Psychiatric disturbances are commonly associated with adult-onset isolated dystonia (AOID); however, the mechanisms underlying psychiatric abnormalities in AOID remain unknown. We aimed to investigate the structural and functional brain changes in AOID patients with anxiety, and identify imaging biomarkers for diagnosing anxiety. Structural and functional magnetic resonance was performed on 69 AOID patients and 35 healthy controls (HCs). The Hamilton Anxiety Scale (HAMA) was used to assess anxiety symptoms in AOID patients and assign patients to AOID with and without anxiety groups. Group differences in grey matter volume, amplitude of low-frequency fluctuations (ALFF), fractional ALFF, and regional homogeneity (ReHo) were evaluated. Area under the receiver operating characteristic curve (ROC AUC) was used as a metric to identify imaging biomarkers for diagnosing anxiety. AOID patients with anxiety exhibited an increased ALFF and ReHo in the left angular gyrus (ANG.L) compared with those without and HCs (voxel P<0.001 and cluster P<0.05, corrected using GRF). A significant positive correlation was observed between ALFF (r = 0.627, P<0.001) and ReHo (r = 0.515, P<0.001) in the ANG.L and HAMA scores in AOID patients. ALFF and ReHo in the ANG.L exhibited an ROC AUC of 0.904 and 0.851, respectively, in distinguishing AOID patients with anxiety from those without and an ROC AUC of 0.887 and 0.853, respectively, in distinguishing AOID patients with anxiety from HCs. These findings provide new insights into the pathophysiology of psychiatric disturbances and highlight potential candidate biomarkers for identifying anxiety in AOID patients.

BACKGROUND: Internal capsule strokes often result in multidomain cognitive impairments across memory, attention, and executive function, typically due to disruptions in brain network connectivity. Our study examines these impairments by analyzing interactions within the triple-network model, focusing on both static and dynamic aspects.
METHODS: We collected resting-state fMRI data from 62 left (CI_L) and 56 right (CI_R) internal capsule stroke patients, along with 57 healthy controls (HC). Using independent component analysis to extract the default mode (DMN), executive control (ECN), and salience networks (SAN), we conducted static and dynamic functional network connectivity analyses (DFNC) to identify differences between stroke patients and controls. For DFNC, we used k-means clustering to focus on temporal properties and multilayer network analysis to examine integration and modularity Q, where integration represents dynamic interactions between networks, and modularity Q measures how well the network is divided into distinct modules. We then calculated the correlations between SFNC/DFNC properties with significant inter-group differences and cognitive scales.
RESULTS: Compared to HC, both CI_L and CI_R patients showed increased static FCs between SAN and DMN and decreased dynamic interactions between ECN and other networks. CI_R patients also had heightened static FCs between SAN and ECN and maintained a state with strongly positive FNCs across all networks in the triple-network model. Additionally, CI_R patients displayed decreased modularity Q.
CONCLUSIONS: These findings highlight that stroke can result in the disruption of static and dynamic interactions in the triple network model, aiding our understanding of the neuropathological basis for multidomain cognitive deficits after internal capsule stroke.

Cushing\'s disease (CD) represents a state of cortisol excess, serving as a model to investigate the effects of prolonged hypercortisolism on functional brain. Potential alterations in the functional connectome of the brain may explain frequently reported cognitive deficits and affective disorders in CD patients. This study aims to elucidate the effects of chronic hypercortisolism on the principal functional gradient, which represents a hierarchical architecture with gradual transitions across cognitive processes, by integrating connectomics and transcriptomics approaches. Utilizing resting-state functional magnetic resonance imaging data from 140 participants (86 CD patients, 54 healthy controls) recruited at a single center, we explored the alterations in the principal gradient in CD patients. Further, we thoroughly explored the underlying associative mechanisms of the observed characteristic alterations with cognitive function domains, biological attributes, and neuropsychiatric representations, as well as gene expression profiles. Compared to healthy controls, CD patients demonstrated changes in connectome patterns in both primary and higher-order networks, exhibiting an overall converged trend along the principal gradient axis. The gradient values in CD patients\' right prefrontal cortex and bilateral sensorimotor cortices exhibited a significant correlation with cortisol levels. Moreover, the cortical regions showing gradient alterations were principally associated with sensory information processing and higher-cognitive functions, as well as correlated with the gene expression patterns which involved synaptic components and function. The findings suggest that converged alterations in the principal gradient in CD patients may mediate the relationship between hypercortisolism and cognitive impairments, potentially involving genes regulating synaptic components and function.

Nearly half of the amyotrophic lateral sclerosis (ALS) patients showed hyperintensity of the corticospinal tract (CST+), yet whether brain functional pattern differs between CST+and CST- patients remains obscure. In the current study, 19 ALS CST+, 41 ALS CST- patients and 37 healthy controls (HC) underwent resting state fMRI scans. We estimated local activity and connectivity patterns via the Amplitude of Low Frequency Fluctuations (ALFF) and the Network-Based Statistic (NBS) approaches respectively. The ALS CST+patients did not differ from the CST- patients in amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) score and disease duration. ALFF of the superior frontal gyrus (SFG) and the inferior frontal gyrus pars opercularis (OIFG) were highest in the HC and lowest in the ALS CST- patients, resulting in significant group differences (PFWE<0.05). NBS analysis revealed a frontal network consisting of connections between SFG, OIFG, orbital frontal gyrus, middle cingulate cortex and the basal ganglia, which exhibited HC>ALS CST+ > ALS CST- group differences (PFWE=0.037) as well. The ALFF of the OIFG was significantly correlated with ALSFRS-R (R=0.34, P=0.028) and mean connectivity of the frontal network was trend-wise significantly correlated with disease duration (R=-0.31, P=0.052) in the ALS CST- patients. However, these correlations were insignificant in ALS CST+patients (P values > 0.8). In conclusion, The ALS CST+patients exhibited different patterns of baseline functional activity and connectivity in the frontal cortex which may indicate a functional compensatory effect.

The brain exhibits intrinsic dynamics characterized by spontaneous spatiotemporal reorganization of neural activity or metastability, which is associated closely with functional integration and segregation. Compared to dynamic functional connectivity, state-dependent effective connectivity (i.e., dynamic effective connectivity) is more suitable for exploring the metastability as its ability to infer causalities between brain regions. However, methods for state-dependent effective connectivity are scarce and urgently needed. In this study, a novel data-driven computational framework, named NHSMM-MAR-sdNC integrating nonparametric hidden semi-Markov model combined with multivariate autoregressive model and state-dependent new causality, is proposed to investigate the state-dependent effective connectivity. The framework is not constrained by any biological assumptions. Furthermore, state number can be inferred from the observed data directly and the state duration distributions will be estimated explicitly rather than restricted by geometric form, which overcomes limitations of hidden Markov model. Experimental results of synthetic data show that the framework can identify the state number adaptively and the state-dependent causality networks accurately. The dynamics of state-related causality networks are also revealed by the new method on real-world resting-state fMRI data. Our method provides a new data-driven computational framework for identifying state-dependent effective connectivity, which will facilitate the identification and assessment of metastability and itinerant dynamics of the brain.

The putamen has been proposed to play a critical role in the development of obsessive-compulsive disorder (OCD). The primary objective of this study was to examine the resting-state regional activity and functional connectivity patterns of the putamen in individuals diagnosed with OCD. To achieve this, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to collect data from a sample of 45 OCD patients and 53 healthy control participants. We aimed to use the regional amplitude of low-frequency fluctuation (ALFF) analysis to generate the ROI masks of the putamen and then conduct the whole brain functional connectivity of the putamen in individuals with OCD. Compared to controls, the OCD group demonstrated decreased ALFF in bilateral putamen. The right putamen also displayed decreased FC with the left putamen extending to the inferior frontal gyrus (IFG), bilateral precuneus extending to calcarine, the right middle occipital cortex extending to the right middle temporal cortex, and the left middle occipital gyrus. The decreased connectivity between the right putamen and the left IFG was negatively correlated with Yale-Brown Obsessive Compulsive scale (Y-BOCS) Obsession Scores. This study aimed to reveal the putamen changes in resting-state activity and connectivity in OCD patients, highlighting the significance of aberrant ALFF/FC of the putamen is a key characteristic of OCD.

Self-ambivalence, a prevalent phenomenon in daily life, has been increasingly substantiated by research. It refers to conflicting self-views and evaluations, primarily concerning self-worth and morality. Previous behavioral research has distinguished self-worth and moral ambivalence, but it remains unclear whether they have separable neural bases. The present study addressed this question by examining resting-state brain activity (i.e., the fractional amplitude of low-frequency fluctuations, fALFF) and connectivity (i.e., resting-state functional connectivity, RSFC) in 112 college students. The results found that self-worth ambivalence was positively related to the fALFF in the orbitofrontal cortex (OFC) and left superior parietal lobule (SPL). The RSFC strength between the SPL and precuneus/posterior cingulate cortex (PCC) was positively related to self-worth ambivalence. Moral ambivalence was positively associated with the fALFF in the left SPL (extending into the temporoparietal junction) and right SPL. The RSFC strengths between the left SPL/TPJ and OFC, as well as the RSFC strengths between the right SPL as a seed and the bilateral middle and inferior temporal gyrus, were associated with moral ambivalence. Overall, the neural bases of self-worth and moral ambivalence are associated with the SPL and OFC, involved in attentional alertness and value representation, respectively. Additionally, the neural basis of moral ambivalence is associated with the TPJ, responsible for mentalizing.

Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.

Aggression can be categorized into reactive aggression (RA) and proactive aggression (PA) based on their underlying motivations. However, previous research has rarely identified the relationship between femininity and RA/PA, and there is a lack of understanding regarding the femininity-related neurofunctional basis of these aggressive behaviors. Thus, this study first examined the relationships between femininity and aggression, then explored the aggression-by-femininity interactions on the fractional amplitude of low-frequency fluctuations using resting-state fMRI among 705 university participants (mean age = 19.14 ± 0.99). The behavioral data indicated that femininity was more negatively associated with RA and PA when masculinity was controlled for. Additionally, the neural data revealed that femininity-specific relationships of RA in the left middle occipital gyrus (i.e. individuals with low femininity had positive relationships between RA and the left middle occipital gyrus, whereas those with high femininity had negative relationships) as well as of PA in the left middle frontal gyrus (i.e. individuals with high femininity showed significant negative relationships, whereas those with low femininity did not exhibit significant relationships). These findings reflect that individuals with varying levels of femininity exhibit distinct neural bases when expressing different subtypes of aggression, which are associated with societal expectations of gender.

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646.