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The developmental neural basis of parafoveal attention encoding in children during natural Chinese reading LI Dongwei, QI Mengdi, TANG Shuning, CHEN Luyao, CUI Xin 2026, 34 (4):  571-582.  doi: 10.3724/SP.J.1042.2026.0571 Abstract ( 119 )   PDF (1276KB) ( 73 )   Peer Review Comments This project proposes a comprehensive developmental cognitive neuroscience framework to investigate how school-age children encode parafoveal information during natural Chinese reading and how such attentional mechanisms shape reading acquisition. Although parafoveal preview and pre-saccadic attention have been widely studied in skilled adult readers, their neural underpinnings in children—especially within non-alphabetic scripts—remain largely unknown. To address this critical gap, the project advances a set of three integrative studies that combine naturalistic eye-tracking paradigms, wearable optically pumped magnetoencephalography (OPM-MEG), and transcranial photobiomodulation (tPBM) to elucidate the dynamic, hierarchical, and developmentally sensitive mechanisms of parafoveal attention. Together, these studies aim to build a multilevel theoretical model of how children’s brains coordinate foveal semantic processing with parafoveal orthographic encoding and how such coordination relates to reading fluency, attentional development, and potential intervention targets. Study 1 focuses on identifying the core neural computations underlying children’s parafoveal attention during natural sentence reading. The central question is whether parafoveal information is encoded at orthographic or semantic levels before the eyes fixate on an upcoming word, and how these pre-saccadic representations relate to children’s eye-movement patterns, including fixation durations and saccadic step-length distributions. Using a gaze-contingent natural reading paradigm, OPM-MEG will record fixation-locked neural dynamics with millisecond precision while children read silently. By aligning MEG data with eye-tracked fixation events, the study will examine oscillatory phase patterns that reflect the depth of parafoveal processing. Multivariate representational similarity analysis (RSA) will be used to determine whether neural activity prior to fixation carries information about upcoming words’ orthographic features or semantic properties. The expected outcome is that younger children will show primarily orthographic-level parafoveal encoding, whereas older children may begin to exhibit emerging semantic-level preview effects. Furthermore, children whose eye movements more closely approximate a Lévy-flight distribution—a signature of efficient exploration—are expected to show deeper pre-saccadic processing and more mature neural oscillatory patterns. These findings will provide foundational evidence of the computational hierarchy through which children allocate attention across foveal and parafoveal regions. Study 2 examines how the neural and behavioral markers identified in Study 1 vary across developmental stages and whether children exhibit age-dependent changes consistent with the proposed multiplexing phase-coding model. This model posits that different linguistic levels (orthographic vs. semantic) can be simultaneously represented in distinct oscillatory phases of the same fixation, enabling a “pipeline” architecture for efficient reading. The study compares younger (7-9 years) and older (10-12 years) children and employs rapid invisible frequency tagging (RIFT) to embed high-frequency flicker signals into parafoveal target words. By computing coherence between the flicker frequency and MEG signals during pre-saccadic windows, the study will quantify the depth and spatial extent of parafoveal attention. Larger coherence differences between valid and invalid previews will indicate deeper encoding. It is expected that with increasing age, children will display (a) larger parafoveal attention breadth, (b) more robust orthographic preview benefits, and (c) emergent semantic-level sensitivity. At the neural level, older children are predicted to show stronger alpha-phase lateralization and more reliable phase-amplitude coupling within frontoparietal networks, indicating maturation of attentional timing mechanisms. Together, these findings will reveal age-related shifts in the hierarchical organization of children’s reading-related attention networks and identify neural signatures marking the transition from “learning to read” to “reading to learn.” Study 3 aims to establish causal evidence for the involvement of the frontal eye field (FEF)—a key node of the frontoparietal attention network—in modulating parafoveal attention during natural reading. Based on the neural markers revealed in Studies 1 and 2, this study applies tPBM targeting the FEF to examine whether enhancing local cortical excitability can increase the depth of parafoveal processing and improve reading fluency. In a randomized, double-blind, sham-controlled design, children will complete natural reading tasks after real or sham stimulation while undergoing eye-tracking and OPM-MEG recordings. The expected outcomes are that real stimulation will (a) strengthen alpha-phase consistency associated with pre-saccadic attention, (b) enhance the coherence between frequency-tagged parafoveal signals and neural activity, and (c) shorten fixation durations or promote more adult-like saccadic patterns. Such results would support the causal role of the FEF in orchestrating the temporal coordination between foveal and parafoveal processing. Additionally, younger children may show greater intervention benefits due to higher neural plasticity, providing insights into sensitive developmental periods for attention-based reading interventions. The theoretical significance of this project lies in proposing and empirically grounding a developmental extension of the multiplexing phase-coding model for reading. By integrating naturalistic tasks, oscillatory dynamics, and developmental comparisons, the project advances a hierarchical-dynamic account of how children’s brains coordinate attention across multiple visual and linguistic layers. This work extends adult reading theories into a developmental framework and clarifies how general attentional maturation interacts with domain-specific literacy acquisition. Practically, the project builds a foundation for brain development-based reading education and opens avenues for safe, non-invasive, and individualized interventions for reading difficulties. By identifying neural markers that jointly reflect moment-to-moment attention allocation and reading ability, the project provides objective indicators for early screening of at-risk children. The incorporation of OPM-MEG and tPBM further lays the groundwork for closed-loop neural modulation systems tailored to children’s neural states. Overall, this research proposal integrates multi-modal neuroscience and developmental psychology to construct a comprehensive scientific basis for enhancing children’s reading outcomes and advancing national goals in brain and cognitive development. References | Related Articles | Metrics

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The role and predictive mechanisms of cognitive function and the central executive network in pain resilience YOU Beibei, GU Huaifei, WEN Hongwei 2026, 34 (4):  583-596.  doi: 10.3724/SP.J.1042.2026.0583 Abstract ( 124 )   PDF (1103KB) ( 71 )   Peer Review Comments Chronic pain profoundly undermines patients’ physical, psychological, and social functioning, highlighting the urgent need for effective coping and management strategies. Psychological resilience plays a pivotal role in buffering the adverse effects of pain, and enhancing resilience has become essential for patients to face biopsychosocial challenges. However, the key factors that promote pain resilience and their underlying mechanisms remain insufficiently understood. Previous studies has demonstrated a positive association between cognitive function and resilience, with interventions targeting cognitive interventions shown to enhance resilience. Building on this work, studies employing neuroimaging and machine learning techniques further revealed that gray matter volume and functional activity within cortical regions of the central executive network (CEN) are associated with pain resilience. Building on these findings, the present research program hypothesizes that cognitive function and the CEN are not only pivotal to the enhancement of pain resilience but also predictive of its longitudinal development. To test this hypothesis, a multicenter, longitudinal study integrating self-report measures and functional magnetic resonance imaging (fMRI) is proposed. This research program comprises three sub-studies. Study 1 adopts a multi-time point longitudinal survey design to examine the relationship between cognitive function and pain resilience among patients with chronic musculoskeletal pain and in healthy controls. Cognitive functioning, pain resilience, and pain-related outcomes are assessed at baseline, 6 months, and 12 months. Cross-lagged panel modeling is used to characterize the directional and temporal associations between cognitive function and pain resilience. Additionally, multi-group structural equation modeling is further applied to determine whether these associations differ between patients and healthy controls. Study 2 employs a multimodal neuroimaging design across two clinical centers. At baseline (Time Point 1), demographic characteristics, cognitive function, pain outcomes (including pain intensity, pain interference, and depressive symptoms), pain resilience and structural and resting-state fMRI data are collected from patients with chronic musculoskeletal pain. Pain resilience is reassessed at 6 months (Time Point 2) and 12 months (Time Point 3). Mediation analyses are conducted to test whether resting-state functional connectivity within the CEN mediates the association between baseline cognitive function and pain resilience at Time Point 3. Internal CEN connectivity (i.e. functional interactions among nodes within the network) serves as the mediator, with seed regions selected based on prior literature. The mediation model is established using data from Center 1 and independently validated in Center 2, enabling robust identification of neural mechanisms underlying cognitive contributions to pain resilience. Study 3 extends the first two studies by developing a multimodal deep learning prediction model using a multicenter prospective framework to predict pain resilience. Guided by the multimodal integration framework, the model incorporates complementary feature domains, including demographic variables, pain outcome indicators, cognitive function measures, and neuroimaging features. Demographic variables enhance clinical applicability and mitigate group-level confounds (e.g., age-related brain changes), thereby improving interpretability of neural predictors. Pain outcomes index clinical symptomatology, cognitive function measures capture psychological context, and neuroimaging features provide a biological foundation. By integrating these multimodal data, the model aims to identify robust, clinically meaningful biomarkers of pain resilience. At baseline (Time Point 1), all domains are assessed. Pain resilience, cognitive function and pain outcomes are reassessed at 6 months (Time Point 2) and 12 months (Time Point 3), with pain resilience additionally evaluated at 18 months (Time Point 4). A Gated Recurrent Unit (GRU) model is used to integrate longitudinal (cognitive function and pain outcomes) and static baseline data (demographics and neuroimaging features) to predict pain resilience at Time Point 4. Training is conducted using data from Center 1, with external validation in Center 2 to ensure robust individualized prediction. Collectively, this research program is expected to clarify the cognitive and neural mechanisms through which cognitive function shapes psychological resilience in individuals with chronic pain. By delineating the cognitive processes and CEN-based neural pathways that support pain resilience, the findings are positioned to advance theoretical models of adaptive coping in chronic pain and inform the development of targeted, personalized interventions for chronic pain management. References | Related Articles | Metrics

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Elucidating the neural mechanisms of eating disorders through the lens of the reward-inhibition dual-system model CHEN Ximei, LI Wei, CHEN Hong 2026, 34 (4):  597-607.  doi: 10.3724/SP.J.1042.2026.0597 Abstract ( 106 )   PDF (1472KB) ( 137 )   Peer Review Comments Over the past three decades, the number of eating disorders in China has increased sharply, and the growth rate ranks among the highest in the world, and has now emerged as the country with the highest number of deaths due to eating disorders globally. In particular, the rapid economic development, widespread dissemination of social media, and suboptimal intervention efficacy have collectively exacerbated eating disorders in China. Effectively preventing eating disorders has thus become an urgent and critical challenge facing the nation. Using the reward-inhibition dual-system interaction as a breakthrough, this project follows a progressive research framework (i.e., structural characteristics, processing mechanisms, and robust predictors) to investigate the crucial neural mechanisms of binge-type eating disorders. The research consists of three studies. Firstly, the novel multi-feature morphometric similarity network technique will be employed to reveal the role of underlying structural covariance between reward and inhibitory control networks in binge-type eating disorders. Secondly, based on the bipartite interaction model of dietary decision making, we will use the revised food reward response inhibition paradigms to examine how the brain’s reward (bottom-up) and inhibitory control (top-down) systems dynamically interact to contribute to binge-type eating disorders. The second study will investigate the impact of food reward cues on response inhibition in individuals with binge-type eating disorders by using the food reward go/no-go and food reward stop signal tasks, combined with multidimensional techniques including brain activation analysis, psychophysiological interaction analysis, and parametric empirical Bayesian dynamic causal modeling. The study focuses on characterizing the information flow properties between dual-system regions under conflict conditions (food reward no-go and food reward stop conditions), aiming to identify specific markers in the progression from binge eating symptoms to binge eating disorder (across healthy control, binge eater, and binge eating disorder groups). Finally, the prospective cohort study will be conducted to further identify the key neuromarkers that can effectively predict the onset and development of binge-type eating disorders. This project aims to construct a neural staging model from the perspective of dual-system interaction, which will deepen our understanding of the full dynamic range of neuromarkers from non-eating disorder to eating disorder conditions. Investigating the occurrence and developmental patterns and mechanisms of binge-type eating disorders is of significant importance for the prevention and intervention of such disorders. In terms of theoretical value, this study examines the mechanisms underlying binge-type eating disorders from the perspective of the interaction between reward and inhibitory control systems. Firstly, it advances from single-system research to the simultaneous investigation of dual systems. By revealing the spatial information flow from the lateral prefrontal cortex to subcortical reward regions in individuals with binge-type eating disorders, it enriches and deepens the dual interaction model of dietary decision-making. Secondly, from a developmental perspective, it provides partial empirical support for the triple interaction model of binge eating disorder, demonstrating that adults with binge eating disorder exhibit core neural features consistent with children and adolescents: dysregulated structural covariance and functional interaction between the brain's reward and inhibitory control systems. Thirdly, by tracing the progression from health to symptom emergence and ultimately to binge-type eating disorders, it explores specific markers in the development of early symptoms into eating disorders, aiming to achieve a more comprehensive understanding of the mechanisms underlying binge-type eating disorders and to provide evidence for the preliminary establishment of a neural staging model. In terms of practical value, this study explores the interactive mechanisms of key neural circuits, which will provide novel insights into the precise identification, early prevention and targeted intervention of binge-type eating disorders. It holds substantial practical significance for reducing problematic eating behaviors, alleviating eating disorders, and promoting physical and mental health. References | Related Articles | Metrics

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Pay inversion and organizational socialization: An integrated multi-theoretical framework WANG Haijiang, ZOU Haoyun, HE Yuheng 2026, 34 (4):  608-625.  doi: 10.3724/SP.J.1042.2026.0608 Abstract ( 125 )   PDF (657KB) ( 163 )   Peer Review Comments In recent years, a special form of pay dispersion between newcomers and incumbents, known as “pay inversion,” has attracted increasing attention. Since the pay system is influenced by the joint effort of market, position, and person factors, newly hired employees may receive higher pay than incumbent employees in the same position (i.e., horizontal pay inversion), or even than their direct supervisors (i.e., vertical pay inversion). Such substantial financial investment in recruiting new employees is likely to shape their organizational socialization process. Traditional socialization research emphasizes that newcomer adjustment results from the interaction between organizational contexts and individual behaviors. Incorporating pay inversion into the organizational socialization framework creates a novel context: organizations expect higher pay to retain newcomers and motivate them to adjust seamlessly; yet incumbents receive comparatively lower pay, which inevitably affects their work experiences and their interactions with newcomers—interactions that are critical to successful socialization. Consequently, in the context of pay inversion, established socialization mechanisms may undergo alteration. To comprehensively investigate the effects of pay inversion on organizational socialization, this study draws on multiple theories (i.e., social identity theory, social comparison theory, social information processing theory, and psychological contract theory) to develop a multi-level, multi-actor interactive framework encompassing four research foci. From the newcomer perspective, this study examines the double-edged effects of pay inversion on newcomers’ proactive socialization behaviors, as well as the moderating role of talent identity (Propositions 1 to 6). From the incumbent perspective, this study differentiates between horizontal pay inversion between newcomers and mentors and vertical pay inversion between star newcomers and leaders. On the one hand, this study investigates the effects of horizontal pay inversion on mentors’ reactions and newcomer learning, incorporating distributive justice and newcomer traits as moderators (Propositions 7 to 11). On the other hand, this study explores the mechanisms through which vertical pay inversion influences leader empowerment and star newcomers’ creativity, emphasizing the moderating roles of leader attribution and organizational climate (Propositions 12 to 15). From the team perspective, this study compares the differentiated responses of newcomers and incumbents to pay inversion and their implications for key organizational outcomes, and further identifies the contingent effects of pay dispersion bases and pay communication in the context of digital intelligence (Propositions 16 to 19). This study makes three primary theoretical contributions. First, whereas existing organizational socialization literature typically treats pay as an important outcome of adjustment, it has largely overlooked its predictive role in the socialization process. By incorporating pay structure into the antecedent framework of socialization and conceptualizing pay inversion as a contextual variable that shapes socialization dynamics, this study extends the theoretical boundaries of organizational socialization research. Second, despite the growing prevalence of pay inversion, scholarly attention to this phenomenon remains limited. By focusing on inverted pay dispersion between newcomers and incumbents and examining its effects on newcomers, incumbents, and their interactions, this study enriches pay dispersion research from a socialization perspective. Third, pay inversion reflects organizations’ disproportionate investments in newcomers versus incumbents, posing significant challenges for talent management. By uncovering talent management conflicts between newcomers and incumbents, as well as the corresponding responses under pay inversion, this study deepens theoretical understanding of organizational talent management. Accordingly, this study offers valuable insights for managerial practice in newcomer development, pay system optimization, and talent management. Moreover, aligned with the strategic human resource management emphasis on coherent combinations of human resource policies and practices, this paper calls for future research to examine human resource policies that are congruent with pay inversion. In sum, by integrating the perspectives of newcomers, incumbents, and teams, this paper develops a process model that theorizes how pay inversion shapes organizational socialization outcomes. It offers theoretical and practical insights into organizational socialization, compensation design, and talent management. References | Related Articles | Metrics

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The differential perception of leaders' response to employee-GenAI advice: A multi-level study based on social comparison view HAN Yi, MA Zhaoyi, ZONG Shuwei 2026, 34 (4):  626-646.  doi: 10.3724/SP.J.1042.2026.0626 Abstract ( 127 )   PDF (729KB) ( 126 )   Peer Review Comments Generative artificial intelligence (GenAI) is deeply integrating into organizational decision-making. This trend means that leaders are now presented with advice originating not only from human employees but also from GenAI and even human-AI collaborative teams. This transformation raises a core research question: In the decision-making process, how do leaders compare and ultimately adopt advice from employees, GenAI, and collaborative human-GenAI teams? What are the underlying cognitive, affective, and behavioral reaction mechanisms? Existing research on this question remains insufficient. Grounded in social comparison theory, this study constructs a multi-level theoretical model. It aims to thoroughly unveil the mechanisms of leaders' differential perceptions regarding employee-GenAI advice, thereby filling a critical theoretical gap in this field and providing guidance for organizations to optimize human-AI collaborative decision-making. While traditional theory has been confined to interpersonal comparisons, this study extends its application to the new dimension of “human-GenAI” comparison. We construct a three-dimensional framework encompassing social dynamic comparison, performance-reward comparison, and agency capability comparison. Based on the theoretical framework, we have designed five interlocking sub-studies that form a cross-level integrated model. This model spans from individual cognitive and affective responses to team-level risk attribution, and further extends to organizational intervention strategies. Sub-Study 1: Advice quality comparison and the affective mediation pathway. This sub-study focuses on how leaders' comparison of advice quality between employees and GenAI influences their feeling of “appreciation,” which in turn drives their adoption intention. It introduces social comparison orientation as a critical boundary condition, revealing that leaders with high social comparison orientation may prefer high-quality GenAI advice to circumvent interpersonal threats. Sub-Study 2: Dual pathways of advice source characteristics and decision effectiveness. Moving beyond generic quality, this sub-study delves into the objective characteristics of the advice source: explainability, accuracy, and affordance. It posits that these characteristics differentially trigger leaders' affective responses (appreciation vs. aversion), which subsequently mediate their decision to adopt or reject advice and ultimately impact decision effectiveness. The model also introduces the perceived relative superiority of the advice source as a moderator, acknowledging that leaders' subjective synthesis of these characteristics can amplify or weaken their reactions. Sub-Study 3: Contextual interaction effects of advice content and strategy. This sub-study investigates the interaction between the content of the advice (task-work vs. interpersonal work) and the strategy of its delivery (direct vs. indirect voice). The model proposes that the effectiveness of advice from different sources varies significantly by task type, while revealing the critical mediating roles played by leader identity threat and identity recognition. This framework systematically clarifies the specific contexts in which employee or GenAI advice proves more effective, and how communication strategies can moderate this dynamic process. Sub-Study 4: Team advice risk and responsibility attribution mechanism. Scaling the investigation to the team level, this sub-study analyzes the risks associated with three team configurations: employee teams, GenAI teams, and employee-GenAI collaborative teams. Based on attribution theory, we propose three core psychological mechanisms—employee team responsibility attribution, GenAI team responsibility attribution, and shared responsibility attribution—that connect team risks with leaders' decisions to adopt or reject advice. Particularly, the proposition that “shared responsibility attribution” leads to leaders rejecting all team advice profoundly reveals the “responsibility ambiguity trap” in human-AI collaboration. Sub-Study 5: Identification of advice barriers and validation of intervention strategies. The final sub-study identifies the psychological and functional barriers that hinder human-AI collaborative advice at the micro-individual level, constructing an influential pathway model of “barriers - motivation - leader response.” Furthermore, by empirically testing the effectiveness of intervention strategies such as training and incentives, this research provides both a theoretical foundation and practical pathways for organizations to overcome these barriers and enhance the quality of human-AI collaborative advice. In summary, the primary theoretical contributions of this research are fourfold: First, it extends the application boundaries of social comparison theory by constructing a multidimensional framework—encompassing social dynamic comparison, performance-reward comparison, and agency capability comparison—tailored to human-AI interaction scenarios. Second, it develops a cross-level integrated model spanning from individual to team levels, systematically revealing the multi-layered mechanisms underlying leaders' advice response. Third, it systematically identifies the dual-effect of GenAI advice adoption and empirically tests intervention strategies, offering a critical transition from theoretical exposition to practical guidance. Fourth, it fosters deep interdisciplinary integration across management, psychology, and artificial intelligence studies, providing a referential variable system and modeling paradigm for subsequent cross-disciplinary research. References | Related Articles | Metrics

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Exploring the behavioral intention-outcome inconsistency effect in consumers’ pro-environmental behavior ZHONG Ke, WANG Zhenbang, YANG Linyun, LI Peimei 2026, 34 (4):  647-665.  doi: 10.3724/SP.J.1042.2026.0647 Abstract ( 117 )   PDF (810KB) ( 88 )   Peer Review Comments Promoting consumers’ pro-environmental behavior has become a prominent research topic in recent years. Prior studies have largely concentrated on the antecedents and interventions that shape pro-environmental behavioral intentions, while paying limited attention to the possibility that individuals’ actual behavioral outcomes may deviate from their intentions. Building on this gap, the present research proposes Behavioral Intention-Outcome Inconsistency Effects in consumers’ pro-environmental behavior and develops a series of studies to explain when and why subjective intentions diverge from objective outcomes. Specifically, the study approaches this issue from the perspective of motivational conflicts in social dilemmas, examining three motivational dimensions: Efficiency, Greed and Fairness considerations, which are based on the GEF theory. It further elaborates three corresponding research propositions: the green efficacy illusion effect, the novelty-evoked rejection effect, and the bystander misattribution effect, and proposes targeted interventions based on these mechanisms. Study 1 focuses on environmental efficiency considerations, examining how consumers evaluate the extent to which pro-environmental behaviors or products generate actual environmental outcomes. Although individuals may accurately assess the environmental efficacy of a single pro-environmental option in isolation, the marketplace often offers multiple substitutable green alternatives. When processing such complex choice sets, consumers are prone to judgment biases that lead them to overestimate whether their decisions have achieved meaningful environmental outcomes. This misperception gives rise to the green efficacy illusion effect, whereby consumers mistakenly believe that their chosen behaviors or products have generated substantial environmental benefits, thereby creating an intention-outcome inconsistency. Study 2 focuses on greed considerations. Within this dimension, two opposing biases may arise: consumers may underestimate the personal benefits of pro-environmental products, or they may overestimate or misjudge their potential personal costs. The present research focuses on the latter bias. Specifically, green products based on new technologies or novel concepts may appear unfamiliar to consumers, triggering rejection driven by prior experiences and affective intuitions. Even when such products convey clear and credible quality signals and consumers acknowledge their environmental efficacy, they may still be irrationally rejected due to experiential or emotional heuristics. This bias gives rise to the novelty-evoked rejection effect, resulting in a behavioral intention-outcome inconsistency between consumers’ pro-environmental intentions and the actual outcomes of their choice. Study 3 focuses on the fairness considerations. In pro-environmental contexts, perceptions of fairness primarily stem from the equitable allocation of responsibility and the fair distribution of benefits. Focusing on responsibility attribution, this study argues that because pro-environmental behaviors often entail personal costs, consumers may exhibit self-serving bias and erroneously shift responsibility onto others, unjustly blaming bystanders who bear little or no responsibility. This pattern reflects the bystander misattribution effect, ultimately generating a behavioral intention-outcome inconsistency in pro-environmental behavior. This research advances the literature on consumer pro-environmental behavior by shifting attention to the divergence between subjective intentions and objective behavioral outcomes. The proposed behavioral intention-outcome inconsistency effect offers a new conceptual lens for understanding this divergence. From this perspective, not only the effects identified in the present research, but also a wide range of related phenomena, warrant further investigation, opening promising avenues for future inquiry. Moreover, this study adopts an integrative theoretical approach rather than relying on a single framework. Insights from social dilemma theory highlight the tension between individual and collective interests. Cognitive bias theory explains systematic errors in judgment and decision making. Together, these perspectives form a unified explanatory model of behavioral intention-outcome inconsistency. This framework clarifies the psychological mechanisms underlying the gap between pro-environmental intentions and actual environmental impact and provides a more comprehensive account of inconsistency in pro-environmental behavior. Finally in terms of practical application the study translates its theoretical insights into actionable managerial strategies. By pinpointing the core psychological causes of behavioral intention-outcome inconsistency in green consumption, this research enables practitioners to design targeted, multifaceted interventions that address individual-level cognitive barriers, thereby enhancing the effectiveness of sustainability initiatives and bringing green consumption closer to its intended environmental goals. References | Related Articles | Metrics

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Dual characteristics of attentional bias in depression: A three-level meta-analysis REN Weicong, FAN Junlong, ZHANG Zhijie 2026, 34 (4):  666-686.  doi: 10.3724/SP.J.1042.2026.0666 Abstract ( 172 )   PDF (4119KB) ( 115 )   Peer Review Comments Background: Depression is a prevalent and debilitating mental disorder characterized by persistent low mood and diminished interest or pleasure. Cognitive theories posit that attentional bias—the preferential allocation of attention toward mood-congruent information—plays a central role in the onset and maintenance of depressive symptoms. While substantial evidence supports the existence of negative attentional bias in depression, the magnitude, stability, and contextual boundary conditions of this effect remain unclear. Moreover, comparatively limited attention has been devoted to how depressed individuals process positive emotional information. Previous meta-analyses have provided valuable insights into attentional processes in depression but have typically focused on negative bias alone and employed models that cannot adequately account for dependency among effect sizes. Consequently, estimates of heterogeneity and moderator effects have often been imprecise. Addressing these methodological and conceptual limitations, the present study represents the first comprehensive three-level meta-analysis to synthesize evidence on both negative and positive attentional biases in depression. By modeling within- and between-study variance simultaneously, this work offers a more rigorous and integrated evaluation of attentional asymmetries, providing new insights into the dual mechanisms of cognitive-affective processing in depression. Aims: This study aimed to (1) quantify the magnitude and consistency of both negative and positive attentional biases among individuals with elevated depressive symptoms, thereby extending the traditional focus on negative bias alone; (2) identify methodological and demographic moderators—such as task paradigm, stimulus type, emotional valence, age, and sample type—that account for variability in effect sizes; (3) refine the conceptualization of attentional bias in depression by framing it as a bidirectional, context-sensitive construct; and (4) integrate the present findings with prior evidence to advance future theoretical models and empirical research. Methods A systematic search was conducted across seven major English and Chinese databases (EBSCO, Web of Science, ScienceDirect, PubMed, CNKI, VIP, and Wanfang) for peer-reviewed studies published between January 1, 2000, and July 8, 2025. Following rigorous screening and double coding, 51 studies examining negative attentional bias (yielding 91 effect sizes) and 33 studies examining positive attentional bias (yielding 56 effect sizes) were included. A three-level random-effects model, implemented in R using the metafor package, was employed to account for sampling variance, within-study dependence, and between-study heterogeneity. Methodological rigor was ensured through sensitivity analyses, outlier diagnostics, and formal assessments of publication bias. Moderator analyses examined the influence of task paradigm, stimulus type, emotional valence, age, and sample characteristics on variability in effect sizes. Results: The meta-analytic findings revealed a significant, moderate negative attentional bias among depressed individuals compared with healthy controls (Hedges’ g = 0.48, 95% CI [0.35, 0.61], p < .001), indicating greater attentional capture by negative or threat-related stimuli. Concurrently, a significant absence of positive attentional bias was observed (Hedges’ g = -0.30, 95% CI [-0.44, -0.18], p < .001), suggesting reduced attentional engagement with rewarding or pleasant stimuli. Moderator analyses demonstrated that task paradigm significantly influenced the magnitude of both negative (F(4, 84) = 4.49, p = .002) and positive (F(3, 50) = 8.74, p < .001) biases. Specifically, the dot-probe paradigm yielded larger negative bias effects than the emotional Stroop task, whereas the free-viewing eye-tracking paradigm showed greater sensitivity to detecting the absence of positive bias compared with the spatial cueing task. Stimulus type also emerged as a significant moderator for positive bias (F(1, 54) = 8.22, p = .006), with pictorial stimuli producing larger effects than verbal stimuli—a pattern approaching marginal significance for negative bias (p = .057). In contrast, age, sample type (clinical vs. subclinical), and stimulus valence did not significantly moderate either form of bias. Conclusions and Implications: This meta-analysis suggests a dual pattern of attentional bias in depression, characterized by heightened attention toward negative information and attenuated engagement with positive stimuli. Such an asymmetrical pattern may reflect an underlying imbalance between enhanced sensitivity to threat and reduced responsiveness to reward, providing a more differentiated account of attentional processing in depression. Methodologically, the application of a three-level hierarchical meta-analytic framework represents a substantial advance over previous syntheses, allowing a more precise estimation of dependent data structures and moderator effects. The identification of task paradigm and stimulus type as major moderators highlights the importance of methodological design in interpreting attentional bias findings and offers guidance for future experimental research. From a theoretical standpoint, these findings help redefine attentional bias as a bidirectional, context-dependent process that bridges cognitive and motivational perspectives. Clinically, the results provide preliminary support for dual-track interventions—those aimed not only at attenuating negative attentional capture but also at enhancing engagement with positive or rewarding stimuli. Nonetheless, given that most included studies employed cross-sectional designs, causal interpretations should remain cautious. Future longitudinal, multimodal, and neurocognitive studies are essential to clarify the temporal and neural mechanisms underlying these dual biases in depression. References | Related Articles | Metrics

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Holding balance brings harmony: A three-level meta-analysis of the relationship between Zhongyong thinking and mental health LYU Yanqi, WEI Qingwang 2026, 34 (4):  687-709.  doi: 10.3724/SP.J.1042.2026.0687 Abstract ( 180 )   PDF (1303KB) ( 259 )   Peer Review Comments Drawing on the Zhongyong practical thinking framework and the dual-factor model of mental health, this study employed a three-level meta-analytic approach to examine the relationship between Zhongyong thinking and mental health, as well as its moderators. Through comprehensive searches of major Chinese and international databases up to April 30, 2025, the final dataset included 56 studies (60 samples, 139 effect sizes, N = 35,410) addressing positive mental health, and 43 studies (45 samples, 136 effect sizes, N = 35,596) concerning negative mental health. Across studies, Zhongyong thinking demonstrated a moderate and stable positive association with positive mental health (r = 0.24), and a moderate negative association with negative mental health (r = -0.21). These findings confirm that Zhongyong thinking functions as a reliable cultural–cognitive resource linked to both enhanced well-being and reduced psychological distress. A closer inspection of mental health indicator types provides a more nuanced understanding of the psychological domains most strongly shaped by Zhongyong thinking. Within positive mental health, the associations with psychological resilience, job satisfaction, and work-related well-being were significantly stronger than those with general life satisfaction, suggesting that Zhongyong thinking may be particularly consequential in contexts requiring dynamic adjustment, conflict integration, and role coordination. In contrast, Zhongyong thinking shows weaker associations with simple or hedonic indicators such as life satisfaction, and its associations with happiness, peace of mind, and positive affect are likewise indistinguishable from this benchmark, suggesting that these outcomes do not activate the context-sensitive balancing processes characteristic of Zhongyong thinking. For negative mental health, no significant differences were observed across indicators (e.g., depression, anxiety), indicating consistent protective effects against psychological distress. One of the most consequential findings concerns measurement heterogeneity. The strength of correlations varied systematically across Zhongyong thinking scales. Measures grounded in beliefs and values or expressive tendencies—such as the Zhongyong Belief–Value Scale and the Zhongyong Opinion Expression Scale—yielded effect sizes that were significantly stronger and more consistent. In contrast, the Zhongyong Practical Self-Evaluation Scale—especially its deliberation and after-event reflection dimensions—showed weaker correlations, likely because the scale does not capture the dynamic, context-dependent “action-self,” and because these subdimensions may reflect early, less mature forms of Zhongyong practice that temporarily resemble rumination or suppression. Future revisions of Zhongyong measures should take care to exclude these factors. Moderator analyses further revealed that key demographic variables (e.g., age, gender, education) and regional differences (Mainland China vs. Taiwan) did not significantly moderate the relationships, underscoring the universal applicability of Zhongyong within Chinese cultural contexts. Publication year significantly moderated the Zhongyong–negative mental health relationship, with stronger correlations in recent studies. Publication bias tests showed mild funnel plot asymmetry—more pronounced for negative mental health—but neither publication status nor sensitivity analyses suggested meaningful inflation of effect sizes. The inclusion of numerous unpublished theses contributed to reducing classical file-drawer bias. Thus, the observed effects appear substantively robust. The findings of this meta-analysis advance current knowledge by clarifying why Zhongyong thinking exhibits consistent yet only moderate associations with mental health. As discussed in prior theory and reinforced by the present evidence, Zhongyong thinking is not a unidirectional cognitive trait that should yield uniformly strong correlations with any single psychological outcome. Instead, it is an inherently dialectical, bidirectional, and context-adaptive form of reasoning, marked by the capacity to balance and coordinate different perspectives in a manner consistent with the principle of “Holding Balance Brings Harmony.” (“执中致和”). Such a cognitive style is not expected to maximize either hedonic affect or simple satisfaction; rather, it moderates tensions, coordinates competing demands, and promotes harmony under conditions of contradiction or conflict. Therefore, a moderate-level correlation is not a limitation but a reflection of the construct’s inherent conceptual structure. In conclusion, this meta-analysis provides the most comprehensive synthesis to date on the relationship between Zhongyong thinking and mental health. By applying a rigorous three-level framework, comparing major measurement approaches, and integrating findings with the Zhongyong practical thinking model, the study clarifies the robustness, scope, and conditions under which Zhongyong thinking contributes to psychological wellbeing. These results highlight how a culturally grounded, balance-oriented mode of reasoning supports adaptive functioning in complex contexts. Together, the findings establish clearer empirical benchmarks and offer a systematic foundation for future research on the psychological mechanisms and applied value of Zhongyong thinking. References | Related Articles | Metrics

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Dorsal-ventral pathway interactions in visual object representation GAO Fei, CAI Houde 2026, 34 (4):  710-725.  doi: 10.3724/SP.J.1042.2026.0710 Abstract ( 107 )   PDF (657KB) ( 105 )   Peer Review Comments Invariant and adaptive visual object processing represent two core mechanisms through which the brain's visual system encodes visual objects. The former refers to the visual system achieving object recognition and categorical classification by representing object features invariantly, despite changes in viewing conditions (such as viewpoint or size). The latter involves the dynamic selection and temporary maintenance of object information by the visual system to achieve object representations adapted to an individual's goals and tasks. From the perspective of dorsal-ventral pathway interactions, this article elaborates on the respective information integration mechanisms underlying invariant and adaptive processing, and summarizes their functional relationships (e.g., static recognition vs. dynamic modulation; feature-driven vs. task-driven). Specifically, the paper first discusses the functional segregation and integration within the dorsal-ventral pathways during invariant visual object processing. It posits that during object feature recognition, the ventral pathway alone is insufficient for representing the global shape crucial for invariant processing. Instead, global shape information represented in the posterior intraparietal sulcus (pIPS) converges with local feature information represented by the ventral pathway in the lateral occipital complex (LOC), thereby supporting invariant visual object processing. Subsequently, the article examines the functional integration mechanisms during adaptive visual object processing. It proposes that the posterior parietal cortex (PPC) acts as a dynamic platform for integrating object information, flexibly selecting task-relevant visual object information from the ventral pathway and temporarily maintaining it within visual working memory (VWM) - supported by the superior intraparietal sulcus (sIPS) - for cognitive operations, thus enabling goal-directed adaptive visual information processing. Accordingly, this article highlights functional interactions between the dorsal and ventral pathways during visual object representation. Invariant visual object representation constitutes a primarily feature-driven (bottom-up) functional integration, providing a stable, veridical, and detailed representation of the visual environment. In contrast, adaptive visual object representation constitutes a primarily task-driven (top-down) functional integration, enabling flexible and effective interaction with the external world. Furthermore, regarding the logical sequence of cognitive processing, adaptive information processing in the dorsal pathway - mediated by attention and VWM - is proposed to build upon the completion of invariant representations in the ventral pathway. Conversely, the dorsal pathway modulates and reshapes VWM-related object information within the ventral occipitotemporal cortex (VOTC) to facilitate cross-pathway functional integration. The mechanisms of dorsal-ventral pathway interaction in visual object processing elucidated herein not only refine our understanding of the neural mechanisms underlying object cognition but also hold significant value for artificial intelligence modeling of object recognition and clinical research on visual perceptual disorders. Future research should focus on development and refinement in five key areas: First, regarding the mechanisms of attention's influence on global shape representation, it is necessary to investigate the functional nature of global shape processing in the dorsal pathway from both bottom-up and top-down attentional perspectives. Second, concerning the potential influence of object familiarity on the representation of global shape and local features in the dorsal-ventral pathways, research should integrate findings from infant development, computational modeling (e.g., DNNs), and neuropsychological studies of brain lesions to explore how changes in object familiarity through learning and training affect the processing and integration of global and local features. Third, regarding how VWM resists interference to maintain processing of goal-relevant stimuli, studies are needed to examine how the dorsal pathway (PPC) integrates information from the prefrontal cortex (PFC) and the ventral pathway within VWM to prioritize task-relevant target information while filtering out irrelevant distractions. Fourth, concerning the impact of endogenous memory information on adaptive visual object representation, attention should be directed to the relationship between the buffering mechanism for multimodal spatiotemporal information input in the angular gyrus (AnG) and the information selection/manipulation functions of the lateral (lIPS) and superior (sIPS) intraparietal sulcus, to elucidate the PPC's mechanisms for adaptive visual representation of internally and externally generated information. Finally, regarding the dynamic bidirectional interactions between the dorsal and ventral pathways during ontogeny - specifically, the driving and supportive role of the earlier-developing dorsal pathway on the later-developing ventral pathway in infancy, and the subsequent supportive/driving influence of the maturing ventral pathway on dorsal pathway development in childhood - research is needed to examine how these directionally distinct interactions during infancy and childhood influence the functional integration of the dorsal-ventral pathways in invariant and adaptive visual object processing. In summary, investigating these aspects is crucial for constructing a comprehensive model of dorsal-ventral pathway interactions in object representation and holds significant prospective value for guiding future research. References | Related Articles | Metrics

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Children’s reputation management in prosocial behavior and its psychological mechanisms SHEN Yue, XIN Cong, ZHENG Yuanxia, LIU Guoxiong 2026, 34 (4):  726-741.  doi: 10.3724/SP.J.1042.2026.0726 Abstract ( 140 )   PDF (609KB) ( 151 )   Peer Review Comments Reputation management, the strategic behavior aimed at controlling others' evaluations to cultivate a desired personal reputation, represents a sophisticated dimension of children's social development. Although early prosocial actions are typically driven by intrinsic motives such as empathy or norm compliance, recent evidence demonstrates that children gradually acquire the ability to act prosocially in order to cultivate a positive reputation. This review systematically examines the expression and development of reputation management across diverse prosocial behaviors, drawing a key distinction between actions that seek a positive reputation as an end in itself and those that use it as a strategic tool. By integrating the cognitive, motivational, and neurophysiological foundations of these processes, we propose a novel integrative model of the underlying mechanisms. Moving beyond a generalized view of prosociality, this review introduces a typological framework for understanding reputation management based on the functional role of reputation. We categorize children's strategic prosocial behaviors into two types: prosocial behavior with reputation as a goal, where the primary aim is to acquire or maintain a positive reputation for its own sake and the delayed social rewards it brings; and prosocial behavior with reputation as a strategy, where a positive reputation is instrumentally used as a means to facilitate immediate or future cooperation and reciprocity. This distinction is illustrated through a detailed analysis of behaviors such as sharing and helping (with reputation as the goal) and cooperation (with reputation as a tool). A central contribution of this review is its integrative analysis of psychological mechanisms, culminating in a comprehensive cognitive-motivational-neural model of reputation management. This model explains how the capacity for reputation management develops. At the cognitive level, four core abilities form the foundation: theory of mind, for inferring others’ values and beliefs; norm understanding, for identifying which behaviors are socially valued and reputation-enhancing; delay of gratification, for sacrificing immediate gains to protect long-term reputational interests; and underlying all of these, working memory—especially social working memory—which provides the computational platform for processing complex social information. Cognitive capacity alone is insufficient without social motivation. From a motivational perspective, the review outlines a developmental framework. Indirect reciprocity provides children with the foundational understanding that a positive reputation can yield future benefits from third-party observers. The desire for social affiliation, which evolves from a simple preference for playmates in early childhood to a complex need for peer acceptance and recognition in middle childhood, heightens children’s concern for how they are evaluated by others. In addition, positive reputation itself serves as a powerful social reward, motivating children to achieve and maintain this desirable state. A further theoretical advance is the integration of neurophysiological findings into the model. Building on adult fMRI studies, this review identifies the medial prefrontal cortex (which supports meta-representations of one's social standing) and the striatum (which processes the value of social rewards and punishments) as the core neural substrates of reputation management. Other brain regions involved in social perception, reward processing, and cognitive control are also likely engaged. This model illustrates how these three layers—motivation, cognition, and neural function—interact dynamically. Social motives drive the engagement of cognitive resources, which are implemented by specific neural circuits, to produce strategic reputational behavior. Feedback from social interactions, in turn, refines cognitive schemas and modulates future motivations. Finally, this review outlines key directions for future research, including: investigating the early emergence of reputation management; studying its role in diverse prosocial behaviors (e.g., prosocial lying, prosocial risk-taking); extending work to more ecologically valid, group, and cross-cultural contexts; elucidating its neurobiological foundations in children; and applying these insights in family and educational settings. In summary, this review offers a comprehensive, multi-level theoretical model of children’s reputation management within prosocial behavior. By differentiating behavioral forms, identifying core mechanisms, and integrating cognitive, motivational, and neural perspectives, it advances the conceptualization of strategic prosociality and sets a clear agenda for future research. References | Related Articles | Metrics

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The driving mechanisms of older workers’ knowledge seeking from younger coworkers ZHAO Hongdan, MA Yunshuo 2026, 34 (4):  742-760.  doi: 10.3724/SP.J.1042.2026.0742 Abstract ( 105 )   PDF (894KB) ( 95 )   Peer Review Comments As population aging intensifies and younger labor becomes increasingly scarce, how to fully develop and utilize the resources represented by older workers has become a pressing issue that organizations urgently need to address. Older workers’ knowledge seeking from younger coworkers, as an important means through which older workers achieve successful aging at work, has gradually attracted scholarly attention. However, the literature on older workers’ knowledge seeking from younger coworkers remains unclear, and systematic examination and deep explication of its antecedents and driving mechanisms are still relatively insufficient. To address these gaps, this study, based on a review of the concept and antecedents of older workers’ knowledge seeking from younger coworkers, proposes an integrative theoretical framework. Firstly, based on a review of the existing literature, this study conceptualizes older workers’ knowledge seeking from younger coworkers. Older workers’ knowledge seeking from younger coworkers is a key link in intergenerational knowledge transfer, emphasizing generational differences and individual voluntariness. Accordingly, this study defines it as the behavior whereby older workers intentionally and proactively acquire younger colleagues’ professional knowledge, experience, insights, and opinions, and learn from those younger colleagues. In addition, this study analyzes similarities and differences between older workers’ knowledge seeking from younger coworkers and other related concepts across six dimensions, namely behavioral goals, behavioral direction, actor relationships, behavioral nature, types of knowledge, and outcome orientation, thereby further clarifying its unique research value. Second, from the theoretical perspectives of motivation, relationships, cognition and identity, and resources, this study systematically identifies key antecedent variables influencing older workers’ knowledge seeking from younger coworkers, covering multi-level factors including individual characteristics, interpersonal interactions, and team and organizational contexts. On this basis, by integrating the theory of planned behavior with the aging-related characteristics of older workers’ knowledge seeking from younger coworkers, this study constructs a systematic driving model that reveals, across the three dimensions of seeking attitudes, subjective norms, and behavioral control, the formation and transformation mechanisms of older workers’ intentions to seek knowledge and their actual seeking behaviors. Specifically, nonessentialist beliefs about aging, future time perspective, expected gains, and perceived usefulness function as components of seeking attitudes; age-inclusive human resource practices, mature-age human resource practices, age-inclusive leadership, and an age-diverse climate function as components of subjective norms; and late-career management self-efficacy, late-career developmental effort, intergenerational trust, and the quality of intergenerational interactions function as components of behavioral control. Together, these factors can strengthen older workers’ intentions to seek knowledge and thereby promote their knowledge seeking behaviors. Furthermore, older workers’ self-monitoring can weaken the transformation of knowledge seeking intentions into behavior, whereas a positive organizational learning climate can strengthen this transformation process. Although this study systematically examines the antecedents and driving mechanisms of older workers’ knowledge seeking from younger coworkers, related research remains at an early stage. Future research can focus on the role of older workers as actors in intergenerational knowledge seeking behaviors and further deepen the following directions: first, continually enrich the driving factors and mechanisms by introducing new antecedents such as STAARA (smart technology, artificial intelligence, automation, robotics, and algorithms) technology and knowledge characteristics; second, construct governance frameworks that address both pre- and post-behavioral phases, including mechanisms that drive the emergence of behaviors and mechanisms that mitigate adverse effects; third, adopt more advanced research designs, such as the experience sampling method (ESM) and longitudinal approaches, to reveal dynamic processes; fourth, conduct localized studies to explore how Chinese contextual factors such as face concerns, traditionality, and collectivist culture affect older workers’ knowledge seeking from younger coworkers; fifth, broaden theoretical perspectives by integrating aging-context features and applying more fitting theories, such as selection, optimization, and compensation theory and socioemotional selectivity theory, to further deepen understanding of older workers’ knowledge-seeking behavior. 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