The overlapping modular organization of human brain functional networks across the adult lifespan.

Previous studies have demonstrated that the brain functional modular organization, which is a fundamental feature of the human brain, would change along the adult lifespan. However, these studies assumed that each brain region belonged to a single functional module, although there has been convergent evidence supporting the existence of overlap among functional modules in the human brain. To reveal how age affects the overlapping functional modular organization, this study applied an overlapping module detection algorithm that requires no prior knowledge to the resting-state fMRI data of a healthy cohort (N = 570) aged from 18 to 88 years old. A series of measures were derived to delineate the characteristics of the overlapping modular structure and the set of overlapping nodes (brain regions participating in two or more modules) identified from each participant. Age-related regression analyses on these measures found linearly decreasing trends in the overlapping modularity and the modular similarity. The number of overlapping nodes was found increasing with age, but the increment was not even over the brain. In addition, across the adult lifespan and within each age group, the nodal overlapping probability consistently had positive correlations with both functional gradient and flexibility. Further, by correlation and mediation analyses, we showed that the influence of age on memory-related cognitive performance might be explained by the change in the overlapping functional modular organization. Together, our results revealed age-related decreased segregation from the brain functional overlapping modular organization perspective, which could provide new insight into the adult lifespan changes in brain function and the influence of such changes on cognitive performance.

Cost-efficiency trade-offs of the human brain network revealed by a multiobjective evolutionary algorithm.

It is widely believed that the formation of brain network architecture is under the pressure of optimal trade-off between reducing wiring cost and promoting communication efficiency. However, the questions of whether this trade-off exists in empirical human brain structural networks and, if so, how it takes effect are still not well understood. Here, we employed a multiobjective evolutionary algorithm to directly and quantitatively explore the cost-efficiency trade-off in human brain structural networks. Using this algorithm, we generated a population of synthetic networks with optimal but diverse cost-efficiency trade-offs. It was found that these synthetic networks could not only reproduce a large portion of connections in the empirical brain structural networks but also embed a resembling small-world organization. Moreover, the synthetic and empirical brain networks were found similar in terms of the spatial arrangement of hub regions and the modular structure, which are two important topological features widely assumed to be outcomes of cost-efficiency trade-offs. The synthetic networks had high robustness against random attacks as the empirical brain networks did. Additionally, we also revealed some differences between the synthetic networks and the empirical brain networks, including lower segregated processing capacity and weaker robustness against targeted attacks in the synthetic networks. These findings provide direct and quantitative evidence that the structure of human brain networks is indeed largely influenced by optimal cost-efficiency trade-offs. We also suggest that some additional factors (e.g., segregated processing capacity) might jointly determine the network organization with cost and efficiency.

Gene expression associated with individual variability in intrinsic functional connectivity.

It has been revealed that intersubject variability (ISV) in intrinsic functional connectivity (FC) is associated with a wide variety of cognitive and behavioral performances. However, the underlying organizational principle of ISV in FC and its related gene transcriptional profiles remain unclear. Using resting-state fMRI data from the Human Connectome Project (299 adult participants) and microarray gene expression data from the Allen Human Brain Atlas, we conducted a transcription-neuroimaging association study to investigate the spatial configurations of ISV in intrinsic FC and their associations with spatial gene transcriptional profiles. We found that the multimodal association cortices showed the greatest ISV in FC, while the unimodal cortices and subcortical areas showed the least ISV. Importantly, partial least squares regression analysis revealed that the transcriptional profiles of genes associated with human accelerated regions (HARs) could explain 31.29% of the variation in the spatial distribution of ISV in FC. The top-related genes in the transcriptional profiles were enriched for the development of the central nervous system, neurogenesis and the cellular components of synapse. Moreover, we observed that the effect of gene expression profile on the heterogeneous distribution of ISV in FC was significantly mediated by the cerebral blood flow configuration. These findings highlighted the spatial arrangement of ISV in FC and their coupling with variations in transcriptional profiles and cerebral blood flow supply.

Predicting visual working memory with multimodal magnetic resonance imaging.

The indispensability of visual working memory (VWM) in human daily life suggests its importance in higher cognitive functions and neurological diseases. However, despite the extensive research efforts, most findings on the neural basis of VWM are limited to a unimodal context (either structure or function) and have low generalization. To address the above issues, this study proposed the usage of multimodal neuroimaging in combination with machine learning to reveal the neural mechanism of VWM across a large cohort (N = 547). Specifically, multimodal magnetic resonance imaging features extracted from voxel-wise amplitude of low-frequency fluctuations, gray matter volume, and fractional anisotropy were used to build an individual VWM capacity prediction model through a machine learning pipeline, including the steps of feature selection, relevance vector regression, cross-validation, and model fusion. The resulting model exhibited promising predictive performance on VWM (r = .402, p < .001), and identified features within the subcortical-cerebellum network, default mode network, motor network, corpus callosum, anterior corona radiata, and external capsule as significant predictors. The main results were then compared with those obtained on emotional regulation and fluid intelligence using the same pipeline, confirming the specificity of our findings. Moreover, the main results maintained well under different cross-validation regimes and preprocess strategies. These findings, while providing richer evidence for the importance of multimodality in understanding cognitive functions, offer a solid and general foundation for comprehensively understanding the VWM process from the top down.

TGR5 promotes cholangiocarcinoma by interacting with mortalin.

Takeda-G-protein-receptor-5 (TGR5) is a G-protein-coupled receptor (GPCR) activated by bile acids, and mortalin is a multipotent chaperone of the HSP70 family. In the present study, TGR5 was detected by immunohistochemistry (IHC) in extrahepatic cholangiocarcinoma (ECC) specimens, and TGR5 expression in ECC tissues and adjacent tissues was compared. In vitro TGR5 was overexpressed and knocked down in human intrahepatic cholangiocarcinoma (ICC) cell line RBE and human extrahepatic cholangiocarcinoma (ECC) cell line QBC-939 to observe its effects on the biological behavior of cholangiocarcinoma (CC) cells, including proliferation, apoptosis and migration. In vivo xenograft model was constructed to explore the role of TGR5 in CC growth. Proteins that interacted with TGR5 were screened using an immunoprecipitation spectrometry approach, and the identified protein was down-regulated to investigate its contribution to CC growth. The present study demonstrated that TGR5 is highly expressed in CC tissues, and strong TGR5 expression may indicate high malignancy in CC. Furthermore, TGR5 promotes CC cell proliferation, migration, and apoptosis resistance. TGR5 boosts CC growth in vivo. In addition, TGR5 combines with mortalin and regulates mortalin expression in the CC cell line. Mortalin participates in the TGR5-induced increase in CC cell proliferation. In conclusion, TGR5 is of clinical significance based on its implications for the degree of malignancy in patients with CC. Mortalin may be a downstream component regulated by TGR5, and TGR5 promotes cholangiocarcinoma at least partially by interacting with mortalin and upregulating its expression. Both TGR5 and mortalin are positive regulators, and may serve as potential therapeutic targets for CC.

Locostatin Alleviates Liver Fibrosis Induced by Carbon Tetrachloride in Mice.

BACKGROUND AND AIMS: Liver fibrosis is featured with excessive deposition of extracellular matrix and fibrous connective tissue hyperplasia. The specific inhibitor of Raf-1 kinase inhibitor protein, locostatin, inhibits the migration of hepatic stellate cells. In this study, we investigated the effect of locostatin on liver fibrosis and its underlying mechanism. METHODS: Carbon tetrachloride (CCl4) was used to induce liver fibrosis in mice, and locostatin was injected intraperitoneally. Liver fibrosis was assessed by Masson and Sirius red staining, hydroxyproline (HYP) assay, and collagen percentage area. Collagen I, collagen III, and α-SMA were detected by RT-PCR and western blot. The levels of MMP-13, MMP-2, TIMP-1, and TIMP-2 were estimated by ELISA. Liver inflammation was evaluated by HE staining and immunohistochemistry; liver myeloperoxidase (MPO), superoxide dismutase, and malondialdehyde were measured by ELISA; and cytokines were by Mouse Cytokine Array Q4000. RESULTS: Compared to the CCl4 group, HYP (208.56 ± 6.12) µg/g, percentage of total collagen at overall region (1.91 ± 0.13), MMP-13/TIMP-1 (0.19 ± 0.01), MPO (1.45 ± 0.04) U/g, TGF-ß (2652 ± 91.20), PDGF-AA (3897 ± 290.69), and E-selectin (1569 ± 66.48) in the liver tissues were decreased significantly in the locostatin-treated group. CONCLUSIONS: Locostatin mitigated liver fibrosis and inflammation induced by CCl4. The mechanism is via inhibition inflammatory cytokines, TGF-ß, PDGF-AA, and E-selectin.

Intrinsic overlapping modular organization of human brain functional networks revealed by a multiobjective evolutionary algorithm.

A wealth of research on resting-state functional MRI (R-fMRI) data has revealed modularity as a fundamental characteristic of the human brain functional network. The modular structure has recently been suggested to be overlapping, meaning that a brain region may engage in multiple modules. However, not only the overlapping modular structure remains inconclusive, the topological features and functional roles of overlapping regions are also poorly understood. To address these issues, the present work utilized the maximal-clique based multiobjective evolutionary algorithm to explore the overlapping modular structure of the R-fMRI data obtained from 57 young healthy adults. Without prior knowledge, brain regions were optimally grouped into eight modules with wide overlap. Based on the topological features captured by graph theory analyses, overlapping regions were classified into an integrated club and a dominant minority club through clustering. Functional flexibility analysis found that overlapping regions in both clubs were significantly more flexible than non-overlapping ones. Lesion simulations revealed that targeted attack at overlapping regions were more damaging than random failure or even targeted attack at hub regions. In particular, overlapping regions in the dominant minority club were more flexible and more crucial for information communication than the others were. Together, our findings demonstrated the highly organized overlapping modular architecture and revealed the importance as well as complexity of overlapping regions from both topological and functional aspects, which provides important implications for their roles in executing multiple tasks and maintaining information communication.

Comprehensive investigating of cytokine and receptor related genes variants in patients with chronic hepatitis B virus infection.

BACKGROUND & AIMS: Chronic hepatitis B virus (HBV) infection is a global health problem and the outcome are associated with both viral factors and host genetic factors. High Throughput Sequencing (HTS) technology were used to identify variants associated with liver disease. METHODS: Fifty-five Chronic hepatitis B (CHB) patients, fifty-three self-healing HBV (SH) patients and 53 healthy controls (HC) were recruited, 404 cytokine and cytokine receptor related genes were captured and sequenced at high depth (>900X), both variant (Fischer's exact test, P value < 0.05) and gene (SKAT-O gene level test, adjust P value < 0.05) level association were used to identify variants and genes associated with CHB. RESULTS: Total 5083 variants have been detected, fifty-four variants were found associated with CHB, most (29/32) variants were located in HLA region, including HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, HLA-DQB2, HLA-DRB1 and HLA-DRB5. Several missense variants were found associated with CHB, including p.E226K in PVR (poliovirus receptor), p.E400A and p.C431R in IL4R (interleukin 4 receptor). Four variants located in 3'UTR (untranslated region) have also been found associated with CHB. CONCLUSION: Our study revealed that high through target region sequencing, combined with association analysis at variant and gene level, would be a good way to found variants and genes associated with CHB even at small sample size. Our data implied that chronic hepatitis B patients who carry these variants need intensive monitoring.

Sorafenib induces autophagic cell death and apoptosis in hepatic stellate cell through the JNK and Akt signaling pathways.

Increasing hepatic stellate cell (HSC) death is an attractive approach for limiting liver fibrosis. We investigated the molecular mechanisms underlying the effects of sorafenib on HSCs. LX2 cells were incubated with sorafenib and a variety of inhibitors of apoptosis, autophagy, and necrosis. Electron microscopy was used to observe autophagosomes. Inhibitors and siRNA were used to examine the role of the Akt/mTOR/p70S6K and JNK pathways. Ultrastructural analysis revealed that rat HSCs treated with 5 µmol/l sorafenib accumulated residual digested material and empty or autophagic vacuoles. Incubating LX2 cells with lysosomal protease inhibitors increased the accumulation of LC3-II, indicating that sorafenib enhances autophagic flux in HSCs. Autophagy may precede apoptosis. Lower concentrations of sorafenib and a shorter treatment time resulted in the dominance of autophagic cell death over apoptosis. Further analysis showed that Beclin 1 is inactivated by the caspases induced by sorafenib during apoptosis. Inhibition of autophagy in LX2 cells using 3-methyladenine treatment or siRNA-mediated knockdown of Atg5 resulted in a marked increase in apoptosis. Finally, sorafenib induced programmed cell death by attenuation and activation of Akt/mTOR/p70S6K and JNK signaling. Sorafenib-induced cell death is mediated by both autophagy and apoptosis. Elucidation of the signaling pathways activated by sorafenib could potentially lead to novel antifibrosis therapies for chronic liver diseases.

Knockdown of Astrocyte Elevated Gene-1 Inhibits Activation of Hepatic Stellate Cells.

BACKGROUND: Astrocyte elevated gene-1 (AEG-1) is a positive regulator of tumorigenesis and a valuable prognostic marker of a diverse array of cancers, including liver cancer; however, the relationship between AEG-1 and hepatic fibrogenesis is not known. OBJECTIVE: The objective of this study was to explore the expression of AEG-1 during hepatic fibrogenesis and determine how AEG-1 regulates the profibrogenic phenotype of hepatic stellate cells (HSCs). METHODS: The levels of AEG-1 were monitored in the fibrotic livers and transforming growth factor-ß (TGF-ß)- or lipopolysaccharide (LPS)-stimulated HSCs. The expression of AEG-1 was knocked down by lentivirus-mediated short hairpin RNA in HSCs, and collagen expression, proliferation assays, apoptosis induction studies, and migration assays were simultaneously conducted in vitro. RESULTS: AEG-1 expression was increased in the fibrotic livers. At the cellular level, TGF-ß or LPS stimulation, which caused HSC activation, induced AEG-1 expression in HSC-T6 and primary rat HSCs (P < 0.05). Knockdown of AEG-1 inhibited collagen I and α-smooth muscle actin expression (P < 0.05), reduced cell proliferation (P < 0.05) and motility (P < 0.05), and induced cell apoptosis (P < 0.05) in HSCs. This antifibrotic effect caused by lack of AEG-1 was associated with the inactivation of PI3K/Akt and the mitogen-activated protein kinase pathway. CONCLUSIONS: Knockdown of AEG-1 suppressed the activation of HSCs by modulating the phenotype and inducing apoptosis. AEG-1 might be a potential target in treatment of hepatic fibrosis.

Heparin-binding epidermal growth factor-like growth factor: a hepatic stellate cell proliferation inducer via ErbB receptors.

BACKGROUND AND AIM: Heparin-binding epidermal growth factor-like growth factor (HB-EGF) has a proliferative effect on several types of cells. However, the role of HB-EGF on hepatic stellate cells (HSCs) is not clear. The present study is to investigate the regulatory effects of HB-EGF on HSC proliferation and apoptosis. METHODS: Activated primary rat HSCs and two HSC cell lines (human LX2 and rat T6) were used in this study. Four inhibitors (CRM197 to HB-EGF, AG1478 to epidermal growth factor receptor [EGFR], PD98059 to mitogen-activated kinase, and LY294002 to phosphatidylinositol 3-kinase) were employed to verify the pathway of HB-EGF on cell proliferation and apoptosis. RESULTS: HB-EGF expression was significantly increased in activated HSCs. HB-EGF increased the expressions of phospho-EGFR and ErbB4 receptors, the phosphorylation of extracellular signal-regulated kinase (ERK) and Akt. Consequently, HB-EGF stimulated HSC proliferation and suppressed HSC apoptosis. Each individual inhibitor specifically inhibited the correlated receptor or enzyme and inhibited HSC proliferation and induced its apoptosis. CONCLUSIONS: HB-EGF promotes HSC proliferation via activation of the EGFR and ErbB4 receptors and, subsequently, via activation of ERK and Akt. Any blockage in the chain obstructs the flow from HB-EGF to HSC proliferation. Therefore, HB-EGF is a potential therapeutic target in liver fibrosis.

Rimonabant inhibits proliferation, collagen secretion and induces apoptosis in hepatic stellate cells.

BACKGROUND/AIMS: Liver fibrosis represents a significant health problem worldwide. Hepatic stellate cells (HSCs) play a critical role in the live fibrosis. Rimonabant (SR141716) is cannabinoid receptor type 1 (CB1) antagonist. The pharmacological effects of rimonabant on HSCs are not well characterized in HSCs. METHODS: CB1 receptor was detected by immunohistochemistry in human liver fibrosis specimens. Cell proliferation was detected by MTT assay. Cell apoptosis, caspase-3 protein expression and cell cycle were detected by TEM and flow cytometry, respectively. Caspase-3 activity was measured using caspase-3 activity assay kit. Collagen secretion was evaluated by radioimmunoassay. CB1 receptor and signaling molecules were evaluated by qRTPCR and Western blot. RESULTS: Immunohistochemistry showed a discrete, punctuated CB1 immunoreactivity in human liver fibrosis specimens. Rimonabant reduced HSC proliferation and increased HSC apoptosis. Cell cycle analysis showed a decrease in G2/M phase cells and an increase in G0/G1 phase cells in HSC-T6 cells treated with rimonabant. Caspase-3 protein expression and activity were increased by rimonabant. Rimonabant decreased collagen secretion in HSC-T6 cells. Moreover, rimonabant inhibited the expression of phosphorylated FAK and ERK and down-regulated CB1 mRNA expression. CONCLUSION: The study provides new insights toward the pharmacological effect of rimonabant on HSCs in vitro. Rimonabant inhibits proliferation, collagen secretion and induces apoptosis in HSCs.

A Hybrid Routing Pattern in Human Brain Structural Network Revealed By Evolutionary Computation.

The human brain functional connectivity network (FCN) is constrained and shaped by the communication processes in the structural connectivity network (SCN). The underlying communication mechanism thus becomes a critical issue for understanding the formation and organization of the FCN. A number of communication models supported by different routing strategies have been proposed, with shortest path (SP), random diffusion (DIF), and spatial navigation (NAV) as the most typical, respectively requiring network global knowledge, local knowledge, and both for path seeking. Yet these models all assumed every brain region to use one routing strategy uniformly, ignoring convergent evidence that supports the regional heterogeneity in both terms of biological substrates and functional roles. In this regard, the current study developed a hybrid communication model that allowed each brain region to choose a routing strategy from SP, DIF, and NAV independently. A genetic algorithm was designed to uncover the underlying region-wise hybrid routing strategy (namely HYB). The HYB was found to outperform the three typical routing strategies in predicting FCN and facilitating robust communication. Analyses on HYB further revealed that brain regions in lower-order functional modules inclined to route signals using global knowledge, while those in higher-order functional modules preferred DIF that requires only local knowledge. Compared to regions that used global knowledge for routing, regions using DIF had denser structural connections, participated in more functional modules, but played a less dominant role within modules. Together, our findings further evidenced that hybrid routing underpins efficient SCN communication and locally heterogeneous structure-function coupling.

Association between gene polymorphisms of IL-28 and response to lamivudine in Chinese rural patients with chronic hepatitis B.

OBJECTIVE: To assess the association between gene polymorphisms (single nucleotide polymorphisms [SNPs]) of rs8099917 and rs12980602 in the IL-28 gene and the response to lamivudine treatment in naïve of Chinese rural patients. MATERIAL AND METHODS: Three hundred and fifty-four naïve chronic hepatitis B (CHB) patients treated with lamivudine were enrolled in this study. Rs8099917 and rs12980602 SNPs were genotyped using matrix-assisted laser desorption/ionization time of flight mass spectrometry. Baseline characteristics and genotypes were compared between 181 patients with treatment response and 173 without response. RESULTS: The IL-28 genotypes were independently associated with responses at 1 year post-treatment with lamivudine in CHB patients (OR for rs8099917 GT/GG vs. TT, 4.097 [95% CI, 1.342-12.512; p = 0.015]; OR for rs12980602CT/CC vs. TT, 2.27 [95% CI, 1.202-4.284; p =0.014]). When adjusting for age, gender, smoking, drinking, and levels of hepatitis B virus (HBV) DNA, alanine aminotransferase, and HBV genotype, the rs8099917 genotype GT (OR, 4.025 [95% CI, 1.316-12.354; p = 0.013] and fibrosis stage (OR, 0.716 [95% CI, 0.432-0.986; p = 0.036] appeared to be associated with a higher probability of response to lamivudine treatment. CONCLUSION: The genotype G/T for rs8099917 of IL-28 gene and early fibrosis stage may be predictive of treatment success.

Trade-offs among cost, integration, and segregation in the human connectome.

The human brain structural network is thought to be shaped by the optimal trade-off between cost and efficiency. However, most studies on this problem have focused on only the trade-off between cost and global efficiency (i.e., integration) and have overlooked the efficiency of segregated processing (i.e., segregation), which is essential for specialized information processing. Direct evidence on how trade-offs among cost, integration, and segregation shape the human brain network remains lacking. Here, adopting local efficiency and modularity as segregation factors, we used a multiobjective evolutionary algorithm to investigate this problem. We defined three trade-off models, which represented trade-offs between cost and integration (Dual-factor model), and trade-offs among cost, integration, and segregation (local efficiency or modularity; Tri-factor model), respectively. Among these, synthetic networks with optimal trade-off among cost, integration, and modularity (Tri-factor model [Q]) showed the best performance. They had a high recovery rate of structural connections and optimal performance in most network features, especially in segregated processing capacity and network robustness. Morphospace of this trade-off model could further capture the variation of individual behavioral/demographic characteristics in a domain-specific manner. Overall, our results highlight the importance of modularity in the formation of the human brain structural network and provide new insights into the original cost-efficiency trade-off hypothesis.

Curcumin ameliorates hydrogen peroxide-induced epithelial barrier disruption by upregulating heme oxygenase-1 expression in human intestinal epithelial cells.

BACKGROUND: Disruption of epithelial tight junctions (TJ) followed by loss of barrier function is of crucial importance in the pathogenesis of a variety of gastrointestinal disorders. Heme oxygenase-1 (HO-1), which can be induced by curcumin (Cur), provides protection against various forms of oxidative stress. AIMS: The protective effect of Cur on oxidative stress-induced intestinal barrier disruption in human intestinal epithelial cells was elucidated in this study. METHODS: H(2)O(2)-induced Caco-2 enterocytic monolayers were incubated in the presence or absence of Cur and/or zinc protoporphyrin (ZnPP). The trans-epithelial electrical resistance (TEER) and the flux of sodium fluorescein in the filter-grown Caco-2 cell monolayers were measured. The expression and localization of the TJ protein occludin and zonula occluden-1 (ZO-1) were evaluated by western blot and immunofluorescence microscopy. The mRNA and protein levels of HO-1 were analyzed by real-time PCR and western blot. RESULTS: Cur attenuated H(2)O(2)-induced disruption of paracellular permeability (TEER 52.02 ± 10.15% vs 22.71 ± 3.11%; sodium fluorescein flux 12.41 ± 2.19% vs 32.00 ± 4.97%, P < 0.05) and induced HO-1 mRNA (6.64 ± 0.48 vs 3.22 ± 0.28, P < 0.05) and protein (291.00 ± 9.17% vs 99.00 ± 10.00%, P < 0.05) expression in Caco-2 cells. After administration of H(2)O(2), occludin and ZO-1 proteins were restored by Cur (occludin 175.67 ± 29.50% vs 53.67 ± 24.19%, P < 0.05; ZO-1 139.67 ± 33.71% vs 36.00 ± 15.88%, P < 0.05) and this effect was blocked by HO-1 inhibitor, ZnPP (occludin 54.67 ± 10.02% vs 168.33 ± 36.47%, P < 0.05; ZO-1 50.00 ± 15.13% vs 117.67 ± 38.81%, P < 0.05). CONCLUSION: Cur protects human intestinal epithelial cells against H(2)O(2)-induced disruption of TJ and barrier dysfunction via the HO-1 pathway.

Common and distinct neural substrates of the compassionate and uncompassionate self-responding dimensions of self-compassion.

Self-compassion is beneficial for individuals' emotional health, but debates regarding its conceptualization are increasing. The present study aimed to explore the neural basis of self-compassion and its compassionate and uncompassionate dimensions and the indirect path from neural basis to emotional health. Structural MRI and Resting-state fMRI data were used to measure the gray matter volume (GMV) and the amplitude of low-frequency fluctuation (ALFF) in 88 healthy college students. We found that individuals with higher self-compassion had decreased GMV in the prefrontal cortex, cerebellum as well as lower ALFF in the occipital lobe. The compassionate and uncompassionate dimensions of self-compassion shared some similarities (e.g., common correlation with GMV in the medial prefrontal cortex, ALFF in the occipital lobe) but also had some differences (e.g., only uncompassionate dimensions correlated with GMV in the lateral prefrontal cortex, ALFF in medial temporal lobe/striatum). The indirect path analyses revealed that corresponding brain characteristics could have associations with emotional health through self-compassion, as well as its uncompassionate dimension, but not compassionate dimension. This exploratory whole-brain study showed some preliminary findings that compassionate and uncompassionate dimensions of self-compassion were related to distinct brain regions, which are both important to the current conceptualization of self-compassion and intervention study.

Functional connectivity dynamics as a function of the fluctuation of tension during film watching.

To advance the understanding of the dynamic relationship between brain activities and emotional experiences, we examined the neural patterns of tension, a unique emotion that highly depends on how an event unfolds. Specifically, the present study explored the temporal relationship between functional connectivity patterns within and between different brain functional modules and the fluctuation in tension during film watching. Due to the highly contextualized and time-varying nature of tension, we expected that multiple neural networks would be involved in the dynamic tension experience. Using the neuroimaging data of 546 participants, we conducted a dynamic brain analysis to identify the intra- and inter-module functional connectivity patterns that are significantly correlated with the fluctuation of tension over time. The results showed that the inter-module connectivity of cingulo-opercular network, fronto-parietal network, and default mode network is involved in the dynamic experience of tension. These findings demonstrate a close relationship between brain functional connectivity patterns and emotional dynamics, which supports the importance of functional connectivity dynamics in understanding our cognitive and emotional processes.

Aberrant large-scale brain modules in deficit and non-deficit schizophrenia.

OBJECTIVE: Schizophrenia is a heterogenous psychiatric disease, and deficit schizophrenia (DS) is a clinical subgroup with primary and enduring negative symptoms. Although previous neuroimaging studies have identified functional connectome alterations in schizophrenia, the modular organizations in DS and nondeficit schizophrenia (NDS) remain poorly understood. Therefore, this study aimed to investigate the modular-level alterations in DS patients compared with the NDS and healthy control (HC) groups. METHODS: A previously collected dataset was re-analyzed, in which 74 chronic male schizophrenia patients (33 DS and 41 NDS) and 40 HC underwent resting-state functional magnetic resonance imaging with eyes closed in a Siemens 3 T scanner (scanning duration = 8 min). Modular- (intramodule and intermodule connectivity) and nodal- [normalized within-module degree (Zi) and participation coefficient (PCi)] level graph theory properties were computed and compared among the three groups. Receiver operating characteristic curve (ROC) analyses were performed to examine the classification ability of these measures, and partial correlations were conducted between network measures and symptom severity. Validation analyses on head motion, network sparsity, and parcellation scheme were also performed. RESULTS: Both schizophrenia subgroups showed decreased intramodule connectivity in salience network (SN), somatosensory-motor network (SMN), and visual network (VN), and increased intermodule connectivity in SMN-default mode network (DMN) and SMN-frontoparietal network (FPN). Compared with NDS patients, DS patients showed weaker intramodule connectivity in SN and stronger intermodule connectivity in SMN-FPN and SMN-VN. At the nodal level, the schizophrenia-related alterations were distributed in SN, SMN, VN, and DMN, and 7 DS-specific nodal alterations were identified. Intramodule connectivity of SN, intermodule connectivity of SMN-VN, and Zi of left precuneus successfully distinguished the three groups. Partial correlational analyses revealed that these measures were related to negative symptoms, general psychiatric symptoms, and neurocognitive function. CONCLUSION: Our findings suggest that functional connectomes, especially SN, SMN, and VN, may capture the distinct and common disruptions of DS and NDS. These findings may help to understand the neuropathology of negative symptoms of schizophrenia and inform targets for treating different schizophrenia subtypes.

Integrated and segregated frequency architecture of the human brain network.

The frequency of brain activity modulates the relationship between the brain and human behavior. Insufficient understanding of frequency-specific features may thus lead to inconsistent explanations of human behavior. However, to date, the frequency-specific features of the human brain functional network at the whole-brain level remain poorly understood. Here, we used resting-state fMRI data and graph-theory analyses to investigate the frequency-specific characteristics of fMRI signals in 12 frequency bands (frequency range 0.01-0.7 Hz) in 75 healthy participants. We found that brain regions with higher level and more complex functions had a more variable functional connectivity pattern but engaged less in higher frequency ranges. Moreover, brain regions that engaged in fewer frequency bands played more integrated roles (i.e., higher network participation coefficient and lower within-module degree) in the functional network, whereas regions that engaged in broader frequency ranges exhibited more segregated functions (i.e., lower network participation coefficient and higher within-module degree). Finally, behavioral analyses revealed that regional frequency variability was associated with a spectrum of behavioral functions from sensorimotor functions to complex cognitive and social functions. Taken together, our results showed that segregated functions are executed in wide frequency ranges, whereas integrated functions are executed mainly in lower frequency ranges. These frequency-specific features of brain networks provided crucial insights into the frequency mechanism of fMRI signals, suggesting that signals in higher frequency ranges should be considered for their relation to cognitive functions.