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Vocal micro-expressions: A new framework for detecting emotional leakage SHEN Xunbing, FENG Tingting, SHENG Jing, PENG Yongmei, LIU Yihui, LI Yafang, CHEN Zhencai 2026, 34 (8):  1299-1308.  doi: 10.3724/SP.J.1042.2026.1299 Abstract ( 79 )   PDF (2423KB) ( 115 )   Peer Review Comments Micro-expressions are brief, involuntary emotional expressions that reveal an individual’s genuine internal affective state. Existing research has predominantly operationalized micro-expressions within the facial modality, restricting both their definition and detection to transient facial muscular activations. This face-centric perspective raises an important yet underexplored question: does a comparable form of emotional leakage occur in the vocal channel? More specifically, might “vocal micro-expressions” exist as subtle, short-lived variations embedded within speech prosody? Addressing this question is critical for advancing a more comprehensive and modality-general account of emotional leakage. A growing body of evidence supports the theoretical and empirical plausibility of vocal micro-expressions. In everyday social interactions, individuals can often infer latent emotional states—such as nervousness, hesitation, or anxiety—from subtle changes in another person’s voice, even when those emotions are intentionally concealed. From the perspective of emotional leakage theory, affective suppression is inherently incomplete, yielding residual activation that propagates through less consciously regulated channels, including vocal production. Speech production, governed by tightly coupled respiratory, phonatory, and articulatory subsystems, is modulated by autonomic arousal and affective dynamics, thereby constituting a plausible substrate for transient, low-amplitude emotional signals. Importantly, such signals are likely to manifest as fine-grained, temporally localized deviations in acoustic features rather than as sustained prosodic patterns. To systematically examine the existence and properties of vocal micro-expressions, the present study proposes the construction of a deception-elicited emotional speech corpus under controlled experimental conditions. Deception is adopted as the elicitation paradigm due to its well-established association with elevated cognitive load and affective arousal, both of which facilitate emotional leakage. Furthermore, deception inherently involves a conflict between internal states and external expressions, thereby increasing the likelihood of transient, involuntary perturbations. Data acquisition is conducted within an interactive communication framework to preserve ecological validity, as deception predominantly occurs in dialogic rather than monologic contexts. Participants engage in structured interaction tasks designed to elicit both deceptive and truthful responses, while multimodal recordings (audio-video) are obtained under both conditions. Temporal synchronization across modalities enables fine-grained alignment between vocal and facial signals, supporting cross-modal validation and integrative analysis. A central methodological challenge lies in the detection and quantification of transient, low-salience vocal perturbations. Unlike facial micro-expressions, which can be captured via high-speed imaging and localized in the spatial domain, vocal micro-expressions are distributed over time and often fall below the threshold of conscious auditory perception due to their brevity and low amplitude. To address this limitation, we introduce a strain-inspired measurement framework defined in acoustic feature space. Specifically, vocal micro-expressions are operationalized as normalized deviations: Micro vocal expression = ΔL/Lo, where ΔL denotes instantaneous deviations in one or a composite set of acoustic features (e.g., fundamental frequency, energy, spectral descriptors, or cepstral coefficients), and Lo denotes the corresponding baseline estimate, computed either at the utterance level or via speaker-adaptive normalization. This formulation enables robust, speaker-invariant quantification while preserving sensitivity to fine-grained temporal fluctuations. Building on this formulation, the temporal dynamics of vocal micro-expressions are parameterized using onset, apex, and offset, providing a principled representation of their emergence, peak intensity, and dissipation. These temporal markers can be extracted via change-point detection or peak analysis algorithms, enabling segmentation of continuous speech into candidate micro-expression events. Such parameterization facilitates both descriptive analysis and downstream modeling, including sequence-based learning and temporal pattern recognition. The proposed framework is evaluated through a series of behavioral and computational experiments aimed at (i) characterizing the statistical and distributional properties of detected vocal micro-expressions and (ii) assessing their discriminative utility in deception detection tasks. Supervised and self-supervised machine learning models, including deep neural architectures, are employed for feature representation, temporal modeling, and classification. By integrating theoretical formalization, ecologically grounded data acquisition, and advanced computational modeling, this work seeks to establish a robust empirical foundation for vocal micro-expressions. More broadly, it extends micro-expression research beyond the facial modality, advancing a unified, multimodal account of emotional leakage and contributing to the development of next-generation systems for affective computing and deception detection. References | Related Articles | Metrics

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When employee meets AI: Research on employee-AI collaboration’s construct measurement, antecedent configuration and influence mechanism CHEN Hui, FENG Chao 2026, 34 (8):  1309-1329.  doi: 10.3724/SP.J.1042.2026.1309 Abstract ( 67 )   PDF (975KB) ( 98 )   Peer Review Comments As artificial intelligence (AI) becomes deeply embedded in organizational contexts, employee-AI collaboration has emerged as a prevalent work pattern. Despite its growing importance, existing research reveals three critical gaps. First, the conceptualization of employee-AI collaboration remains fragmented, lacking an integrated typology and validated measurement instruments. Second, prior studies predominantly examine the net effects of single factor on employee-AI collaboration, neglecting the configurational nature of how multiple factors jointly shape employee-AI collaboration patterns. Third, the consequences of employee-AI collaboration yield inconsistent findings, with limited attention to differentiating collaboration types and the dual cognitive-affective mechanisms linking them to employee outcomes. To address these gaps, this research develops a comprehensive framework, and conducts three studies encompassing the typologies, antecedents, and consequences of employee-AI collaboration. Study 1: Employee-AI Typologies and Scale Development. Study 1 proposes a 2 × 2 typology of employee-AI collaboration based on two fundamental dimensions: agency (employee-centric vs. AI-centric) and interaction intensity (low vs. high). This dual-dimensional framework moves beyond prior unidimensional classifications and captures the complexity of human-AI partnering into four typologies: Augmentation, Symbiosis, Assistance and Substitution. Below are the detailed explanations of four typologies. Augmentation employee-AI collaboration (employee-centric agency, high interaction): Employees remain core actors while AI serves as an intelligent partner, providing knowledge transfer and decision support through frequent bidirectional interactions to enhance employees’ professional capabilities. Symbiosis employee-AI collaboration (AI-centric agency, high interaction): Employee and AI form a tightly coupled joint cognitive system, mutually dependent and complementary, co-optimizing tasks and decisions through real-time adaptation. Assistance employee-AI collaboration (employee-centric agency, low interaction): AI acts as a passive tool responding to specific commands without engaging in employees’ cognitive processes or capability development. Substitution employee-AI collaboration (AI-centric agency, low interaction): AI autonomously performs tasks originally done by employees, who retain minimal supervisory control. Based on the above four typologies, Study1 develops and validates four separate scales corresponding to each collaboration type. Study 2: Configurational Antecedents of Employee-AI Collaboration. Grounded in sociotechnical systems theory, Study2 identifies eight contextual factors spanning four subsystems: employee (employee’s AI literacy, employee’s AI awareness), AI (AI capability, AI reliability), task (task complexity, task type), and organization (organizational resources, organizational culture). Using fuzzy-set qualitative comparative analysis (fsQCA), Study2 investigates their synergistic effects through a configurational approach, and uncover how combinations of these factors jointly lead to different collaboration patterns. Study 3: Consequence Mechanisms and Interventions of Employee-AI Collaboration. Based on the Cognitive-Affective Processing System (CAPS) theory, study 3 proposes a dual-pathway model linking each collaboration type to employee job performance and well-being through cognitive (cognitive expansion, cognitive slackness) and affective (positive affect, negative affect) mechanisms. This study also theorizes four matched managerial interventions: decision sovereignty cultivation for Augmentation (reinforcing employee agency), dynamic contribution evaluation for Symbiosis (ensuring perceived fairness), function expansion programs for Assistance (preventing instrumental thinking inertia), and transition support for Substitution (mitigating replacement anxiety). Hypotheses include linear, curvilinear, and comparative effects across types. Consequently, this research makes several important theoretical contributions in employee-AI collaboration field. First, this research develops an integrative typology of employee-AI collaboration. By integrating agency and interaction intensity, this research constructs a 2×2 framework categorizing collaboration into four distinct typologies: Augmentation, Symbiosis, Assistance, and Substitution. This dual-dimensional approach overcomes the limitations of prior unidimensional classifications and provides conceptual clarity. It further develops and validates corresponding scales, addressing the lack of measurement instruments and enabling future empirical research. Second, adopting a configurational approach, this research reveals how employee, AI, task, and organizational factors interdependently shape employee-AI collaboration patterns. It advances socio-technical systems theory by specifying how social and technical subsystem elements combine to produce distinct work system configurations in the AI era. Third, this research unpacks the cognitive-affective mechanisms through which different collaboration types affect employee outcomes, addressing calls for more comprehensive process models in human-AI research. It explains why collaboration can be both beneficial and detrimental—depending on collaboration type and mediating pathways—and responds to the neglect of affective processes in prior work. Finally, introducing corresponding managerial interventions offers actionable insights for organizations seeking to optimize employee-AI partnerships. By specifying which interventions fit which collaboration patterns, the research provides a contingency framework for human resource management in increasingly hybrid work environments. The above findings will help employees recognize their collaboration patterns and develop complementary skills; guide managers in tailoring AI implementation and support strategies; and enable organizations to allocate resources effectively toward interventions that enhance both performance and employee well-being. The ultimate goal of this research is to foster human-AI synergy where technology augments rather than diminishes human potential at work. References | Related Articles | Metrics

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The conceptualization, antecedents, and multilevel effects of leader strengths use HAI Shenyang, YANG Bo, GUO Tengfei, XIN Zhaoyang, LIU Liu, FU Anguo 2026, 34 (8):  1330-1350.  doi: 10.3724/SP.J.1042.2026.1330 Abstract ( 55 )   PDF (1103KB) ( 63 )   Peer Review Comments In an era of intensifying talent competition and rapid organizational transformation, leader strengths use has become increasingly central to sustaining team performance and adaptability. Although leader strengths use has attracted growing scholarly attention, important limitations remain. Specifically, prevailing conceptualizations are largely derived from Western contexts, offering limited insight into the structure of leader strengths use in Chinese organizational contexts. In addition, existing research has focused primarily on the outcomes of leader strengths use, particularly short-term, individual-level performance, while paying relatively little attention to its antecedents and to its broader effects at the team level. This lack of conceptual clarity and multilevel perspective limits our understanding of how strengths-based leadership practices are formed and how they shape broader organizational functioning. To address these limitations, this study clarifies the conceptualization of leader strengths use and examines its antecedents, dynamic processes, and multilevel consequences. Grounded in the social construction of leadership theory, this study clarifies the construct of leader strengths use as a socially constructed leadership process rather than a narrow form of support for subordinates’ strengths use. Leader strengths use is defined as a multidimensional leadership behavior through which leaders model the use of their own strengths, activate followers’ strengths, and coordinate complementary strengths within the team. This formulation extends prior work in two respects. It moves beyond conceptualizations centered solely on support for followers’ strengths use, and it treats strengths coordination as part of the construct itself rather than as a downstream consequence. To establish the construct, this study combines grounded theory and scale development to establish the conceptual domain of leader strengths use and to develop a measure with sound psychometric properties. In doing so, this study specifies the construct more precisely and anchors it in three core dimensions: strengths modeling, strengths activation, and strengths coordination. Building on this conceptual foundation, we further propose that leader strengths use is shaped by the joint influence of organizational, leader, and follower conditions. Rather than treating antecedents as independent predictors, we adopt a configurational perspective and argue that multiple combinations of conditions may give rise to leader strengths use. At the organizational level, developmental human resource practices are expected to provide normative support and resources that legitimize strengths-based leadership. At the leader level, proactive personality and leader strengths knowledge are proposed to shape leaders’ beliefs about human potential and their capability to identify and mobilize strengths. At the follower level, perceived subordinate competence is expected to influence leaders’ judgments about the feasibility of strengths-based allocation and coordination. To examine these interdependent conditions, we propose to use fuzzy-set qualitative comparative analysis (fsQCA) to identify configurational antecedents and equifinal pathways to high levels of leader strengths use. In addition, we conceptualize leader strengths use as a dynamic process rather than a static behavioral tendency. Drawing on self-determination theory, we propose that engaging in strengths use enhances leaders’ motivation, which in turn increases the likelihood of subsequent strengths use, forming a self-reinforcing gain cycle. Finally, we advance a multilevel perspective on the consequences of leader strengths use. Building on the leadership process model, we propose that leader strengths use influences job performance at both the individual and team levels, and that these effects are contingent on key boundary conditions. At the team level, we argue that the congruence between leader strengths use and organizational support for strengths use shapes positive team processes, including shared strengths awareness, trust, and coordination, which in turn are expected to influence team commitment, performance, and innovation over time. At the individual level, we propose that leader strengths use affects subordinates’ performance and innovation through strengths-based job crafting, with these effects contingent on contextual factors such as career insecurity and career future time perspective. To test these propositions, we outline a multi-method empirical strategy combining multi-wave multisource surveys, polynomial regression with response surface analysis, and experimental designs. Collectively, this research makes several contributions. First, it advances a more precise conceptualization of leader strengths use grounded in a Chinese context. Second, it introduces a configurational and dynamic perspective to explain the antecedents of leader strengths use and its evolution over time. Third, it develops a multilevel theoretical account of the consequences and boundary conditions of leader strengths use. By bringing together insights on construct development, antecedents, processes, and outcomes, this study provides a useful foundation for future empirical research on leader strengths use and talent management in organizations. References | Related Articles | Metrics

Meta-Analysis

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The shared neural mechanisms of emotional contagion and bodily self-representation WANG Dan, CHEN Wenfeng, WANG Hui, FU Yujia, LIU Junye, LIU Zhengkui 2026, 34 (8):  1351-1370.  doi: 10.3724/SP.J.1042.2026.1351 Abstract ( 44 )   PDF (10014KB) ( 112 )   Peer Review Comments A fundamental question in social neuroscience concerns the mechanisms by which individuals understand and respond to others’ emotional states. Theories of embodied simulation and shared representation propose that understanding others is intrinsically linked to self-processing, suggesting that emotional and self-referential processes are interdependent components of the social brain. Emotional contagion, defined as the tendency to automatically share or resonate with others’ emotions, represents a key manifestation of this process. However, direct neural evidence linking EC to a basic form of self-processing—namely bodily self-representation, as indexed by self-face processing—remains limited. Identifying this shared neural basis is critical for clarifying the embodied reference frame underlying social interaction. This meta-analysis aimed to systematically and quantitatively examine the shared neural substrates of emotional contagion and bodily self-representation (operationalized using self-face recognition tasks). In addition, Meta-Analytic Connectivity Modeling (MACM) was employed to move beyond anatomical overlap and characterize the functional network organization of these shared regions, providing network-level and functionally specific evidence for shared representation accounts. Based on 56 eligible fMRI studies, ALE analyses revealed significant convergent activation in the right inferior frontal gyrus (IFG), bilateral insula, and fusiform gyrus (FG) across both task domains. These regions overlap with key nodes of the frontoparietal action observation network and the salience network, supporting embodied simulation, interoceptive integration, and self-referential processing. MACM analyses further revealed consistent co-activation patterns associated with IFG- and insula-centered networks. These patterns converged on the middle frontal gyrus, precentral gyrus, superior and inferior parietal lobules, dorsal anterior cingulate cortex, and occipitotemporal cortices. Together, these findings suggest that shared mechanisms extend beyond focal regions to distributed functional networks involved in action-perception coupling, attentional regulation, and self-other integration. Building on these findings, we propose a multilayered embodied mechanism linking emotional contagion and bodily self-representation. At the perceptual level, FG sensitivity to self-relevant and socially meaningful faces suggests that self-relatedness modulates early social perception. At the sensorimotor level, overlapping IFG and inferior parietal activation supports automatic motor simulation underlying both emotion mimicry and self-recognition. At the interoceptive level, the insula and dorsal anterior cingulate cortex integrate external emotional cues with internal bodily states, enabling the mapping of others’ emotions onto one’ s own experiential framework. This integrative architecture may also account for individual differences in emotional contagion, as responses are modulated by targets’ self-relevance, social significance, and the congruence of internal physiological states. This research advances the theoretical understanding of emotional contagion by moving beyond the traditional “imitation-feedback” model toward an “embodied meaning construction” perspective. It demonstrates that emotional contagion is not a passive, mechanical replication but a process deeply rooted in the individual’s physical self-representation. Furthermore, the observed right-hemisphere dominance underscores its critical role in maintaining an integrated self-concept and facilitating interpersonal emotional coupling. These findings offer a unified neural framework for social cognition and provide potential insights for clinical interventions in social-emotional disorders, such as autism spectrum disorders, where self-other mapping mechanisms are often disrupted. References | Related Articles | Metrics

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Longitudinal changes and social causes of older adults’ ageing attitudes in China SONG Haojie, YIN Qian, ZHANG Qiang, YANG Yansui 2026, 34 (8):  1371-1385.  doi: 10.3724/SP.J.1042.2026.1371 Abstract ( 59 )   PDF (698KB) ( 54 )   Peer Review Comments Aging attitudes refer to how older adults psychologically evaluate their own aging process. Studies have analyzed the causes of aging attitudes from the perspectives of individual characteristics and family relationships. However, few have explored the social causes of aging attitudes, and even fewer have examined their historical trends over time. According to social ecosystem theory, aging attitudes are not isolated within individuals; rather, they are psychological states that evolve through interactions with the social environment. Nevertheless, the temporal trends of aging attitudes among Chinese older adults and their social causes remain unclear. To address this gap, this study conducted a cross-temporal meta-analysis of 72 articles (224 independent studies, N=48,539) to examine the changing trends and social causes of aging attitudes among Chinese older adults from 2008 to 2023. The results revealed two main findings. (1) The overall level of aging attitudes showed a significant upward trend over the 16-year period, characterized by an increase in the psychological growth dimension and a decline in the psychosocial loss dimension, while no significant change was observed in the physical change dimension. Specifically, over the past sixteen years, the aging attitudes level among older adults in China increased by 2.70 z-scores. The physical change dimension level decreased by 0.75 z-scores, the psychological growth dimension level increased by 1.65 z-scores, and the psychosocial loss dimension level decreased by 2.40 z-scores. (2) Social welfare subsidies (i.e., per capita national expenditure on elderly welfare, and the proportions of older adults receiving old-age allowances, care allowances, and elderly service allowances), elderly care services (i.e., the number of care beds and the number of social workers in institutions and communities), and social participation services (i.e., the number of associations for older adults) significantly predicted changes in aging attitudes. However, the results also revealed differences in the effects of these social factors. First, regarding welfare security, the per capita national expenditure on elderly welfare and the proportion of older adults receiving old-age allowances had significant and long-term positive effects on aging attitudes. In contrast, the effects of the proportions of older adults receiving care allowances and elderly service allowances were primarily short-term. Second, regarding elderly care services, the number of institutional and community care beds and the number of social workers showed significant immediate positive effects on aging attitudes, but these lagged effects diminished notably. Third, regarding social participation services, the number of older adult associations had a significant positive effect on aging attitudes, but this effect only emerged with a two-year lag. This study makes two major contributions. First, it reveals the long-term dynamic trajectory of aging attitudes and the differential trends across its dimensions. Previous cross-sectional studies have focused on individual differences at single time points, which cannot capture how aging attitudes change over time. Focusing on the period of accelerated population aging in China from 2008 to 2023, this study presents the historical trend of aging attitudes and reveals distinct trends across dimensions: psychosocial loss dimension significantly decreased over time, psychological growth dimension significantly increased, while the physical change dimension showed no significant change. These findings deepen the understanding of aging attitudes as a multidimensional construct and illuminate its dynamic and complex nature. Second, grounded in social ecosystem theory, this study examines the effects of welfare security, elderly care services, medical services, and social participation services on the changes in aging attitudes. The results reveal differentiated effect patterns: universal and residual welfare subsidies have different temporal sustainability effects; elderly care services provide primarily immediate psychological benefits; and social participation services exhibit a significant lagged effect. These findings demonstrate that the social environment exerts an effect on psychological cognition, and they further reveal the complex temporal boundary conditions of this effect, specifically immediate, short-term, and long-term effects. References | Related Articles | Metrics

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The influence of socially responsible human resource management on employee work outcomes: A meta-analysis ZHANG Xiaoyan, SU Fangguo 2026, 34 (8):  1386-1409.  doi: 10.3724/SP.J.1042.2026.1386 Abstract ( 45 )   PDF (2219KB) ( 76 )   Peer Review Comments Socially responsible human resource management (SRHRM) represents a critical direction within the field of sustainable human resource management. However, existing empirical findings on the relationship between SRHRM and employee work outcomes remain fragmented and inconsistent, and the sources of these discrepancies are still unclear. To address this gap, the present study employed a meta-analytic approach to provide a comprehensive and quantitative integration of the relationships between SRHRM and three major categories of employee outcomes—attitudes, well-being, and performance—while also identifying boundary conditions that help explain prior inconsistencies. To this end, this study synthesized effect sizes from 105 empirical articles (k = 109, N = 55,076) to examine the relationships between SRHRM and various work-related outcome variables. The results revealed that SRHRM exhibited robust and differentiated relationships across different variables. Specifically, SRHRM was strongly and positively correlated with organization-targeted attitudes ($\bar{\rho }$ = .51), psychological well-being ($\bar{\rho }$ = .55), and organizational citizenship behavior ($\bar{\rho }$ = .54); moderately and positively correlated with job-targeted attitudes ($\bar{\rho }$ = .31), in-role performance ($\bar{\rho }$ = .42), proactive behavior ($\bar{\rho }$ = .45), and prosocial behavior ($\bar{\rho }$ = .46); weakly and negatively correlated with deviant behavior ($\bar{\rho }$ = -.26); and showed a non-significant correlation with health ($\bar{\rho }$ = .05). Beyond these direct correlations, this study applied meta-analytic structural equation modeling (MASEM) to examine whether the strength of SRHRM’s effects varied across distinct theoretical perspectives. MASEM results revealed the differential explanatory power of two dominant perspectives in the SRHRM literature—social exchange theory and social identity theory. Specifically, SRHRM promoted proactive behavior primarily by improving social exchange quality between employees and the organization, while it influenced organizational citizenship behavior primarily by strengthening employees’ organizational identification. These findings highlight the pervasive positive impact of SRHRM on diverse workplace outcomes; they also reveal a potential dark side that may emerge from its practical implementation. To further explain the heterogeneity in prior research, this study systematically examined three sets of moderators: study design characteristics, level of analysis, and national cultural context. First, methodological design partially moderated the observed relationships. Notably, SRHRM showed stronger correlations with attitudinal and performance variables (e.g., job satisfaction, proactive behavior) in longitudinal studies than in cross-sectional studies, suggesting that SRHRM practices could have a time-lag effect and might be better captured by time-sensitive research designs. Second, the level of analysis emerged as an important boundary condition. The relationship between SRHRM and health was significant only when SRHRM was measured at the organizational or team level, indicating potential gaps in implementation or perception when HR policies are translated into employee experiences. Third, national culture (long-term versus short-term orientation) moderated several relationships. Contrary to conventional expectations, the positive correlations between SRHRM and in-role performance and prosocial behavior were weaker in long-term oriented cultures, revealing a potentially complex fit between HR practices and cultural values. Based on these findings, this study makes several important theoretical contributions. First, it provides the first meta-analysis of the SRHRM literature, offering robust effect size estimates of the relationships between SRHRM and a range of employee work outcomes, thereby comprehensively evaluating the effects and practical value of SRHRM. Second, by integrating and empirically comparing the mechanisms of social exchange and social identity through MASEM, this study advances a more nuanced theoretical framework for understanding how SRHRM influences employee performance. Third, by identifying important moderators related to methodology, level of analysis, and cultural difference, this study provides empirical explanations for inconsistent findings in prior literature. Fourth, this study responds to the external-oriented bias in corporate social responsibility (CSR) research by demonstrating that CSR policies and practices directed at employees (i.e., SRHRM) significantly influence employees’ attitudes, well-being, and performance, thereby providing empirical support for future research on the micro-foundations of stakeholder theory. From a practical perspective, this findings suggest that SRHRM should not be viewed merely as a compliance or reputational tool but rather as a strategic investment for fostering positive employee attitudes, psychological flourishing, and valued organizational behaviors. However, the non-significant relationship with health-related well-being also points to a potential dark side in the implementation of SRHRM policies (e.g., role overload, resource depletion), suggesting that practitioners should accompany social responsibility initiatives with more effective organizational support systems and ensure that SRHRM is implemented in a truly sustainable and employee-centered manner. References | Related Articles | Metrics

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The sequential nature of cognitive control and its neurocognitive mechanisms HUANG Jiamin, YANG Guochun 2026, 34 (8):  1410-1426.  doi: 10.3724/SP.J.1042.2026.1410 Abstract ( 60 )   PDF (604KB) ( 105 )   Peer Review Comments Cognitive control is a dynamic regulatory mechanism that enables individuals to achieve goal-directed behaviors. Although traditional research has largely emphasized comparisons between discrete, isolated control states (e.g., high versus low conflict in the Stroop task), real-world control-driven behaviors are inherently sequential. They require the preservation of goal consistency, flexible updating across multiple steps, and integration over extended temporal windows. To address this gap, this review systematically investigates behavioral, computational, and neural evidence to pioneer a shift from discrete-state comparisons to a sequential processing framework. We highlight a profound convergence between studies of cognitive control and serial memory, proposing that the sequential nature of cognitive control represents a critical interdisciplinary frontier. A core contribution of this review is that it outlines an evolving trend in the literature toward studying long sequence of abstract control. Traditionally, research on cognitive control has focused on short-sequence effects, such as congruency sequence effects, post-error slowing, and switch costs. These effects are primarily driven by local, reactive adjustments such as conflict monitoring, associative learning, and the active inhibition of recently executed or irrelevant task sets (e.g., the N-2 repetition cost). However, a growing body of work has turned the interest to the long-term effects of cognitive control and the long control sequences. Executing long sequences requires the establishment of long-term higher-order representations, supported by proactive mechanisms including hierarchical chunking, temporal predictive coding, and abstract sequence compression. Concurrently, in contrast to the more concrete sequences (e.g., word or number sequences) emphasized in the past, the literature on sequence memory has also shifted its interest toward abstract sequences (e.g., rule series) and sequence abstraction (e.g., learning from concrete sensory inputs to construct abstract relational transition graphs). The convergence of these two fields highlights a promising interdisciplinary area: the study of cognitive control sequences. Critically, the seemingly distinct fields of cognitive control and sequence memory exhibit substantial cross-talk. For instance, both domains share an interest in suppression effects (i.e., suppressing completed items/tasks to avoid interference) and commonly employ sequence working memory paradigms to investigate their core questions. Moreover, their representative neural regions demonstrate strong functional interaction: (1) The prefrontal-hippocampal loop binds transient control states into episodic, context-rich sequence representations. During offline or resting states, the hippocampus generates rapid sequence replay that drives prefrontal activation, supporting memory consolidation and structural generalization. (2) The cortico-basal ganglia-thalamic circuits translate abstract rules into executable action flows, with the striatum forming sequence chunk boundaries, the globus pallidus regulating execution speed, and the thalamus gating the execution of learned subroutines back to the prefrontal cortex. Together, these findings indicate that the integration of cognitive control and sequence memory is functionally plausible. To formalize this theoretical integration, we explicitly introduce the concept of the Representation of Cognitive Control Sequence, defined as the brain's memory representation of structured sequences composed of multiple abstract cognitive control states arranged in a specific temporal order. Methodologically, we advocate for paradigm innovations such as the Abstract Cognitive Task Sequence (ACTS) and conflict sequence designs, combined with representational geometry analyses, to quantify the abstract dynamics of these control states. Furthermore, the translational implications of this sequential perspective are substantial. In clinical psychopathology, re-evaluating psychiatric disorders through a sequence-level lens offers novel diagnostic and interventional pathways. In artificial intelligence, our framework provides biologically grounded constraints (such as hierarchical chunking and replay-based sequence consolidation) that address the "goal-maintenance" deficit in current models, offering a neurobiologically plausible blueprint for autonomous agents capable of adaptive, multi-step planning. In conclusion, by establishing cognitive control sequence as a core construct, we bridge the historical divide between cognitive control and sequence memory research, yielding transformative insights for both clinical intervention and brain-inspired computing. References | Related Articles | Metrics

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Metacognitive regulation and neurophysiological mechanisms of temporal error monitoring CUI Qian, JIA Yunxuan, LI Baike 2026, 34 (8):  1427-1438.  doi: 10.3724/SP.J.1042.2026.1427 Abstract ( 46 )   PDF (608KB) ( 87 )   Peer Review Comments Temporal error monitoring (TEM) refers to the metacognitive process through which individuals detect, evaluate, and regulate deviations in their own temporal judgments. It enables individuals not only to assess whether a timing response is accurate, but also to use internal and external cues to improve later behavior. Although previous studies show that humans can monitor timing errors even without explicit feedback, current findings remain fragmented across behavioral, computational, and neurophysiological levels. The present review therefore examines the metacognitive regulation of TEM and its neural basis, focusing on three mechanisms—self-evaluation, feedback-based regulation, and decision-confidence regulation—and, on this basis, proposes a two-stage, three-pathway integrative model. The review first organizes the major paradigms used to study TEM. Opt-out tasks index implicit monitoring by asking participants to keep or discard a timing response without external feedback. Self-evaluation tasks assess explicit metacognitive access by requiring judgments of error direction, magnitude, or confidence after a temporal estimate. Reattempt-decision tasks focus on feedback-guided adjustment by examining whether participants choose to retry after receiving performance-related information. Together, these paradigms indicate that TEM is not a single ability, but a coordinated process involving error detection, evaluation, and regulation. A first major claim of this review is that self-evaluation constitutes the foundational mechanism of TEM. Even without feedback, individuals can detect and correct temporal deviations on the basis of internal representations. This suggests that TEM depends on a metacognitive readout of self-generated timing signals rather than solely on external comparison. Computationally, this process can be understood within a sequential diffusion framework derived from the opposing Poisson drift-diffusion model. Temporal judgments arise from competition among noisy accumulators, and post-response comparisons among them provide information about whether a response was too early or too late, as well as the magnitude of deviation. This account shifts the explanation of temporal self-monitoring from a single internal clock to a distributed evidence-based mechanism. A second major claim is that feedback-based regulation serves as an important but supplementary route for improving temporal judgments. External feedback provides an objective reference that can compensate for limitations in internal timing signals, yet different forms of feedback differ in effectiveness. Correct/incorrect, absolute-error, and signed-error feedback vary in informational value, with signed-error feedback appearing especially effective because it specifies both direction and magnitude. At the same time, feedback does not simply replace internal monitoring. Its influence depends on whether external information is consistent with the individual’s own evaluation of performance. A third major claim concerns decision-confidence regulation. Confidence is treated not merely as a retrospective report, but as an estimate of the reliability of one’s temporal judgment. It does not directly encode error direction or magnitude. Instead, it regulates how strongly self-evaluation and feedback influence later decisions and corrections. Another contribution of the review is the integration of neurophysiological findings. Beta activity is closely related to the generation and maintenance of internal temporal representations, whereas alpha activity is more strongly associated with the readout and evaluation of self-generated timing states. Alpha-beta coupling and coordination between the timing network and the default mode network further indicate that self-evaluation in TEM depends on distributed neural interactions. In feedback-based regulation, feedback-related negativity reflects rapid prediction-error processing, whereas the P3 component is more closely linked to the motivational and evaluative significance of feedback. Findings involving prefrontal and orbitofrontal regions further suggest that confidence has a distinct neural basis and may influence second-order monitoring even when first-order timing performance remains relatively intact. Based on the above evidence, this review proposes a two-stage, three-pathway model of TEM. In the first stage, internal temporal error representations are formed through temporal encoding, memory, and comparison processes. These representations include both content information, such as error direction and magnitude, and quality-related information, such as uncertainty and representational reliability. In the second stage, three interactive pathways operate on this representation. The self-evaluation pathway extracts endogenous information about temporal deviation from internal representations; the feedback-based pathway uses accumulated feedback history to generate exogenous calibration signals; and the confidence-regulation pathway uses uncertainty-related cues to adjust parameters such as integration weight, learning rate, and decision threshold. The main innovation of this model is that it explicitly distinguishes the generation of temporal errors from their metacognitive regulation, while assigning confidence a modulatory role in the integration process. In summary, this review reorganizes the TEM literature around three metacognitive regulatory mechanisms, integrates behavioral and neurophysiological evidence within a unified account, and proposes a novel two-stage, three-pathway model to explain how temporal errors are monitored and regulated. These contributions deepen current understanding of the metacognitive architecture of time perception and provide a theoretical basis for future research on development, ecological task design, and clinical application. References | Related Articles | Metrics

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The circadian rhythm and its specific regulation of cognitive function YAN Kaikai, GUO Bowen, CHEN Xing, MAO Tianxin, RAO Hengyi 2026, 34 (8):  1439-1455.  doi: 10.3724/SP.J.1042.2026.1439 Abstract ( 68 )   PDF (1277KB) ( 72 )   Peer Review Comments The circadian rhythm is an endogenous timing system adapted to Earth’s rotation, and its stability is vital for health and cognition. Circadian disruption impairs cognitive performance, which fluctuates diurnally—typically troughing from early morning to late morning and recovering from late afternoon to night. Further studies show that circadian regulation is domain-specific: different cognitive functions have distinct peak phases and sensitivities, suggesting different neural mechanisms. However, existing research has three major limitations. First, the conceptual definition and underlying mechanisms of circadian effects remain unclear. Second, studies have largely focused on attentional vigilance and working memory, lacking systematic cross-domain comparisons, especially under differentiated intrinsic mechanisms. Third, neural evidence remains fragmented and limited. Thus, systematically clarifying how circadian rhythms differentially regulate cognitive functions through distinct intrinsic mechanisms is a key scientific question. The classic two-process model of sleep-wake regulation posits that cognitive performance during wakefulness is governed jointly by the homeostatic process (Process S) and the circadian process (Process C). During early daytime wakefulness, Process C counteracts the accumulating effect of Process S, maintaining cognitive performance; during the biological night, the wake-promoting effect of Process C diminishes, and cognitive performance reaches its nadir; it recovers the next day as Process C strengthens. However, different experimental paradigms vary considerably in their control over confounding factors, leading to divergent interpretations of the mechanisms involved. Physiologically, the circadian rhythm depends on a multilevel network involving molecular clocks, the central clock, and the endocrine system. The suprachiasmatic nucleus regulates subcortical arousal systems through neural projections and modulates the rhythmic secretion of hormones such as melatonin and cortisol, thereby broadly conveying temporal signals to different brain regions. This framework provides a neurophysiological basis for distinguishing between broad and narrow circadian effects. To systematically investigate the effects of the circadian rhythm on cognitive functions and their temporal distribution, this review included 73 studies, covering subjective sleepiness, attentional vigilance, complex executive function, working memory, risk decision-making, and moral behavior. Analyses of broad circadian effects revealed that subjective sleepiness, attentional vigilance, and complex executive function exhibited a robust pattern of lower levels in the morning and higher levels in the evening, suggesting they may be subject to general regulation by global arousal levels. In contrast, results for working memory and risk decision-making showed high heterogeneity, while moral behavior did not display a stable rhythmic pattern. These differences may arise from methodological factors, such as incomplete coverage of measurement times, and also suggest that the neural circuits underlying different cognitive functions may respond to circadian regulation in functionally specific ways. For narrow circadian effects, researchers typically use post-hoc analyses based on the two-process model or its derivatives to isolate the cognitive fluctuations driven purely by Process C. The results showed that subjective sleepiness, attentional vigilance, and complex executive function still followed a consistent pattern of lower levels in the morning and higher levels in the evening, indicating that narrow circadian effects may exert general regulation on cognitive functions by modulating common arousal mechanisms. At the same time, significant differences in peak phases were observed across cognitive functions, suggesting that the endogenous circadian clock may provide specific temporal regulation to distinct brain regions or networks via differentiated neural or endocrine pathways. Taken together, the behavioral evidence suggests that circadian rhythms influence cognitive functions through both a general regulatory mechanism based on global arousal and differentiated regulatory mechanisms relying on distinct neural circuits. Integrating evidence from functional magnetic resonance imaging and electroencephalography studies, circadian rhythms may influence cognitive functions through two mechanisms. First, they exert general regulation by modulating global arousal levels. The circadian rhythm regulates arousal-related structures such as the hypothalamus, thalamus, and locus coeruleus, as well as their ascending drive to cortical states, dynamically shaping time windows such as the circadian trough and the wake maintenance zone, thereby exerting relatively non-specific effects on a broad range of cognitive functions. Second, they exert specific regulation by modulating activity in task-relevant brain regions or functional networks. Broad circadian effects differentially modulate specific cortical networks and their information processing over time, selectively influencing the efficiency and peak phases of different cognitive functions. Finally, this review outlines directions for future research. Future research should integrate multimodal neural data with computational models, combine targeted neuromodulation techniques to establish causal relationships, and explore precision light-based intervention strategies based on specific time windows, thereby providing precise cognitive protection for individuals with circadian rhythm disorders. By distinguishing circadian effects driven by different intrinsic mechanisms and integrating behavioral and neural evidence, this review aims to construct a clear framework for how circadian rhythms influence cognitive functions and to provide mechanistic explanations for their effects on human cognition. References | Related Articles | Metrics

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Applying wise intervention to promote prosocial behavior KOU Yu, DING Yue, YANG Xiaojun, ZHA Yichang 2026, 34 (8):  1456-1467.  doi: 10.3724/SP.J.1042.2026.1456 Abstract ( 61 )   PDF (611KB) ( 80 )   Peer Review Comments Prosocial behavior refers to actions that benefit others and society, such as helping, sharing, and cooperating. It not only promotes psychological well-being and positive social relationships, but also contributes to social harmony. This paper first reviews existing intervention strategies for prosocial behavior, then introduces the core principles of wise intervention. On this basis, this paper proposes a wise intervention framework for promoting prosocial behavior and suggests directions for future research. Prior research has developed a range of intervention approaches from behavioral, cognitive, and emotional perspectives, demonstrating generally positive effects. However, these approaches often involve high implementation costs, show limited stability over time, insufficiently address heterogeneity in intervention effects, and are not fully adapted to digital contexts. As an alternative, wise intervention focuses on the meanings and inferences individuals draw about themselves, others, and the situations they are in, and uses precise, theory- and research-based techniques to alter these meanings. By reshaping individuals’ meaning making and fostering more adaptive interpretations, wise intervention targets the psychological processes underlying behavior. In fact, wise interventions have achieved substantial progress in domains such as education, health, and interpersonal relationships, as illustrated by intervention strategies including growth mindset and self-affirmation. Prosocial behavior is fundamentally shaped by individuals’ meaning making. Whether people engage in prosocial behavior often depends on their beliefs about behavioral outcomes, social norms, and self-concept. Accordingly, the present study proposes a wise intervention framework for prosocial behavior. The wise intervention framework for prosocial behavior has three main emphasis. First, the framework centers on individuals’ meaning-making processes and specifies intervention strategies based on three fundamental psychological needs—the need to understand, the need to belong, and the need for self-integrity. Individuals often underestimate the positive impact of their actions on others and overlook the self-benefits of prosocial engagement. By providing evidence-based information that highlights the dual benefits of prosocial behavior for both others and the self, interventions can correct such mispredictions and activate intrinsic prosocial motivation. Thus, interventions targeting the need to understand aim to recalibrate biased interpretations of prosocial behavior. As people are more likely to follow the behavior patterns of majority, by conveying descriptive social norms and fostering shared group identity, prosocial behavior can be framed as both prevalent and socially valued, thereby aligning it with individuals’ motivation for social inclusion. Hence, interventions addressing the need to belong focus on strengthening social connectedness and shaping normative perceptions. In addition, drawing on self-affirmation theory and cognitive dissonance theory, strategies such as value reflection and “saying-is-believing” exercises can promote the internalization of prosocial meanings and facilitate self-persuasion. Therefore, interventions targeting the need for self-integrity aim to reinforce a positive and coherent self-concept. Second, the framework posits that intervention effects are sustained through a recursive “meaning-behavior-situation” process: reconstructed meanings promote prosocial behavior, which generates positive interpersonal feedback and improved situations, and these situational changes in turn reinforce prosocial meanings, forming a self-sustaining cycle. Third, the framework emphasizes the role of heterogeneity in intervention effectiveness. Specifically, outcomes depend on both individual plasticity (e.g., prior meanings and baseline prosocial tendencies) and environmental affordance, particularly psychological affordance that support the meanings promoted by the intervention. Introducing wise intervention into the domain of prosocial behavior not only extends its scope of application, but also deepens the understanding of prosocial behavior plasticity and provides a new direction for developing more efficient intervention strategies. Future research should further specify intervention targets and populations based on theoretical and empirical evidence, and develop precise, context-sensitive intervention designs. Rigorous randomized controlled trials in real-world settings are needed to evaluate both short-term and long-term effects, complemented by multi-method approaches that integrate behavioral, self-report, and contextual data. Particular attention should be given to examining heterogeneity, including how individual characteristics and environmental affordance jointly shape intervention effectiveness. In addition, future research should promote the development of digital interventions to enhance scalability and accessibility. Overall, future studies should continue to explore precise intervention approaches for promoting prosocial behavior, so as to better integrate theory and practice and provide actionable insights for education and social governance. References | Related Articles | Metrics

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The impact of economic inequality on status anxiety and its socio-psychological mechanisms ZHAO Yafei, ZHANG Yue, ZHANG Robert Jiqi, GUO Yongyu 2026, 34 (8):  1468-1488.  doi: 10.3724/SP.J.1042.2026.1468 Abstract ( 123 )   PDF (721KB) ( 156 )   Peer Review Comments Against the backdrop of persistently rising economic inequality, status anxiety has emerged as a pervasive societal mentality with profound implications for individual well-being and social cohesion. Thstudy develops a systematic theoretical framework to investigate how economic inequality systematically generates and shapes status anxiety within the context of China’s distinctive social structure. By shifting the analytical focus beyond the Western-centric preoccupation with “middle-class anxiety”, this inquiry extends to encompass all social strata, with particular attention to the vast lower-middle and disadvantaged groups. The study begins by reconceptualizing status anxiety through a two-dimensional, four-quadrant typology. While existing research has largely confined status anxiety to interpersonal horizontal comparisons, this framework introduces a vertical temporal comparison dimension—comparison with one’s expected self—and integrates both horizontal-vertical cognitive comparisons with approach-avoidance motivational processes. This typology distinguishes four distinct types of status anxiety along a gradient of intensity. In the first quadrant, individuals perceive themselves as superior to others horizontally and meet their self-expectations vertically. Satisfied on both dimensions, they experience minimal, nearly non-existent status anxiety. In the second quadrant, individuals meet vertical self-expectations but face horizontal disadvantage. While vertical satisfaction buffers some stress, the threat of falling behind relative to others triggers moderate-to-high anxiety dominated by horizontal deprivation. In the third quadrant, individuals suffer from both horizontal disadvantage and vertical disappointment. This “double deprivation”—failing to match others or one’s own expectations—creates a dual predicament that generates the highest level of status anxiety. In the fourth quadrant, individuals are horizontally advantaged yet fall short of their vertical self-expectations. Despite social success, the frustration of not becoming their “ideal self” leads to moderate-to-high anxiety dominated by vertical deprivation. Collectively, this typology extends classical theories such as social identity theory and relative deprivation theory by incorporating temporal comparison and motivational dynamics into the analysis, offering a more nuanced analytical lens for understanding the complexity and gradation of status anxiety. The analysis then turns to the mechanisms through which economic inequality shapes status anxiety, proposing an integrated micro-macro dual-path framework that links structural pressures with individual psychological and behavioral responses. At the micro level, economic inequality fosters materialistic values, induces overwork, and reinforces zero-sum beliefs—maladaptive reactions that directly catalyze status anxiety. Materialism sets unattainable goals, overwork depletes physical and mental resources, and zero-sum beliefs frame social relations as sources of perpetual threat. At the macro level, economic inequality erodes perceived social justice by undermining the sense of opportunity equity, diminishing belief in social mobility, and shaping attributions of wealth and poverty—for instance, by leading individuals to attribute success to family background rather than personal effort. Through these intertwined pathways, economic inequality systematically erodes the perceived legitimacy of the social system and generates pervasive anxiety at its source. Central to the analysis is a grounding in the reality of China’s unique social structure. In contrast to the relatively mature “olive-shaped” societies characteristic of Western developed countries, China exhibits a distinctive structural profile—often conceptualized as a “Tu-shaped” (resembling the Chinese character “土”) configuration—marked by a vast and vulnerable lower-middle stratum coexisting with a relatively small upper stratum. This structural reality suggests that status anxiety is not exclusive to the middle class but rather permeates all social strata, with its manifestations and generative mechanisms varying significantly by structural position. By foregrounding this context, the framework offers a theoretical complement to the study of inequality-induced mentalities in non-Western settings shaped by specific structural constraints. The study further considers how several key factors—including individuals’ socioeconomic status, prevailing meritocracy beliefs, and the contemporary media environment—may moderate the proposed relationships. Taken together, this study provides a new theoretical lens for understanding the profound linkages between economic inequality and individual psychological states. The paper concludes by discussing theoretical contributions, acknowledging research limitations, and outlining future directions and governance implications aimed at mitigating status anxiety and fostering a healthier, more resilient societal mentality. References | Related Articles | Metrics