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ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

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    Academic Papers of the 27th Annual Meeting of the China Association for Science and Technology
    Invasive brain-computer interface applications: Decoding and modulation of memory
    TIAN Liuqing, CHEN Yanlin, LIN Meiling, CHEN Dong, WANG Liang
    2026, 34 (2):  191-209.  doi: 10.3724/SP.J.1042.2026.0191
    Abstract ( 262 )   PDF (814KB) ( 308 )   Peer Review Comments
    Brain-Computer Interface (BCI) technology offers a transformative approach to establishing direct communication pathways between the brain and external devices, heralding a new era in neuroscience and clinical neurology. While significant progress has been made in applying BCI to restore motor function in paralyzed individuals, research is rapidly advancing into the more complex domain of decoding and modulating higher cognitive functions such as memory and emotion. We provides a comprehensive review of invasive BCI research focused on episodic memory, with particular emphasis on the neural mechanisms underlying its core component—spatial memory—and the critical influence of emotional valence. Memory dysfunction is a central pathological feature of many neurological and psychiatric disorders, as seen in the progressive memory loss characteristic of Alzheimer’s disease (AD) and the maladaptive consolidation of traumatic memories in post-traumatic stress disorder (PTSD). The current lack of effective treatments for these conditions highlights the urgent clinical need for precise neuromodulation technologies.
    The first part of this review synthesizes recent breakthroughs in decoding the neural substrates of spatial memory and emotional valence, hallmarked by a critical paradigm shift in experimental approaches. Intracranial recording studies in humans based on real-world navigation tasks provide more valuable insights than constrained desktop-based virtual reality paradigms, due to their higher ecological validity. These studies indicate that hippocampal theta oscillations serve as a robust biomarker for decoding movement states and velocity, characterized by short-duration bursts whose frequency correlates with movement speed. Furthermore, the entorhinal cortex exhibits grid cell-like periodic activity, working together with "memory trace cells" in the hippocampus to encode spatial locations and goal representations. Beyond self-motion information, environmental boundaries are also distinctly represented through specific oscillatory patterns in the medial temporal lobe, a process strongly modulated by task relevance and cognitive demand. Concurrently, research on emotional valence has identified distinct neural circuits: negative emotions such as fear are linked to beta-band synchrony in the amygdala-hippocampal network, whereas positive valence and reward processing involve the dopaminergic system and are reflected in high-frequency activity and sharp-wave ripples in the hippocampus. These detailed mechanistic insights offer a foundational map of neurobiological targets for selective intervention.
    Building on this advanced in decoding, the field is undergoing a strategic pivot from open-loop to closed-loop neuromodulation. Traditional open-loop deep brain stimulation (DBS), which uses fixed stimulation parameters, has shown limited efficacy and poor adaptability to the brain's dynamic states, with effects often being inconsistent across different memory tasks. In contrast, next-generation closed-loop BCIs can monitor specific neural signatures in real time—such as particular oscillatory couplings during memory encoding or slow-wave-ripple events during sleep-dependent consolidation—and deliver personalized, spatially targeted electrical stimulation at optimal moments. Recent empirical evidence from human studies confirms that this adaptive "monitoring-decoding-intervention" framework can significantly enhance both memory encoding efficiency and long-term consolidation. For instance, stimulation triggered by detected slow-wave oscillations during NREM sleep has been shown to enhance the coupling between slow waves, spindles, and ripples, thereby improving memory performance. This represents a critical evolution from static, unidirectional stimulation to a dynamic, bidirectional brain-machine dialogue.
    Looking forward, the convergence of dynamic network neuroscience models—which provide the real-time 'blueprint' of brain network activity—with next-generation electrodes—which provide the tools for high-resolution interaction—paves the way for building truly adaptive systems that can dynamically interpret and respond to brain states. Future developments will need to address the challenges of profound individual variability in neural signatures and ensure the long-term stability of recording interfaces. Furthermore, advancing beyond simple classification to the reconstruction of rich memory content requires more sophisticated decoding algorithms capable of handling the nonlinear, non-stationary nature of neural signals across different brain states. The integration of deep learning models with high-density, flexible electrode arrays may enable more precise mapping of distributed memory networks. Despite these challenges, closed-loop BCI technology—grounded in precise mechanistic insights from cognitive neuroscience—holds great potential to revolutionize the treatment of memory disorders. By enabling real-time, adaptive interaction with the brain's memory networks, this technology paves the way for personalized therapeutic strategies that can dynamically respond to the changing needs of patients with neurological and psychiatric conditions, ultimately restoring cognitive function and improving quality of life.
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    Conceptual Framework
    The concept connotation, formation and impact mechanism of knowledge disruption
    FENG Jiaojiao, LIU Yi, LIU Jun
    2026, 34 (2):  210-226.  doi: 10.3724/SP.J.1042.2026.0210
    Abstract ( 239 )   PDF (684KB) ( 293 )   Peer Review Comments
    This study systematically investigates the phenomenon of individual knowledge disruption within turbulent environments characterized by rapid technological advancements, such as artificial intelligence, and shifting market dynamics. The study's primary innovation lies in its conceptual and empirical examination of knowledge disruption as a perceived threat to the adequacy of one's domain-specific expertise, triggered by external environmental shocks.
    The research is structured around three interconnected studies. The first study aims to achieve conceptual clarity by rigorously defining knowledge disruption and distinguishing it from related constructs like knowledge updating, knowledge reconstruction, and knowledge innovation. A key innovation is the proposed differentiation of two distinct dimensions: cross-domain knowledge disruption (complementary challenges from external, non-core knowledge) and within-domain knowledge disruption (substitutive threats from new knowledge within one's core field). Based on the dynamic and boundary characteristics of knowledge management, this study will develop and validate a reliable measurement scale for these dimensions, addressing a significant methodological gap in the literature. The study will employ a combined qualitative and quantitative research methodology. Based on the conceptual framework of knowledge disruption outlined above, it will develop measurement scales for cross-domain knowledge disruption and within-domain knowledge disruption, and validate their reliability.
    The second study delves into the formation mechanism of employee knowledge disruption, exploring how environmental dynamism (comprising both technological turbulence and market turbulence) translates into the subjective experience of disruption. The investigation focuses on unveiling the parallel mediating roles of work competency and professional control, thereby revealing the pathways through which external turbulence triggers feelings of knowledge inadequacy. Furthermore, the study examines the cross-level moderating effects of organizational environmental scanning and individual dynamic capabilities, offering a comprehensive framework that incorporates both organizational and individual factors that may attenuate or exacerbate the impact of environmental turbulence on knowledge disruption.
    The third study examines the impact mechanism of knowledge disruption. A innovative element is testing a dual-pathway model where the two types of disruption lead to divergent outcomes through different motivational and behavioral processes. It is proposed that cross-domain knowledge disruption may foster innovation performance and work resilience by triggering a knowledge restructuring process. Conversely, within-domain knowledge disruption is hypothesized to hinder these outcomes.
    The study further investigates how individual mindset (growth mindset versus fixed mindset) moderates these relationships, particularly examining how growth mindset strengthens the positive path from cross-domain disruption to innovation through knowledge restructuring, while fixed mindset reinforces the negative path from within-domain disruption to performance outcomes.
    As for theoretical contributions, this study creatively constructed a series of mechanisms from encountering knowledge disruption to responding to it from the perspective of self-threat. At present, there are very few individual complete mechanism chains regarding knowledge disruption. Therefore, this study, against the backdrop of environmental turbulence, reveals the dynamic process from the cause to the consequence of individual knowledge disruption. Moreover, knowledge serves as the foundation for allocating status and prestige in the professional hierarchy system. Therefore, knowledge disruption implies the possibility of losing social respect or status, that is, facing self-threat. Most existing studies regard individual knowledge as a kind of resource. In this study, knowledge disruption is regarded as a threat to the self-concept. Based on relevant theoretical foundations of self-concept such as threat rigidity theory, the formation mechanism and influence mechanism of knowledge disruption in a turbulent environment are explored. Studying the formation mechanism and the impact mechanism on work results and capabilities in the turbulent environment of knowledge disruption from the perspective of self-threat not only provides a new theoretical perspective for the research in the field of individual knowledge management, but also expands the research content of this field.
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    Dynamic processing of conversational intelligence features in marketing digital humans and its neural mechanisms
    PEI Guanxiong, DONG Bo, JIN Jia, MENG Liang, ZHANG Jialin
    2026, 34 (2):  227-238.  doi: 10.3724/SP.J.1042.2026.0227
    Abstract ( 139 )   PDF (642KB) ( 147 )   Peer Review Comments
    As a new-generation human-computer interaction interface, marketing digital humans' conversational intelligence systems have emerged as a crucial engine for driving consumption upgrades and cultivating new quality productive forces in the digital economy. Nevertheless, the mechanisms through which the conversational intelligence features of marketing digital humans influence consumer behavior remain unclear due to the complexity of multidimensional conversational intelligence characteristics, the dynamics of multi-turn interaction patterns, and the challenges in decoupling dual-trust effects, which hinders the healthy development of the marketing digital human industry. Guided by the cognitive-affective trust theory, this study primarily investigates: (1) the consumer behavior phenomena under the interactive influence of multidimensional conversational intelligence features and various external factors; (2) the dynamic cognitive process resulting from the impact of conversational intelligence features on dual trust; (3) the cognitive neuroscience mechanisms underlying dual trust in marketing digital human; and (4) the optimization of conversational intelligence features in marketing digital human and practical application validation. Based on these research findings, the study aims to explore effective pathways for leveraging marketing digital humans' conversational intelligence systems to enhance consumer experiences, optimize business costs, and improve efficiency.
    In terms of behavioral phenomena, this research expands the current literature's holistic understanding of how marketing digital humans' conversational intelligence features influence consumer behavior. The advancement of large language model technology has created opportunities for digital humans to reshape human-computer interaction patterns in sales scenarios. However, studies on the multifaceted interactions between multidimensional conversational intelligence features and external factors affecting consumer behavior are still in their nascent stages, lacking systematic and comprehensive characterization of phenomena and identification of key elements. This study intends to employ methods such as panel vector autoregression models to characterize the phenomena of interactions among multidimensional heterogeneous elements and the differential impacts of various conversational intelligence features on consumer behavior, thereby contributing to a holistic understanding and isolating critical influencing factors.
    In terms of psychological processes, this study innovatively proposes a dynamic trust processing framework for multi-turn conversations with marketing digital humans. Perceived trust is a crucial factor influencing the consumer-digital human interaction ecosystem and marketing effectiveness. Current research on perceived trust in digital human conversational contexts predominantly examines single-turn interactions or adopts static perspectives. However, real interactions between humans and digital humans are characterized by multi-turn, bidirectional exchanges, and the establishment of human-computer trust is a continuously dynamically adjusted calibration process. Trust levels evolve over time and eventually stabilize. Unlike previous structural analysis paradigms, this study adopts a process-tracing paradigm and employs Bayesian decision modeling to construct a psychological process coding model for trust levels. This approach helps explain the psychological processes underlying human-computer interaction behaviors, enhances the depth of theoretical construction, and provides richer evidence for comparing and validating divergent conclusions in the field of human-computer trust.
    In terms of underlying mechanisms, this study systematically unveils the neural mechanisms of dual trust in marketing digital humans. According to cognitive-affective trust theory, consumer trust comprises two dimensions: cognitive trust and affective trust. Different conversational intelligence features exert differentiated effects on dual trust, which in turn diversely impact consumer behavior. However, due to the subjective and implicit nature of trust perception, distinguishing between cognitive trust and affective trust through consumer self-reports is challenging. Neuromarketing methods offer significant advantages in observing implicit variables. This study plans to utilize fMRI as a tool for characterizing the neural mechanisms of dual trust and researching consumer behavior. By disentangling the effects of dual trust, assessing differences in activation intensity, and distinguishing effective functional pathways, a brain network model of dual trust will be constructed. Furthermore, this study intends to use neural data, behavioral data, and historical consumption data as input variables, with trust levels and purchase intention as output variables. Based on a deep learning approach combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, a predictive model of consumer behavior in marketing digital human conversational contexts will be developed.
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    Research Method
    Applications of transcranial alternating current stimulation in psychological research
    DONG Yaohua, TANG Yuyao, ZHANG Dandan
    2026, 34 (2):  239-250.  doi: 10.3724/SP.J.1042.2026.0239
    Abstract ( 163 )   PDF (924KB) ( 160 )   Peer Review Comments
    Transcranial alternating current stimulation (tACS) is a non-invasive electrical neuromodulation technique that delivers periodic microcurrents of specific frequencies via electrodes placed on the scalp, thereby modulating neural oscillations in targeted brain regions. By entraining these oscillations, tACS can alter specific cognitive functions or alleviate clinical symptoms. A recent development, temporal interference (TI) stimulation, extends the capability of tACS by superimposing two or more high-frequency currents with slightly different frequencies to generate low-frequency envelope signals in deep brain areas, such as the hippocampus, enabling targeted modulation beyond cortical regions. Since its introduction into psychological research in 2008, tACS has been widely used to elucidate causal links between neural oscillations across distinct frequency bands and various cognitive processes, offering a powerful approach to probe the functional roles of brain rhythms.
    The primary mechanism of tACS is the synchronization of neural electrical activity. By delivering alternating currents at specific frequencies, tACS can align neural oscillations in the target brain region to align in phase. This phase-dependent modulation induces rhythmic fluctuations in presynaptic membrane potentials, thereby facilitating synaptic plasticity and dynamically regulating cortical excitability. Specifically, the mechanism can be described at three levels: Regulation of local neural oscillations, optimization of brain network connectivity, and enhancement of neural plasticity. At the local oscillation level, tACS induces synchronization between endogenous oscillations and exogenous currents by applying stimulation that matches the intrinsic rhythm of the target region. At the network level, tACS modifies synchronization and coupling properties of endogenous oscillations, including frequency-specific synchronization and cross-frequency phase-amplitude coupling, by delivering alternating currents with adjustable phase differences across brain regions. At the plasticity level, the modulatory effects of tACS rely on the activation of synaptic plasticity, which can persist for minutes to hours after stimulation ends.
    tACS modulates neural oscillations at specific frequencies to regulate the synchronization and coupling states of brain functional networks, thereby influencing a wide range of cognitive functions. This frequency-specific modulation provides a novel perspective for elucidating the neural basis of cognitive processes and advancing interventions for mental and neurological disorders. Evidence from previous studies suggests that tACS at different frequencies exerts relatively distinct functional effects: Alpha band primarily influences sensory processing and spatial attention; beta band motor control; and theta- and gamma- band play critical roles in learning, memory, and emotion regulation. Furthermore, in the field of interpersonal interaction research, tACS has been shown to enhance neural synchrony between brains, thereby promoting collaboration, intention understanding, and social learning.
    Currently, the field of tACS remains in an early stage of development, with its mechanisms of neural activity, practical application methods, and stimulation parameters yet to be fully elucidated. Therefore, we propose that future research should focus on three key aspects. First, precise control of the phase relationship between the applied alternating current and the brain’ s spontaneous EEG rhythms is essential. Most existing studies have neglected this phase difference, and misalignment may weaken the entrainment effect of tACS on spontaneous oscillations, reducing intervention efficacy. Achieving accurate neural modulation requires real-time monitoring of spontaneous EEG phase before and during stimulation. Novel algorithms such as stimulation artifact source separation (SASS) can support this process by enabling real-time phase adjustment to maintain optimal phase alignment, thereby maximizing neural entrainment. Furthermore, the development of closed-loop modulation systems employing adaptive tACS protocols is needed to dynamically regulate EEG rhythms. Second, individual differences must be taken into account for personalized tACS protocols. Some studies highlight the benefits of personalized stimulation frequencies, while optimizing stimulation targets based on individual anatomy has been shown to enhance regulatory effects. In addition, incorporating control frequencies in tACS research is crucial for accounting for non-specific effects and validating the specificity of particular stimulation frequencies, thereby strengthening causal inferences. Third, systematic evaluation of treatment protocols and the persistence of therapeutic effects in clinical applications is needed. Although some studies have investigated the lasting efficacy of tACS in patients with depression, Parkinson’ s disease, and other disorders, follow-up durations have been relatively short, insufficient to translate immediate effects into long-term benefits.
    Overall, tACS has become a powerful tool for investigating the causal links between neural oscillations and cognitive processes in the human brain, and future research should focus on achieving precise neural modulation and conducting systematic clinical evaluation to better elucidate underlying mechanisms and guide therapeutic applications.
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    Regular Articles
    Simplify complexity: The neural mechanisms underlying ensemble perception
    SUN Huanxiang, ZHANG Fan, LI Sijia, ZHANG Xiuling, JIANG Yi
    2026, 34 (2):  251-270.  doi: 10.3724/SP.J.1042.2026.0251
    Abstract ( 203 )   PDF (1220KB) ( 215 )   Peer Review Comments
    Ensemble perception, the process by which the visual system extracts summary statistical information (e.g., mean and variance) from groups of similar objects at a brief glance, is critical to human adaptive functioning. While the behavioral characteristics of this “gist” perception are well researched, its underlying neural mechanisms remain elusive. The present work reviews the temporal dynamics of ensemble perception, evaluates leading theoretical models in light of key empirical findings, and distinguishes the neural substrates underlying ensemble versus single-item processing. Based on existing evidence, the review proposes a “Coarse-Fine-Refine” model that reconciles divergent findings on visual information processing pathways, temporal stages, and computational mechanisms.
    A primary focus of the review is the controversial temporal dynamics of ensemble processing. We first examine evidence for an early, automatic extraction of summary statistics. Event-related potential (ERP) studies suggest that mean emotional information can be processed with limited attention, supported by the absence of spatial attention components (N2pc) and the presence of visual mismatch negativity (vMMN) to changes in unattended ensemble items. Such findings suggest a rapid, pre-attentive mechanism of ensemble perception. However, this view is challenged by other studies. For instance, some failed to find vMMN in the absence of attention during mean orientation perception, suggesting that at least some ensemble features require attentional resources. Furthermore, recent MEG/EEG studies revealed that a precise and stable representation correlated with behavioral performance only emerges at much later time windows (e.g., 400-700 ms). These controversial findings suggest a possible multi-stage process, beginning with a rapid, coarse estimate followed by a slower, refined calculation.
    The review then scrutinizes the integration mechanisms in ensemble perception. Early hypotheses, such as the Signal Pooling Hypothesis, posit a hierarchical, feedforward process where signals from individual items are averaged or pooled at progressively higher levels of the visual pathway. Computational models, like the Population Response Model, provide a plausible neural implementation for this. However, a growing body of evidence challenges a simple linear averaging account. Regression-based ERP studies demonstrate that ensemble perception may rely on non-additive integration, capturing global interactions between items rather than mere summation of individual elements.
    We also address the possible dissociation between the neural coding of the ensemble and its individual members. fMRI and MEG evidence suggests that ensemble emotion preferentially relies on the dorsal visual stream (e.g., intraparietal sulcus), particularly the rapid magnocellular (M-pathway) input. In contrast, individual item identification depends on the ventral stream (e.g., fusiform gyrus) and parvocellular (P-pathway) processing. Reverse Hierarchy Theory (RHT) also posits a neural dissociation between ensemble and individual representations, proposing that “vision at a glance” (ensemble gist) arises first via a fast feedforward sweep, whereas “vision with scrutiny” (individual details) requires slower, top-down attentional feedback.
    In summary, while research on the neural mechanisms of ensemble perception has made significant progress, it remains in a critical phase of development, with several key questions yet to be resolved: (1) using high-resolution imaging to delineate the specific contributions of different brain areas, including V1 and dorsal versus ventral stream regions; (2) clarifying the interplay between feedforward and feedback signals; (3) resolving the domain-general versus domain-specific debate; and (4) examining how ensemble mechanisms are shaped by neural development and individual experience. We further argue for a crucial distinction between neural activity related to “ensemble perception” (the overall response to multiple stimuli) and “statistical summary representation” (the specific neural computation of a statistic). Failing to separate these concepts tends to misattribute general neural summation effects, such as the increase in N170 amplitude evoked by multiple faces, to specific mechanisms of statistical representation. Addressing these questions will be essential for a complete understanding of the mechanisms underlying ensemble perception.
    Finally, based on existing evidence, we propose an integrative “Coarse-Fine-Refine” model. In Phase 1, a rapid, domain-general “gist” is extracted, driven by the M-pathway projecting low-spatial-frequency information to dorsal and frontoparietal regions, forming an initial, rough summary or prediction. In Phase 2, a slower, domain-specific process mediated by the P-pathway analyzes high-spatial-frequency details within specialized ventral/occipital regions (e.g., face- or orientation-specific features). In Phase 3, iterative calibration occurs via recurrent feedforward-feedback loops between high-level (frontoparietal) and feature-specific (ventral/occipital) areas. This interaction uses the initial “coarse” prediction to modulate the “fine” processing, resulting in a final, precise ensemble representation. This framework synthesizes the complex roles of distinct neural pathways and resolves ongoing debates on temporal dynamics (early vs. late) and processing mechanisms (general vs. specific), offering a plausible neural hypothesis for how the brain “simplifies complexity”.
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    The influence of sensory modalities and experience deprivation on the neural basis of reading: Evidence from tactile Braille reading
    LI Peiqi, ZHANG Yu, TIAN Mengyu
    2026, 34 (2):  271-282.  doi: 10.3724/SP.J.1042.2026.0271
    Abstract ( 82 )   PDF (1956KB) ( 97 )   Peer Review Comments
    Both the deprivation of sensory experience and the acquisition of cultural skills such as reading can induce plastic changes in the brain. On the one hand, sensory experience deprivation, such as lifelong loss of visual input in congenital blindness leads to large-scale reorganization of cortical function, with occipital “visual” regions becoming responsive to non-visual modalities and even higher-order cognition such as language, memory or numerical reasoning. On the other hand, the acquisition of cultural inventions such as reading sculpts the cortex in domain-specific ways, with the ventral occipito-temporal cortex (vOTC) developing a specialized “visual word form area” (VWFA) in literate individuals. Braille reading in blind individuals provides a unique natural model in which sensory modality (tactile rather than visual) and lifelong visual deprivation jointly shape the reading network. In this review, we summarize recent neuroimaging evidence with a focus on three central questions: (1) whether the early visual cortex in blind individuals contains reading-specific representations; (2) whether the visual word form area within the ventral occipito-temporal cortex retains cross-modal orthographic processing functions; and (3) whether the parietal cortex could host an analogue of the VWFA, a putative “tactile word form area”.
    First, converging evidence from fMRI, TMS and lesion studies indicates that early visual cortex contributes to Braille reading. However, what information these regions encode remains unclear. Some evidence indicates that early visual cortex is involved in higher-level tactile discrimination, but whether this activity is specific to Braille reading remains controversial. Other evidence suggests that early visual cortex participates in higher-level linguistic processing and may be integrated into the language network in blindness, implying that its activation during Braille reading could reflect lexical or semantic processing rather than tactile analysis. Paradigms that confound tactile shape processing with naming or phonological tasks further complicate interpretation. A key next step is to determine whether occipital activation in Braille reading reflects a reading-selective mechanism or instead stems from broader linguistic or executive processing, and, if selectivity exists, to identify the nature of the representations involved.
    The second question concerns whether the VWFA in blind individuals preserves its canonical role in orthographic analysis via cross-modal plasticity, or whether it is repurposed entirely for higher-order linguistic computation, as proposed by the cognitively pluripotent cortex hypothesis. Although some studies report Braille-selective activation patterns resembling those in sighted readers, their reliance on contrasts between Braille words and low-level tactile controls makes it difficult to determine whether such effects reflect true orthographic processing or simply the presence of linguistic content. Other findings instead reveal sensitivity of the VWFA to spoken language, syntactic structure and broader linguistic demands—properties not typically seen in the sighted brain. Moreover, blindness appears to alter the internal representational hierarchy of ventral occipito-temporal cortex, blurring the traditional gradient from low-level letter features to higher-order word forms. Disentangling genuinely orthographic computations from more general linguistic processing therefore remains a central challenge for future work.
    The third question concerns whether tactile orthographic processing may be supported by the parietal lobe rather than the ventral stream, a hypothesis that remains relatively underexplored but potentially important. The posterior parietal cortex is a plausible candidate for such a role, given its documented involvement in tactile shape discrimination and its anatomical and functional connectivity with language-related frontal regions. Converging evidence shows that parietal activity is sensitive to Braille letter length and sublexical structure, while other findings suggest a hierarchical gradient from somatosensory encoding anteriorly to word-level preference posteriorly. These observations raise the possibility of a parietal “tactile word form area.”
    Taken together, current research provides compelling evidence that Braille reading engages a distributed network spanning somatosensory, parietal, occipital and language regions, but the division of labor between parietal and occipital cortices remains unresolved. Progress will require more cautiously controlled and methodologically diverse experimental designs to disentangle tactile, orthographic and linguistic computations. Moreover, the neural basis of individual differences in Braille reading proficiency remains largely unexplored, despite its clear relevance for educational interventions. Addressing these open questions will not only refine theories of cortical recycling and pluripotency but also provide principled guidance for designing targeted Braille literacy training programs.
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    Does music listening facilitate cognitive processing? Revisiting previous debates from an attention network perspective
    SUN Yifan, HE Qin, ZHANG Chang, CHEN Ning
    2026, 34 (2):  283-298.  doi: 10.3724/SP.J.1042.2026.0283
    Abstract ( 160 )   PDF (565KB) ( 249 )   Peer Review Comments
    Despite decades of investigation, the cognitive effects of music listening remain inconsistent. While numerous studies demonstrate that music can improve attention, memory, and creativity, others reveal interference or null effects. These contradictory findings, often described as the “double-edged sword effect”, highlight the lack of a unifying theoretical framework explaining when and how music facilitates or impairs cognition. Moving beyond affective and motivational interpretations, this study redefines the problem through the lens of cognitive neuroscience by introducing a new Music-Attention Network Model grounded in the attention network theory (Posner & Petersen, 1990). This integrative model positions attention as the central mechanism through which music exerts its influence on cognitive processing.
    The model proposes that music affects cognition via three interrelated regulatory pathways—emotional arousal, cognitive load, and temporal dynamics—each corresponding to distinct attentional sub-networks (alerting, orienting, and executive control). Together, these pathways explain the context-dependent and state-dependent nature of music’s cognitive impact.
    The emotional arousal pathway proposes that music influences cognitive efficiency by altering both affective and physiological states. Drawing on the broaden-and-build theory, the model suggests that pleasant, moderately arousing music expands the scope of attention and improves orienting efficiency, whereas highly arousing or unpleasant music tends to narrow attentional focus and impair performance. Moderate emotional stimulation appears to promote flexible and adaptive allocation of attentional resources, while excessive arousal or negative affective tone triggers over-focusing and cognitive rigidity. This dual mechanism provides a coherent account of the bidirectional effects of music reported across behavioral, electrophysiological, and neuroimaging studies.
    The cognitive load pathway emphasizes the interplay between external auditory input and the limited capacity of working memory. Background music competes with task-related processing for attentional resources; its impact follows a non-linear, inverted-U pattern consistent with the Yerkes-Dodson law. Moderate external load can stabilize alertness and reduce mind-wandering, whereas overload induces interference. Individual differences—such as working memory capacity, personality traits, and task complexity—further moderate this relationship. The concept of an “optimal cognitive load level” thus clarifies why music benefits simple or monotonous tasks but hinders complex or high-demand ones.
    The temporal dynamic pathway introduces the dimension of time into understanding how music shapes cognitive processing. The effects of music are inherently dynamic rather than static, evolving through processes such as emotional aftereffects, habituation, and changes in arousal regulation over time. In advance music conditions, short-term facilitation often arises from residual arousal that gradually diminishes, whereas background music may initially sustain vigilance but later induce fatigue through prolonged engagement. This temporal dynamicity highlights that the impact of music depends not only on its acoustic features but also on the temporal distance between listening and task performance, revealing a time-sensitive pattern of cognitive modulation.
    The model also incorporates insights from the Dynamic Attending Theory (DAT), which explains how rhythmic structures in music synchronize internal attentional rhythms with external temporal regularities through neural entrainment. This synchronization allows listeners to anticipate upcoming events and allocate attentional resources precisely at predicted moments of significance. In this way, musical rhythm transforms temporal predictability into enhanced attentional precision. Integrating this mechanism with the attention network framework bridges the temporal and spatial dimensions of attentional control, positioning DAT as a complementary account of how music dynamically guides the flow of attention over time.
    Collectively, the Music-Attention Network Model provides a unified explanation for the dual nature of music’s cognitive effects. Whether facilitative or disruptive, the outcome depends on the dynamic interaction among emotional arousal, cognitive demand, temporal context, and individual characteristics. Rather than treating music as a fixed enhancer or distractor, the model conceptualizes it as a context-sensitive modulator operating through multiple, interacting pathways. A further theoretical innovation lies in the concept of functional generalization, which proposes that music-induced improvements in attentional efficiency can transfer to higher-order cognitive domains such as working memory, reasoning, and creativity. Within a top-down control framework, music optimizes executive networks by promoting rhythmic entrainment and cross-frequency phase synchronization, thereby improving neural efficiency across cognitive domains. Converging evidence from music training research and neuroimaging studies also supports this view: long-term musical experience enhances connectivity among auditory, parietal, and prefrontal cortices, reflecting domain-general neural plasticity.
    This framework offers several methodological implications. Future studies should employ multi-level designs that integrate behavioral paradigms (e.g., the Attention Network Test) with neuroimaging techniques such as fMRI, fNIRS, or EEG to directly quantify how different musical conditions modulate each attentional sub-network. Computational modeling approaches—including reinforcement learning and neural dynamic simulations—can further characterize how musical features compete or cooperate with task demands in the allocation of cognitive resources.
    In summary, this study advances a novel theoretical framework that reconceptualizes the relationship between music listening and cognitive processing. It demonstrates that attention—rather than emotion or motivation alone—serves as the core mediator linking musical experience to cognitive outcomes. By introducing the constructs of optimal arousal, optimal load, temporal dynamicity, and functional generalization, the model provides a cohesive and testable account of prior inconsistencies and establishes a foundation for future cross-disciplinary research. This integrative perspective enriches the understanding of music’s role in cognition, offering new insights for both theoretical inquiry and applied domains such as education, rehabilitation, and human-computer interaction.
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    Emotional body odor: Mechanisms in emotional communication and biological significance
    ZHOU Xingpan, LIU Peihan, WU Qi, LEI Yi
    2026, 34 (2):  299-312.  doi: 10.3724/SP.J.1042.2026.0299
    Abstract ( 166 )   PDF (566KB) ( 199 )   Peer Review Comments
    This review synthesizes recent empirical findings on emotional body odors (EBOs) and advances a unified evolutionary framework that repositions EBOs as adaptive chemical communicators rather than unanalyzed background cues. Rather than repeat basic definitions, the review focuses on three innovations. First, it integrates multi-level evidence—behavioral, autonomic, electrophysiological, neuroimaging, and molecular—to map the specific response profiles that different EBOs evoke in receivers. Second, it offers a critical molecular and receptor-level appraisal that challenges the default classification of EBOs as pheromones. Third, it proposes the “communicative chemical evolution hypothesis,” a testable model that links learning, selection, and population dynamics to stages in the functional maturation of chemical signals.
    Empirical synthesis reveals reproducible, emotion-specific effects. Negative EBOs (fear, anxiety, anger, sadness) trigger rapid threat-oriented cascades. Fear body odor (FBO) reliably increases sympathetic markers, modulates facial motor responses (orbicularis oculi, corrugator supercilii), reduces heart rate variability, and biases perceptual and decision processes toward threat. Electrophysiology shows early sensory amplification (N1/P1) and enhanced face-processing components (N170, P3), while neuroimaging highlights amygdala-fusiform-ventromedial prefrontal circuits that mediate threat detection and attention allocation. Anxiety odors produce similar autonomic shifts, strengthen startle reflexes, and bias risk assessment. Anger odors amplify skin conductance and recruit thalamic-hypothalamic-insula-amygdala-cingulate pathways, particularly in high-trait-anxiety participants. Sadness-related chemosignals (e.g., from tears) decrease testosterone and sexual arousal in males, and dampen hypothalamic and reward-related responses. By contrast, positive EBOs (e.g., happiness odor) increase parasympathetic indices, induce Duchenne smiles, elevate late positive potentials (LPP), and enhance cognitive flexibility and cooperative tendencies. Across studies, the functional dichotomy is robust: negatives favor rapid defense and avoidance; positives promote affiliation and exploration.
    Comparative and cross-cultural evidence provides preliminary support for partial universality. Cross-species responses to FBOs (dogs, horses) and consistent effects across East Asian and Western samples suggest conserved processing biases. However, most evidence stems from controlled lab paradigms that use direct nasal delivery of concentrated samples. This raises ecological validity concerns and limits inferences about real-world sender-receiver dynamics.
    At the molecular level, the review identifies a central gap: EBOs lack clearly identified, steroidal molecules at biologically plausible concentrations that would parallel classical pheromones (e.g., androstadienone). Receptor evidence is likewise scarce, and human vomeronasal function appears vestigial. These facts argue against uncritical classification of EBOs as pheromones. The review proposes instead that EBOs function primarily via the main olfactory epithelium and associative learning mechanisms, interacting with individual experience to produce stable behavioral regularities.
    The communicative chemical evolution hypothesis formalizes this view. It frames EBOs on a continuum from chemical cues (metabolic by-products) to chemical signals (contextually exploited cues) and, under stringent conditions of genetic fixation and sender-receiver reciprocity, to releaser pheromones. The model emphasizes three drivers of functional transition: (1) unique chemical features that allow consistent discrimination; (2) repeated cue-response pairings that generate learned associations and canalize responses; and (3) population-level selection that stabilizes sender and receiver strategies (a Baldwin-effect mechanism). By integrating learning and selection, the model explains cross-cultural consistency without presuming purely innate coding.
    The review also evaluates empirical limitations and methodological fixes. Current work over-relies on single-receiver paradigms, neglects sender benefits, and ignores chronic exposure consequences. To move the field forward, the review recommends: multi-agent interaction experiments to capture bidirectional dynamics; twin and family designs to partition genetic and experiential variance; longitudinal intergenerational sampling to detect fixation; virtual reality coupled with high-resolution olfactometers for ecological control; and metabolomic fingerprinting to discover candidate biomarkers. These approaches will enable direct tests of sender-receiver reciprocity, fitness consequences, and the molecular prerequisites for pheromone status.
    Finally, the review sketches translational pathways. If validated, EBO-based interventions could augment exposure therapies, enhance social-skill training, or serve as adjuncts in assistive technologies for autism spectrum disorders. Yet translation requires caution: weak effect sizes, contextual dependence, and ethical issues around manipulation of chemosignals demand rigorous validation.
    In sum, this review advances theory and method by (1) distinguishing signal from cue at molecular and behavioral scales, (2) articulating a testable evolutionary pathway for EBOs, and (3) specifying concrete empirical programs to evaluate whether, when, and how human emotional chemosignals become evolutionarily stabilized communicative tools.
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    The mechanisms of locus coeruleus-norepinephrine system in attention
    XING Lianzi, CHEN Yujie, MIAO Chengguo, ZHANG Yang
    2026, 34 (2):  313-330.  doi: 10.3724/SP.J.1042.2026.0313
    Abstract ( 91 )   PDF (555KB) ( 116 )   Peer Review Comments
    The locus coeruleus-norepinephrine (LC-NE) system is a central neuromodulatory system in the brain that orchestrates attentional processes across the brain through its widespread neural projections and norepinephrine (NE) release mechanisms. According to classical attentional theories, attention comprises three subsystems: alerting, orienting, and executive control. Although extensive studies have highlighted the LC-NE system's significant involvement across these subsystems, its specific neural mechanisms regulating attention remain incompletely elucidated. Therefore, this review aims to systematically explore the neurophysiological mechanisms underlying LC-NE modulation of attention, summarize physiological indicators reflecting its activity, and integrate current advances on its functional roles across attentional subsystems and its implications for attention-related disorders.
    The locus coeruleus (LC) is a vertebrate-specific NE nucleus and the primary site for NE synthesis and release in the brain. LC neurons project widely to regions critical for attention and executive control, including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), parietal cortex, thalamus, and amygdala, forming the anatomical basis of LC-NE-mediated attentional regulation. NE released by LC neurons exerts excitatory or inhibitory effects via receptors with varying affinities, dynamically influencing attention. Furthermore, LC neurons exhibit two firing patterns: tonic and phasic. Tonic activity reflects the baseline firing state, while phasic activity, triggered by salient or goal-relevant stimuli, enhances selective processing and suppresses irrelevant input. When tonic activity is maintained at moderate levels, phasic responses are most pronounced, demonstrating optimal attentional control. Both excessively low and high tonic activity attenuate phasic responses, leading to distraction and impaired task performance. These dynamic activity patterns enable adaptive gain modulation, balancing exploitation and exploration to optimize behavioral flexibility. This reflects the complex neural basis of attention regulation within the LC-NE system.
    The functional dynamics of the LC-NE system can also be reflected through behavioural and neurophysiological indicators. Pupil dilation, which reflects arousal levels and cognitive effort, correlates strongly with LC firing patterns and serves as a reliable proxy for LC-NE activity. Event-related potentials (ERPs), particularly the P3 and N2 components, also provide indirect indicators of LC modulation of attention. Multimodal studies combining pupillometry, electrophysiology, and functional magnetic resonance imaging (fMRI) have revealed dynamic LC-cortical interactions, validated the link between LC-NE activity and attention, and highlighted population differences in LC-NE function and potential attentional deficits.
    Functionally, the LC-NE system regulates cortical gain across multiple attentional subsystems. In alerting, LC-mediated NE release modulates global arousal and cortical baseline activity, contributing to sustained readiness through its widespread projections. In orienting, phasic LC activation triggers a “network reset,” facilitating rapid attentional shifts by coordinating interactions between the dorsal and ventral attention networks. In executive control, broad NE projections to the PFC and related control networks enhance conflict monitoring, inhibitory control, and flexible cognitive strategy adjustment. Notably, dysfunction within the LC-NE system has been closely associated with attention-related disorders such as attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), suggesting that it may represent a potential neural target for therapeutic intervention.
    Despite significant progress in recent years, key challenges remain in elucidating LC-NE modulation of attention. Future research should prioritize three directions: (1) Observational precision—integrating pupillometry, ERPs, intracranial electrophysiology, and high-resolution neuroimaging to achieve temporally and spatially precise tracking of LC-NE activity during attentional processes; (2) Causal mechanisms—employing causal perturbation methods such as pharmacological manipulations, transcranial magnetic stimulation, and deep brain stimulation to validate the LC-NE system’s role in attentional processing, complemented by multimodal measures to capture its dynamic effects; and (3) Network and modeling approaches—further investigating dynamic LC connectivity with key attentional nodes (e.g., PFC, parietal cortex, temporoparietal junction) across developmental stages, and integrating predictive coding and gain control frameworks to construct unified computational models of LC-NE-driven attentional regulation. This review contributes by integrating receptor-level mechanisms, firing patterns, and attentional subsystems into a unified framework, and by synthesizing multimodal evidence to highlight complementary approaches to investigating the mechanisms of the LC-NE system in attention.
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    The psychotherapeutic mechanisms and neural basis of Eastern mindfulness
    WU Kai
    2026, 34 (2):  331-347.  doi: 10.3724/SP.J.1042.2026.0331
    Abstract ( 515 )   PDF (756KB) ( 518 )   Peer Review Comments
    This paper introduces an innovative “therapy-neural-culture continuum” framework that reconceptualizes mindfulness as a holistic psychological intervention, elucidating the unique psychotherapeutic mechanisms and neural foundations of Eastern mindfulness. Rooted in Chinese Mahāyāna (Han) Buddhism and integrated with Confucian and Daoist philosophies, Eastern mindfulness addresses the limitations of Western mindfulness models, which have often undergone decontextualization and ethical omission, leading to conceptual reductionism and potential adverse effects. By restoring the integral Three Trainings—śīla (morality), samādhi (concentration), and prajñā (wisdom)—as a unified system of mental cultivation, this approach transcends individualistic and instrumental adaptations, providing a culturally grounded pathway for deep psychological transformation and enhanced intervention safety.
    A central innovation lies in the psychological reinterpretation of Eastern mindfulness’s theoretical core, distilled into four interrelated pillars: emptiness (śūnyatā), Buddha-nature (tathāgatagarbha), bodhisattva practice, and non-duality. Emptiness is reframed as cognitive de-reification, enabling practitioners to perceive thoughts and self-concepts as transient processes rather than fixed entities. This aligns with the defusion process in acceptance and commitment therapy (ACT), yet surpasses cognitive behavioral therapy’s (CBT) reappraisal techniques by fundamentally challenging the reality of mental constructs. Buddha-nature reframes healing as the realization of inherent potential rather than the correction of deficits, paralleling posttraumatic growth (PTG) theory in which trauma catalyzes resilience and wisdom beyond mere recovery. Bodhisattva practice transforms motivation from self-centered relief to altruistic fulfillment, promoting prosocial behavior through compassion training—supported by evidence of enhanced empathy, gratitude, and reduced bias. Non-duality fosters psychological flexibility, integrating opposing experiences such as pleasure and pain, enabling value-driven living amid distress, as demonstrated in studies of emotional adaptability. Collectively, these pillars define Eastern mindfulness as a wisdom-oriented psychotherapeutic model that unites ethical, cognitive, and relational dimensions.
    The practice architecture is reconstructed through the Three Trainings as an interdependent psychological model. Morality (śīla) functions as ethical self-regulation, reducing inner conflict and strengthening psychological immunity through disciplined conduct, establishing a secure foundation for deeper contemplative work. Concentration (samādhi) enhances attentional stability and emotional regulation via focused-attention and loving-kindness meditation, bridging external behavioral harmony with internal cognitive clarity. Wisdom (prajñā) culminates in metacognitive insight, paralleling open monitoring meditation, deconstructing the illusion of self for profound transformation. Unlike Theravāda’s emphasis on individual liberation, Mahāyāna’s prajñā integrates altruistic insight, emphasizing compassionate awakening. This spiral progression ensures comprehensiveness, as each training reciprocally reinforces the others, forming a dynamic system of behavioral ethics, cognitive clarity, and transcendental understanding. The study further outlines these mappings through conceptual modeling, highlighting how Eastern mindfulness fuses Buddhist ethics, Confucian moral harmony, and Daoist natural balance into a relational, holistic approach that surpasses Western models focused solely on attention and awareness.
    Clinically, although direct randomized controlled trials (RCTs) on the integrated Eastern framework are limited, aggregated evidence from related interventions supports its efficacy. Compassion and loving-kindness meditation reduce anxiety, enhance positive affect, and improve social cognition. Body-mind practices such as Qigong and Baduanjin alleviate depression, stress, and inflammation by upregulating serotonin and brain-derived neurotrophic factor (BDNF), and by modulating autonomic nervous system activity. Ethical and compassion-based practices reduce compassion fatigue and strengthen prosocial connectedness, while wisdom-oriented practices foster non-dual awareness and self-transcendence, mitigating self-centered cognition.
    At the neural-physiological level, the model innovatively delineates multi-pathway integrations. Morality engages compassion-prosocial circuits, activating the dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (TPJ) for empathy while downregulating the amygdala to achieve emotional equilibrium, with gamma synchrony marking stable trait changes. Concentration modulates default mode-executive control network (DMN-ECN) dynamics, reducing rumination via posterior cingulate cortex (PCC) deactivation and enhancing executive regulation through anterior cingulate (ACC) and prefrontal (PFC) engagement. Wisdom activates insight-deconstruction pathways, diminishing self-referential processing in the DMN and amplifying gamma/theta oscillations linked to cognitive flexibility. Systemic effects manifest through the neuroendocrine-immune axis, where HPA-axis downregulation lowers cortisol, enhanced vagal tone increases HRV and parasympathetic dominance, and anti-inflammatory shifts (e.g., interleukin-6 reduction) foster resilience. Cultural neuroscience further clarifies that repetitive engagement in these practices shapes “culturally patterned neural activity”, accounting for Eastern mindfulness’s superior safety, ethical depth, and integrative efficacy.
    Future work should focus on empirical verification, protocol standardization, and cross-cultural adaptation. The paper calls for high-quality RCTs, neuroimaging validation, and indigenous psychometric development to establish Eastern mindfulness as a scientifically robust Chinese psychotherapy paradigm. Ultimately, this therapy-neural-culture continuum not only restores mindfulness’s Buddhist essence but also positions it as a bridge linking therapy, neuroscience, and culture, offering globally relevant insights for ethical, transformative, and culturally attuned mental health interventions, and expanding the scientific boundaries of mindfulness research.
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    Moralization: How do people ascribe moral meaning to morally neutral things?
    ZHANG Haotian
    2026, 34 (2):  348-363.  doi: 10.3724/SP.J.1042.2026.0348
    Abstract ( 363 )   PDF (1219KB) ( 349 )   Peer Review Comments
    Moralization refers to the process through which individuals ascribe moral meanings to previously neutral behaviors, beliefs, or objects. This paper systematically reviews the psychological mechanisms, theoretical models, and consequences of moralization and proposes an integrative “Cognitive-Affective-Social (CAS)” model that incorporates macro-level social factors overlooked by existing frameworks. Drawing on multidisciplinary evidence, the study advances a comprehensive understanding of how moral beliefs emerge, intensify, and influence individual and collective behavior.
    Previous research has primarily conceptualized moralization through two models: the moral amplification model (Rhee et al., 2019) and the push-and-pull model (Feinberg et al., 2019). The former delineates moralization as a two-stage process, moral recognition and moral amplification, manifested in moral judgments, attitudes, and the expansion of moral concern. The latter emphasizes the dynamic interplay between moralization (push) and de-moralization (pull) across emotional and cognitive domains. Despite their contributions, both models treat moralization as an individual-level phenomenon, neglecting the broader sociocultural contexts in which it unfolds. To address this gap, this paper introduces the “cognitive-affective-social (CAS)” integrative model of moralization, positing that moralization arises from the interactive effects of cognitive (such as perceived harm, cognitive reflection, moral identity, ideology), affective (such as disgust, anger), and social (such as inequality, cultural tightness, social crises) antecedents.
    At the cognitive level, individuals who are more sensitive to perceived harm or who view morality as central to their self-concept are more likely to moralize neutral issues. Those who endorse binding moral foundations such as loyalty, authority, and purity also tend to see neutral behaviors as moral issues. This tendency is further strengthened among individuals with conservative ideology. Affective processes, especially emotions of disgust and anger, trigger rapid moral intuitions and amplify moral condemnation. At the macro-social level, social threats such as inequality, cultural tightness, and crises (for example, pandemics or terrorism) enhance the tendency to moralize everyday behaviors. The proposed CAS model integrates these multilevel factors into a dynamic framework. The CAS model further illustrates the dynamic interactions between these three domains: social factors can trigger specific cognitive appraisals (e.g., of harm) and emotional responses (e.g., moral outrage), which in turn cause moralization. Furthermore, cognitive and emotional factors can drive moralization on their own, or function interactively as both cause and effect, ultimately working in tandem to influence the process of moralization. This integrative approach bridges micro and macro perspectives, offering a more comprehensive understanding of moralization processes.
    The paper further elaborates on the double-edged consequences of moralization. On the one hand, moralization enhances social cohesion, motivates prosocial behavior, and legitimizes collective moral norms. It sustains moral identity, strengthens goal commitment, such as healthy living and hard work, and provides psychological standing for actions. On the other hand, however, moralization can foster cognitive biases, stigmatization, polarization, and intergroup hostility. Highly moralized beliefs promote dehumanization of outgroups, the spread of misinformation, and moral dogmatism, often amplified by social media algorithms that reward moral and emotional content. Thus, moralization simultaneously stabilizes social order and fuels social conflict.
    In response to these ambivalent outcomes, the paper outlines several future research directions. First, it calls for a systematic exploration of de-moralization, the process through which individuals or societies detach moral meaning from issues once moralized. Understanding its mechanisms and potential interventions, such as intellectual humility, shared moral values, and meta-cognitive training, is essential for mitigating moral conviction. Second, it highlights the role of social media technologies in accelerating moral amplification and moral contagion, creating moral echo chambers that reinforce ideological divisions. The paper argues that future research should develop mechanistic models explaining how digital affordances such as anonymity and virality transform moral cognition and expression. Third, the paper extends the moralization framework to the age of artificial intelligence. As AI systems increasingly assume decision-making roles, humans begin to moralize AI agents themselves, treating them as moral agents, patients, or proxies depending on perceived mind attributes. This raises novel questions about the moral responsibility of AI and AI users. Empirical findings reveal that resistance to AI often stems from moral rather than instrumental objections, and that AI users are perceived as having less morality. These emerging phenomena demonstrate that moralization is not confined to human relations but extends to human-machine interaction, signaling a new frontier for moralization studies. Finally, the paper advocates developing indigenous perspectives on moralization within Chinese cultural contexts. Traditional Chinese thought, characterized by pan-moralization, infuses moral meanings into natural, material, and ritual domains. For instance, the moral symbolism embedded in jade, archery, and landscape appreciation exemplifies this tendency to moralize material and social practices as reflections of morality. Investigating these indigenous moralization phenomena will provide invaluable cultural diversity and novel insights into the global understanding of moral psychology.
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    Mechanisms of generation, situational characteristics and positive psychological effects of collective effervescence
    DUAN Ying, YIN Keli
    2026, 34 (2):  364-378.  doi: 10.3724/SP.J.1042.2026.0364
    Abstract ( 385 )   PDF (656KB) ( 430 )   Peer Review Comments
    Collective effervescence, first introduced by Émile Durkheim, refers to the intense shared emotional arousal that emerges in collective gatherings. While Durkheim emphasized its role in strengthening solidarity and shaping social norms, psychology long neglected this phenomenon due to its focus on individual processes. Over the past two decades, however, collective effervescence has re-emerged as a central topic in social psychology, benefiting from interdisciplinary approaches. This article systematically examines its psychological mechanisms, situational features, and positive outcomes, while also highlighting unresolved questions and practical implications.
    From a contemporary psychological perspective, collective effervescence is not only a strong shared emotional experience, but also a process of perceived emotional synchronization, and a sense of social connection and self-expansion that combines a sense of connection with a sense of the sacred. Unlike ordinary collective emotions, it involves reciprocal amplification, heightened unity, and transformative experiences that reshape both self-perception and group relations. Collective effervescence can arise in religious rituals, civic gatherings, cultural festivals, sports events, and everyday interactions. The digital era has further expanded it into online environments, where synchronous symbolic exchanges and mediated attention evoke collective experiences despite the absence of physical co-presence.
    The generation of collective effervescence involves multiple interacting factors. Cognitive, behavioral, and emotional processes constitute its psychological basis: participants gather in shared time and space, focus attention on common symbols, synchronize actions, and resonate emotionally with one another. Social identity theory explains the shift from individual to collective identity during collective effervescence, embodied cognition clarifies the role of bodily mimicry and synchronous movement, and emotion theories account for processes of appraisal, transmission, and amplification. Together, these perspectives demonstrate that collective effervescence entails both cognitive transformation and relational bonding.
    Situationally, collective effervescence appears both in cyclical events with deep historical traditions and in spontaneous gatherings such as protests or demonstrations. It also occurs in digital communities, where shared attention and symbolic participation sustain emotional synchrony across distance. At the individual level, collective effervescence enhances positive affect, strengthens belongingness, reduces loneliness, and elicits self-transcendent emotions such as awe and pride. These effects may endure through nostalgic recollections that renew positive feelings long after the event. At the group level, it consolidates identity, fosters cohesion, strengthens trust, and reinforces social norms.
    Nevertheless, important gaps remain. Current research has primarily emphasized bottom-up mechanisms such as mimicry and contagion, while top-down pathways—guided by cultural traditions, symbolic cues, and collective memory—require more systematic analysis. Differences between single and cyclical forms are poorly understood, particularly with respect to path dependence across repeated experiences. Moreover, while most findings highlight beneficial effects, collective effervescence can also generate negative outcomes such as irrational behavior, norm violations, or destructive group dynamics. Cultural-psychological dimensions are likewise underexplored. Collective effervescence may serve as a vehicle of cultural continuity and cross-cultural exchange, yet the processes that sustain it across diverse cultural settings remain unclear. Finally, despite the substantial practical implications of collective effervescence—with potential applications in education, community development, and organizational management, as well as in high-stress settings—empirical research on its translational value remains limited.
    In conclusion, collective effervescence is a powerful yet understudied phenomenon linking individual psychology with collective life. Future studies should explore the top-down mechanisms of emotional convergence, further investigate the generation of online collective effervescence, examine its potential negative effects and cultural psychological impacts, and actively explore its practical applications. Advancing this research will not only enrich theoretical understanding of collective experiences but also provide insights into addressing urgent societal challenges related to mental health, social cohesion, and cultural integration.
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    2025 Reviewer List of "Advances in Psychological Science"
    2026, 34 (2):  379-380. 
    Abstract ( 129 )   PDF (242KB) ( 119 )  
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