Institute of Psychology, Chinese Academy of Sciences
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Individuals with High Social Anhedonia but not Schizophrenia Exhibited Altered Empathy in Daily Life
Background and Hypothesis Despite empathic abnormalities exhibited in both clinical and subclinical samples of schizophrenia (SCZ) in the laboratory, understanding of their empathy in the real world remains limited. This study applied the experience sampling method (ESM) to investigate empathy in people with SCZ and high social anhedonia (SocAnh), as well as its associations with social pleasure and emotional states in daily life.Study Design Thirty-one participants with SCZ, 31 individuals with high SocAnh, and 32 healthy controls completed a 7-day ESM survey (10 surveys per day) to assess empathy, social pleasure, and emotional states in daily life. The empathic accuracy task was used to measure empathy accuracy (EA) in the laboratory. Multilevel regression models were estimated to examine group differences of the ESM variables and their associations.Study Results Compared to controls, people with SCZ showed lower EA but comparable cognitive and affective empathy in daily life, whereas Individuals with high SocAnh exhibited similar EA but lower affective empathy in daily life. Positive association between social pleasure and empathy was found across 3 groups. Empathy for positive emotions predicted increased positive emotional states in individuals with high SocAnh and controls, but not in people with SCZ. Positive emotional states predicted greater empathy in individuals with high SocAnh, which was not observed in the other 2 groups.Conclusions Our findings revealed altered empathy in daily life among people at-risk for SCZ but not in clinical patients, shedding light on a better understanding of social cognitive changes in SCZ spectrum
Identifying Opponent's Neuroticism Based on Behavior in Wargame
Traditional neuroticism assessments primarily rely on self-report questionnaires, which can be difficult to implement in highly confrontational scenarios and are susceptible to subjective biases. To overcome these limitations, this study develops a machine learning-based approach using behavioral data to predict an opponent's neuroticism in competitive environments. We analyzed behavioral records from 167 participants on the MiaoSuan Wargame platform. After data cleaning and feature selection, key behavioral features associated with neuroticism were identified, and predictive models were developed. Neuroticism was assessed using the 8-item neuroticism subscale of the Big Five Inventory. Results indicate that this method can effectively infer an individual's neuroticism level. The best-performing model was LinearSVR, which balances interpretability, robustness to noise, and the ability to capture moderate nonlinear relationships-making it suitable for behavior-based psychological inference tasks. The correlation between predicted scores and self-reported questionnaire scores was 0.606, the R-squared value was 0.354, and the test-retest reliability was 0.516. These behavioral features provide valuable insights into neuroticism prediction and have practical applications in psychological assessment, particularly in competitive environments where conventional methods are impractical. This study demonstrates the feasibility of behavior-based neuroticism assessment and suggests future research directions, including refining feature selection techniques and expanding the application scenarios.</p
Happy mouth and fearful eyes: insights into emotional facial features from ERP
Facial expressions enable individuals to assess and understand emotions conveyed by others. Two crucial sources of expressive cues on the human face-the eyes and the mouth-capture attention and serve as reliable shortcuts for expression recognition. However, how the brain effectively extracts emotional information from these diagnostic features remains unknown. We investigated this issue using an electroencephalogram combined with a rapid serial visual presentation task in which participants were asked to recognize facial expressions (fear, happiness, and neutrality) from three formats (whole face, eye region, and mouth region). We found that participants recognized happy expressions from the mouth region more accurately than the other expressions, affirming the role of diagnostic features in facilitating bottom-up attentional capture. The isolated eye region with higher visual saliency induced the largest P1 component. Diagnostic features, such as a happy mouth and fearful eyes, elicited a larger N170 component compared to non-diagnostic features, such as a fearful mouth and happy eyes. Source analysis of N170 showed that the fusiform gyrus exhibited similar patterns in response to these emotional features. The P3 was effective in discriminating between different emotional content. When whole faces were visible, fearful and happy expressions were not distinguishable in the N170, while the P3 amplitude was larger when induced by fearful faces than by happy faces. Our study contributes to understanding how facial features play distinct roles in emotional perception, attention, and facial processing
Suicide attempts in elderly Han Chinese patients with major depressive disorder: prevalence and associated factors
Objective: Suicide attempts (SA) are common in elderly patients with major depressive disorder (MDD), but few studies have focused on the prevalence and associated factors in elderly Chinese Han patients with MDD. Method: A total of 266 first episode and drug na & iuml;ve older patients with MDD (age >= 50 years) were recruited. We measured depressive symptoms, anxiety symptoms and psychotic symptoms by the Hamilton Depression Rating Scale (HAMD), the Hamilton Anxiety Rating Scale (HAMA), the positive subscale of the Positive and Negative Syndrome Scale (PANSS) and the Clinical General Impression Inventory (CGI-S). Fasting serum samples were collected to measure thyroid hormone levels and metabolic parameters. Results: The prevalence of SA was 24.4 %. Patients with SA had higher HAMD, HAMA, PANSS positive subscale and CGI-S scores, as well as higher levels of TSH, TgAb, TPOAb, FBG, TC, LDL-C, TG, and systolic and diastolic blood pressure. Logistic regression analysis showed that suicide attempts were correlated with HAMA score, CGI-S score and TC levels in elderly patients with MDD. Conclusions: The findings show a high prevalence of suicide attempts in elderly patients with MDD. In elderly patients with MDD, severity of anxiety, CGI-S score and TC levels were associated factors for suicide attempts.</p
The Assessment of Body Image Based on Large Language Model
Assessing adolescent body image is crucial for mental health interventions, yet traditional methods suffer from limited dimensional coverage, poor dynamic tracking, and weak ecological validity. To address these gaps, this study proposes a multidimensional evaluation using large language models (LLMs) and compares its criterion validity against a dictionary-based method and expert ratings. We defined four dimensions-perception, positive attitude, negative attitude, behavior-by reviewing the body-image literature and built a validated dictionary through expert ratings and iterative refinement. A four-step prompt-engineering process, incorporating role-playing and other optimization techniques, produced tailored prompts for LLM-based recognition. To validate these tools, we collected self-reported texts and scale scores from 194 university students, performed semantic analyses with Llama-3.1-70B, Qwen-Max, and DeepSeek-R1 using these prompts, and confirmed ecological validity on social media posts. Results indicate that our multidimensional dictionary correlated significantly with expert ratings across all four dimensions (r = 0.515-0.625), providing a solid benchmark. LLM-based assessments then outperformed both the dictionary and human ratings, with zero-shot LLMs achieving r = 0.664 in positive attitude (vs. expert r = 0.657) and DeepSeek-R1 reaching r = 0.722 in perception. Role-playing techniques significantly improved the validity in the perception dimension (Delta r = +0.117). Consistency checks revealed that the DeepSeek model reduced error dispersion in extreme score ranges by 48.4% compared to human ratings, with the 95% consistency limits covering the fluctuations of human scores. Incremental validity analysis showed that LLMs could replace human evaluations in the perception dimension (Delta R 2 = 0.220). In ecological validity checks, the Qwen model achieved a correlation of 0.651 in the social media behavior dimension-53.1% higher than the dictionary method. We found that LLMs demonstrated significant advantages in the multidimensional assessment of body image, offering a new intelligent approach to mental health measurement.</p
Cross-Category Attentional Biases Driven by Visual Mental Imagery of Social Cues
In cluttered and complex natural scenes, selective attention enables the visual system to prioritize relevant information. This process is guided not only by perceptual cues but also by imagined ones. The current research extends the imagery-induced attentional bias to the unconscious level and reveals its cross-category applicability between different social cues (e.g., eye gaze and biological motion). Using a visual imagery task combined with an attentional bias paradigm, we showed that imagining a gaze cue biased selective attention toward the imagery-matching eye gaze. Removing the imagery task obliterated the attentional effect, emphasizing the pivotal role of mental imagery in driving the observed results. Furthermore, the attentional bias persisted even when the physically presented eye gazes were rendered invisible, suggesting the automaticity of the effect and a dissociation between attention and consciousness. When the imagery content involved biological motion cues, cross-categorical attentional bias toward imagery-matching eye gaze was evident. However, this cross-categorical effect did not extend to nonsocial arrow cues-imagining an arrow cue failed to bias attention toward imagery-matching eye gaze, though arrow cues induced within-categorical attentional biases for imagery-matching arrows. These findings point to the existence of shared mechanisms dedicated to processing different social cues rather than nonsocial cues. Taken together, the present study highlights a novel mechanism through which social cue-based imagery guides spatial attention, which operates independently of visual awareness and is supported by a dedicated social module, shedding light on the intricate interplay between the internal mental representations and the external physical world
Object recognition based on particle motion characteristics
近年来,目标识别是认知神经科学和计算机视觉领域的研究热点。目前大多数研究主要聚焦于外观特征和视觉系统腹侧通路的作用,并基于此建立目标识别模型。然而,外观特征容易受到视角变化、遮挡、观看距离等因素的影响,发生显著变形,导致识别正确率降低。与之相比,运动特征在这些条件下仍表现出更高的稳定性和区分度,能够为目标识别提供更有效的线索。每个物体的运动特征受其结构特性、内部动力系统(如肌肉系统)和外部环境(尤其是重力)的限制,表现出独特的模式。尽管运动特征具有诸多优势,但它在目标识别中的作用未得到充分研究。为了只提取出运动信息,本研究将运动物体抽象为单一质点,去除所有外观信息,仅保留它在全局空间中的运动轨迹。
在目标识别中,首要任务是判断运动物体是否具有生命,这一判断对后续的分类和行为决策具有重要意义。在自然界中,物体大致可分为有生命体和无生命体两类。经过数百万年的进化,有生命体发展出独特的运动模式,这些模式难以无生命体(包括机械物体)所模仿。与此同时,人类及其他动物也演化出通过 运动线索快速判断生命性的能力,这种能力叫做生命度知觉。然而,对于有生命运动的关键特征及生命度感知的认知机制,目前仍不清楚。
在本研究中,我们选择鸟类和无人机分别作为有生命体和无生命体的代表。首先,在受控环境下(自制拍摄箱和空旷停车场),我们拍摄了 3 种不同体型的家养鸟类(黄玉鸟、珍珠鸟和鸽子)和 3 种对应体型的无人机(Tello、Mavic Pro和 Phantom4)的飞行视频,构建了一个小型鸟类和无人机飞行轨迹数据集。通过系统地比较鸟类和无人机的运动特征差异,我们发现与无人机相比,鸟类表现出大的加速度、角速度和轨迹波动,运动灵活性更高。利用该数据集中的运动轨 迹作为行为学实验中的视觉刺激,我们发现人类观察者可以快速地判断出运动目标的类别,在判断时主要依赖轨迹波动和加速度特征。此外,在判断过程中,人 类观察者采用了一种特征匹配策略,当他们观察到物体的运动特征和有生命体的典型运动模式相匹配时,便判断运动物体是有生命的;反之,则将它判断为无 命的。最后,基于人类判断时采用的认知策略,我们构建了一个基于质点运动特征的生命度分类器,它可以快速且准确地分类测试集中的飞行轨迹,分类效果甚至优于人类观察者。
尽管实验室数据集提供了有价值的初步发现,但也存在一些局限性,例如目标类别有限、鸟类和无人机拍摄距离差异较大、鸟类在受限环境中的飞行模式与真实环境存在差异、轨迹数量有限等。为了提高数据集的规模和生态效度,我们进一步构建了一个大规模自然环境飞行轨迹数据集,涵盖鸟类(主要为乌鸦和海鸥)在自然栖息地的飞行视频,和无人机(Mavic Pro 和 Phantom4)在复杂环境下(山地、城市和海洋)的飞行视频。这个数据集是目前为止规模最大的可见光下鸟类和无人机小目标飞行轨迹数据集。基于这个数据集,我们同评估了多种轨迹分类模型,包括现有的轨迹分类模型、卷积神经网络和时间序列模型。实验结果表明,卷积神经网络模型的表现最好,表明局部运动模式对于区分两类物体具关键作用。此外,我们探究了鸟类和无人机在适应重力环境方面的差异。我们 重点比较了二者的加速度特征,验证了鸟类的加速度确实显著大于无人机,这种差异在垂直方向上尤为显著,尤其是在升力小于重力的情况下。这表明,与无人机被动克服重力的方式不同,鸟类能够更加灵活地利用重力来调整自身速度,从而实现更节能高效的运动。
综上所述,本研究系统地探讨了有生命体运动的关键特征、生命度感知的认知机制,并构建了基于运动特征的分类模型,充分论证了运动信息在目标识别中的重要作用和有效性。该研究拓展了我们对运动信息在目标识别中作用的理解,为后续深入探究运动特征以及视觉系统背侧通路在目标识别中的作用和功能奠定了基础,并为基于运动和多模态的信息识别模型提供了理论支持。此外,鸟类与无人机在运动特性上的差异,也为下一代仿生无人机的设计提供了重要的参考与启发。</p
Interplay Between Childhood Trauma, Psychopathologies and Brain Functional Networks: Evidence from Three Different Clinical and Subclinical Samples with Mental Disorders
童年创伤指个体在儿童和青少年时期所经历的各种虐待和忽视,包括情感虐待、身体虐待、性虐待、情感忽视和身体忽视五种类型。精神分裂症、双相障碍和重性抑郁症的童年创伤发生率显著高于一般人群。研究表明童年创伤与心理病理症状存在显著关联,并且与默认模式网络、突显网络和边缘系统的脑功能连接异常密切相关。然而现有研究大多集中于童年创伤的累积风险评分,缺乏对不同类型童年创伤与患者心理病理症状、脑功能网络异常之间关联模式的系统探究。同时,以往研究一般只聚焦于单一诊断群体,缺乏跨诊断群体及其对应的亚临床群体(如分裂型特质、双相特质或阈下抑郁群体)的比较研究。为弥补上述研究不足,本论文采用网络分析方法和静息态功能磁共振成像技术,系统探讨了不同类型童年创伤与精神分裂症、双相障碍、重性抑郁症患者及其亚临床特质群体的心理病理症状、静息态脑功能网络的关联模式。
研究一采用网络分析探讨在跨诊断临床患者中不同类型童年创伤和心理病理症状之间的关系。招募 418 名精神分裂症患者、215 名双相情感障碍患者和 236 名重性抑郁症患者完成临床症状访谈和童年创伤自评问卷,估计偏相关网络并进行不同诊断组的网络比较。结果显示,情感虐待在网络中表现为核心节点;不同类型童年创伤与心理病理症状的关系存在差异:情感虐待、情感忽视与抑郁症状相关,身体虐待与躁狂症状相关,性虐待与阳性症状和紊乱症状相关,情感忽视、身体忽视与阴性症状的动机/愉悦感缺损维度相关。网络比较结果显示三个诊断组的网络结构相似,支持了童年创伤与心理病理症状关系的跨诊断一致性。
研究二采用网络分析探讨在一般大学生群体中不同类型童年创伤与心理病理症状的关系。招募 1813 名大学生完成童年创伤、分裂型特质、双相特质和阈下抑郁症状的自评问卷并估计偏相关网络。结果发现情感虐待被识别为核心节点;不同类型童年创伤与心理病理症状的关系存在特异性:情感虐待与阳性分裂型特质、白日梦倾向、情绪不稳定和阈下抑郁症状相关,性虐待与阳性分裂型特质相关,情感忽视和身体忽视与阴性分裂型特质及动机水平相关,而身体忽视与紊乱分裂型特质相关。此外,这些结果在包含 427 名大学生的独立样本中得到了重复验证。
研究三考察不同类型童年创伤与精神分裂症、双相障碍和重性抑郁症患者静息态功能连接个体间变异性异常改变之间的关系。招募 78 名精神分裂症患者、 44名双相障碍患者、43 名重性抑郁症患者和 85 名健康对照,完成临床症状访谈、自评问卷和静息态脑成像扫描。结果发现:与健康对照组相比,精神分裂症和双相障碍患者表现出默认模式网络的静息态功能连接个体间变异性增加,而三组患者均表现出突显网络和边缘系统的静息态功能连接个体间变异性增加。此外,精神分裂症患者左内侧前额叶皮层的功能连接个体间变异与情感忽视呈负相关,而重性抑郁症患者右侧颞极的功能连接个体间变异与身体忽视呈负相关。
研究四考察不同类型童年创伤与高分裂型特质、高双相特质及阈下抑郁群体静息态功能连接个体间变异性异常改变之间的关系。招募 42 名高分裂型特质、45 名高双相特质、39 名阈下抑郁以及 80 名对照组被试,完成自评问卷和静息态脑成像扫描。结果发现:相比对照组,仅高分裂型特质组在默认模式网络中右侧楔前叶/后扣带回的静息态功能连接个体间变异性呈现增加趋势。此外,在高分裂型特质组中,该脑区的静息态功能连接个体间变异性与情感忽视呈正相关。而这种相关性在高双相特质组和阈下抑郁组中没有发现。
综上所述,本研究表明,不同类型的童年创伤可能在心理病理学和神经层面对精神分裂症、双相障碍、重性抑郁症患者及其亚临床特质群体产生不同的影响。这些发现有助于深化对童年创伤如何影响临床和亚临床人群的理解。</p
Subtyping Major Depressive Disorder Based on Brain Imaging Meta-Analysis and Big Data-Driven Approaches
重性抑郁障碍(Major Depressive Disorder, MDD)一般称抑郁症,是一种高发、致残性强且容易复发的精神障碍,对个人和社会都造成了严重的负担。近 20 年来,抑郁症一直是全球各年龄段失能的主要原因之一,约占精神障碍导致的总失能数的 37%。尽管神经影像技术取得了显著进展,但目前抑郁症的诊断仍依赖于临床访谈或量表评定,治疗方案的选择多依赖医生的临床经验,缺乏有效的生物标志物。功能磁共振成像(Functional Magnetic Resonance Imaging, fMRI),特别是静息态功能磁共振(Resting-State Functional Magnetic Resonance Imaging, RfMRI),因其非侵入性、无创性、安全性及较高的时空分辨率,能够揭示大脑的 动态功能变化,并为寻找抑郁症的生物标志物和有效治疗靶点提供了巨大潜力。
然而,尽管关于抑郁症的脑影像研究已经积累了大量成果,但对于抑郁症的内在神经功能机制仍缺乏共识,抑郁症的脑影像研究结果仍存在较大的异质性,缺乏稳定且可重复的生物标志物。此外,精神疾病的诊疗框架与脑影像研究框架之间存在不匹配,它们各自关注的焦点和采用的术语不同,基于症状学的抑郁症诊断评估标准与认知神经科学研究中的神经影像特征和神经行为功能缺乏系统的映射规则,导致两者难以直接结合。这种异质性和学科壁垒共同导致了抑郁症影像研究结果在临床诊疗中的应用受到限制。因此,甄别抑郁症脑影像结果不一致的成因,探明抑郁症疾病异质性是否及如何带来脑影像结果的不一致,是当前 研究的核心科学问题。
在此背景下,本研究旨在克服现有磁共振成像方法学问题,探索稳定的抑郁症的“症状-脑功能”亚型,并为基于多层级信息构建可应用于临床的抑郁症分型标志提供理论和数据支持。具体而言,研究一关注方法学问题或差异可能带来的抑郁症脑功能影像研究结论异质性,通过对近 30 年抑郁症功能磁共振成像研究进行了系统性综述,严格排除了样本量不足、头动未有效校正以及统计方法和多重比较校正策略选择不当等功能磁共振研究中的关键方法学问题可能带来的假阳性结果这一异质性来源后,依旧发现纳入研究无法就抑郁症的脑功能影像异常模式形成一致结论。该结果提示抑郁症患者群体及疾病本身的异质性可能是其脑影像研究结论异质性的重要来源,对抑郁症患者症状及功能的异质性研究不可忽视,此外,精神疾病的脑影像研究应采用更大样本量、规范的预处理流程、严格的统计和多重比较校正策略以及开放科学的研究模式,以增强研究结果的可重复性和可比较性。研究二聚焦于探索抑郁症的症状功能异质性时所面临的临床诊断标准与神经科学研究框架间的学科差异,将精神病学症状维度与认知神经科学的多层级功能指标纳入统一分析体系,利用脑影像元分析方法结合自然语言处理技术构建抑郁症症状与功能之间的关联模型,并通过同时与特定功能及症状关联的磁共振实验研究进一步验证该元分析模型与真实数据的关联性及其可解释性。同 时,研究二通过脑影像元分析生成的抑郁症症状和功能特异性先验种子图谱可用于引导后续抑郁症亚型的聚类分析研究。基于前述研究,研究三旨在探索适用于抑郁症脑影像大数据的聚类模型,通过系统比较不同脑影像指标和聚类算法构成的 140+聚类模型的表现,发现多视图核谱聚类算法(multi-view kernel spectral clustering, MVKSC)结合研究二生成的先验种子图谱引导的多维症状功能融合图谱构建聚类模型,有效提升了类内类间区分度,并在区分抑郁症患者与健康个体时具有更优越的性能。最后,研究四对最优聚类模型进行跨站点十折随机交叉验证并建立“症状-脑功能”亚型,探讨该各亚型的临床症状及脑功能特征,发现了 具有特异性症状和脑功能特征的抑郁症亚型,有效区分出健康/疑病型、生理调节异常型、焦虑失眠型、高自知典型抑郁型和低自知典型抑郁型这五种抑郁症亚型,并发现了各亚型特异性的症状特征和症状关联脑功能异常模式,表明该亚型分类具有较强生态效度和临床应用潜力。
本研究结合静息态功能磁共振成像数据与多维度临床数据,采用自然语言处理、基于特征词的元分析(或称作关联分析)、功能磁共振成像分析、聚类分析等方法,系统研究抑郁症的症状异质性及其亚型。同时,研究中采用了严格的数据预处理和统计分析策略,以提高结果的可靠性和可重复性。此研究有助于澄清抑郁症功能磁共振研究结果的异质性来源,并为抑郁症的亚型分类提供新的方法和神经影像学证据。通过探索抑郁症的临床症状与脑功能的关系,我们期望为未来精神障碍的精准诊断和个性化治疗提供理论依据。</p
The Construction of a Systematic Empathy Framework and its Psychological and Neural Mechanisms
共情指的是对他人情绪和感受的识别、理解和响应。根据他人情绪或感受效价的不同,共情可以分为积极共情和消极共情。尽管共情已在多个领域得到广泛研究,但不同领域的专家对于共情概念的定义和内涵一直存在争议,当前争议的焦点主要集中在共情子成分范围的划分。为了解决该问题,本论文基于共情的心理过程,整合心理学、医学以及神经科学三个领域对共情子成分的广泛定义,遵 循“可测量”和“可分离”的原则,提出将共情划分为五个子成分:情绪识别、情感共情、动机共情、行为共情和换位思考,并通过四个研究探寻其心理和神经机制。研究一从行为层面考察共情子成分之间的关系;研究二采用磁共振成像技术,探讨共情子成分及整体感知和调节过程;研究三结合行为和磁共振成像技术,考察不同因素对共情子成分的影响及其脑机制;研究四结合共情的影响因素,重点考察不同训练方案对共情及其子成分的提升效果和原理。
研究一通过三个行为实验考察五个共情子成分之间的关系。实验一招募 35 名被试,收集每个被试对 96 个他人经历(积极、消极和中性各 32 个)的情绪识别、情感共情和动机共情数据。通过多层次中介分析,我们发现情感共情完全中介情绪识别和动机共情之间的关系,该结果在积极和消极共情中均成立。通过相关分析和个体间相关分析,发现该三个成分在个体内和个体间均存在显著的相似性,但积极条件的相似性显著低于消极条件。实验二招募 30 名被试,收集被试在不同换位思考方式下和不使用换位思考时对情绪识别、情感共情和动机共情的影响。结构方程模型显示,换位思考在积极共情条件下对情绪识别、情感共情和 动机共情均存在直接正向作用,在消极共情条件下对情绪识别和情感共情存在直接的正向影响,但对动机共情没有直接影响。实验三招募 24 对同性别被试,收集被试 A 在不同换位思考方式下和不使用换位思考时,想帮助被试 B 减轻疼痛的程度(动机共情)以及实际选择(行为共情)的数据。结构方程模型显示,换位思考对动机共情和行为共情均存在直接的正向作用。
研究二采用磁共振成像技术,分别探讨积极和消极条件下情绪识别、情感共情和动机共情等过程中的脑激活和编码异同(实验四)以及感知过程和调节过程的脑网络机制(实验五)。实验四采用一般线性模型(General Linear Model, GLM) 分析,发现积极和消极共情在推断他人状态的心理理论脑区和高级认知控制区存在共享的激活。通过参数调节(Parametric Modulation)分析,发现三个分数对应的主要编码脑区并不相同,积极和消极共情在情绪识别阶段存在共享的编码方式,但在情感和动机共情上不存在。通过功能连接和个体间相关分析,发现积极和消极共情在个体内和个体间均存在显著的神经活动相似性,但积极条件的相似性显著低于消极条件。实验五采用动态因果模型(Dynamic Causal Modeling, DCM)分析,探讨共情自下而上的感知过程和自上而下的调节过程中的动态神经网络变化。 首先,通过 GLM 和前人研究确认双侧额下回三角区在面孔识别过程中的重要作用,并设定该区域为感知过程的起始点;选择双侧颞上沟为感知后期脑区;背外侧额上回、内侧前额叶以及楔前叶则被纳入调节过程。DCM 分析结果显示,右侧额下回三角区在感知过程中可能更侧重外部信息的处理,而左侧额下回三角区则更侧重与内部脑区间的交流;背外侧额上回在积极共情条件下对内侧前额叶的神经活动产生抑制作用,但在消极共情条件下没有观察到这一现象;内侧前额叶在积极和消极条件下均对楔前叶起抑制作用。
研究三包括两个实验,从两个不同的角度探讨影响因素对共情子成分的影响及其脑机制。实验六利用 484 名有效被试数据,包括人口学基本信息、人际反应指针(IRI)共情量表以及磁共振成像结构和静息态数据。研究发现,性别对共情的影响集中于情感共情(女性>男性),但在动机共情和换位思考上没有显著影响;磁共振数据分析揭示,左侧脑岛是解释性别差异的关键脑区。实验七招募 41 名交谊舞舞者和 40 名对照被试,收集人口学基本信息、IRI 共情量表以及磁共振成像结构和静息态数据。研究发现,交谊舞舞者的动机共情显著高于对照组,但在情感共情和换位思考上与对照组无差异;磁共振数据分析结果显示,前扣带回是 解释差异的关键脑区,明确了长期社会交互因素对共情的影响。
研究四(实验八)针对不同类型的影响因素、共情的子成分以及训练后不同时间段的共情提升效果展开探讨。该研究采用元分析的方法,汇总 110 个共情训练研究的数据(情感共情 29 个样本、1583 名被试;动机共情 36 个样本、2310 名被试;行为共情 39 个样本、1971 名被试;换位思考 40 个样本、2670 名被试;情绪识别由于只有 2 个样本未纳入分析)。元分析结果表明,共情训练在整体上存在中-大的正效应量,且效果可维持到训练后六个月;调节变量分析显示,不同的子成分的训练效果差异明显,情感共情效应量小,动机共情的效应量为小中,而换位思考效应量中等,行为共情的效应量为中-大。从训练效果维持的角度来看,情感共情的效果无法维持,而换位思考和动机共情可维持至三个月,行为共情维持效果由于置信空间较大,无法做出确定的结论。从影响因素的角度分析,旨在增强社会关系的训练方法(积极的社会互动,如朋辈支持,戏剧活动等)在情感共情、动机共情以及行为共情三个维度上的训练效果均优于其他两种方法(即旨在调节共情者自身的训练方法和增强对共情对象了解情况的训练方法),且调节共情者自身的训练效果最差。
总体而言,本论文基于共情的心理过程提出一个“可测量”和“可分离”的共情系统框架,探讨了共情子成分之间的关系,不同类型因素对共情子成分的影响及其脑机制,并最终分析了共情训练的提升效果及其原理。本论文为深入理解共情的行为表现及其脑机制提供了实证证据,也为共情干预研究奠定了理论基础,有望助力提升人们的共情水平,促进人际良性互动和社会和谐发展。</p