Institute of Psychology, Chinese Academy of Sciences
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ERP representational similarity analysis reveals the prediction of semantic features in minimal phrasal contexts
No full textExisting studies demonstrate that comprehenders can predict semantic information during language comprehension. Most evidence comes from a highly constraining context and it is less investigated that whether individuals predict following semantic information in a less constraining context. In the present study, we investigated semantic prediction when reading minimal adjective-noun phrases using electroencephalography (EEG) combined with representational similarity analysis (RSA). Native Chinese Mandarin comprehenders were presented with animate-constraining or inanimate-constraining adjectives, followed by animate-congruent or animate-incongruent nouns. EEG amplitude analysis revealed an N400 for incongruent conditions. Critically, we quantified the similarity between patterns of neural activity, and animate-constraining adjectives revealed greater similarity than inanimate-constraining adjectives before the presentation of the nouns. This pre-noun similarity effect suggests pre-activation of animacy-related semantic information of nouns, and provides evidence for the prediction of semantic features of upcoming words, even in minimal phrase contexts
Micro-Expression Key Frame Inference
No full textMicro-expressions (MEs) are brief, involuntary facial movements critical for detecting lies, drawing growing interest in psychology and computer science. However, annotating ME can burden human coders with excessive time commitment and overwhelming information that compromises coding reliability and efficiency. Such difficulties in data annotation also led to the small sample size problem and hindered the development of ME analysis. Specifically, our psychological research highlights the complexities involved in human annotation of key frames. To facilitate the annotating process of ME, we proposed the Micro-Expression Key Frame Inference (ME-KFI) problem, aiming to identify MEs' temporal locations from a single frame, reducing manual annotation effort. We propose a Micro-Expression Contrastive Identification Annotation (MECIA) method as a solution to ME-KFI, including three modules: a contrastive module, an identification module, and an annotation module, corresponding to the three steps of manual annotation. The network's outputs infer the key frame of ME clips. MECIA demonstrates superior performance over random baselines on SAMM and CAS(ME)2 databases and maintains comparable recognition accuracy with ground-truth clips.</p
Hierarchical and distinct biological motion processing in macaque visual cortical areas MT and MST
No full textIt is widely accepted that biological motion (BM) perception involves the posterior superior temporal sulcus (pSTS). Yet, how individual neurons and neural circuits in pSTS encode BM remains unclear. Here we combined electrophysiological recordings with neural network modeling to elucidate BM computations in two subregions of pSTS. We recorded single-cell activity from the middle temporal area (MT) and the medial superior temporal area (MST) of three macaque monkeys when they viewed point-light displays portraying BM walking in different directions (left vs. right), orientations (upright vs. inverted), and forms (intact vs. scrambled). We found that, while individual neurons in both MT and MST showed selectivity for these features, neural populations in MST but not MT exhibit BM-specific encoding, i.e., preferential representation of intact upright BM-the defining characteristic of BM recognition. A neural network model trained to replicate these neurophysiological findings implicated that, BM-specific encoding in MST may arise from feedforward connectivity patterns, i.e., MT subpopulations selective for linear translational motion and nonlinear optic flow projected preferentially to distinct MST cells. Taken together, our findings highlight hierarchical and distinct BM processing in MT and MST, advancing our understanding of BM computations in pSTS at the single-cell and neural circuit levels in the primate brain
The Relative Contributions of Conceptual and Perceptual Information to Visual Memory
No full textVisual memory contains conceptual and perceptual information, but existing evidence regarding their relative contributions is sparse and inconsistent. In the current study, we conducted a thorough experiment to see whether conceptual and perceptual information are encoded and retrieved the same to produce similar levels of false recognition and output interference (declining memory performance during testing). Participants studied images under different study times (20/500/2000 ms) and encoding tasks (conceptual/perceptual). Participants were tested with targets and foils with different levels of similarity to targets. We observed that foils with low conceptual similarity and high perceptual similarity (CLPH) and foils with high conceptual similarity and low perceptual similarity (CHPL) produced similar levels of false recognition and output interference when study time was 2000 ms and when the encoding task was perceptual-oriented. However, when study time was 20 ms or 500 ms and the encoding task focused on conceptual information, the CHPL foils produced a larger false alarm rate than the CLPH foils. The 20 ms and conceptual conditions also produced a larger decrease in false alarm rate (greater output interference) for the CHPL foils. The results indicate that, under a brief study time and a conceptual-oriented study procedure, conceptual information is encoded more strongly than perceptual information to play a more vital role in visual memory. We apply visual and verbal memory theories to account for our findings and show the potential to represent and describe memory processes across modalities using models of spreading activation and differentiation.</p
Adaptation of the virtual assessment of mentalizing ability and evaluation of its utility and psychometric properties in Chinese individuals on the schizophrenia spectrum
No full textSchizophrenia is associated with impairments in theory of mind (ToM), the ability to understand and attribute mental states. However, the nature of the deficits across ToM subconstructs (viz., first- and second-order cognitive ToM, and first- and second-order affective ToM) remains unclear, partly due to assessment issues. The current study aimed to first adapt an ecologically valid ToM assessment tool, namely, the Virtual Assessment of Mentalizing Ability (VAMA), for use among healthy Chinese individuals (Study 1). We then compared 39 schizophrenia patients with 37 controls, and 48 individuals with high social anhedonia (SA) with 54 individuals with low SA (Study 2) using the adapted version of VAMA and Yoni Task. Results of Study 1 showed that the adapted VAMA demonstrated acceptable reliability (item-total correlation and test-retest reliability for total score, r = 0.731, pFDR < 0.01) and construct validity (main effect of Order and Type). In Study 2, schizophrenia patients performed significantly worse than controls, making more "hypermentalizing" and "no mentalizing" ToM errors. Moreover, hypermentalizing error in the patient group was found to be significantly associated with their negative symptoms (r = 0.388, pFDR < 0.05). Interestingly, the VAMA results differed from those of the Yoni Task, possibly due to differences in task complexity. Finally, individuals with high SA showed impairments in second-order cognitive ToM compared to the controls. Overall, our findings suggest that the VAMA can be adapted for use in China, and is sensitive to ToM impairments in clinical and at-risk groups. Limitations on the psychometric properties were discussed
Quantitative threshold effects identiffcation of urban green exposure on multidimensional human health – A case study in Xiamen City, China
No full textUrban green spaces benefit health, and several cities have set specific greening targets or proposed guidelines to increase the presence of green spaces. However, the development of urban green spaces is restricted by the complex urban environment. The quantitative threshold effects of passive green exposure levels and human health are still not clear. Addressing this gap is crucial for effective urban planning, particularly in densely built environments with limited land resources, as it helps prevent uneven resource distribution and waste. This study explored a threshold effects identification framework related to human health based on quantifying passive green exposure, which characterizes the supply and service capacity of urban green spaces. A case study in Xiamen included a survey of 902 investigated individuals was conducted to collect self-reported health data. Their passive green exposure was quantified using open access geospatial data to quantify the individuals' actual green visibility, availability and proximity. A generalized additive model (GAM) was employed to detect non-linear relationships and identify threshold effects by its derivative. The results showed significant non-linear relationships exist between green visibility and availability and physical health in Xiamen City, with threshold effects. At the individual level, achieving the green visibility thresholds (0.1 and 0.15) and availability thresholds (0.26 and 0.35) were associated with significant social health benefits. Future research should integrate both active and passive green exposure metrics and employ threshold effects identification in different urban contexts, providing more accurate guidance for healthier urban green spaces planning.</p
Suicidal ideation data augmentation and recognition technology based on large language models
No full text自杀已成为全球性公共卫生难题,传统的自杀意念识别方法主要依赖患者主动求助,而基于文本分析的自动识别模型则受限于标注数据的稀缺性。本研究创新性地提出一种基于大语言模型的数据增强方法,旨在提升自杀意念文本识别的精度。研究采用双阶段设计：研究1聚焦于数据增强,研究2验证增强效果。在研究1中,选用ChatGLM3-6B和Qwen-7B-Chat作为底层模型,结合有监督学习策略与零样本和少样本学习方法,优化训练数据集质量。通过8组严谨的对比实验,结果显示两类自研模型在数据增强方面表现卓越,其处理后数据集的综合得分分别达到0.90和0.92,显著优于基线模型(p <0.001)。研究2进一步评估了数据增强对识别模型性能的影响,结果表明,增强后的模型在识别准确率和正确拒绝率指标上全面超越最佳基线模型(p <0.001)。本研究不仅验证了基于大语言模型的数据增强方法在提升自杀意念识别模型性能方面的有效性,还为心理健康领域的人工智能应用开辟了新方向。这种方法有望在保护用户隐私的同时,提供及时、有效的自杀风险早期预警,为自杀预防工作提供重要的技术支持和研究思路。未来研究可着眼于扩大数据异质性、优化提示工程设计、引入人机交互范式等,进一步拓展该方法在促进临床心理诊断领域的应用。</p
The Mechanism of Music Interpersonal Synchronous Activity Promoting Social Bonding
No full text音乐活动是引发自发社会影响的人类活动之一，伴随音乐的人际同步活动在生活中随处可见，能够对个体之间的社会联结产生显著影响。目前大多数研究聚焦在人际同步对亲社会行为的作用机制上，探讨范围较为单一狭窄。社会联结是包括了亲社会行为在内范围更大的涵盖性术语，音乐在人际同步影响社会联结的路径中起到的作用没有被系统梳理。音乐能够提供节奏框架和情感框架，在人际同步活动促进社会联结的过程中发挥独特作用；音乐活动的不同形式在其中的作用效果也不同。参考“生理-心理-社会”框架对音乐人际同步活动影响社会联结的机制进行梳理，旨在探明音乐人际同步活动是否以及如何影响社会联结，并为后续理论研究和干预研究的发展指明方向。</p
Dark Brain Energy Toward an Integrative Model of Spontaneous Slow Oscillations
No full textNeural oscillations facilitate the functioning of the human brain in spatial and temporal dimensions at various frequencies. These oscillations feature a universal frequency architecture that is governed by brain anatomy, ensuring frequency specificity remains invariant across diderent measurement techniques. Initial magnetic resonance imaging (MRI) methodology constrained functional MRI (fMRI) investigations to a singular frequency range, thereby neglecting the frequency characteristics inherent in blood oxygen level-dependent oscillations. With advancements in MRI technology, it has become feasible to decode intricate brain activities via multi-band frequency analysis (MBFA). During the past decade, the utilization of MBFA in fMRI studies has surged, unveiling frequency-dependent characteristics of spontaneous slow oscillations (SSOs) believed to base dark energy in the brain. There remains a dearth of conclusive insights and hypotheses pertaining to the properties and functionalities of SSOs in distinct bands. We surveyed the SSO MBFA studies during the past 15 years to delineate the attributes of SSOs and enlighten their correlated functions. We further proposed a model to elucidate the hierarchical organization of multi-band SSOs by integrating their function, aimed at bridging theoretical gaps and guiding future MBFA research endeavors.</p
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