Institute of Psychology, Chinese Academy of Sciences
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Distinct Structural Alterations in Cortical and Subcortical Regions in Females With Acute Anorexia Nervosa: A Cross-Sectional MRI Study With BMI-Matched Healthy Controls
No full textObjective This study aimed to explore potential disease-specific and weight-related neurostructural alterations in patients with acute anorexia nervosa (AN).Method Employing a novel BMI-matched design, structural MRI data were collected from 36 females with AN, 35 normal-weight healthy controls (NHC), and 29 underweight healthy controls (UHC). Cortical (thickness, surface area) and subcortical (volume) morphometry measures were computed via FreeSurfer. Group differences were tested using generalized linear models, with associations examined for BMI, symptom severity, and weight suppression (lifetime highest minus current weight).Results Compared with UHC, AN patients exhibited subcortical volume reductions in the bilateral pallidum and caudate, left putamen, and right thalamus, as well as cortical thinning in default mode network regions (bilateral inferior parietal lobule, right precuneus, posterior cingulate cortex) and the left cuneus, indicating potential disease-specific alterations. Comparisons between UHC and NHC revealed BMI-related alterations, reflected in surface area reductions of the right orbitofrontal cortex and left insula, and in volume reductions of the bilateral amygdala, right hippocampus, and left thalamus. Within AN, weight suppression was negatively associated with cortical thickness across 44 regions, suggesting a possible link with prior weight loss.Conclusions By including BMI-matched healthy control groups, this study provides preliminary evidence for distinguishing disease-specific from BMI-related neurostructural alterations in patients with AN. Future research may help clarify the role of weight suppression
Visual congruency of performers' movements enhances vocal music reward through Mu entrainment
No full textThere is emerging evidence that a performer's body movements may enhance music-induced pleasure. However, the neural mechanism underlying such modulation remains largely unexplored. This study utilized behavioural, psychophysiological, and electroencephalographic data collected from 32 listeners (analysed sample = 31), as they watched and listened to vocal (Mandarin lyrics) and violin performances of pop music videos. None were familiar with Mandarin, and none had significant training in string instruments. Stimuli featured either congruent or incongruent audiovisual parings within the same instrument. We found that congruent visual movements, as opposed to incongruent ones, significantly increased both subjective pleasure ratings and skin conductance responses. While Mu-band power suppression occurred in the presence of visual movements regardless of congruency; congruent movements enhanced the coherence between the music envelope and Mu-band oscillations (so-called Mu entrainment). Effect sizes for both measures were greater for vocal than violin music, though no interaction was observed. Mediation analysis demonstrated that Mu entrainment to vocal music significantly mediated the visual modulation of music-induced pleasure and that this effect occurs primarily for familiar vocal rather than unfamiliar violin movements. In conclusion, our study provides evidence that congruent visual movements enhance music pleasure by promoting Mu entrainment, potentially through sensorimotor integration mechanisms
Implied gravity promotes coherent motion perception
No full textGravity, a constant in Earth's environment, constrains not only physical motion but also our estimation of motion trajectories. Early studies show that natural gravitational acceleration facilitates the manual interception of free-falling objects. However, whether implied gravity affects the perception of coherent motion patterns from local motion cues remains poorly understood. Here, we designed a motion coherence threshold task to measure the visual discrimination of coherent global motion with natural (1 g) and reversed (-1 g) gravitational accelerations. Across five experiments, we showed that the perceptual thresholds of motion coherence were significantly lower under the natural gravity than the reversed gravity condition, regardless of variations in stimulus parameters and visual contexts. These convergent results suggest that the human visual system inherently extracts the gravitational acceleration cues conveyed by local motion signals and integrates them into a unified global motion, thereby facilitating the visual perception of complex motion patterns in natural environments
Role of baseline resting-state functional connectivity of the nucleus accumbens subregions in antidepressant treatment in major depressive disorder
No full textThe nucleus accumbens (NAc) plays a crucial role in the pathophysiology of major depressive disorder (MDD), and abnormal resting-state functional connectivity (rsFC) of NAc subregions has been found in MDD. However, it is unclear whether the altered rsFC of NAc subregions can predict the efficacy of antidepressant treatment, and whether antidepressants are capable of restoring the altered rsFC of NAc subregions in MDD. The purpose of this study was to investigate the role of rsFC of the NAc subregions in antidepressant treatment for MDD. Restingstate functional magnetic resonance imaging (fMRI) data were collected from 46 unmedicated MDD patients at baseline and after 12 weeks of escitalopram treatment, along with fMRI data from 58 healthy controls (HCs). We examined group differences in rsFC of the NAc subregions between MDD patients and HCs, explored whether the altered rsFC at baseline was associated with treatment efficacy, and evaluated whether antidepressant treatment could normalize rsFC abnormalities in the NAc subregions in MDD. Compared to HCs, MDD patients exhibited decreased rsFC between the NAc subregions and the middle cingulate cortex (MCC). Lower levels of rsFC between the NAc subregions and the MCC at baseline predicted greater improvement in depressive symptoms. Furthermore, rsFC between the NAc subregions and the MCC increased following antidepressant treatment in MDD. Our findings suggest that rsFC alterations between the NAc subregions and the MCC may serve as a potential biomarker for predicting antidepressant treatment efficacy, and that dysfunction in the frontal-ventral striatum circuitry may represent a key therapeutic target for MDD
Uncovering the depressive symptom network in self-harming rural children: a Bayesian undirected network analysis
No full textSelf-harm among children is a growing public health concern, particularly in rural settings where unique socioeconomic and environmental factors increase vulnerability. This study explored depressive symptom networks in rural children with and without self-harm behaviors, using Bayesian undirected network analysis to identify symptom-level differences and inform targeted interventions. Data were collected from 2,009 rural elementary school students (Mage = 10.73 years, SD = 1.65) across seven Chinese provinces. Depressive symptoms were assessed using the Child Depression Inventory, and self-harm behaviors were identified through selfreported measures. Bayesian undirected network analysis compared depressive symptom networks between children with (N = 417) and without (N = 1592) self-harm behaviors. The results revealed that children with self-harm behaviors exhibited less densely connected symptom networks, with Anhedonia, Feeling Unloved, and Somatic Concerns as the most central symptoms. In contrast, children without self-harm behaviors displayed denser, strongly clustered networks, with Anhedonia, Permissive Worrying, and Somatic Concerns as central symptoms. Significant differences in network density and clustering coefficients were observed between the two groups. These findings suggest that self-harming children experience more fragmented emotional and social dynamics, while non-self-harming children demonstrate stronger symptom interconnectivity that may support better emotional regulation. These findings emphasize the need for rural-specific mental health policies and services, including school-based programs, telepsychiatry, and community-driven efforts to reduce mental health stigma and improve early detection of depressive symptoms and self-harm behaviors. By addressing the unique challenges of rural communities, this study contributes to improved mental health outcomes and supports the development of evidence-based, symptom-focused interventions for underserved populations.</p
Boosting your mood: How exercise and the amygdala dance together
No full textAccumulative evidence has shown that functional heterogeneity exists in subregions of amygdala. Recently, exercise serving as automatic emotion regulation has been observed to induce the altered activation of amygdala associated with mood change. However, the specific role of subregions of amygdala underlying these effects are not fully understood. By using resting-state functional magnetic resonance imaging (rs-fMRI), this study examined whether the subregions of amygdala play distinct roles in mood improvement induced by acute exercise. Participants (n = 76) aged 18-22 were recruited and randomly divided into the exercise group and the control group. The exercise group received a 30-minute intervention with moderate-intensity exercise while the control group completed a reading control task at resting state. Whole-brain rs-fMRI scans were conducted before and after the interventions. Moreover, participants' moods were also assessed using the Positive and Negative Affect Schedule (PANAS) and Abbreviated Profile of Mood States. A mixed-effect model was used to analyze the Group x Time interaction on functional connectivity (FC) seeded from medial amygdala (mAmyg) and lateral amygdala (lAmyg) subregions in each hemisphere. Results revealed that exercise-induced mood improvements were correlated with significant Group x Time interaction effects on FC, showing a notable right-hemispheric predominance. Specifically, enhanced connectivity of the right mAmyg with orbitofrontal cortex, parietal, and cerebellar regions was associated with reduced negative affect and increased self-esteem. Concurrently, enhanced connectivity of the right lAmyg with the orbitofrontal cortex and striatum was linked to a broad spectrum of improvements, including reduced tension and anger, and increased vigor. These findings suggest that acute exercise improves mood via distinct, lateralized neural pathways centered on different amygdala subregions. The mAmyg and lAmyg play complementary roles in automatic emotion regulation, with the right mAmyg modulating affective valence and self-evaluation, while the right lAmyg appears to regulate a broad spectrum of mood states and enhance positive arousal. This work provides a more nuanced neurobiological model for the therapeutic effects of exercise.</p
Exploring the alterations in microstate dynamics during the migraine cycle and detecting pre-ictal phases
No full textBackgroundMicrostate analysis captures brief but critical fluctuations in brain activity, making it a powerful tool for exploring the cyclic nature of migraine. In this study, we aimed to investigate microstate features during different migraine phases and develop a classification model to identify the pre-ictal phase.MethodsFrom May 2023 to June 2024, we conducted a cross-sectional study with consecutive recruitment, collecting resting-state electroencephalography data from 174 individuals with migraine without aura and 50 healthy controls, followed by classification of migraine phases. Microstate features, Lempel-Ziv complexity, and sample entropy were compared across five groups. A model was developed to identify the pre-ictal phase and validated on a test set.ResultsMicrostate features, particularly for microstates A and B, exhibited dynamic changes across the migraine cycle. The duration of microstate A was significantly longer in the inter-ictal phase than in the pre-ictal phase, whereas microstate B showed prolonged duration in the pre-ictal phase compared to healthy controls and the post-ictal phase. Microstate A displayed reduced coverage in the pre-ictal phase, whereas microstate B had increased occurrence and coverage during the pre-ictal and ictal phases. Transition probabilities also varied significantly: the pre-ictal phase showed elevated transitions from microstates A, C, and D to B, and the post-ictal phase showed reduced transitions from C and D to A. A classification model based on these microstate features achieved an area under the receiver operating characteristic curve (AUROC) of 0.85 (0.73-0.95), an area under the precision-recall curve (AUPRC) of 0.83 (0.66-0.95), and an F1 score of 0.78 (0.62-0.90) in the training set; and an AUROC of 0.84 (0.69-0.97), an AUPRC of 0.86 (0.67-0.98), and an F1 score of 0.81 (0.65-0.93) in the test set, indicating robust performance in identifying the pre-ictal phase.ConclusionThrough the observation of cyclic alterations in the microstates of patients with migraine, we identified a reduction in microstate A and an enhancement in microstate B during the pre-ictal phase. These changes may indicate a heightened sensitivity to auditory stimuli and increased activity in the visual cortex, providing new insights into migraine pathophysiology. Our model effectively identified the pre-ictal phase, offering a promising approach for early intervention in migraine attacks
The prevalence and clinical correlates of severe anxiety symptoms in first-episode drug-na?ve schizophrenia: a Chinese population study
No full textObjectiveAlthough anxiety symptoms frequently co-occur with schizophrenia and may substantially influence disease progression and treatment outcomes, systematic investigations of this comorbidity remain limited. This study aimed to investigate the prevalence and clinical correlations of severe anxiety symptoms among Chinese patients with first-episode drug-naive (FEDN) schizophrenia. MethodsThis cross-sectional study enrolled 255 FEDN schizophrenia patients. Comprehensive clinical and demographic data were collected from all participants. Psychiatric symptoms were assessed using PANSS, while anxiety and depression symptoms were evaluated using the 14-item Hamilton Anxiety Rating Scale (HAMA-14) and the 24-item Hamilton Depression Rating Scale (HAMD-24), respectively. Participants were stratified into two groups based on the presence or absence of severe anxiety symptoms, defined by a HAMA score >= 29. Multivariate logistic regression analysis was employed to identify potential correlates associated with severe anxiety symptoms in FEDN schizophrenia patients. ResultsThe prevalence of severe anxiety symptoms among patients with FEDN schizophrenia was 51.8% (132/255). Multivariable logistic regression analysis revealed that both elevated HAMD-24 scores (OR = 1.17, 95% CI: 1.11-1.22, p < 0.001) and higher high-density lipoprotein cholesterol (HDL-c) levels (OR = 4.70, 95% CI: 1.53-14.4, p = 0.007) were independently associated with increased risk of severe anxiety symptoms. The area under the curve (AUC) analysis revealed distinct predictive capabilities: HAMD-24 demonstrated strong standalone predictive ability (AUC = 0.868), while HDL-c showed limited discriminative capacity (AUC = 0.592) despite statistical significance in multivariable regression. ConclusionThis study highlights the substantial prevalence of severe anxiety symptoms among patients with FEDN schizophrenia. Our multivariable analysis identified HAMD-24 scores and HDL-c levels as significant factors associated with severe anxiety symptoms in this population. These findings enhance our understanding of anxiety mechanisms in FEDN schizophrenia, potentially informing future treatment strategies.</p
Digital Escape and Behavioral Modeling Investigating Algorithm-Driven Video Usage and Mental Health Outcomes Among Working Adults
No full textWith the rapid expansion of algorithm-curated short video platforms, discussions have intensified over their potential to contribute to excessive use and to influence employees’ mental health in occupational settings. This study explores how algorithmic video consumption impacts mental health outcomes-specifically depression, anxiety, and fatigue-among working adults. Using a computational behavioral modeling approach, we propose a moderated mediation model where loneliness leads to distress via video addiction, moderated by self-efficacy. Data from 559 employees in China were analyzed, incorporating behavioral features such as usage time, context, and content preference. Evidence from SEM revealed that loneliness influenced distress indirectly, while self-efficacy moderated this association. To inform the development of platform-side mechanisms for mitigating overuse, we present a conceptual framework for behavioral signal extraction, aimed at converting passive usage data into predictive digital biomarkers. These findings inform the design of algorithm-aware intervention systems that support employee mental well-being in digital environments.</p
Feature similarity, a sensitive method to capture the functional interaction of brain regions and networks to support flexible behavior
No full textThe brain is a dynamic system where complex behaviours emerge from interactions across distributed regions. Accurately linking brain function to cognition requires methods sensitive to these interactions. We introduce Feature Similarity (FS), which integrates a broad set of interpretable time-series features-such as covariance, temporal dependencies, and entropy -to move beyond traditional single-metric approaches. FS captured functional brain organization: regions within the same network showed greater similarity than those in different networks, and FS identified the principal gradient from unimodal to transmodal cortices. Compared with Pearson correlation-based functional connectivity (FC) and 46 out of 49 statistical pairwise interaction metrics (SPIs), FS demonstrated greater sensitivity to task modulation. Critically, FS revealed a task-dependent dstrongly with the Visual network during working memory but with the default mode network during long-term memory. FS thus provides a powerful tool for uncovering task-specific brain network interactions.ouble dissociation in the Dorsal Attention Network, interacting more</p
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