Institute of Psychology, Chinese Academy of Sciences
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Effect of an AI agent trained on a large language model (LLM) as an intervention for depression and anxiety symptoms in young adults: A 28-day randomized controlled trial
No full textBackground: Young adults face emotional problems in their daily lives. Considering that youth are prevalent among mobile internet users, it would be helpful if functions that can intervene in young people's depression and anxiety can be designed based on short video apps. Large language model (LLM)-based AI conversational agents based on short video apps may play an important role in intervening in young adults' negative emotions. Methods: This study is a 28-day randomized controlled trial (RCT) in which 865 participants were randomly assigned to an intervention group or a waiting group, and each user was asked to engage in a total of 28 days of dialog intervention with the AI agent and complete three psychological questionnaires. Results: The dialog intervention significantly reduced depression in the intervention group at two weeks and significantly reduced both depression and anxiety in the intervention group at four weeks. Conclusions: This study found evidence that the LLM-based conversational agent could effectively alleviate the mild anxiety and depressive symptoms of young adults with negative emotions through dialog interventions when the AI companion bot is used sufficiently enough
Social skills interventions for children and adolescents with high-functioning autism spectrum disorder: a narrative review
No full textBackground and Objective: Deficits in social skills are the major symptoms of high-functioning autism spectrum disorder (HFASD). Recently, various intervention methods targeting social skills of children and adolescents with HFASD have been developed. This study reviews related articles published within the last decade to provide a better understanding of the status and limitations of research in this field. Methods: The Education Resources Information Center, Psychology and Behavioral Sciences Collection, PsycINFO, PubMed, and Web of Science databases were used to search for peer-reviewed studies published between January 1, 2014 and July 13, 2024. After reasonable deletion exclusion criteria, 39 studies on social skills interventions for children and adolescents with HFASD were summarized. Key Content and Findings: Twenty-one intervention methods were examined in 39 studies. Four categories emerged according to the basic theories and implementation procedures of these 21 methods: methods rooted in cognitive behavioral therapy (CBT), naturalistic intervention (NI), art therapy, and miscellaneous methods. Studies on methods based on CBT and NI have provided substantial evidence of the effectiveness of these two categories. Art therapy has also gained some empirical support, but not enough for an adequate conclusion. Miscellaneous methods lack sufficient empirical support, with most implemented without a control group. Moreover, only 10 among the 21 methods used randomized controlled trials, and the sample size of most studies was small. Conclusions: We recommend methods based on CBT and NI when practitioners and caregivers select intervention methods for children and adolescents with HFASD. Further research with a larger sample size and a more rigorous design is necessary to validate the effectiveness of art therapy and miscellaneous methods
Comparative Analysis of Comorbidity Networks of Anxiety and Depression in Elderly Individuals with and without a History of Falls
No full textTraditional psychopathological views symptoms as manifestations of latent disorders, while recent perspectives reconceptualize mental health as multidimensional continuums. The network analysis model elucidates dynamic symptom interactions via 'comorbidity networks', where co-occurring symptom clusters form nodes driving disorders. Although falls are associated with exacerbated anxiety and depression in older adults, prior research lacks network analysis examining associations between fall history and anxiety-depression comorbidity patterns. This study compared anxiety-depression comorbidity network structures between older adults with and without fall history to identify potential differences in symptom interactions. 371 elderly participants (169 with fall history, 202 without; mean age 81.00 ± 8.12, 60.4% male) were recruited from 10 Anhui elderly care institutions via convenience sampling. Data were collected via one-on-one interviews using GAD-7 (Cronbach's α=0.930) and PHQ9(α=0.849). Network analysis via EBICglasso in R assessed global structure, edge weights, node strength centrality, and robustness. Results showed fall history correlated with higher anxiety and depression scores (p< 0.05). Global network structure and connectivity did not differ, but specific edges and node centrality varied. In the fall group, 'uncontrollable worries' and 'inability to relax' (anxiety) were core nodes; in the non-fall group, 'excessive worries' (anxiety) and 'inferiority' (depression) were central. Significant edge differences included 'inferiority-suicidal symptoms' (p=0.023) and 'excessive worries-irritability' (p= 0.007). Network robustness was confirmed (CS-C > 0.5). Findings demonstrate distinct symptom interaction patterns associated with fall history despite preserved global architecture. Symptom-specific intervention targets 'uncontrollable worries' for the fall group and 'inferiority' for the non-fall group may optimize network-based approaches to elderly mental health management.</p
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
Effects of individualized rTMS on functional connectivity related to the default mode network and frontal-parietal network in major depressive disorder: exploratory analysis of a randomized controlled trial
No full textObjective: Repetitive transcranial magnetic stimulation (rTMS) has been shown to alleviate depressive and anxiety symptoms in patients with major depressive disorder (MDD), typically by targeting the dorsolateral (DLPFC) or dorsomedial prefrontal cortex (DMPFC). Based on a pre-registered randomized controlled trial, this study presents an exploratory neuroimaging analysis investigating the impact of rTMS targeting the DLPFC versus the DMPFC on functional connectivity with the default mode network (DMN) and frontal-parietal network (FPN) in patients with MDD. Methods: Sixty-four MDD patients were randomly assigned to DLPFC-rTMS (n = 36) or DMPFC-rTMS (n = 28) groups for a 21-day intervention. Symptoms were evaluated with Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA). Changes in individualized functional connectivity (inFC) between individualized targets and DMN/FPN were assessed and correlated with symptom improvements. As a control analysis, FC was evaluated based on the group-based seeds of DLPFC or DMPFC. Additionally, symptom-specific circuit map comparisons were conducted. Results: Both groups showed symptom improvements and changes in inFC with the DMN and FPN, but the specific connectivity profiles differ. In the DMN, the DLPFC-rTMS group showed decreased negative connectivity between left DLPFC and precuneus (t = -2.39, p = 0.022), while the DMPFC-rTMS group showed increased positive inFC between DMPFC and precuneus (t = -2.78, p = 0.01, FDR adjusted p = 0.034) and PCC (t = -3.15, p = 0.004, FDR adjusted p = 0.028). In the FPN, the DLPFC group showed decreased negative inFC with medial superior frontal gyrus (t = -2.35, p = 0.024) and decreased positive inFC with inferior parietal lobule (t = 2.3, p = 0.028). The DMPFC group showed increased positive connectivity with inferior frontal gyrus (t = -3.65, p = 0.001, FDR adjusted p = 0.019) and su pplementary motor area (t = -2.24, p = 0.033), and decreased negative connectivity with middle cingulate cortex (t = 2.27, p = 0.032). Canonical correlation analysis revealed a strong association between inFC changes and depression symptom improvement in the DMPFC-rTMS group (r = 0.57). Group seed-based FC changes were limited to the FPN and correlated with depressive improvement in the DLPFC-rTMS group (r = 0.52). Symptom-specific circuit maps linked to depression and anxiety were consistent across targets
Eye blinks synchronize with musical beats during music listening
No full textAuditory-motor synchronization, the alignment of body movements with rhythmic patterns in music, is a universal human behavior, yet its full scope remains incompletely understood. Through four experiments with 123 young nonmusicians, integrating eye-tracking, neurophysiological recordings, white matter structural imaging, and behavioral analysis, we reveal a previously unrecognized form of synchronization: spontaneous eye blinks synchronize with musical beats. Blinks robustly synchronized with beats across a range of tempi and independently of melodic cues. Electroencephalogram recordings revealed a dynamic correspondence between blink timing and neural beat tracking. Blink synchronization performance was linked to white matter microstructure variation in the left superior longitudinal fasciculus, a key sensorimotor pathway. Additionally, the strength of blink synchronization reflected the modulation of dynamic auditory attention. These findings establish blink synchronization as a novel behavioral paradigm, expanding the auditory-motor synchronization repertoire and highlighting the intricate interplay between music rhythms and oculomotor activity. This discovery underscores a cross-modal active sensing mechanism, offering new insights into embodied music perception, rhythm processing, and their potential clinical applications
Eye blinks synchronize with musical beats during music listening
No full textAuditory-motor synchronization, the alignment of body movements with rhythmic patterns in music, is a universal human behavior, yet its full scope remains incompletely understood. Through four experiments with 123 young nonmusicians, integrating eye-tracking, neurophysiological recordings, white matter structural imaging, and behavioral analysis, we reveal a previously unrecognized form of synchronization: spontaneous eye blinks synchronize with musical beats. Blinks robustly synchronized with beats across a range of tempi and independently of melodic cues. Electroencephalogram recordings revealed a dynamic correspondence between blink timing and neural beat tracking. Blink synchronization performance was linked to white matter microstructure variation in the left superior longitudinal fasciculus, a key sensorimotor pathway. Additionally, the strength of blink synchronization reflected the modulation of dynamic auditory attention. These findings establish blink synchronization as a novel behavioral paradigm, expanding the auditory-motor synchronization repertoire and highlighting the intricate interplay between music rhythms and oculomotor activity. This discovery underscores a cross-modal active sensing mechanism, offering new insights into embodied music perception, rhythm processing, and their potential clinical applications
Visual awareness sharpens and accelerates attentional sampling through enhancing inhibitory neural modulation in the attention network
No full textAttentional sampling, orchestrated by neural oscillations within the frontoparietal attention network, sequentially focuses on stimuli in a dynamic pattern, thereby enhancing the efficiency of attentional selection. However, the role of conscious awareness in this default attentional process remains largely unexplored. Here, we employed the Chromatic Flicker Fusion (CFF) method to render attentional cues invisible and investigated how cue awareness modulates attentional sampling. Using a high-temporal-resolution behavioral paradigm and electroencephalography (EEG) combined with the temporal response function (TRF) approach, we found that both visible and invisible cues induced rhythmic behavioral sampling and reset connectivity between the frontal and right occipito-parietal regions, indicating that attention samples rhythmically regardless of cue awareness. Crucially, visible cues not only elicited stronger behavioral inhibition and enhanced neural alpha activity, but also triggered faster attentional sampling (similar to 8 Hz vs. similar to 4 Hz) and higher-frequency frontoparietal coupling (alpha vs. theta band). These findings demonstrate that the conscious representation of attentional cues influences inhibitory neural responses within the frontoparietal attention network and modulates the attentional sampling process
Genome-Wide by Lifetime Environment Interaction Studies of Brain Imaging Phenotypes
No full textBrain structure and function show substantial individual differences, finely controlled by genes, environments, and their interactions. Despite the increasing knowledge about genetic and environmental main effects, gene-environment interaction effects on brain phenotypes remain elusive. This study investigates genome-wide by environment (41 exposures) interactions on 598 brain imaging phenotypes in 7084 healthy young adults. Both univariate and multivariate analyses identify 486 significant gene-environment interactions, scattered across the genome, exposome, and phenome. These interactions explain more variances of phenotypes than genetic and environmental main effects (100% of genetic and 96% of environmental main effects are non-significant). Variants with interactions are enriched in intronic and intergenic regions, comprising 79 regulatory variants and 145 associated with brain gene expression. Protein-protein interaction network analyses reveal distinct interaction networks for genes associated with air pollution (hubs: H4C6, SMARCA4, and RPS11) and urbanicity (hubs: CCND1, CALM3, and CDK2) exposures. Genes that interacted with air pollution exposures exhibit enrichment in pathways related to metal ion detoxification and homeostasis. For time-varying exposures, 144 interactions demonstrate sensitive periods, predominantly in childhood (ages 4-7) and adolescence (ages 12-15). These findings highlight the value of genome-wide by exposome-wide interaction studies, which may offer crucial information for optimizing brain health outcomes
Who is AI? The Impact of Identity Labels in Multi-Round Trust Games
No full text人工智能技术的普及使理解身份标签如何影响人类信任决策至关重要。采用多轮信任博弈范式，真人被试两两配对，分别作为投资人和代理人进行互动，通过指导语操纵双方对自己身份（“真人”或“AI”）认知，考察其对信任博弈的影响。结果显示，与保持真人身份相比，投资人扮演AI时投资比例降低，社会规范敏感性下降；尤其在面对被认知为真人的对家时，扮演AI的投资人决策更加随机且弱化学习依赖。代理人扮演AI时返还比例提高，内疚参数上升，更依赖即时信息而非历史经验，在面对AI投资人时内疚上升更明显。这表明AI身份标签通过印象管理机制（改变社会监督预期）和刻板印象激活（内化AI行为特征）双重路径影响信任决策，为理解人类信任决策提供了新视角。</p
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