The complexity of brain activity reflects its ability to process information, adapt to environmental changes, and transition between states. However, it remains unclear how schizophrenia (SZ) affects brain activity complexity, particularly its dynamic changes. This study aimed to investigate the abnormal patterns of brain activity complexity in SZ, their relationship with cognitive deficits, and the impact of antipsychotic medication. Forty-four drug-naive first-episode (DNFE) SZ patients and thirty demographically matched healthy controls (HC) were included. Functional MRI-based sliding window analysis was utilized for the first time to calculate weighted permutation entropy to characterize complex patterns of brain activity in SZ patients before and after 12 weeks of risperidone treatment. Results revealed reduced complexity in the caudate, putamen, and pallidum at baseline in SZ patients compared to HC, with reduced complexity in the left caudate positively correlated with Continuous Performance Test (CPT) and Category Fluency Test scores. After treatment, the complexity of the left caudate increased. Regions with abnormal complexity showed decreased functional connectivity, with complexity positively correlated with connectivity strength. We observed that the dynamic complexity of the brain exhibited the characteristic of spontaneous, recurring \"complexity drop\", potentially reflecting transient state transitions in the resting brain. Compared to HC, patients exhibited reduced scope, intensity, and duration of complexity drop, all of which improved after treatment. Reduced duration was negatively correlated with CPT scores and positively with clinical symptoms. The results suggest that abnormalities in brain activity complexity and its dynamic changes may underlie cognitive deficits and clinical symptoms in SZ patients. Antipsychotic treatment partially restores these abnormalities, highlighting their potential as indicators of treatment efficacy and biomarkers for personalized therapy.

Suicide is the second leading cause of death in youth, and depression is a strong proximal predictor of adolescent suicide. It is important to identify psychological factors that may protect against suicide ideation in depressed adolescents. Self-compassion may be such a factor. Converging evidence indicates the inverse association between self-compassion and suicide ideation, but the neural mechanisms underlying their link remain unknown. Because self-referential caudate activity is associated with both self-compassion and suicide ideation, its functional connectivity might explain their relationship. In this study, we examined the relationship between self-compassion and caudate functional connectivity during self-appraisals, a typical self-referential paradigm, and their associations with suicide ideation in both depressed and healthy youth. In the scanner, 79 depressed youth and 36 healthy controls evaluated, from various perspectives, whether phrases they heard were self-descriptive. Self-compassion and suicide ideation were rated with self-report and interview-based measures. We found that self-compassion was associated with stronger left caudate functional connectivity with bilateral posterior superior temporal sulcus/temporoparietal junction, the left middle temporal gyrus (MTG), and the left middle occipital gyrus during positive versus negative self-appraisals. Stronger left caudate connectivity with the left MTG explained the association between higher self-compassion and lower suicide ideation, even controlling for non-suicide ideation depression severity, anxiety severity, and non-suicidal self-injurious behavior. The findings suggest that the left caudate to MTG connectivity during positive versus negative self-referential processing could be a biomarker to be targeted by neural stimulation interventions for reducing suicide ideation in depressed youth, combined with self-compassion interventions.

UNASSIGNED: Excessive daytime sleepiness (EDS) and caudate nucleus volume alterations have been linked to Alzheimer\'s disease (AD), but their relationship remains unclear under the context of subjective cognitive decline (SCD).
UNASSIGNED: This study aimed to investigate the relationship between EDS and caudate nucleus volume in patients with SCD.
UNASSIGNED: The volume of entire brain was measured in 170 patients with SCD, including 37 patients with EDS and 133 non-EDS, from the Sino Longitudinal Study on Cognitive Decline (SILCODE). Participants underwent a comprehensive assessment battery, including neuropsychological and clinical evaluations, blood tests, genetic analysis for APOE ɛ4, and structural MRI scans analyzed using the fully automated segmentation tool, volBrain.
UNASSIGNED: Patients with EDS had significantly increased volume in the total and left caudate nucleus compared to non-EDS. The most significant cognitive behavioral factor associated with caudate nucleus volume in the EDS was the Auditory Verbal Learning Test-recognition.
UNASSIGNED: These findings suggest that EDS may be associated with alterations in caudate nucleus volume, particularly in the left hemisphere, in the context of SCD. Further research is necessary to understand the underlying mechanisms of this relationship and its implications for clinical management.

Past cross-sectional chronic pain studies have revealed aberrant resting-state brain activity in regions involved in pain processing and affect regulation. However, there is a paucity of longitudinal research examining links of resting-state activity and pain resilience with changes in chronic pain outcomes over time. In this prospective study, we assessed the status of baseline (T1) resting-state brain activity as a biomarker of later impairment from chronic pain and a mediator of the relation between pain resilience and impairment at follow-up. One hundred forty-two adults with chronic musculoskeletal pain completed a T1 assessment comprising a resting-state functional magnetic resonance imaging scan based on regional homogeneity (ReHo) and self-report measures of demographics, pain characteristics, psychological status, pain resilience, pain severity, and pain impairment. Subsequently, pain impairment was reassessed at a 6-month follow-up (T2). Hierarchical multiple regression and mediation analyses assessed relations of T1 ReHo and pain resilience scores with changes in pain impairment. Higher T1 ReHo values in the right caudate nucleus were associated with increased pain impairment at T2, after controlling for all other statistically significant self-report measures. ReHo also partially mediated associations of T1 pain resilience dimensions with T2 pain impairment. T1 right caudate nucleus ReHo emerged as a possible biomarker of later impairment from chronic musculoskeletal pain and a neural mechanism that may help to explain why pain resilience is related to lower levels of later chronic pain impairment. Findings provide empirical foundations for prospective extensions that assess the status of ReHo activity and self-reported pain resilience as markers for later impairment from chronic pain and targets for interventions to reduce impairment. PRACTITIONER POINTS: Resting-state markers of impairment: Higher baseline (T1) regional homogeneity (ReHo) values, localized in the right caudate nucleus, were associated with exacerbations in impairment from chronic musculoskeletal pain at a 6-month follow-up, independent of T1 demographics, pain experiences, and psychological factors. Mediating role of ReHo values: ReHo values in the right caudate nucleus also mediated the relationship between baseline pain resilience levels and later pain impairment among participants. Therapeutic implications: Findings provide empirical foundations for research extensions that evaluate (1) the use of resting-state activity in assessment to identify people at risk for later impairment from pain and (2) changes in resting-state activity as biomarkers for the efficacy of treatments designed to improve resilience and reduce impairment among those in need.

It is of vital importance to establish an objective and reliable model to facilitate the early diagnosis and intervention of internet gaming disorder (IGD). A total of 133 patients with IGD and 110 healthy controls (HCs) were included. We extracted radiomic features of subcortical structures in high-resolution T1-weighted MRI. Different combinations of four feature selection methods (analysis of variance, Kruskal-Wallis, recursive feature elimination and relief) and ten classification algorithms were used to identify the most robust combined models for distinguishing IGD patients from HCs. Furthermore, a nomogram incorporating radiomic signatures and independent clinical factors was developed. Calibration curve and decision curve analyses were used to evaluate the nomogram. The combination of analysis of variance selector and logistic regression classifier identified that the radiomic model constructed with 20 features from the right caudate nucleus and amygdala showed better IGD screening performance. The radiomic model produced good areas under the curves (AUCs) in the training, validation and test cohorts (AUCs of 0.961, 0.903 and 0.895, respectively). In addition, sex, internet addiction test scores and radiomic scores were included in the nomogram as independent risk factors for IGD. Analysis of the correction curve and decision curve showed that the clinical-radiomic model has good reliability (C-index: 0.987). The nomogram incorporating radiomic features of subcortical structures and clinical characteristics achieved satisfactory classification performance and could serve as an effective tool for distinguishing IGD patients from HCs.

Although most category learning studies use feedback for training, little attention has been paid to how individuals utilize feedback implemented as gains or losses during categorization. We compared skilled categorization under three different conditions: Gain (earn points for correct answers), Gain and Loss (earn points for correct answers and lose points for wrong answers) and Correct or Wrong (accuracy feedback only). We also manipulated difficulty and point value, with near boundary stimuli having the highest number of points to win or lose, and stimuli far from the boundary having the lowest point value. We found that the tail of the caudate was sensitive to feedback condition, with highest activity when both Gain and Loss feedback were present and least activity when only Gain or accuracy feedback was present. We also found that activity across the caudate was affected by distance from the decision bound, with greatest activity for the near boundary high value stimuli, and lowest for far low value stimuli. Overall these results indicate that the tail of the caudate is sensitive not only to positive rewards but also to loss and punishment, consistent with recent animal research finding tail of the caudate activity in aversive learning.

Movement and muscle control are crucial for the survival of all free-living organisms. This study aimed to explore differential patterns of cortical and subcortical activation across different stages of muscle control using functional magnetic resonance imaging (fMRI). An event-related design was employed. In each trial, participants (n = 10) were instructed to gently press a button with their right index finger, hold it naturally for several seconds, and then relax the finger. Neural activation in these temporally separated stages was analyzed using a General Linear Model. Our findings revealed that a widely distributed cortical network, including the supplementary motor area and insula, was implicated not only in the pressing stage, but also in the relaxation stage, while only parts of the network were involved in the steady holding stage. Moreover, supporting the direct/indirect pathway model of the subcortical basal ganglia, their substructures played distinct roles in different stages of muscle control. The caudate nucleus exhibited greater involvement in muscle contraction, whereas the putamen demonstrated a stronger association with muscle relaxation; both structures were implicated in the pressing stage. Furthermore, the subthalamic nucleus was exclusively engaged during the muscle relaxation stage. We conclude that even the control of simple muscle movements involves intricate automatic higher sensory-motor integration at a neural level, particularly when coordinating relative muscle movements, including both muscle contraction and muscle relaxation; the cortical and subcortical regions assume distinct yet coordinated roles across different stages of muscle control.

The cognitive impairment will gradually appear over time in Parkinson\'s patients, which is closely related to the basal ganglia-cortex network. This network contains two parallel circuits mediated by putamen and caudate nucleus, respectively. Based on the biophysical mean-field model, we construct a dynamic computational model of the parallel circuit in the basal ganglia-cortex network associated with Parkinson\'s disease dementia. The simulated results show that the decrease of power ratio in the prefrontal cortex is mainly caused by dopamine depletion in the caudate nucleus and is less related to that in the putamen, which indicates Parkinson\'s disease dementia may be caused by a lesion of the caudate nucleus rather than putamen. Furthermore, the underlying dynamic mechanism behind the decrease of power ratio is investigated by bifurcation analysis, which demonstrates that the decrease of power ratio is due to the change of brain discharge pattern from the limit cycle mode to the point attractor mode. More importantly, the spatiotemporal course of dopamine depletion in Parkinson\'s disease patients is well simulated, which states that with the loss of dopaminergic neurons projecting to the striatum, motor dysfunction of Parkinson\'s disease is first observed, whereas cognitive impairment occurs after a period of onset of motor dysfunction. These results are helpful to understand the pathogenesis of cognitive impairment and provide insights into the treatment of Parkinson\'s disease dementia.

Previous studies have indicated a potential relationship between zinc and epilepsy. The aim of this study is to investigate the causal relationship between zinc, zinc-dependent carbonic anhydrase, and gray matter volume in brain regions enriched with zinc and epilepsy, as well as explore the possible mechanisms by which zinc contributes to epilepsy. First, this study assessed the risk causality between zinc, carbonic anhydrase, and gray matter volume alterations in zinc-enriched brain regions and various subtypes of epilepsy based on Two-sample Mendelian randomization analysis. And then, this study conducted GO/KEGG analysis based on colocalization analysis, MAGMA analysis, lasso regression, random forest model, and XGBoost model. The results of Mendelian randomization analyses showed a causal relationship between zinc, carbonic anhydrase-4, and generalized epilepsy (p = 0.044 , p = 0.010). Additionally, carbonic anhydrase-1 and gray matter volume of the caudate nucleus were found to be associated with epilepsy and focal epilepsy (p = 0.014, p = 0.003 and p = 0.022, p = 0.009). A colocalization relationship was found between epilepsy and focal epilepsy (PP.H4.abf = 97.7e - 2). Meanwhile, the MAGMA analysis indicated that SNPs associated with epilepsy and focal epilepsy were functionally localized to zinc-finger-protein-related genes (p < 1.0e - 5). The genes associated with focal epilepsy were found to have a molecular function of zinc ion binding (FDR = 2.3e - 6). After the onset of epilepsy, the function of the gene whose expression changed in the rats with focal epilepsy was enriched in the biological process of vascular response (FDR = 4.0e - 5). These results revealed mechanism of the increased risk of epilepsy caused by elevated zinc may be related to the increase of zinc ion-dependent carbonic anhydrase or the increase of the volume of zinc-rich caudate gray matter.

BACKGROUND: Apathy is a common neuropsychiatric manifestations in Parkinson\'s disease (PD), but neural network mechanisms still remain elusive. We aim to investigate the topological alteration of the brain structural network in PD with apathy.
METHODS: In the present study, a total of 47 apathetic PD (aPD) patients, 37 non-apathetic PD (naPD) patients, and 40 healthy controls (HCs) were enrolled. Diffusion tensor imaging (DTI) in conjunction with graph-theoretic approaches were used to explore the alterations of topological properties of the WM structural network arising from apathy in PD. One-way analysis of covariance and post hoc analyses were performed to explore differences among the three groups. Correlations were ascertained to examine relationships between the Starkstein Apathy Scale (AS) scores and significantly different network metrics among the three groups.
RESULTS: Both aPD and naPD patients remained small-world topology. However, compared with the naPD patients, aPD patients showed increased clustering coefficient (Cp) at the global level. At the regional level, aPD exhibited decreased nodal properties, mainly in the right dorsolateral prefrontal cortex (DLPFC), the right caudate nucleus (CAU), the right hippocampus, and the right superior parietal gyrus. Further, AS scores were negatively correlated with degree centrality of the right DLPFC (r = -0.254, p = 0.020) and the right CAU ( r = -0.357, p = 0.001) in the pooled patients with PD.
CONCLUSIONS: The findings suggested that apathy in PD presented relatively optimized global topological properties of the brain structural network and disrupted topological organization of the regional network, particularly involving the fronto-striatal-limbic circuits. The altered topological properties of abnormal brain regions might be used to understand the physiopathologic mechanism of the neural network in aPD patients.