDPD. Significant abnormal FC was found between R-SG and ACC in TDPD-SD but was not shown to correlate with clinical data.

Ventral Visual Pathway-Cerebellar Circuit Deficits in Alcohol Dependence: Long- and Short-Range Functional Connectivity Density Study

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.

Frequency-Specific Abnormalities Of Functional Homotopy In Alcohol Dependence: A Resting-State Functional Magnetic Resonance Imaging Study

PURPOSE

Alcohol dependence (AD) is a relapsing mental disorder, typically occurring with concurrent tobacco misuse. Studies have reported disruption of the structural connectivity between hemispheres in the brain of individuals with AD. However, alterations in interhemispheric interactions and the specificity of frequency bands in individuals with AD remain unknown. Voxel-mirrored homotopic connectivity (VMHC) allows examination of functional interactions between mirrored interhemispheric voxels. Here, we use VMHC to investigate homotopic connectivity in AD and alcohol and nicotine co-dependence (AND) subjects.

PATIENTS AND METHODS

VMHC and seed-based functional connectivity (FC) in 24 AD, 30 AND, and 35 sex-, age-, and education-matched healthy control (HC) subjects were calculated for different frequency bands (slow-5, slow-4, and typical bands).

RESULTS

Individuals with AD demonstrated significantly reduced VMHC in bilateral cerebellum posterior lobe (CPL) and increased VMHC in bilateral middle frontal gyrus (MFG) compared to that in HCs in the typical and slow-4 bands; higher VMHC in the MFG was positively correlated with the dependence-severity score. In all bands of the VMHC analysis, no significant differences were found between the AND and other groups. Subsequent seed-based FC analysis demonstrated all regions with abnormal VMHC exhibited altered FC with its counterpart in the contralateral hemisphere in the typical and slow-4 frequency bands. The FC value between bilateral CPL within AD subjects negatively correlated with alcohol intake.

CONCLUSION

Our findings provide further evidence of the role of disruptions within the brain circuitry supporting cognitive control in the development of AD. Alterations in neural activities in the CPL and MFG might be a biomarker of dependence severity in AD patients as assessed using clinical questionnaire and features. Because of the frequency specificity in VMHC, we must consider frequency effects in future AD functional magnetic resonance imaging studies.

Abnormal Global Brain Functional Connectivity in Primary Insomnia Patients: A Resting-State Functional MRI Study

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.

Altered Regional Cortical Brain Activity in Healthy Subjects After Sleep Deprivation: A Functional Magnetic Resonance Imaging Study

Objective: To investigate acute sleep deprivation (SD)-related regional brain activity changes and their relationships with behavioral performances.

Methods: Twenty-two female subjects underwent an MRI scan and an attention network test at rested wakefulness (RW) status and after 24 h SD. The amplitude of low-frequency fluctuations (ALFF) was used to investigate SD-related regional brain activity changes. We used the receiver operating characteristic (ROC) curve to evaluate the ability of the ALFF differences in regional brain areas to distinguish the SD status from the RW status. We used Pearson correlations to evaluate the relationships between the ALFF differences in brain areas and the behavioral performances during the SD status.

Results: Subjects at the SD status exhibited a lower accuracy rate and a longer reaction time relative to the RW status. Compared with RW, SD showed significant lower ALFF values in the right cerebellum anterior lobe, and higher ALFF areas in the bilateral inferior occipital gyrus, left thalamus, left insula, and bilateral postcentral gyrus. The area under the curve values of the specific ALFF differences in brain areas were (mean ± std, 0.851 ± 0.045; 0.805–0.93). Further, the ROC curve analysis demonstrated that the ALFF differences in those regional brain areas alone discriminated the SD status from the RW status with high degrees of sensitivities (82.16 ± 7.61%; 75–93.8%) and specificities (81.23 ± 11.39%; 62.5–93.7%). The accuracy rate showed negative correlations with the left inferior occipital gyrus, left thalamus, and left postcentral gyrus, and showed a positive correlation with the right cerebellum.

Conclusions: The ALFF analysis is a potential indicator for detecting the excitation–inhibition imbalance of regional cortical activations disturbed by acute SD with high performances.

Altered Long- and Short-Range Functional Connectivity Density in Healthy Subjects After Sleep Deprivations

Objective: To investigate the brain functional organization induced by sleep deprivation (SD) using functional connectivity density (FCD) analysis.

Methods: Twenty healthy subjects (12 female, 8 male; mean age, 20.6 ± 1.9 years) participated a 24 h sleep deprivation (SD) design. All subjects underwent the MRI scan and attention network test twice, once during rested wakefulness (RW) status, and the other was after 24 h acute SD. FCD was divided into the shortFCD and longFCD. Receiver operating characteristic (ROC) curve was used to evaluate the discriminating ability of those FCD differences in brain areas during the SD status from the RW status, while Pearson correlations was used to evaluate the relationships between those differences and behavioral performances.

Results: Subjects at SD status exhibited lower accuracy rate and longer reaction time relative to RW status. Compared with RW, SD had a significant decreased shortFCD in the left cerebellum posterior lobe, right cerebellum anterior lobe, and right orbitofrontal cortex, and increased shortFCD in the left occipital gyrus, bilateral thalamus, right paracentral lobule, bilateral precentral gyrus, and bilateral postcentral gyrus. Compared with RW, SD had a significant increased longFCD in the right precentral gyrus, bilateral postcentral gyrus, and right visuospatial network, and decreased longFCD in the default mode network. The area under the curve values of those specific FCD differences in brain areas were (mean ± std, 0.933 ± 0.035; 0.863~0.977). Further ROC curve analysis demonstrated that the FCD differences in those brain areas alone discriminated the SD status from the RW status with high degree of sensitivities (89.19 ± 6%; 81.3~100%) and specificities (89.15 ± 6.87%; 75~100%). Reaction time showed a negative correlation with the right orbitofrontal cortex (r = −0.48, p = 0.032), and accuracy rate demonstrated a positive correlation with the right default mode network (r = 0.573, p = 0.008).

Conclusions: The longFCD and shortFCD analysis might be potential indicator biomarkers to locate the underlying altered intrinsic brain functional organization disturbed by SD. SD sustains the cognitive performance by the decreased high-order cognition related areas and the arousal and sensorimotor related areas.

Aberrant regional brain activities in alcohol dependence: a functional magnetic resonance imaging study

OBJECTIVE

Whether moderate alcohol consumption has health benefits remains controversial, but the harmful effects of excessive alcohol consumption on behavior and brain function are well recognized. The aim of this study was to investigate alcohol-induced regional brain activities and their relationships with behavioral factors.

SUBJECTS AND METHODS

A total of 29 alcohol-dependent subjects (9 females and 20 males) and 29 status-matched healthy controls (11 females and 18 males) were recruited. Severity of alcohol dependence questionnaire (SADQ) and alcohol use disorders identification test (AUDIT) were used to evaluate the severity of alcohol craving. Regional homogeneity (ReHo) analysis was used to explore the alcohol-induced regional brain changes. Receiver operating characteristic (ROC) curve was used to investigate the ability of regional brain activities to distinguish alcohol-dependent subjects from healthy controls. Pearson correlations were used to investigate the relationships between alcohol-induced ReHo differences and behavioral factors.

RESULTS

Alcohol-dependent subjects related to healthy controls showed higher ReHo areas in the right superior frontal gyrus (SFG), bilateral medial frontal gyrus (MFG), left precentral gyrus (PG), bilateral middle temporal gyrus (MTG), and right inferior temporal gyrus (ITG) and lower ReHo areas in the right cerebellum posterior lobe (CPL), left rectal gyrus (RG), and right cluster of pons and cerebellum anterior lobe (CAL). ROC curve revealed high area under the curve (AUC) values (mean ± SD: 0.864 ± 0.028; range: 0.828-0.911) of ReHo differences. Diagnostic analysis showed that these areas alone discriminated alcohol-dependent subjects from healthy controls with high degree of sensitivities (mean ± SD: 81.25% ± 11.49%; range: 62.5%-100%) and specificities (mean ± SD: 81.75% ± 12.36%; range: 67.5%-100%). Years of drink showed negative correlation with left RG (r = -0.493, p = 0.007), the same finding was shown between AUDIT and right CPL (r = -0.52, p = 0.004).

CONCLUSION

Alcohol dependence is associated with aberrant regional activities in multiple brain areas. ReHo analysis may be a useful biological indicator for the detection of regional brain activities in individuals with alcohol dependence.

Aberrant prefrontal-parietal-cerebellar circuits in alcohol dependence

OBJECTIVE

To identify whether the amplitude of low-frequency fluctuations (ALFF) analysis has the potential to serve as a biological marker to detect alcohol-induced spontaneous brain activities and distinguish the patients with alcohol dependence from the healthy subjects.

METHODS

We utilized the ALFF analysis to report on the alcohol-induced spontaneous brain activities in 29 patients with alcohol dependence (9 female, 20 male) relative to 29 status-matched healthy subjects (11 female, 18 male). Receiver operating characteristic curve was used to test the ability of the ALFF analysis in discriminating the patients with alcohol dependence from the healthy subjects. Pearson correlation was used to evaluate the relationships between the signal value of those ALFF differences in brain areas and behavioral characteristics.

RESULTS

Alcohol-induced brain differences located in the right inferior parietal lobule and right supplementary motor area with significant higher ALFF values, and in the left precuneus and bilateral cerebellum posterior lobe with lower ALFF values. The movement-related areas were significantly correlated with each other (P<0.05). Receiver operating characteristic curve revealed good area under the curve values (mean, 0.86±0.079; 0.774-0.951) of the ALFF differences in those specific brain areas, as well as high degree of sensitivities (mean, 80.84%±14.01% or 80%±14.56%; 62.5%-100%) and specificities (mean, 83.32%±9.31%; 70.8%-95.8% or 84.16%±8%; 75%-95.8%).

CONCLUSION

The ALFF analysis may serve as a biological indicator to detect the spontaneous brain activities in patients with alcohol dependence. The prefrontal-parietal-cerebellar circuit appears to be disturbed by long-term alcoholism in patients with alcohol dependence.