Institute of Psychology, Chinese Academy of Sciences
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Connectome-based predictive modeling of handwriting and reading using task-evoked and resting-state functional connectivity
No full textPrevious studies have shown that functional connectivity-based models can characterize individual differences in human behavior. However, the applicability of such models to skilled motor behavior remains largely unexplored. In this study, we employed a connectome-based predictive modeling (CPM) approach to predict individual differences in handwriting skills using handwriting task-related and resting-state functional magnetic resonance imaging (fMRI) data. Our results demonstrated that general functional connectivity (GFC) metrics, which capture shared features across task-evoked and resting-state functional connectivity, reliably reflect individual differences in handwriting speed. This predictive model involved multiple functional networks associated with motor, visual, and executive control processes. Furthermore, we found that the GFC-based model derived from handwriting task and resting-state data also predicted individual differences in reading ability, revealing both shared and distinct neural substrates underlying handwriting and reading skills. These findings highlight the potential of neuroimaging in the diagnosis of handwriting-and reading-related disorders
Revealing hierarchical organization via frequency oscillations: Comment on: "Dark brain energy: Toward an integrative model of spontaneous slow oscillations" by Gong & Zuo
No full textItch Sensitivity Questionnaire: A Validated Tool for Assessing Sensitization in Chronic Pruritus
No full textUnderstanding biological motion through the lens of animate motion processing
No full textBiological motion (BM), the movement generated by living entities, transmits signals of life and conveys vital cues for animacy perception. In this review, we synthesize empirical findings from human and non-human animal studies to reveal how BM enjoys a unique position in visual perception as an animate motion and how it elicits animacy perception. Compared to non-biological and inanimate motions, BM engages specialized perceptual processing mechanisms and a dedicated cortical-subcortical network. Local motion cues, especially the foot movements of terrestrial animals, are pivotal in driving such specificity, and emerging evidence supports the existence of an innate, evolutionarily conserved "Life Detector" or "Step Detector" tuned to such information in the human and other vertebrate brains. The direct perception of animacy from BM relies on the processing of low-level kinematic features and mid-level motion features embedded in both intrinsic joint movements and extrinsic body motion. While ecological constraints and implied internal energy sources may serve as generic factors affecting animacy perception from visual motion, how precise BM features (both in intrinsic and extrinsic movements) combine to influence animacy percepts and the neural implementation remain largely unexplored. Addressing these gaps will help establish a framework for understanding BM through the lens of animate motion processing. This approach will offer deeper insights into how the life detection system hardwired in the vertebrate brain distinguishes animate from inanimate motion, further uncovering its broader cognitive and evolutionary implications.</p
Active positive searching versus passive negative avoidance: A comparative investigation of large-scale offline attention bias modification training in nonclinical adolescents
No full textAttentional bias (AB), characterized by a disproportionate allocation of attention toward threat-related stimuli, constitutes a well-established cognitive mechanism underlying anxiety disorders. As a targeted intervention, attentional bias modification (ABM) has garnered substantial empirical support for its efficacy in attenuating AB and ameliorating anxiety symptomatology. This study evaluated and compared the effectiveness of three major ABM training paradigms in reducing attentional bias manifestations: dot-probe task-based ABM (DPT-ABM), emotional spatial cueing task-based ABM (ESCT-ABM), and visual search task-based ABM (VST-ABM). Using the attention to negative inventory (ANI) scale, we screened 202 non-clinical adolescents exhibiting elevated levels of negative attentional bias (NAB) and randomly assigned them to either an active modification group (DPT-ABM, ESCT-ABM, or VST-ABM) or a matched control group (DPT-C, ESCT-C, or VST-C). Participants underwent eight offline training sessions across a four-week period. Attentional bias scores (ABS), learning anxiety, and sense of agency (SoA) were assessed at pre-test and post-test intervals. Additionally, a three-month follow-up evaluation was conducted to examine long-term changes in ABS. The results showed that VST-ABM led to significant and sustained reductions in ABS compared to its control group, while other paradigms did not produce such effects. This study provides new evidence that active search training for positive emotional stimuli in VST-ABM is more effective than passive avoidance training of negative stimuli in reducing negative attentional bias and improving emotional well-being in non-clinical adolescents
Aberrant anterior insula underlies interoceptive deficits in alexithymia among schizophrenia patients
No full textObjective: This study aims to investigate the unique neural mechanisms underpinning abnormal interoception in schizophrenia patients with comorbid alexithymia. The focus is on identifying aberrant activation patterns and functional connectivities of the insula cortex with regions involved in emotional processing. Methods: Fifty schizophrenia patients were assessed using the Toronto Alexithymia Scale (TAS) and the Multidimensional Assessment of Interoceptive Awareness (MAIA). Task-based fMRI scans were conducted to observe brain activation patterns during interoceptive conditions. Results: Alexithymic patients showed higher alexithymia and lower interoception compared to non-alexithymic patients. During the interoceptive task, alexithymic patients exhibited reduced activation in the anterior insula (AI), while no difference was observed in the posterior insula (PI). Functional connectivity analysis revealed reduced connectivity between the AI and the anterior cingulate cortex (ACC) as well as the superior frontal gyrus (SFG) in alexithymic patients. Moreover, the connection between the AI and the ACC mediated the relationship between interoception and alexithymia. Conclusion: These results suggested that alexithymic schizophrenia patients struggle to integrate interoceptive afferents with emotional salience, and highlighted AI's role in the interplay between interoceptive awareness and emotional articulation in alexithymic schizophrenia, suggesting a potential neurobiological pathway for targeted interventions. Trial registration: The research is registered with the China Clinical Trials Registry (CCTR), under the registration number ChiCTR2400080313 on January 15, 2024.</p
Implementation of Primary Psychological Healthcare Policy to Address the Risk of Depression in Underprivileged Children and Adolescents, in the Entire Lower-Middle-Economic-Status City of China: An Observational, Multicenter, and Single-Arm Cohort Study
No full textBackground: Given the historically high incidence of depressive disorders among children/adolescents, efforts to implement universally accessible primary psychological health care policies have been undertaken globally. However, the practical implementation and its association with depression risk reduction remain uncertain, particularly for underprivileged children/adolescents who are underrepresented in the current system.Methods: A large-scale cohort of underprivileged children/adolescent population aged 6-18 was enrolled (n = 290,239). Subgroups with specific underprivileged conditions were identified, including de facto unattended children/adolescents (dfUCA), orphans, and children/adolescents facing especially difficult circumstances, "left-behind" and "single-parent" children/adolescents. A subgroup of matched typically developing individuals was also included. These subgroups underwent longitudinal assessments for the incidence of identifying depression on Oct 30, 2022 (baseline, before implementing primary psychological health care policy), May 21, 2023 (half year follow-up), and Oct 29, 2023 (1-year follow-up), respectively.Results: At baseline, nearly twice as high incidence of depression was found in the underprivileged group (13.9%, 95% confidence interval [CI]: 13.7-14.1) as in the control group (7.5%, 7.2-7.7). After the implementation of the primary psychological policy, at the half year follow-up, a notable decrease in the incidence of depression was observed in both the underprivileged group (5.8%, relative risk reduction (RRR) = 51.6%, 51.5-51.7, p < 0.001) and the typically developing group (4.0%, RRR = 34.5%, 27.9-41.0, p < 0.001), particularly among orphan girls aged 12-18. The observed changes in depression incidence across all underprivileged populations were statistically noninferior compared to the typically developing group (all p < 0.001). At the 1-year follow-up, the observed benefits were consistent across all subgroups when compared to baseline. The average expenditure per child/adolescent was $1.6 in implementing such a health care policy.Conclusions: Implementing the primary psychological health care policy is associated with a reduction in the citywide risk of depression among underprivileged children/adolescents in low-middle-income areas
Advances in food flavor analysis and sensory evaluation techniques and applications: Traditional vs emerging
No full textFood flavor represents a complex, multisensory experience shaped by the interplay of volatile and non-volatile components, texture, and consumer perception. This review examines both traditional and emerging technologies in food flavor analysis, focusing on their applications, strengths, and limitations. Although traditional methods, such as sensory evaluation and chemical analysis, provide valuable insights, they are constrained by subjectivity and the inability to fully capture the dynamic nature of flavor perception. In contrast, emerging interdisciplinary approaches-integrating neuroimaging techniques and machine learning-are offering a deeper understanding of how flavors are processed by the brain and how they influence consumer behavior. The future of flavor analysis is likely to depend on the integration of chemical, sensory, psychological, and neurological data, which will enable a more comprehensive, personalized, and dynamic approach. Such integration is expected to advance our understanding of flavor perception and drive innovations in food product development, thereby enhancing consumer satisfaction
Cross-Lagged Panel Networks of Distinct Complex Post-Traumatic Stress Disorder Symptom Trajectories Among Young Adults With Adverse Childhood Experiences
No full textBackground and Objectives: Young adults with a history of adverse childhood experiences (ACEs) may exhibit varying trajectories of complex post-traumatic stress disorder (CPTSD) symptoms over time. Unraveling the patterns of interactions between CPTSD symptoms across distinct trajectories is crucial. This study aimed to investigate the longitudinal relationships, changes, and central symptoms in CPTSD networks over time across distinct CPTSD trajectory groups.Methods: This longitudinal study followed 1277 university students (47.5% male) who reported ACEs from China through three waves of surveys. ACEs were assessed at baseline, while symptoms of CPTSD were measured at all three time points. Growth mixture modeling (GMM) was used to identify CPTSD symptom trajectories, and cross-lagged panel network (CLPN) analysis estimated the longitudinal relationships among CPTSD symptoms within these trajectories.Results: Two distinct and consistent CPTSD symptom trajectories were identified: a high-risk group and a resistance group. In the high-risk group, "disturbed relationships" (DRs) and "negative self-concept" (NSC) emerged as the strongest predictors of other symptoms at various time points. In the resilient group, the predictive influence of DR and NSC on other symptoms was attenuated. Instead, "affective dysregulation" (AD) emerged as the central symptom, demonstrating the strong predictive associations with other symptom domains.Conclusions: These findings reveal directional relationships among symptoms in young adults. Symptoms related to disturbances in self-organization (DSO), identified through centrality indices, are key drivers of symptom network development in different CPTSD trajectories. Targeting these symptoms in interventions for young adults with ACEs may help prevent or reduce CPTSD progression
The effectiveness of a sentence completion test for depression screening using large language models
No full textDepressive symptoms pose a significant mental health challenge globally, including in Thailand. The aim of this study was to assess the effectiveness of a sentence completion test for depression using large language models (LLMs). To improve objectivity and reduce bias in assessments, this study detects and classifies the trends in depression, modernizing the screening process with a newly developed depression sentence completion test. This research examines the four key areas: 1) family, 2) society, 3) health, and 4) self-concept among 373 participants, aged 20 to 40. Additionally, four models were applied to test: 1) LLAMA 3.1-8B, 2) Gemma2-9B, 3) Qwen2-7B, and 4) Typhoon1.5-7B. The result revealed that health, self-concept, and DIFF (Difference) were strongly related to sentiment levels with strong positive values of 0.48, 0.49, and 0.54, respectively, which might mean that they are significant indicators of depression risk. Family and society had positive but lower values of 0.27 and 0.19, respectively. Statistical validation confirms model reliability with a 0.78 lower bound accuracy (p <= .05). In the evaluation of all Thai-compatible LLMs, random forest models consistently performed better than decision tree classifiers in the classification of depression risk. LLaMA3.1 and Gemma2 produced the highest sensitivity. Ethical problems have to be considered when using LLMs in mental health. Embedding diverse populations and dynamic updating to sample data in future studies will assure greater accuracy and generalization across different demographic groups.</p
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