ISSN 1671-3710
CN 11-4766/R

Current Issue

    For Selected: Toggle Thumbnails
    Conceptual Framework
    Cross-modal analysis of facial EMG in micro-expressions and data annotation algorithm
    WANG Su-Jing, WANG Yan, Li Jingting, DONG Zizhao, ZHANG Jianhang, LIU Ye
    2024, 32 (1):  1-13.  doi: 10.3724/SP.J.1042.2024.00001
    Abstract ( 332 )   PDF (2775KB) ( 521 )   Peer Review Comments
    Micro-expression analysis combined with deep learning has become a major trend. However, the small sample size problem has always hindered the further development of micro-expression analysis relying on deep learning. Micro-expressions are brief, subtle facial expressions, so the time cost and labor cost of micro-expression data annotation are very high, which leads to the problem of small sample size. To further improve the performance of micro-expression spotting and recognition, a huge amount of micro-expression samples is still needed for deep learning model training. Consequently, this research direction has an urgent desire to solve the problem of micro-expression data annotation. To address this issue, our research uses facial electromyographic (EMG) signals as a technical means to propose a set of solutions to the problem of micro-expression annotation from three aspects: automatic annotation, semi-automatic annotation, and unsupervised annotation of micro-expression data.
    First, we use physiological psychology methods to combine facial EMG signals and behavioral cognitive psychology experiments to explore the physiological characteristics of micro-expressions. In this study, we recorded the signal frequency and amplitude during the contraction of facial muscles or muscle groups. And relevant EMG metrics were used to accurately and objectively quantify the three features of micro-expressions, namely, short presentation time, small movement amplitude, and asymmetry, to provide a theoretical basis for subsequent research on annotation and intelligent analysis of micro-expressions.
    Second, for automatic annotation, this study proposes an automatic annotation scheme for micro-expressions based on distal facial electromyography. Specifically, we deploy EMG electrodes around the face without obscuring the facial expression being expressed. In this way, automatic annotation of micro-expression data by combining EMG information with video is implemented. Meantime, we design a psychological paradigm for inducing facial muscle movements. And based on the electromyographic signal pattern of micro-expressions, we develop an algorithm for automatic micro-expression annotation. Finally, we integrated the automatic annotation process and designed an automated annotation interactive software, which can greatly save the time of micro-expression annotation, reduce the workload of micro-expression coders, and solve the problem of small samples in micro-expression database to a certain extent.
    Third, for semi-automatic annotation, we focus on the temporal action localization of micro-expressions (METL), i.e., the process of inferring the onset and offset frames of a micro-expression segment, based on the manual annotation of a single frame within that micro-expression. In particular, we propose a Micro-Expression Contrastive Identification Annotation (MECIA) method as a solution to METL. The backbone of the proposed MECIA method is a deep learning network. The network contains three modules: a contrastive module, an identification module, and an annotation module, corresponding to the three steps of manual annotation. The network's outputs infer the temporal localization of micro-expression clips. The experiments demonstrate that our inferred micro-expression intervals can correspond well to ground-truth intervals, demonstrating the potential of this approach to improve the efficiency of vision-based micro-expression annotation.
    Fourth, for unsupervised annotation, due to the limited number of annotated micro-expression samples, we propose a self-supervised learning-based micro-expression analysis algorithm implemented in massive unsupervised annotation face and expression videos. Precisely, we provide time-domain supervised information for unsupervised annotation face videos based on the correspondence between facial EMG and facial expressions. And we design a Transformer-based self-supervised model for cross-modal contrastive learning, which utilizes EMG signals to enhance network learning of features targeting micro-expression action change patterns. Specifically, the introduction of EMG signals enhances the contrastive learning model to capture the weak dynamic facial changes in the time domain. This self-supervised learning model incorporating EMG signals can strengthen the model's understanding of visual features. In addition, cross-modal learning allows the model to learn more generalized features and enhance the robustness of the system.
    References | Related Articles | Metrics
    Effect of attachment-relevant episodic simulation on adult attachment security
    CAO Xiancai, WANG Dahua, BAI Xuejun
    2024, 32 (1):  14-26.  doi: 10.3724/SP.J.1042.2024.00014
    Abstract ( 631 )   PDF (758KB) ( 1056 )   Peer Review Comments
    Considering the positive effect of secure attachment on relationships and well-being, the plasticity of attachment is an important research topic in the field of adult attachment. To explore the plasticity of attachment, we first need to understand how individuals attain attachment security. The control-system model of attachment posits that the way for individuals to attain security is to access the internal representation of attachment. Previous research only concentrated on accessing the secure-base script, which is a kind of internal representation including a series of procedural knowledge that summarizes the basic features of receiving support from an attachment figure, to attain attachment security. However, the function of attachment-relevant episodic simulation is overlooked during this process. Attachment-relevant episodic simulation refers to mentally simulating a series of future episodes regarding successfully support seeking and receiving support during distressful situations. Inspired by the research on episodic simulation, our previous research proposed and confirmed that attachment-relevant episodic simulation could also act as a way to attain security in the control-system model of attachment. However several research questions remain unsolved. What's the uniqueness of the attachment-relevant episodic simulation when acting as a way to attain attachment security? What's the mechanism of this effect? And how to conduct attachment intervention inspired by this new route. This research proposal will solve these questions through three studies.
    First, Study 1 will investigate the effect of attachment-relevant episodic simulation on adult attachment security and its uniqueness. We will compare the attachment-relevant episodic simulation with other ways of attaining security in their frequency of use, effect, and to what extent affected by attachment orientations during daily life. Besides, study 1 also wants to explore in which situation individuals will depend more on attachment-relevant episodic simulation to attain attachment security.
    Second, Study 2 will investigate the mechanism of this effect from the content and the cognitive process of attachment-relevant episodic simulation. Four experiments will be conducted to compare the effect of attachment-relevant episodic simulation with attachment-relevant semantic thinking, attachment-irrelevant episodic simulation, positive emotion induction, and attachment-relevant episodic simulation of unrelated situations. Another two experiments will use the episodic specificity induction and episodic coherence induction to manipulate the specificity of episodic retrieval and the coherence of episodic construction of attachment-relevant episodic simulation, then find their effect on attachment security.
    Third, based on the results of Study 2, Study 3 will use the natural language processing technique to develop several classifiers to classify the attachment-relevant episodic simulation. We developed a training procedure by using these classifiers. Firstly, we will ask participants to provide their daily distressful events and simulate attachment-relevant episodes one by one. After each simulation, the classifiers will be used to identify whether this simulation could help individuals to attain security or not, if not, then judge whether the invalid simulations derived from their content, specificity of episodic retrieval, or the coherence of episodic construction. After that, the feedback and training will be given to participants accordingly. With this training procedure, study 3 also wants to compare the short-term and long-term effect of this procedure with the repeated attachment priming method on trait attachment security.
    All in all, the current research project will provide a supplement for the attachment control-system model. Specifically, in addition to the secure base script, we proposed that attachment-relevant episodic simulation also could act as a way to attain attachment security. The results of the current project will investigate this proposition repeatedly and could learn the uniqueness and mechanism of this new path to attain security. This new path could provide an explanation for the situational flexibility of the attachment system on the one hand, and benefit for learning the plasticity of attachment and promoting trait attachment security on the other hand.
    References | Related Articles | Metrics
    Conceptualization of time poverty and its impact on well-being: From the perspective of scarcity theory
    SUN Xiaomin, YANG Shuting, KONG Xiaoshan, LIU Zhenzhen, MA Rongzi, YUAN Yue, ZHANG Nan, JIANG Xinying, CAO Peiling, BAO Ruiji, LIN Yiqin, LI Ning, LI Zhihang
    2024, 32 (1):  27-38.  doi: 10.3724/SP.J.1042.2024.00027
    Abstract ( 933 )   PDF (716KB) ( 1385 )   Peer Review Comments
    In today's fast-paced world, increasing numbers of individuals are facing time poverty, i.e., having too much to do and not enough time. It can impact people's cognitive processes and behaviors by affecting their attention. However, the extant literature provides only a limited understanding of the influence of time poverty and its effects on individual multi-faceted well-being. Therefore, a comprehensive investigation of the concept of time poverty and its impact on well-being is of great importance theoretically and practically. The current study intends to present a three-dimensional theoretical model for the construct of time poverty from an integrated perspective, aiming to explore its effects on multi-faceted subjective well-being and investigate the potential mechanisms by which time poverty reduces well-being based on scarcity theory.
    Specifically, the current study proposes a three-dimensional structure for the concept of time poverty, which includes length, intensity, and quality. Most researchers agree that spending an excessive amount of time on paid work or unpaid domestic work and having an insufficient amount of free time leads to time poverty. Moreover, the number of tasks to be completed per unit of time may be an independent source of pressure resulting in the perception of time poverty. The stressful pace caused by over-rapid task completion and too short intervals could increase the sense of time poverty. Lastly, the quality dimension of time poverty comprises time integrity, time autonomy, and time synchronization. Low time quality could worsen the perception of time poverty. Based on the three-dimensional model of time poverty, the current study aims to develop a time poverty scale and construct a large-scale Chinese time poverty database. This database is designed to collect demographic information as well as the level of time poverty of representative samples, aiming to explore the dominant type of time poverty for different demographic groups and trace the dynamic changes in time poverty over time.
    Furthermore, the current study proposes that time poverty can have a significant impact on people's well-being. Time poverty can develop a scarcity mindset, leading people to focus on the scarcity of time. Consequently, they overemphasize productivity, resulting in a strong inclination of completing more tasks in a shorter amount of time. Such a mindset shifts people's attention from the activity's process to its results, reducing intrinsic motivation and, as a result, ruining people's well-being. An excessive focus on productivity can also harm interpersonal and family well-being by underestimating the importance of investing time and energy in nurturing relationships, thereby lowering the quality of relationship-oriented interactions. Therefore, we argue that by promoting the over-productivity orientation, time poverty can adversely affect individual, interpersonal, and family well-being. Furthermore, time poverty in one spouse's workplace produces an over-productivity tendency which then spills over to the family environment and is conveyed to the other spouse in their daily interactions. Such processes are likely to negatively influence both parties' well-being.
    Overall, the current project develops a three-dimensional time poverty theoretical model, based on which a time poverty scale will be developed. With the new scale, a large-scale database will be constructed. The project will explore the experiences of different groups of people with distinct characteristics in Chinese society, and how such experiences influence personal, interpersonal, and family well-being. The results of the current project are of great importance for not only the successful coping of time poverty for individuals but also for societies aiming to improve the well-being of their people.
    References | Related Articles | Metrics
    The impact of resource type on green consumption: Is time or money more important?
    SUN Jin, CHEN Chen
    2024, 32 (1):  39-57.  doi: 10.3724/SP.J.1042.2024.00039
    Abstract ( 357 )   PDF (650KB) ( 568 )   Peer Review Comments
    Environmental issues are related to human growth in the long term, and people are becoming increasingly aware of the necessity of green consumption. Time and money are two important resource types. Individuals' green consumption behavior is inevitably affected by these two resources in cognitive thinking and decision-making. However, the underlying mechanism of how resource type affects green consumption is still unclear. In order to further explore the impact of resource type on green consumption, the present study introduces time and money into the field of green consumption and builds a theoretical framework. First of all, Study 1 reveals that time resources promote green consumption and that money resources decrease green consumption (Experiment 1). Then, based on construal level theory and human value, Study 2 investigates the underlying mechanism of the impact of time and money resources on green consumption. Specifically, time resources activate high-level construal and self-transcendence, which can promote the intention of green consumption. On the contrary, money resources stimulate low-level construal and self-enhancement, which will reduce the intention of green consumption (Experiment 2). Study 3 examines the boundary condition through individual factors: when green consumption emphasizes the interests of the whole society or others, time resources are more likely to promote consumers' willingness to purchase green products, however, when green consumption emphasizes the interests of themselves or families, money resources are more likely to promote consumers' willingness to purchase green products, and the emotional response level plays a mediating role in this effect (Experiment 3). Study 4 aims to explore the impact of nudge, which often encourages consumers to engage in green consumption. Time resources are more likely to promote consumers' willingness to explicitly ask for switching to a green mode, while money resources are more likely to promote consumers' willingness to accept a green mode as the default, and environmental self-responsibility plays an intermediary role in this effect (Experiment 4). Study 5 and Study 6 explore the moderating effects of product innovation and typicality, respectively. Time resources will lead to a higher preference for central innovative green products or typically green products, while money resources will lead to a higher preference for peripheral innovative green products or atypically green products, and product effectiveness perception plays an intermediary role in these effects (Experiments 5 and 6). The above studies not only explore the positive role of time and money resources in promoting green consumption, but also provide new ideas for companies to use resource type to guide green consumption.
    References | Related Articles | Metrics
    Regular Articles
    Emotional T2 attenuates attentional blink: A window to understanding the preferential processing of emotion
    SUN Meng, LIU Zejun, JIA Xi, SHANG Chenyang, ZHANG Qin
    2024, 32 (1):  58-74.  doi: 10.3724/SP.J.1042.2024.00058
    Abstract ( 226 )   PDF (546KB) ( 352 )   Peer Review Comments
    Attentional blink (AB) refers to the phenomenon in which identifying the first target (T1) in a series of distractors often interferes with the recognition of the second target (T2) occurring within 200~500 ms after T1. This phenomenon reflects the limitation of conscious processing in temporal dimension. However, studies have found that compared to neutral T2, emotional T2 can attenuate attentional blink. This provides an observation window and a research tool for understanding the prioritized processing of emotional stimuli in humans. The attenuation effect of emotional T2 on AB is influenced by factors such as T2 arousal, T1 task difficulty, T2 task demand, emotional expectation, and anxiety levels. It is generally believed that the arousal level of emotional T2 plays a crucial role in attenuating AB. However, when the difficulty of the T1 task increases, the preferential processing of emotional T2 is partially inhibited. Individuals determine the depth of processing for emotional target T2 based on task demands. In the detection task, emotional T2 is more easily detected as potential target compared to neutral T2, showing a detection advantage. However, whether this detection advantage can be translated into a discrimination advantage depends on the emotional relevance of the task demand. In emotion recognition tasks, task-relevant emotional information appearing within AB period can be effectively extracted. However, in non-emotion recognition tasks, the late-stage elaborate processing of task-irrelevant emotional information is inhibited by task demands and emotional expectations. Anxious individuals are more sensitive to negative emotional stimuli, which increases the attenuation effect of emotion on AB. In addition, emotional T2 still exhibits an emotional processing advantage when appearing at lag 1 compared to neutral T2, although most studies have not found the Lag 1 sparing effect of emotional T2.
    The attenuation effect of emotional T2 on AB primarily involves regions associated with reactive processing of emotional information, such as the amygdala and the anterior cingulate cortex. Patients with amygdala lesion are unable to exhibit the attenuation effect of emotional T2 on AB. The activation of the amygdala is associated with early emotional responses, while the anterior cingulate cortex may be involved in early attentional selection of emotional information. In the temporal dimension, EEG results indicate that emotional T2 has processing advantages across multiple cognitive stages compared to neutral T2, and the enhanced early-stage sensory processing of emotional information is crucial.
    Based on the two-stage model, we propose the " Attentional Enhancement and Consolidation Competition Hypothesis " hypothesis, which suggests that the processing of target mainly consists of two stages: detection and consolidation. During the early target detection stage, the emotional saliency of T2 allows the stimuli to capture attention rapidly and obtain enhanced processing. This attentional enhancement enables individuals to detect more emotional targets. Furthermore, stimuli that receive attentional enhancement during the target detection stage are less interference from masking stimuli during T1 consolidation and are more likely to enter the consolidation stage. Whether this advantage can be transformed into a consolidation advantage is influenced by top-down factors such as task demand and emotional expectation. When the task demand is related to emotional features, emotional information gains a consolidation advantage. When the task demand is related to non-emotional features, the elaborate representation of emotional information would be suppressed, especially under high emotional expectancy conditions. In summary, the attenuation effect of emotion on AB involves both automatic emotional processing and goal-oriented processing driven by top-down factors. The emotional saliency of emotional T2 itself promotes early attentional selection within the blink period, primarily driven by subcortical regions such as the amygdala. The consolidation of emotional T2 is influenced by factors such as task demand and is primarily modulated by prefrontal cortical areas associated with cognitive control.
    In future research, it would be beneficial to investigate how the amygdala, anterior cingulate cortex, and prefrontal cortex coordinate in the attenuation effect of emotion on attentional blink. Additionally, it is important to investigate whether these brain regions have separate roles in both emotion-implicit tasks and emotion-explicit tasks.
    References | Related Articles | Metrics
    How does value influences memory: A perspective from specificity
    ZHONG Yuxuan, JIANG Yingjie
    2024, 32 (1):  75-84.  doi: 10.3724/SP.J.1042.2024.00075
    Abstract ( 276 )   PDF (426KB) ( 388 )   Peer Review Comments
    Selective encoding and retrieval of valuable information are fundamental for individual survival and development, so how to guarantee the optimization of memory effects has been a key focus on memory research. In recent years, many studies have revealed the dual-mechanism for value-directed remembering, with automatic and strategic mechanisms both contributing to the differential storing of high- and low-value information. The previous studies of the dual- mechanism framework have greatly emphasized its independence, arguing that automatic and strategic mechanisms work separately. However, the present study found that both two mechanisms play a role in the process of value influence memory, the automatic mechanism and the strategic mechanism are specific to different contexts. The reward system and medial temporal lobe regions were more activated when the automatic mechanism was dominant, while deep semantic processing brain regions and executive control systems were more activated when the strategic mechanism was dominant.
    From the perspective of specificity, the present research analyzes and describes the respective roles played by the two mechanisms in terms of different learning contexts, goal-directed, test duration and age stages of the participants. The mechanisms of value influence memory are context-dependent. In the Monetary incentive encoding (MIE) paradigm, high-value information is automated to attract participants' attentional resources, the automatic mechanism plays a dominant role and the role of the strategic mechanism is almost non-existent. In the Value-directed remembering (VDR) paradigm, the strategic mechanism formed by metacognitive monitoring and control and the automatic mechanism will work together and the role of the strategic mechanism is dominant. The mechanisms of value influence memory are goal-directed. The automatic mechanism plays a dominant role when the goal of the task is recognition test and the strategic mechanism plays a dominant role when the goal of the task is free recall test. In this process, value-directed metamemory plays an important role in the selection of dual mechanisms. The mechanisms of value influence memory are time-differentiated. The automatic and strategic mechanisms overlap in time course and play a dominant role at different times, with the automatic mechanism acting over a longer time course. The mechanisms of value influence memory are age-related. In childhood and adolescence, the automatic mechanism plays a dominant role and strategic mechanism begins to play a gradual role. In adulthood, automatic and strategic mechanisms play different roles in different contexts. In old age, strategic mechanism plays a dominant role and the role of automatic mechanism diminishes.
    In summary, the mechanisms of value influence memory are specific, with learning contexts being the Monetary incentive encoding paradigm, goal-directed being recognition test, long delayed tests and pre-adulthood, where the automatic mechanism dominate. With learning contexts being the Value-directed remembering paradigm, goal-directed being free recall test, short immediate tests and post-adulthood, where strategic mechanism dominate. In-depth research on dual mechanisms of value-directed remembering can further reveal the modulating effect of reward on human memory and its neural basis, but there are the following issues to be further explored in this field: First, most of the current studies separate the roles of the two mechanisms and future studies should explore the roles that automatic and strategic mechanisms play together in different contexts. Second, the Monetary incentive encoding paradigm and the Value-directed remembering paradigm have two factors that affect the experimental results, namely goal-directed and interspersed testing, which are inseparable and whose specific impact on dual mechanisms needs to be further explored. Further, it should be focused on how value-directed metamemory monitors and controls the memory process and selects the dominant mechanism of value-directed remembering. Finally, it is necessary to further explore the joint and specific roles played by automatic and strategic mechanisms within the incidental memory paradigm.
    References | Related Articles | Metrics
    Effects of motivation on error processing: Controversy and integration
    LI Yaqin, ZHAO Ruolan, YANG Qing
    2024, 32 (1):  85-99.  doi: 10.3724/SP.J.1042.2024.00085
    Abstract ( 204 )   PDF (543KB) ( 345 )   Peer Review Comments
    Errors are annoying and threatening. How to effectively monitor errors and adjust behaviors is important for one's goal achievement and social adaptation. Error processing is a high-level cognitive process that detects the occurrence of errors and makes subsequent adjustments. It can be characterized by brain activations (e.g., anterior cingulate cortex, ACC; dorsolateral prefrontal cortex, dlPFC), behavioral indicators (e.g., post-error accuracy, post-error slowing), and electroencephalogram (EEG) components (e.g., error-related negativity, ERN; error positive, Pe). Numerous studies have shown that motivation (e.g., reward, punishment, etc.) can affect error processing, but the findings are inconsistent.
    By comparing previous studies, we propose that factors such as age, gender, experimental design (e.g., task paradigms, motivation manipulations, trial-by-trial feedback, etc.), personality (e.g., neuroticism, conscientiousness, reward and punishment sensitivity, etc.) and culture (e.g., collectivist vs. individualist) may affect the relationship between motivation and error processing. Integrating them together, we further propose that task relevance could serve as a potential joint mechanism for these effects, that is, in tasks that are highly relevant to individual goals (i.e., motivation is highly tied to error consequences), error processing would be enhanced (e.g., heightened ERN/Pe amplitude) when one's motivation is stronger; but in low relevant tasks (i.e., motivation is less tied to error consequences), the motivational effects on error processing would be weaker (e.g., motivation may fail to enhance, or even decrease ERN/Pe amplitude).
    Within this theoretical framework, the above factors may moderate the relationship between motivation and error processing by affecting task relevance. For example, cultural factors may moderate the relationship between motivation and error processing through the mechanism of task relevance. For instance, Europeans and Americans may pay greater attention to self-relevant contexts and ignore other-relevant contexts compared to Asians, resulting in differences in attentional engagement in subsequent error processing tasks and differences in ERN amplitude. In social-evaluative threat situations, collectivist may be more sensitive to social threats and prone to associate errors with personal status and "face". This could strengthen the correlation between social evaluation motivation and error consequences, thereby enhancing error monitoring. In addition, gender and culture may interact to influence task relevance, thereby influencing the relationship between motivation and error processing. For instance, in social-evaluative threat situations, women (who are prone to form interdependent self-construal) may exhibit higher sensitivity to social errors (i.e., heightened task relevance) than men (who are prone to form independent self-construal), resulting in stronger error monitoring when motivation level increases. This new viewpoint may contribute to explaining the complex relationship between motivation and error processing.
    Future research should first empirically examine the moderating effects of the above factors and task relevance. Second, future research may explore the impact of motivation on different types of errors (e.g., unaware errors vs. aware errors). This is meaningful because some studies have shown that error types can affect error monitoring and post-error adjustment strategies, and the motivational effects can differ in reaction time of aware and unaware errors. Therefore, the motivational effects on error processing may also be affected by different types of errors. Third, it is also interesting to separate endogenous and exogenous motivations to explore their distinct influences on error processing. For example, one can explore the motivational function of error itself, that is, like surprise, error itself may have motivational function on subsequent error processing, which can be different to that induced by the exogenous motivation (e.g., reward, punishment). Last, future research can explore how motivational and cognitive factors may interact to affect error processing, and whether cognitive ability differences (e.g., attentional capacity, working memory capacity) can explain the inconsistent effects of motivation on error processing. We believe these measures would help advance the motivational theory of error processing.
    References | Related Articles | Metrics
    Comparison of models of eye movement in reading
    CHEN Songlin, CHEN Xinwei, LI Huangxia, YAO Panpan
    2024, 32 (1):  100-117.  doi: 10.3724/SP.J.1042.2024.00100
    Abstract ( 186 )   PDF (773KB) ( 251 )   Peer Review Comments
    Based on sequential processing theory, parallel processing theory and interactive activation theory, some classic models about eye movement control are constructed to simulate the eye movements, experimental effects, and to explore the possible cognitive mechanisms of information processing during reading. A systematic and in-depth comparative analysis of five classic models (E-Z Reader 10th, SWIFT, Glenmore, OB1 Reader and CRM) was made in this paper. Specifically, the similarities and differences among these models were analyzed and discussed.
    There are similarities among the five models: visual acuity and word frequency are all considered to influence the recognition of letters/ Chinese characters and words; common eye movement patterns including fixation, regression and saccade are all simulated; typical experimental effects such as word frequency, word length, word prediction, and preview effects are well explained.
    The core difference of the five models is whether the distribution of attention in the perceptual span is sequential or parallel, and this difference evoked significant consequences on the five models. First, different claims were made regarding letter/Chinese character recognition and word recognition. The sequential attention shift (SAS) models claimed that multiple words cannot be processed simultaneously, while the parallel graded processing (PG) models raised the opposite argument. Second, different interpretations of common eye movement patterns were made. For example, the SAS models claimed that regressions are derived from post-lexical integration, while the PG models argued that regressions come from lexical recognition. Third, different explanations for some typical effects were made. For example, the SAS models argued that readers cannot obtain semantic meanings from preview, and there is no parafoveal on foveal effect, while the PG models made the opposite argument. Forth, each model can explain some specific effects that other models cannot. For example, based on the special feature of Chinese script (the lack of word boundary demarcation), CRM raised a reasonable explanation for the word segmentation and preferred viewing location in Chinese reading; E-Z Reader simulated some effects of post-lexical integration which were not considered in other models; SWIFT, Glenmore, and OB1 all discussed the effects of extralinguistic factors which were not included in other models.
    For the future development of eye movement control models, researchers may need to take the following aspects into consideration. First, post-lexical integration needs to be considered and simulated. Semantic integration plays an important role in reading. But only E-Z Reader contained a module of post-lexical integration and simulated the possible mechanism of semantic integration. More attentions should be laid on the semantic integration procedure for further model development. Second, the word order coding in reading should be considered. Compared to the SAS models which provided a relatively intuitive answer to word order coding, the PG models require a clear answer to this question. OB1 Reader tried to solve this problem by adding a spatiotopic representation module, which however is not suitable for Chinese reading due to the specific features of Chinese. Further studies need to focus on understanding how word order is coded in Chinese reading under the framework of parallel processing. Third, some extralinguistic factors need to be considered. Now, SWIFT, Glenmore, and OB1 Reader discussed the influences of reader specificity or task difficulty in eye movement patterns in reading. In the future, more extralinguistic factors such as age, gender, intelligence, attention and language proficiency level should be considered to make the model more interpretable. Forth, general standards to compare the suitability of models should be made. Each model simulated specific experimental effects based on their corresponding empirical data, which makes it difficult to compare different models quantitatively and directly. Future studies should try to build a unified large-scale database for the convenience of comparing the explanatory power of different models for the same effect. Last, the possibility of cross-language explanations should be explored. Each of the existing models was based on a specific language. In future studies, researchers may try to explore whether the models based on a specific language can be applied to other languages.
    References | Related Articles | Metrics
    Dynamic collaboration of reading neural pathways driven by the processing demands
    DANG Min, CAI Wenqi, CHEN Fakun, WANG Xiaojuan, YANG Jianfeng
    2024, 32 (1):  118-130.  doi: 10.3724/SP.J.1042.2024.00118
    Abstract ( 104 )   PDF (1328KB) ( 159 )   Peer Review Comments
    Constructing a unified cognitive and neurophysiological model is a central issue in cognitive neuroscience studies of visual word reading. Cognitive theoretical models of reading agree that reading results from the division of labor between phonological and semantic processing pathways, and cognitive neuroscience studies have also shown that the reading neural network results from the dynamic collaboration between dorsal and ventral neural pathways. In order to systematically elaborate this dynamic collaboration mechanism of the reading network, the latest research progress is systematically disentangled from the following three aspects by combining the two levels of neural function and physiological basis.
    Firstly, it points out that the underlying processing demand is the essence of the dynamic collaboration between the dorsal and ventral neural pathways. Reading different types of words recruits an overlapped neural network, and their differences result from a dynamic interaction between phonological and semantic processing regions. This section reviewed studies that suggest that dynamic changes characterize the activation of reading-related brain regions. The activation of these brain regions is influenced by bottom-up stimulus properties and modulated by top-down task demands. Reading different types of words requires the division of labor between dorsal and ventral neural pathways, manifested in the difference in the pattern of interplay between phonological and semantic processing. The underlying cognitive processing may determine the activation of reading-related brain regions involved.
    Secondly, it further elucidates how underlying processing demands drive the division of labor and collaborative patterns between the dorsal and ventral neural pathways under different levels of orthographic depth. Cross-linguistic differences, mainly influenced by corpus properties and corresponding processing strategies, show neural differences in collaboration patterns between functional reading brain regions. We elaborate on this issue regarding both cross-linguistic comparative and bilingual studies. Evidence from cross-linguistic comparative studies reveals that word reading at different orthographic depths relies on different functional brain region activations, brain region connectivity patterns, and neurophysiological basis. The resulting differences in brain mechanisms for cross-linguistic reading rely on varying degrees of dependence on dorsal and ventral neural pathways. Evidence from bilingual studies suggests that bilinguals selectively rely on either dorsal or ventral neural pathways and the dynamics of connectivity patterns between brain regions, depending on the properties of the corpus, when reading words with different orthographic depths in the two languages. In turn, the similarity of the two languages mastered by bilinguals affects the activation pattern of the reading neural network.
    Lastly, it profoundly analyzes how latent processing shapes the dynamic collaboration between neural pathways through the shaping effect of language experience. The shaping effect of reading experience on related brain mechanisms is not only reflected in the influence on the activation sensitivity of brain regions corresponding to reading processing components but also affects the connectivity mechanisms among reading functional brain regions and further shapes the differences in collaboration mechanisms among different neural pathways. In particular, we review the studies to show how reading experience shapes the visual word form area, the form-sound processing area, and their connections with other reading functional brain areas. It also shows how reading experience shapes the dorsal/ventral neural pathway division of labor and cooperation mechanisms.
    This review expounds upon the dynamic collaboration mechanism of reading neural pathways driven by processing demands from three distinct perspectives, which not only helps to clarify the internal processing mechanisms of the brain neural network during visual word reading but also provides new evidence for the construction of a universal cognitive and neurophysiological model across languages.
    References | Related Articles | Metrics
    Neurocognitive basis underlying interpersonal emotion regulation
    DONG Wanxin, YU Wenwen, XIE Hui, ZHANG Dandan
    2024, 32 (1):  131-137.  doi: 10.3724/SP.J.1042.2024.00131
    Abstract ( 403 )   PDF (409KB) ( 636 )   Peer Review Comments
    Interpersonal emotion regulation refers to the process in which one person intentionally influences the emotional state of another person during social interactions. It has been found to be beneficial for individual psychological well-being and the development of social relationships, and it has distinct advantages compared to Interpersonal emotion regulation (i.e. individual's regulation of their own emotional states). In recent years, research on the cognitive and neural mechanisms underlying interpersonal emotion regulation has gained momentum, providing some insights into the neural basis of this process. Specifically, interpersonal emotion regulation involves the participation of the mentalizing system (including the ventromedial prefrontal cortex, the temporo-parietal junction, and the anterior insula), the emotional response system (including the amygdala and the insula), and the emotion regulation system (including the frontal and parietal lobes), with the mentalizing system being the core brain area.
    This present review focused on these three brain networks and provided an overview of the current understanding of the neural mechanisms underlying extrinsic and intrinsic interpersonal emotion regulation. In extrinsic interpersonal regulation, the regulator relies on the mentalizing system to infer the emotional state of the target and selects appropriate emotion regulation strategies for him. The regulator also needs to engage the emotion regulation system to actively search for and implement emotion regulation strategies, in order to alter the neural activity levels of the target's emotion response system. Furthermore, the regulator's reward system is likely involved and promotes emotion regulation during prosocial helping. In intrinsic interpersonal regulation, the target relies on the mentalizing system to understand the regulating intentions and behaviors of others. With the help of others providing regulation strategies, the target' s reliance on the prefrontal control system tends to decrease during emotion regulation. However, the field of interpersonal emotion regulation is still relatively new, and our understanding of its cognitive and neural mechanisms, particularly the cognitive neuroscientific mechanisms, is still limited.
    Based on existing research, we believed there are four important issues that need to be addressed in future studies. Firstly, the current research on the brain mechanisms underlying extrinsic and intrinsic interpersonal emotion regulation is still incomplete, and the available neuroscientific evidence is insufficient. We recommended that future studies utilize brain imaging techniques such as functional magnetic resonance imaging (fMRI), along with innovative research paradigms in interpersonal emotion regulation, to explore those unanswered questions. Secondly, most existing studies have focused on the neural activity of single brains and lack dual-brain research. However, dual-brain evidence is essential for constructing cognitive neuroscientific models of interpersonal emotion regulation. We suggested using whole-brain coverage techniques such as electroencephalography and near-infrared spectroscopy hyperscanning to reveal the interactive processes between regulator and target. Thirdly, the cognitive neuroscientific models of interpersonal emotion regulation are not yet fully developed, and the specific brain regions that distinguish interpersonal regulation from self-regulation need further investigation and clarification. We recommend future research to fully consider the interactive and complex nature of interpersonal emotion regulation, examine the impact of various factors such as interpersonal relationship contexts, gender, personality traits, and intimacy levels on interpersonal emotion regulation using a combination of neurophysiological observations, behavioral measurements, and path analysis techniques to reveal the cognitive mechanisms underlying the interaction between regulator and target. Fourthly, there is currently a lack of applied research in the field, particularly in terms of noninvasive neuromodulation as well as a lack of intervention studies. We recommend that future applied research be conducted in two areas: enhancing the interpersonal emotion regulation abilities of healthy individuals through training and providing clinical interventions for specific populations such as individuals with depression.
    In conclusion, the field of interpersonal emotion regulation is still emerging, and further research should prioritize addressing the aforementioned issues to advance this important area of research.
    References | Related Articles | Metrics
    Balanced time perspective and mental health: Mechanisms and theoretical framework
    LI Xiaobao, YU Xuchen, LYU Houchao
    2024, 32 (1):  138-150.  doi: 10.3724/SP.J.1042.2024.00138
    Abstract ( 358 )   PDF (588KB) ( 542 )   Peer Review Comments
    Time Perspective is a crucial psychological framework that allows individuals to classify, organize, and manage their life and social experiences, describing how individuals view their past, present, and future. Recent research suggests that achieving a balance between the past, present, and future time perspectives is essential for optimizing social adaptation, facilitating well-being, and promoting mental health. Thus, much attention has been paid to the relationships between balanced time perspective (BTP) and mental health. However, the theoretical framework and underlying mechanisms linking BTP to mental health remain unclear due to the lack of clarity in its concept and limited measurement methods. Our review aims to clarify the conceptual orientations of BTP and explore the underlying mechanisms between BTP and mental health.
    The concept of BTP is developed based on time perspective research, specifically according to Zimbardo Time Perspective Theory. This theory suggests that time perspective is an individual's adaptive process of external social and cultural environment. And different time perspectives may lead to various behavioral decisions and mental health outcomes. There are five common time perspectives, including Past Positive (viewing the past in a positive light), Past Negative (viewing the past in a negative attitude), Present Hedonistic (a preference for immediate gratification), Present Fatalistic (a helpless and fatalistic outlook of life), and Future (a tendency to plan for the future). All of these time perspectives are evidently associated with happiness-related variables. In contrast to a specific temporal bias, the idea of a balanced time perspective is proposed to optimize individuals' well-being and mental health.
    Based on the existing literature, this review first distinguished two conceptual orientations of BTP. One is the “time shift orientation” BTP, which is defined as the cognitive process or mental ability to effectively switch between different time perspectives based on situational demands. The other is “general healthy orientation” BTP, which combines high level of adaptive time perspectives (e.g., Past Positive, Future, and Present Hedonistic) with low levels of maladaptive time perspectives (e.g., Past Negative and Present Fatalistic), reflecting an overall positive outlook on subjective time. The former is a theoretical concept with limited research on measuring the process or capacity of switching between time perspectives. The latter is the dominant focus of current research, and the existing scales and methods of BTP are all designed to assess the general healthy orientation toward the past, the present, and the future.
    Our review also proposed a dual-pathway theoretical framework to clarify the direct and indirect paths between BTP and mental health. The direct pathway emphasizes the direct effect of habitual temporal cognitive processes on mental health. The indirect pathway highlights the role of BTP in influencing adaptive behaviors, which in turn affect mental health. In terms of the time shift orientation BTP, higher BTP requires individuals to effectively switch between time perspectives. Such a switching capacity might help individuals to have greater psychological and social adaptation. Additionally, higher BTP enables individuals to better observe and evaluate environmental characteristics, thereby inhibiting maladaptive time perspectives and exhibiting adaptive time perspectives. This necessitates strong self-regulation abilities in individuals. Therefore, the self-regulation process, including self-control and flexible selection of emotional regulation strategies, may serve as underlying mechanisms linking time shift orientation BTP and mental health. Regarding the general healthy orientation, the higher the BTP is, the more likely individuals are to positively think about the past, experience the present, and anticipate the future, resulting in good mental health. For instance, recalling past positive experiences and anticipating positive future events can directly facilitate life satisfaction and positive emotions. Conversely, viewing the past and future from a negative perspective is easy to induce negative emotions. General healthy orientation BTP can also indirectly promote mental health through a range of adaptive behaviors. For example, individuals with high levels of adaptive time perspectives (e.g., Past Positive and Future) tend to have more adaptive behaviors such as planning, healthy eating, exercise, and environmental protection. On the contrary, individuals higher on Past Negative and Present Fatalistic are likely to exhibit problematic behaviors such as aggression and substance abuse. These behaviors can further promote or damage mental health. In addition, the dual-pathway model also discussed the potential moderating role of age and life environment between BTP and mental health. Future research should aim to clearly distinguish between these different conceptual orientations of BTP, focus on developing measurement methods for time shift orientation BTP, and deepen both theoretical and empirical exploration of BTP and mental health, particularly within the context of Chinese culture.
    References | Related Articles | Metrics
    Deterrence or signal? The function of third-party intervention
    GUO Yuchen, LIU Yanbin, CHENG Yuan
    2024, 32 (1):  151-161.  doi: 10.3724/SP.J.1042.2024.00151
    Abstract ( 196 )   PDF (515KB) ( 286 )   Peer Review Comments
    Third-party intervention is fundamental to shaping and sustaining social norms and plays an important role in the evolution of human communities. Compensation and punishment are two principal methods of third-party intervention which refer to third parties paying the price themselves, either to punish the offenders who caused the harm or to compensate the victims. Third parties can intervene in various ways. Actions such as verbal criticism, gossip, social isolation and physical or financial punishment of the offender are third-party punishment, whereas psychology and financial assistance, and provision of information are third-party compensation.
    Third-party intervention plays a central role in enforcing social norms and has two functions. First, it reinforces social norms by restoring the balance of gains and losses and returning the situation to what it “ought” to be under social norm conventions. This function is primarily related to individuals' retributive motives, which are concerned with ensuring that offenders suffer and innocents are compensated. Furthermore, third-party intervention reinforces social norms by motivating society members to adhere to them and inhibit norm-breaking behaviors. This function is primarily related to consequentialist motives of individuals, which are concerned with deterring future transgressions. Although many studies have affirmed the significant role of third-party interventions in promoting norm compliance, some debate remains. First, some studies have found that third-party punishment does not always promote normative compliance, particularly when it lacks persistence or legitimacy. Second, some researchers suggest that only third-party punishment is effective in promoting normative compliance, as third-party compensation does not reduce the adaptability of violations, and therefore does not deter violations. In contrast, others have contended that third-party compensation contributes significantly to the promotion of normative compliance. To elaborate on the conflicting findings regarding the impact of third-party interventions on normative compliance, it is necessary to explore the internal mechanisms.
    According to deterrence and social learning theories, the deterrent effect is a critical mechanism of third-party punishment for inhibiting offending behavior because it serves as a warning to offenders and other members of society that the current behavior is unacceptable and will result in punishment. As people fear expected punishment, they refrain from committing the behavior. However, the deterrent effect may not be the sole mechanism through which third-party interventions exert influence, as many studies have discovered evidence that challenges the deterrence theory. In addition, this mechanism does not clarify the impact of third-party compensation. We suggest that normative signaling effects may constitute another crucial mechanism of action. The theory of social norm perception suggests that the attitudes and behaviors of other group members constitute a crucial source of information for individuals to perceive social norms. Both third-party punishment and compensation serve as explicit signals against current norm-breaking behavior and clarify social values and norms. After observing or experiencing third-party interventions, individuals may perceive the opposition of interveners to the violation, which implies descriptive social norms (i.e., others are unlikely to engage in such behavior), as well as the implicit commitment of interveners to normative compliance, which implies injunctive social norms (i.e., others believe such behavior is unacceptable). This enables individuals to adjust their perceptions of social norms and adapt their behavior accordingly. Therefore, signaling social norms is an important but undervalued mechanism for third-party intervention in reinforcing social norms.
    Research on third-party interventions has been productive. However, several issues require further exploration. First, it lacks a clear understanding of the function of third-party compensation and rewards in maintaining social norms. Second, the boundary conditions moderating the impact of third-party interventions on normative compliance remain unclear. For example, contextual factors and the costs of intervention behavior may shape their effectiveness in delivering normative signals. Furthermore, additional exploration is required to determine the sustainability of the effects of third-party intervention.
    References | Related Articles | Metrics
    Dancing with AI: AI-employee collaboration in the systemic view
    YIN Meng, NIU Xiongying
    2024, 32 (1):  162-176.  doi: 10.3724/SP.J.1042.2024.00162
    Abstract ( 415 )   PDF (679KB) ( 676 )   Peer Review Comments
    AI-employee collaboration is an interactive system composed of “AI-human-organization” with the goal of completing tasks efficiently. Promoting AI-employee collaboration is crucial for driving the deep integration of AI and the real economy, as well as the mental health and career development of employees in the digital era. However, the conceptual connotation of AI and AI-employee collaboration has not yet been systematically elaborated in the literature, which has led to ambiguity in the meaning of AI in organizations as well as confusion between concepts of different AI application. In addition, the research of AI-employee collaboration is fragmented and complex across disciplines, and the academic community lacks a comprehensive understanding of the current status and future direction of AI-employee collaboration research. Based on the above limitations, we conducted a comprehensive search of the literature related to AI-employee collaboration, coded the publication information, theoretical basis, core research conclusions and other contents of the literature, and organized the content of the paper based on a systemic review after reading the literature in depth. We first clarify the concept and dimensions of AI in the workplace, and then discuss the systemic view of AI-employee collaboration, and further clarify the conceptual connotation of AI-employee collaboration from the systemic view. This helps to unify the academic dialogue and lay the foundation for subsequent research on AI-employee collaboration. Then, based on the systemic view of AI-employee collaboration, the paper constructs a research framework of AI-employee collaboration using I-P-O paradigm, and describes AI-employee collaboration as input, process and output of a system in detail. At the input of the system, AI, employees, and organizations work together to drive the design, implementation, and use of AI. At the AI level, we review from three dimensions: physical attributes, mental attributes and ethical attributes. At the employee level, we review from four aspects: attitude, KSAs, personalities and demographic characteristics. At the organizational level, we review from three perspectives: organizational readiness, organizational support, organizational climate and culture. In the process of the system, actors operate around work tasks, and they influence the output by performing the tasks. Therefore, the process is a task configuration, including two aspects: task goal and interaction approaches. We further propose that optimizing AI-employee collaboration requires attention to the dynamic matching of interaction approaches and task goal. At the output of the system, we summarize the outcomes of three actors: employees, AI and organization. The research framework explicitly describes the components and internal mechanisms of AI-employee collaboration system, and provides a basic theoretical framework guide for further more in-depth research. Finally, based on the limitations of the research framework, we propose future research prospects from five perspectives. (1) Future research should emphasize the ethical issues in AI-employee collaboration system, providing more empirical and experimental evidence for the impact of ethical attributes on AI-employee collaboration. (2) Future research should develop objective measurements of the organizational consequences of AI-employee collaboration. (3) Future research should explore more individual factors that may influence AI-employee collaboration, such as prompt ability, cultural values, etc. (4) Future research should further elaborate the task configuration of AI-employee collaboration and examine the efficiency and effectiveness of AI-employee collaboration with different task configurations. (5) Future research should expand the research framework based on the new developments of I-P-O paradigm, such as feedback loops.
    References | Related Articles | Metrics
    Psychological and behavioral consequences of debt and its mechanism
    WANG Luxiao, XIN Ziqiang
    2024, 32 (1):  177-188.  doi: 10.3724/SP.J.1042.2024.00177
    Abstract ( 360 )   PDF (626KB) ( 544 )   Peer Review Comments
    The gradual escalation of household debt in China has emerged as one of the prominent concerns in the lives of its citizens. Debt is a legally or morally binding obligation on the part of an individual to repay another person or institution, either immediately or at some point in the future. Although debt is a concept rooted in the domain of economics, the economic actions of individuals can be elucidated through the lens of psychological mechanisms. Specifically, the decision-making and management of debt exhibit inherent psychological characteristics. Simultaneously, debt can exert a significant influence on personal behaviors and result in distinct psychological consequences. However, there exists a notable absence of a comprehensive and systematic review regarding debt from a psychological standpoint. Therefore, this paper endeavors to provide an in-depth review of the psychological and behavioral ramifications associated with various forms of debt and their underlying psychological mechanisms.
    Clarifying the classification framework for debt is an essential prerequisite for elucidating its potential effect. Grounded in its intrinsic attributes, debt can be dichotomized into objective and subjective debt. Objective debt pertains to the concrete obligation of an individual or household to reimburse a debt and the attendant degree of that obligation, whereas subjective debt concerns the subjective perception of the burden imposed by a debt. Debt can also be classified based on its specific utilization or repayment time.
    Debt stress is a direct consequence of indebtedness. The extent to which individuals experience debt stress is positively associated with the magnitude of their actual debt, i.e., the higher the objective debt level, the greater the subjective perception of debt stress. The relationship between debt and debt stress is further influenced by the type of debt and individual differences. On one hand, various debt categories elicit varying degrees of perceived threat. Mortgage and long-term loans, for example, entail lower levels of threat and consequently result in reduced debt stress. On the other hand, diverse demographic cohorts exhibit differing levels of perceived threat when confronted with debt. Specifically, women and individuals with lower incomes are more prone to perceiving debt as threatening, leading to heightened debt stress when they are indebted.
    Debt and debt stress can further result in various psychological and behavioral consequences. Firstly, debt can diminish an individual's well-being, giving rise to psychological health issues such as anxiety and depression. Secondly, debt can lead to shortsighted and impulsive behaviors (e.g., dropping out, excessive drinking), shifts in consumption patterns (including irrational and conspicuous consumption), and increased engagement in unethical behavior. Lastly, debt can also detrimentally affect the psychological well-being of the indebted individual's romantic partner, all while exerting subtle influences on the financial habits and self-regulation capacities of their offspring.
    The effects of debt involve psychological mechanisms, one is the threat-compensation mechanism, i.e., debt exerts its influence through mechanisms encompassing the obstruction of psychological needs and compensatory responses. Being a relatively negative personal experience, indebtedness can undermine an individual's self-esteem and sense of control. This, in turn, leads to an outpouring of unmet psychological needs that affect well-being and psychological health, and a preference for conspicuous consumption as compensation for these thwarted needs. Another is the cognitive resource depletion mechanism, that is, debt signifies a deficiency in objective resources, and prolonged resource scarcity depletes an individual's cognitive resources. Consequently, individuals become more fixated on immediate gains and encounter difficulties in self-control, thereby engendering short-sightedness and unethical behaviors.
    Upon a comprehensive review of the extant literature, we pointed out that existing studies exhibit deficiencies in terms of perspectives, methodology, and theoretical frameworks. Regarding the perspectives, future research could identify the moderators of the effects of debt both at macro and micro levels, with specific attention to the influence of national economic development, cultural differences, and individual perceptions of debt threat. And delve into a broader spectrum of psychological and behavioral consequences of debts, such as unethical behavior for the organization and pro-social behavior.
    Regarding tools and methodologies, future research is suggested to systematically delineate the dimensions of debt and develop scales to measure debt stress. Furthermore, in future research, the methodology employed should extend beyond surveys and incorporate a multidisciplinary approach encompassing experimental paradigms, longitudinal designs, and methods from the field of social cognitive neuroscience, which enables the provision of a more robust foundation of causal and physiological evidence concerning the influence of debt.
    From a theoretical standpoint, previous studies mostly relied on classical theories to expound certain facets of debt, with a predominant focus on the drivers of borrowing behavior and debt management practices. Future research could construct an integrated theoretical framework that describes the nature of debt and elucidates the consequences of debt.
    References | Related Articles | Metrics