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ISSN 0439-755X
CN 11-1911/B

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    25 November 2026, Volume 58 Issue 11 Previous Issue   

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    Feedback refines visual perception by reducing sensory noise and calibrating perception-action mapping
    SUN Qi
    2026, 58 (11):  2167-2177.  doi: 10.3724/SP.J.1041.2026.2167
    Abstract ( 41 )   HTML ( 3 )  
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    It has been proposed that systematic biases in visual perception can be consistent with a cascaded computational framework of “efficient encoding—Bayesian decoding—perceptual–response mapping.” However, this framework has primarily been developed for open-loop perception under no-feedback conditions. Feedback is a core component of perceptual learning, yet its computational locus within this cascade remains unclear. In the present study, we employed a 2 (feedback: present/absent, between-subjects) × 3 (response range: 80°, 160°, 240°, within-subjects) mixed experimental design, combined with seven alternative Bayesian observer models, to systematically examine how feedback modulates sensory noise ($\kappa $), prior integration weight ($w$), and the mapping scaling factor ($\alpha $). Behavioral results showed that feedback significantly attenuated overestimation bias and reduced estimation variability under wide response ranges. Model comparison identified the best-fitting model, whose parameters revealed that feedback significantly increased sensory encoding precision (larger $\kappa $) and decreased mapping gain (smaller $\alpha $), whereas prior integration weight ($w$) did not change significantly. These findings indicate that feedback optimizes visual perception through a dual mechanism—reducing sensory encoding noise and calibrating perceptual–response mapping gain—rather than by updating prior beliefs. At the computational level, this supports the separability of prior construction and feedback-driven modulation, and extends the open-loop perception framework to closed-loop learning scenarios.

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    Perspective Taking Shapes Creative Performance in Human-AI Collaboration*
    ZHANG Man, PENG Yang, WANG Yajie, HU Huiqing, CHEN Shi, ZHAO Qingbai
    2026, 58 (11):  2178-2199.  doi: 10.3724/SP.J.1041.2026.2178
    Abstract ( 71 )   HTML ( 1 )  
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    Group creativity is widely viewed as an emergent product of individual creativity and the interaction processes among group members. Throughout ongoing interactions, individuals continuously build on one another’s prior ideas, enabling the creative process to emerge dynamically at the group level. Within this process, perspective-taking has been recognized as a core cognitive mechanism. Perspective-taking refers to understanding problems, ideas, and situations from others’ viewpoints. With the rapid development of generative artificial intelligence (AI), AI is increasingly participating in creative tasks as a collaborative partner rather than merely as a tool. However, whether human-AI collaboration differs from human-human collaboration in terms of creative performance and perspective-taking behavior remains unclear. In addition, the actor-partner interdependence model (APIM) posits that an individual’s creative performance can be influenced by both their own perspective-taking behavior (actor effects) and their partner’s perspective-taking behaviors (partner effects). Whether these actor and partner effects differ between human-human and human-AI collaboration has not yet been systematically investigated.

    This study employed a between-subjects experimental design with a sample of 169 university students, who were randomly assigned to either the human-human collaboration or human-AI collaboration groups. Participants completed two creative tasks, the Alternative Uses Task (AUT) and the Product Improvement Task (PIT), During the tasks, they interacted with their partners (human or AI) via a custom-built online chat platform and took turns to generate creative ideas within a fixed time limit. Creative performance was evaluated in terms of novelty, usefulness, fluency, and flexibility. Perspective-taking behavior was quantified based on idea-category overlap between partners. Immediate perspective-taking was coded when participant’s idea fell into the same category as the partner’s immediately preceding idea, whereas delayed perspective-taking was coded when it matched a category introduced by the partner earlier in the interaction.

    The results showed that: (1) In both AUT and PIT tasks, human-AI collaboration showed significantly higher idea novelty and more frequent perspective-taking than human-human collaboration. (2) The relationship between perspective-taking and creative performance varied across the two collaboration types, tasks, and creativity indicators. In human-human collaboration group, both the actor and partner effects of perspective-taking on idea fluency were significantly positive across both tasks. The partner effect of perspective taking on idea flexibility was significantly positive only in the PIT. In human-AI collaboration group, AI’s immediate perspective-taking exhibited significant positive actor and partner effects on idea fluency in the AUT task, whereas humans’ immediate perspective-taking exhibited significant negative actor and partner effects on idea flexibility. In the PIT task, humans’ delayed perspective-taking exhibited significant positive actor and partner effects on idea fluency and flexibility, whereas AI’s delayed perspective-taking exhibited significant negative actor and partner effects on idea novelty.

    These findings suggest that the effects of perspective-taking on creative performance differ between human-human and human-AI collaboration. Specifically, its effects vary across creativity tasks, creativity indicators, and collaborator roles. Our findings extend theoretical accounts of collaborative creativity and provide new insights into the creative dynamics of human-AI collaboration.

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    Effects of AI viewpoint divergence on group creative performance: Cognitive-neural mechanisms
    ZHOU Zhihao, QIAO Xinuo, ZHANG Wenyu, TONG Shuai, HAO Ning
    2026, 58 (11):  2200-2217.  doi: 10.3724/SP.J.1041.2026.2200
    Abstract ( 70 )   HTML ( 1 )  
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    Generative AI is increasingly integrated into collaborative work, yet how characteristics of AI-generated viewpoints shape group creative performance remains insufficiently understood. AI viewpoint divergence refers to the extent to which AI-generated viewpoints are distributed across semantic space and differ in content. Drawing primarily on the Motivated Information Processing in Groups model, this study examined whether high versus low AI viewpoint divergence differentially affects the novelty and usefulness of group ideas in scientific and everyday creativity tasks. It also examined whether these effects are associated with cognitive processing variables and prefrontal neural indicators during human-AI co-creation.

    We designed a dyad-AI collaborative paradigm in which two participants worked with AI to complete one scientific and one everyday creativity task. We recruited 180 participants. After excluding one dyad because one participant did not follow the task instructions, the final sample comprised 89 dyads (44 in the high-divergence condition and 45 in the low-divergence condition). We used a 2 × 2 mixed design, with AI viewpoint divergence as a between-dyad factor and task type as a within-dyad factor. Group creative performance was assessed in terms of novelty and usefulness. We also measured AI utilization strategies, perspective-taking strategies, and semantic features of human-generated and group-generated ideas, and used fNIRS hyperscanning to measure prefrontal inter-brain synchronization and intra-brain functional connectivity.

    Manipulation checks showed that AI-generated viewpoints in the high-divergence condition were more semantically dispersed than those in the low-divergence condition. High AI viewpoint divergence increased the novelty of group ideas, but this benefit emerged primarily in the everyday creativity task. In contrast, high AI viewpoint divergence reduced the usefulness of group ideas across both task types. Mediation analyses showed that AI exclusion-based generation strategies and semantic features of human ideas mediated the association between AI viewpoint divergence and group creative performance. Brain-behavior integration analyses further indicated that prefrontal inter-brain synchronization and intra-brain functional connectivity were indirectly associated with novelty and usefulness through AI utilization strategies, perspective-taking strategies, and semantic features.

    These findings indicate that AI viewpoint divergence does not uniformly enhance group creativity. Instead, its effects depend on task constraints and on how groups search for, select, adopt, and semantically reorganize AI-generated information. The study extends the application of the Motivated Information Processing in Groups model to human-AI co-creation and provides empirical evidence for cognitive processing pathways and neural associations linking AI viewpoint divergence to the distinct outcomes of novelty and usefulness in group creative performance. Practically, AI support for creative collaboration should be calibrated to task openness, domain constraints, and the stage-specific demands of idea generation and evaluation.

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    Dynamic effects of multiround positive and negative feedback from robots and humans on trust and collaboration
    XUAN Hongzhou, ZHU Jiaying, LAI Qianen, HE Guibing
    2026, 58 (11):  2218-2235.  doi: 10.3724/SP.J.1041.2026.2218
    Abstract ( 41 )   HTML ( 2 )  
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    Human-robot collaboration is gradually emerging as a new mode of work in intelligent organizations. Trust serves as the foundation for cooperation among team members, and it is established and dynamically evolves through interaction. Therefore, it is particularly important to understand how human-robot interaction influences trust and how this process differs from interpersonal interaction. Through one pilot experiment and two formal experiments, the present study examined, from a dynamic perspective, the effects of multi-round feedback from robot versus human sources on the evolution of trust and cooperation. The pilot experiment was conducted to select appropriate positive and negative feedback statements. In the formal experiments, participants collaborated with either a robot or a human teammate to complete five rounds of an investment decision-making task, during which they evaluated each other between rounds. Participants received four rounds of negative feedback from either a robot or a human teammate in Experiment 1, and four rounds of positive feedback in Experiment 2. The results showed that, in the context of multi-round negative feedback, trust and cooperation exhibited a clearer source-dependent pattern. Specifically, under robot-generated negative feedback, trust and cooperation were more likely to follow a “lagged-cumulative” evolutionary pattern, characterized by delayed responses and cumulative effects. In contrast, under human-generated negative feedback, trust and cooperation were more likely to follow an “immediate-responsive” evolutionary pattern, characterized by higher sensitivity and stronger adaptability. However, in the context of multi-round positive feedback, no significant differences were found in the dynamic effects of different feedback sources on trust and cooperation. This study provides empirical evidence for understanding the differentiated evolution of human-robot trust and interpersonal trust from a dynamic perspective, and offers practical implications for the design of feedback strategies in hybrid teams.

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    The animacy effect in visuospatial memory: Facilitating item memory while impairing location integration
    CHENG Shi, YU Lu, LI Haojun, LIU Jichao, LI Xuanxuan, ZHAO Xiaomei
    2026, 58 (11):  2236-2250.  doi: 10.3724/SP.J.1041.2026.2236
    Abstract ( 37 )   HTML ( 1 )  
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    The modulation mechanism of multisensory category learning on feature processing and category selection*
    WU Jie, CHE Zixuan
    2026, 58 (11):  2251-2269.  doi: 10.3724/SP.J.1041.2026.2251
    Abstract ( 39 )   HTML ( 1 )  
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    Although prior research has investigated how unisensory training modulates perceptual sensitivity and decision criteria, the computational mechanisms and neural underpinnings associated with category learning through coordinated auditory-visual experience remain insufficiently characterized. To address this gap, the present study systematically examines how multisensory category learning reconfigures the temporal dynamics of feature processing and category selection. We combined high-temporal-resolution electroencephalography (EEG) with trial-by-trial hierarchical Bayesian drift-diffusion modeling (HDDM) to jointly characterize neural response trajectories and latent cognitive processes.

    The participants first completed a multisensory category-learning phase. Four arbitrary categories were defined by orthogonal auditory (pure-tone frequency) and visual (vehicle shape) morph continua. Each category corresponded to a distinct quadrant in the resulting two-dimensional stimulus space. Participants received accuracy feedback after every response. In the subsequent test phase, participants performed a two-alternative odd-ball task; on each trial, they judged on whether a briefly presented multisensory stimulus belonged to a prespecified target category or to any of the three nontarget categories. Critically, the stimuli were varied parametrically along both the auditory and visual continua. Half of the trials featured prototypical exemplars (0% morph distance from the category centroid), whereas the other half featured high-variance exemplars (±49% morph distance). This finding fully crossed, orthogonal manipulation of perceptual typicality (prototype vs. deviant) and decision relevance (target vs. nontarget) enabled a functional dissociation between neural processes supporting early feature processing and those subserving category selection information.

    The behavioral results revealed that prototypical stimuli were classified with significantly higher accuracy and shorter reaction times than deviant stimuli were. In contrast, nontargeted decisions were both more accurate and faster than target decisions were, whereas nontarget trials comprised a heterogeneous set of within- and between-category deviants. To isolate the latent cognitive mechanisms underlying these behavioral dissociations, we applied hierarchical Bayesian drift-diffusion modeling (HDDM). With respect to stimulus typicality, prototypes were associated with higher drift rates (v), more conservative decision thresholds (a), and stronger starting-point biases (z) toward the correct response boundary. With respect to decision relevance, target decisions exhibited lower drift rates, more liberal thresholds, and attenuated starting-point biases than nontarget decisions did. Neurophysiological analyses extended these computational insights. Prototypical stimuli elicited larger N250 amplitudes over bilateral occipital-temporal electrodes, followed by enhanced frontal selection positivity (FSP) and a late positive component (LPC) over fronto-central and parietal electrodes. Time-frequency analyses further revealed concomitant increases in alpha and beta power over the parietal and occipital regions. In contrast, target decisions were associated with the larger FSP and dual-peaked LPC complexes over frontoparietal sites. They were also accompanied by widespread suppression of alpha and beta oscillations. Importantly, multivariate ridge regression indicated that trial-level FSP amplitudes and alpha/beta power positively predicted drift rates for deviant stimuli. With respect to target categorization, both FSP/LPC amplitudes and alpha/beta power positively predicted drift rates. Moreover, alpha power exerted a robust negative influence on decision thresholds for both the deviant and target conditions.

    Collectively, these findings support a dual-pathway architecture dynamically shaped by multisensory category learning. A rapid feed-forward pathway, indexed by the FSP and increased alpha/beta synchrony over parieto-occipital regions, supports the automatic extraction of diagnostic multisensory features, operating independently of current task demands. A slower, memory-dependent pathway—characterized by functional coupling between the FSP and the late positive complex (LPC), alongside desynchronization of alpha/beta oscillations—is engaged during active rule retrieval and conflict monitoring, particularly under conditions of decision uncertainty.

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    The Normalization Mechanism of Emotional Modulation on Rhythmic Temporal Attention
    CAI Jinfang, WANG Sibo, YUE Xiaoxi, LIN Youting, SUN Yanliang
    2026, 58 (11):  2270-2288.  doi: 10.3724/SP.J.1041.2026.2270
    Abstract ( 41 )   HTML ( 1 )  
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    Emotion fundamentally reconfigures the allocation of attentional resources. Although the normalization model of attention has well explained the regulatory mechanism of emotion on spatial attention, how emotion regulates rhythmic temporal attention through underlying neural computational gain mechanisms remains unclear. Grounded in the normalization framework, the present study investigates whether emotional states regulate temporal attention through specific gain computations and how they alter the trajectory of expectation formation. We hypothesized that distinct emotional valences would recruit qualitatively different strategies (response gain versus contrast gain) to modulate steady-state processing, while simultaneously reshaping the temporal dynamics of attentional deployment to accommodate environmental uncertainty.

    Two experiments were conducted involving 26 healthy Han Chinese university students (13 in Experiment 1; 13 in Experiment 2). In Experiment 1, a 3 (Emotional valence: positive, neutral, negative) × 2 (Rhythmic validity: valid, invalid) × 5 (Stimulus contrast) within-subjects factorial design was employed. Emotional states were induced via validated audiovisual clips. Participants completed an orientation discrimination task using Gabor targets embedded within rhythmic streams. To mathematically characterize the attentional gain profiles, the Naka-Rushton equation was fitted to the discriminability (d') data for each participant. This allowed for the precise decomposition of modulation into response gain (amplification of asymptotic response, indexed by d'max) and contrast gain (enhancement of sensitivity, indexed by c50). Experiment 2 investigated the dynamic evolution of attentional allocation using a 3 (Emotional valence) × 5 (Rhythmic strength: 1 to 5 cues) × 2 (Rhythmic validity) design with target contrast fixed at a supra- threshold level. Crucially, we extended the dynamic normalization model by incorporating a parameterized rhythmic strength coefficient to quantify the accumulation of attentional gain over time. This extended model was optimized against behavioral data using Bayesian Adaptive Direct Search (BADS) to estimate the parameters governing the temporal distribution of attentional weights (wav).

    Experiment 1 revealed a robust valence-dependent dissociation in gain mechanisms. Under negative emotional states, the attentional gain (defined as the d' differential between valid and invalid conditions) exhibited a monotonic increase as a function of stimulus contrast. Computational modeling confirmed that negative emotion selectively elevated d'max in valid trials without modulating c50, a signature characteristic of a response gain mechanism. Conversely, positive and neutral emotions yielded a non-monotonic, inverted-U shaped gain function. Model parameters indicated a significant reduction in the semi-saturation constant (c50) for valid trials under positive emotion, with no significant alteration in d'max, indicative of a contrast gain mechanism. Experiment 2 demonstrated that while rhythmic cueing facilitated performance across all conditions, emotion significantly modulated the magnitude and temporal precision of this effect. The reaction time validity effect was markedly attenuated under both positive and negative emotions relative to the neutral condition. The extended dynamic normalization model achieved an exceptional goodness-of-fit (R-squared > 90%) across conditions. Parameter analysis revealed that in neutral states, attentional resources were sharply focused on the predicted time point; however, under emotional arousal (both positive and negative), the distribution of attentional resources became significantly more equipotent between valid and invalid intervals. This finding suggests that emotion flattens the temporal weighting function, effectively broadening the temporal window of attention.

    This study constitutes the first empirical and computational instantiation of the normalization model within the domain of emotional modulation of rhythmic temporal attention. The findings establish a dual regulatory framework: emotion selects distinct steady-state gain mechanisms based on valence—amplifying signal magnitude via response gain under negative emotion (supporting a “threat-vigilance” mode) and enhancing perceptual sensitivity via contrast gain under positive emotion (supporting an “opportunity-seeking” mode). Furthermore, emotion promotes dynamic flexibility by expanding the temporal attentional window. This broadening reflects a strategic trade-off wherein the cognitive system sacrifices peak temporal precision to maintain heightened sensitivity to unexpected events in volatile environments. Collectively, these results validate the normalization model as a canonical framework for deciphering emotion-cognition interactions and underscore the critical role of emotion in dynamically reconfiguring the computational architecture of temporal attention.

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    When movement meets beauty: The embodied influence of horizontal movement on facial aesthetic judgment considering gender differences
    LI Linghe, REN Weicong, HAN Haibin, WANG Hanlin
    2026, 58 (11):  2289-2307.  doi: 10.3724/SP.J.1041.2026.2289
    Abstract ( 42 )   HTML ( 1 )  
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    Recent research in embodied cognition suggests that bodily movements influence abstract cognitive processes, including aesthetic evaluation, through metaphorical associations. The focus of this study is on how horizontal hand movements affect facial aesthetic judgments and whether these embodied effects vary by gender. Building on the idea that directional movements are metaphorically associated with evaluative concepts, we hypothesized that enacting leftward movement would enhance aesthetic perception and decision efficiency compared with rightward movement. We also hypothesized that this effect would be more pronounced in female participants and that manipulating spatial reference points would modulate the approach-avoidance tendencies underlying the metaphorical mappings.

    Three experiments were conducted with a study group of 143 right-handed Chinese university students, all with normal or corrected-to-normal vision and no history of neurological or psychological disorders. In each experiment, participants performed aesthetic judgments on facial images associated with varying levels of attractiveness while executing horizontal hand movements or key presses. All facial stimuli were selected from standardized databases and were uniformly processed. Electroencephalography data were recorded in all experiments using 64-channel electrode caps based on the international 10-20 system, and behavioral responses were collected using E-Prime software. The variables of the experimental design included the joint classification response condition and spatial reference position, while gender was treated as a between-participants variable. Data were analyzed using mixed-design analysis of variance (ANOVA), hierarchical drift diffusion modeling, and event-related potentials (ERPs) techniques to examine behavioral differences and their underlying cognitive and neural mechanisms.

    The results supported our hypotheses. In the metaphor-congruent trials, participants responded more quickly and accurately in facial aesthetic judgments than in metaphor-incongruent trials, suggesting that directional motor actions facilitated aesthetic processing when aligned with metaphorical associations. Hierarchical drift diffusion model (HDDM)analyses further revealed that performing leftward movement increased drift rate, decreased the decision threshold, and shortened non-decision time, indicating more efficient evidence accumulation and less cautious decision-making. These effects were particularly pronounced among female participants, reflecting gender differences in embodied sensitivity. ERP data provided converging neural evidence: the N170 component showed greater amplitudes under leftward movement, indicating enhanced early-stage face processing; both EPN and P300 amplitudes were also elevated in metaphor-congruent conditions, reflecting stronger emotional engagement and evaluative motivation. Notably, gender differences were significant in some experiments, with female participants showing faster responses and stronger approach-oriented tendencies; however, in experiment 3, when spatial reference frames were manipulated to modulate approach-avoidance tendencies, this gender effect was strongly reduced, suggesting that contextual reference plays a regulatory role in embodied aesthetic processing.

    In this study, we demonstrated that horizontal motor experience exerts an embodied influence on facial aesthetic processing, and that this effect varies by gender. Behavioral, computational, and neurophysiological evidence revealed that aesthetic judgments are shaped not only by visual input, but also by motor actions and their metaphorical associations. This study expands the understanding of embodied aesthetics and highlights gender differences in sensitivity to embodied cues. These findings have practical implications for product design, user interfaces, and marketing, especially when motion-based interaction influences evaluation. Optimizing embodied interaction design requires attention to individual differences, particularly gender.

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    The joint modulation of language distance and task demands on the neural mechanisms underlying bilingual lexical processing
    QI Yun, CAI Wenqi, LI Zhilin, YANG Jianfeng, WANG Xiaojuan
    2026, 58 (11):  2308-2321.  doi: 10.3724/SP.J.1041.2026.2308
    Abstract ( 44 )   HTML ( 1 )  
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    Whether bilinguals share the same neural mechanisms for processing their first language (L1) and second language (L2) is a question of broad interest to researchers. Existing studies have accumulated substantial evidence, yet findings remain divergent. The primary sources of inconsistency lie in the language distance between bilinguals' L1 and L2, as well as differences in experimental tasks. Leveraging the advantages of meta-analysis, the present study examined brain activation patterns during L1 and L2 lexical processing in two groups of bilinguals: Chinese-English bilinguals with distant language distance (logographically-alphabetic) and alphabetic-alphabetic bilinguals with close language distance—across different tasks (phonological and semantic). Results showed that in phonological tasks, Chinese-English bilinguals recruited the left inferior parietal lobule/supramarginal gyrus more for L2, a region implicated in orthography-to-phonology conversion; in contrast, alphabetic bilinguals with close language distance shared overlapping neural mechanisms for L1 and L2. In semantic tasks, Chinese-English bilinguals engaged the left middle frontal gyrus and left precuneus more for L1 to support orthography-to-semantics conversion. In contrast, alphabetic bilinguals recruited the left middle temporal gyrus more for L1 for phonology-to-semantics conversion, and engaged language-control regions including the left middle frontal gyrus/inferior frontal gyrus, insula, and inferior parietal lobule more for L2. Further comparisons of brain activation during language-switching tasks between the two bilingual groups also revealed that alphabetic bilinguals with close language distance required greater involvement of executive control regions. Collectively, these findings indicate that the differential brain activation patterns observed when bilinguals process L1 and L2 arise from differences in underlying cognitive processes, jointly driven by language distance and task demands.

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    P300-based CIT can reveal fake identity information
    Jiayu CHENG, Haoran WANG, Wang FENG, Genyue FU, Liyang SAI
    2026, 58 (11):  2322-2336.  doi: 10.3724/SP.J.1041.2026.2322
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    Enhanced reactive inhibition but impaired intentional inhibition in individuals with heroin use disorder
    XU Mengsi, WU Shiyan, XU Yanxi, WANG Zhenhong
    2026, 58 (11):  2337-2354.  doi: 10.3724/SP.J.1041.2026.2337
    Abstract ( 57 )   HTML ( 4 )  
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    Asymmetry of diagnostic information integration in audiovisual category learning
    LIN Yunyi, HUANG Danyang, HUANG Hui, TANG Wenqin, LIU Zhiya
    2026, 58 (11):  2355-2370.  doi: 10.3724/SP.J.1041.2026.2355
    Abstract ( 39 )   HTML ( 2 )  
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    The present study employed a family resemblance category learning paradigm to investigate the integration mechanisms and asymmetry of audiovisual diagnostic information in multidimensional category learning. A total of 153 college students participated in two experiments, and computational modeling was used to analyze the categorical representations formed after learning. Experiment 1 examined the influence of auditory diagnosticity on visual category learning by manipulating auditory diagnosticity at three levels: high (0.9), congruent (0.75), and low (0.6). Results showed that when audiovisual diagnosticity was congruent, learners processed information from both modalities most effectively, demonstrating cross-modal integration gain. Experiment 2 examined the influence of visual diagnosticity on auditory category learning and found that the integration gain under the congruent condition did not emerge; visual diagnosticity had no significant effect on the acquisition of auditory feature dimensions, reflecting the relative independence of audiovisual information processing. Overall, cross-modal information integration in multidimensional category learning is asymmetric: visual tasks can integrate auditory information, whereas auditory tasks show only limited integration of visual information. This study provides the first evidence for the learning efficiency and representational strategies in multidimensional auditory category learning and discusses differences in representational mechanisms between visual and auditory category learning.

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    Associations between working memory and mathematical ability in elementary school children: A cross-grade network analysis
    ZHU Xiaoliang, QIU Hongxiao, LIN Liang, WANG Xinliang, YANG Xiujie, ZHAO Xin
    2026, 58 (11):  2371-2389.  doi: 10.3724/SP.J.1041.2026.2371
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    Despite extensive research demonstrating a close relationship between working memory (WM) and mathematical ability, the specific associations between the subcomponents of these two constructs and their developmental trends across grades remain unclear. In the present study, we recruited 875 children from lower (Grade 1), middle (Grade 3), and upper (Grade 5) elementary school grades and used a network analysis approach to systematically examine the relations between WM subcomponents and different domains of mathematical ability, as well as whether these relations vary across grades. The results showed that, in the lower grades, verbal WM capacity and verbal WM updating had the strongest positive associations with arithmetic ability; visuospatial WM capacity showed the strongest positive association with arithmetic ability among children in the middle and upper grades; and verbal WM capacity was most strongly associated with logical thinking in the middle grades and with spatial imagination in the upper grades. Furthermore, network comparisons revealed that the connection strength between verbal WM updating and arithmetic ability was significantly weaker in the middle grades than in the lower and upper grades, and that the connection strength between verbal WM updating and spatial imagination was significantly weaker in the lower grades than in the upper grades. This study offers a new perspective on the relationship between WM and mathematical ability and its developmental patterns, carrying important educational implications for designing interventions to enhance mathematical ability in school-age children.

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    Warmth or competence? Exploring the impact of donation recognition on subsequent donations and information sharing
    ZHU Yue, ZHANG Anran, XU Zhengliang
    2026, 58 (11):  2390-2404.  doi: 10.3724/SP.J.1041.2026.2390
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    An increasing number of charitable organizations provide recognition for donations to encourage subsequent donations and information sharing, thereby enhancing donor retention and expanding their influence. Drawing on objective self-awareness theory, self-consistency theory, and impression-management theory, this study examines how different recognition sources and types affect subsequent donations and information sharing, as well as the underlying mechanisms. Across one field experiment and three laboratory experiments, the results show that when beneficiaries provided recognition, warmth-based recognition (vs. competence-based recognition) induces donors to enter an objective self-awareness, which subsequently activates self-consistency motives and increases their intention to donate again. In contrast, when charitable organizations provided recognition, competence-based recognition (vs. warmth-based recognition) strengthens donors’ subjective self-awareness, which subsequently activates impression-management motives and increases their intention to share the recognition. By revealing the differential effects and underlying mechanisms of recognition source and type on donors’ subsequent donations and information sharing, this study not only extends the literature on donation recognition but also provides implications for charitable organizations in designing donation recognition.

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