Institute of Psychology, Chinese Academy of Sciences
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Longitudinal effects of parent-child relationship quality on adolescent non-suicidal self-injury: the role of serotonergic multilocus genetic variation
No full textThe present study examined the impact of serotonergic multilocus genetic variation, parent-child relationship quality and gender on the developmental trajectory of adolescent non-suicidal self-injury (NSSI). A sample of 552 first-year junior high school students from Hunan Province, China, participated in a three-wave longitudinal study. The study included detailed questionnaires and genetic sampling, conducted over a period of one and a half years. We hypothesize that parent-child relationship quality and serotonergic multilocus genetic profile score (MGPS) interact to influence adolescent NSSI trajectories, with possible gender differences. Using latent growth curve modeling (LGCM), the results revealed a linear decrease in NSSI over time, with parent-child relationship quality significantly predicting initial NSSI levels. The interaction between serotonergic MGPS and parent-child relationship quality predicted the intercept but not the growth rate of NSSI. There were also gender differences, such that female adolescents were more vulnerable to the combined effects of parent-child relationship quality and genetic factors, patterns that emerged for both initial NSSI intercept and slope. These results highlight the pivotal role of genetic and environmental factors, particularly parent-child relationship quality, in adolescent mental health. This work suggests that future interventions may be designed to strengthen parent-child relationships and tailored to genetic risks and gender-specific vulnerabilities.</p
Dissociation of Stimulus Representation and Response Selection in Conflict Processing of Multiple Frames of Reference
No full textHumans use multiple frames of reference (FORs) to represent spatial information, for example, one egocentric FOR (anchored on the observer) and various intrinsic FORs (anchored on the objects in the environment). Previous studies have shown that the cognitive resource competition of FORs will lead to FOR-based conflicts (e.g., egocentric-intrinsic, intrinsic-intrinsic) and their interactions. However, it remains unclear whether these conflicts and their interactions occur during the cognitive process stage of stimulus-representation, response-selection, or both. In our study, on the basis of a modified two-cannon task, the spatial congruency and response congruency of two cannons (intrinsic FORs anchored) were manipulated to localize the two process stages of intrinsic-intrinsic conflict. The results revealed that intrinsic-intrinsic conflict was affected by both factors, indicating that response time (RT) in the spatially incongruent condition was longer than that in the spatially congruent condition and that RT in the response incongruent condition was longer than that in the response congruent condition. Furthermore, an interaction between egocentric-intrinsic and intrinsic-intrinsic conflicts was observed, showing that the egocentric-intrinsic conflict did not change between the spatially congruent and incongruent conditions but increased from the response congruent condition to the response incongruent condition. These findings suggest that intrinsic-intrinsic conflict occurs in both the stimulus-representation and response-selection stages, whereas egocentric-intrinsic conflict occurs only in the response-selection stage. The two conflicts share a common conflict processing mechanism in the response-selection stage
Measuring understandability of intelligent systems Scale development and validation across three domains
No full textWhile modern intelligent systems using black-box algorithms have proved their usefulness in many areas, whether the systems’ decisions and intentions can be fully understood by human users is still a critical question. However, the measurement of system understandability is lacking, and it undermines the development of this direction. To fill in such a gap, we conducted three studies to construct a scale to measure the understandability in three intelligent systems. In Study 1, we developed the original scale items through document analysis and expert interviews. In Study 2, we exposed 307 participants to autonomous vehicle systems which provided different amounts of information in simulated takeover scenarios. The participants’ responses towards these systems were collected using the developed scale. Exploratory factors analysis found 4 factors (Explanation Comprehensiveness, Trustworthiness Calibration, Cognitive Accessibility, and Explanation Necessity), and they had significant correlation with important attitudinal behavioral outcomes including trust, usage intention, and satisfaction. In Study 3, we further validated the structural and criterion-related validity of the scale using a new sample of 347 participants interacting with medical and financial decision support systems. The results indicate that the developed scale is a reliable and effective tool for assessing understandability in different intelligent systems, with potential to significantly enhance the design of intelligent systems to be more user-friendly and comprehensible.</p
Enhanced Speech Emotion Recognition in Noisy Environments: Adaptive Emotion Denoising Diffusion Approach With Iterative Confidence Learning Strategy
No full textSpeech emotion recognition (SER) in noisy environments is challenging due to the overlap of emotional cues with background noise. This paper proposes a novel approach to transfer emotional information from clean to noisy speech, ensuring robust recognition even in adverse conditions. First, 3D Multi-Resolution Modulated Filtered Cochleogram features are extracted to capture dynamic emotional information, while delta and delta-delta features enhance emotional dynamics in both time and frequency domains. Additionally, the Emotional BiMamba Encoder, utilizing bidirectional parallel processing through the Multi-time View Bidirectional State Space Model is designed to capture complex emotional patterns across temporal scales, preserving short-and long-term dependencies. Next, the Adaptive Emotion Denoising Diffusion (AEDD) based on a diffusiondenoising probabilistic model, applies confidence filtering to select representative emotional segments and transfer emotional information from clean to noisy speech, addressing noisy emotional data scarcity. Finally, the Iterative Confidence Learning Strategy (ICLS) enhances the classification network (CN) through a twostage learning process, progressively adapting CN to noisy feature distributions while ensuring consistency during diffusion. The experimental results show significant improvements over the state-of-the-art methods on three datasets: on IEMOCAP, WA increases by 5.07%, UA by 5.23%, and WF1 by 5.44%; on CASIA, WA and UA rise by 2.72%, and WF1 by 2.23%; and on EMODB, WA improves by 3.46%, UA by 3.23%, and WF1 by 3.45%. These consistent gains across different signal-to-noise ratios further validate the effectiveness of the proposed method.</p
Utilizing the Visual Working Memory Paradigm Based on the "Global-First" Topological Approach to Optimize Psychiatric Disorders Diagnosis and Differentiation
No full textCurrent diagnostic methods present major challenges in accurately diagnosing and differentiating psychiatric disorders. Due to the key role of visual working memory (VWM) for cross-diagnosis research on information processing deficits, we developed a new VWM paradigm based on the "global-first" topological visual perception theory to detect different psychiatric disorders among age groups. In young groups, significant differences in accuracy were observed between topological change and no-shape-change (all p 0.70-0.98] suggests clinical utility, further validation against traditional diagnostic instruments (e.g., DSM-5 criteria, symptom scales) is required to establish its role in clinical practic
Interoceptive abnormalities in COPD patients: Their predictive role in anxiety and acute exacerbation of COPD
No full textChronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, significantly impacting both physical and psychological health. Anxiety, a prevalent comorbidity in COPD, exacerbates respiratory symptoms, impairs disease management, and increases healthcare utilization. Interoceptive sensitivity, the ability to perceive and interpret internal bodily signals, plays a critical role in managing chronic conditions, yet its influence on healthcare utilization in COPD remains underexplored. This study investigates the relationship between interoceptive sensitivity, anxiety sensitivity, and acute exacerbation hospitalization rates in COPD patients, aiming to identify potential therapeutic targets to improve patient outcomes. A cross-sectional study was conducted among 73 COPD patients recruitedboth outpatients and inpatients of respiratory department. Interoceptive sensitivity was assessed using a body perception questionnaire-very short form scale, and autonomic nervous system (ANS) reactivity was assessed through body perception questionnaire 20-autonomic nervous system. Anxiety sensitivity was measured with the anxiety sensitivity index-3 physical concerns subscale. Depression and anxiety were evaluated by PHQ-9 and GAD-7 seperately. Acute exacerbation of COPD (AECOPD) was identified by self-reported hospitalizations and verified via medical records over the preceding year, according to GOLD 2023 criteria. Logistic regression models were used to analyze the associations between interoceptive sensitivity, anxiety sensitivity, and its correlation with AECOPD. Higher interoceptive sensitivity was associated with a 28.4% reduction in the likelihood of AECOPD (odds ratios = 0.716, 95% confidence intervals: 0.58-0.88, P = .002), suggesting a protective effect. Conversely, elevated anxiety sensitivity increased AECOPD by 126.6% (odds ratios = 2.266, 95% confidence intervals: 1.32-3.89, P = .003). Other demographic and clinical factors, including age, body mass index, and COPD duration, were not significant predictors of AECOPD. The findings reveal the dual role of interoceptive sensitivity and anxiety sensitivity in influencing healthcare utilization among COPD patients. Interventions targeting interoceptive skills and anxiety sensitivity, such as mindfulness-based therapy, may improve symptom management, reduce emergency healthcare utilization and hospital admission, and enhance overall quality of life in this population. Future research should explore longitudinal and interventional studies to further elucidate these relationships.</p
The Time-Space Frame in Road Signs Affects Pathfinding Driving Performance: Results From Bayesian Networks
No full textThe time-space frame affects individuals' travel preference by modifying the way information is presented, but its impact on driving behavior during travel remains unknown. The present study examined whether road sign under either time or space frames affects driving performance, using a simulated driving pathfinding experiment. A total of 53 participants took part in the experiment, each completing seven pathfinding tasks. The study found that road signs under the space frame created a longer psychological distance compared to those under the time frame, demonstrating the presence of the time-space framing effect. Bayesian Networks showed that the probability of risky driving under the space frame was higher than under the time frame. Male drivers showed a higher probability of risky driving under the space frame. These results suggest that longer psychological distances can lead to more dangerous driving behaviors. Driving safety can be enhanced by presenting drivers with information framed in different ways
Parental Marital Quality and School Bullying Victimization: A Moderated Mediation Model of Parent-Child Attachment and Child Gender
No full textBackground/Objectives: School bullying is a significant issue that negatively impacts children's well-being, emphasizing the need to identify family-related factors contributing to bullying victimization. This study explored the potential link between parental marital quality and school bullying victimization by employing a moderated mediation model. Methods: Parent-child attachment, measured separately as father-child and mother-child attachment, was tested as a mediator, with child gender included as a moderator. Data were collected from both children and their mothers, comprising 358 mother-child pairs recruited from three primary schools in suburban Beijing, China. Results: Results revealed that greater parental marital quality was associated with a lower risk of bullying victimization, with father-child attachment mediating this relationship. Furthermore, child gender moderated the mediating effect of father-child attachment, such that the indirect pathway from parental marital quality to bullying victimization through father-child attachment was statistically significant for girls but not for boys. Conclusions: These findings highlight the importance of father-child attachment in preventing bullying victimization and suggest that gender-sensitive implications may be necessary
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.</p
The neurocognitive mechanism underlying math avoidance among math anxious people
No full textThis study explores the cognitive and neural mechanisms underlying math avoidance in individuals with high math anxiety (HMA), a pattern contributing to reduced practice and poor performance. Using an approach-avoid conflict paradigm and both general linear mixed model and Hierarchical Drift Diffusion Model (HDDM) regression analyses, we found their avoidance behavior is primarily driven by heightened sensitivity to task difficulty, rather than reward sensitivity. Task difficulty sensitivity also mediated the link between math anxiety and avoidance tendency. Neuroimaging revealed distinct activation in the ventral valuation network (e.g., nucleus accumbens, hippocampus) and cognitive control regions (e.g., precuneus, mid-cingulate cortex, temporo-parietal junction) in HMA individuals. Functional connectivity among these regions effectively distinguished HMA from low math anxiety participants. Additionally, activations in the hippocampus, mid-cingulate cortex, and posterior insula mediated the relationship between math anxiety and avoidance. These findings highlight the cognitive and neural bases of math avoidance and may inform targeted interventions.</p
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