ISSN 1671-3710
CN 11-4766/R


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    Conceptual Framework
    Micro-expression spotting method based on human attention mechanism
    LI Jingting, DONG Zizhao, LIU Ye, WANG Su-Jing, ZHUANG Dongzhe
    2022, 30 (10):  2143-2153.  doi: 10.3724/SP.J.1042.2022.02143
    Abstract ( 1481 )   HTML ( 89 )  
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    Micro-expressions are facial movements that are extremely short and not easily perceived, often generated under high pressure. Micro-expressions can reveal the individual's hidden real emotions and are important non-verbal communication clues, widely used in lies detection and other fields. Due to the difficulty of eliciting, collecting, and labeling micro-expression samples, micro-expression-related research becomes a typical small-sample-size (SSS) problem. In order to enlighten the application of micro-expression analysis technology in complex real-life scenarios such as national security and clinical consultation, this study focuses on the SSS problem and proposes a micro-expression spotting method based on human attention mechanism with multi-branching self-supervised learning through the intersection of computer and psychology.

    First, this study conducts an exploration related to attentional resources based on the cognitive mechanisms of psychological micro-expressions. A behavioral-experimental paradigm combining eye-movement techniques and a presentation-judgment paradigm with subthreshold emotion priming effects was used to examine the cognitive mechanisms of selective attention allocation in micro-expression recognition and to refine the distinct regions of interest in human recognition of micro-expressions. Thus, the model is effectively and directly enabled to acquire important micro-expression features from the input information. Then the relevant attention modules are further generated from multi-dimensions (time domain, spatial domain, and channel domain) by the deep learning network to improve the performance of the network in extracting micro-expression features with the limited sample size.

    Second, this study proposes a multi-branching self-supervised learning method based on the human attention mechanism for micro-expression spotting. Training in many unlabeled video samples for the pre-text tasks enables the model to extract features from regions of interest of micro-expressions, including structural and detail features and video dynamic change patterns. Thus, the limitation caused by the SSS problem could be avoided.

    Finally, the current data released for micro-expressions are video samples and do not include the corresponding depth information. This study will carry out a depth information-based micro-expression spotting method based on the first micro-expression database that includes image depth information being created by our research team. It enables self-supervised learning to learn the corresponding action patterns from the geometric information of the scene.

    This research will achieve theoretical and technological breakthroughs in the field of automatic micro-expression spotting, improve the accuracy and reliability, and lay the foundation for the application of micro-expression spotting in realistic and complex scenarios.

    Second, it can achieve the data augmentation of micro-expression samples by mining micro-expression clips in unlabeled videos. Thus, the micro-expression small sample problem could be solved, and the performance improvement of traditional supervised micro-expression spotting methods could be improved.

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    Mechanism of prognosis and intervention strategy for child posttraumatic stress disorder: Based on the long tail effect theory
    GUO Jing, LIU Xiaohan, HUANG Ning
    2022, 30 (10):  2154-2163.  doi: 10.3724/SP.J.1042.2022.02154
    Abstract ( 842 )   HTML ( 39 )  
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    Prevention and intervention of post-traumatic stress disorder (PTSD) in children is an important issue of the healthy China strategy. The world health organization (WHO) predicted that global burden of child injury will continue to rise, especially in low and middle-income countries. It is estimated that 10% to 20% of children after traumatic events will experience post-traumatic stress disorder symptoms such as warning, evasion, and negative emotions. PTSD confer a heavy long term burden of disease among children. And Child PTSD was indicated to have a long tail effect, as great heterogeneity exists among children with PTSD regarding their following health outcomes. In addition, post-traumatic stress disorder in children is highly correlated with behavior problems, depression, substance abuse, crime, and suicide, and its negative effects can last into adulthood and even have intergenerational transmission effects. Current studies on the developmental outcome of PTSD in children mostly focus on whether PTSD symptoms decrease, increase or persist in children, while ignoring the types, mechanisms of prognosis, and intervention strategies of Child PTSD. Specifically, the types, characteristics, and mechanism of the developmental outcome of PTSD (transforming into physical and mental health, behavioral health, and other problems) have rarely been systematically explored, especially in the Chinses cultural context. For the reduction in the occurrence and development of PTSD, the trauma-focused cognitive behavioral intervention was proved to be rather effective in reducing the level of PTSD. However, there is not enough evidence from large-sample-sized, long-term randomized controlled studies based on school settings, and a shortage of targeted interventions for different stages of PTSD development. Therefore, it is of great academic value and practical significance to clarify the pathway of the occurrence and trajectory of PTSD in children, provide joint intervention programs based on the school setting, and reduce the risk of their transition to other physical and mental diseases. Moreover, based on a school-based teacher-children-parents cooperation framework, we would provide targeted intervention services to reduce the risk of Child PTSD, further shed light on individual-centered care in clinical practice. The purpose of this study is to conduct a follow-up investigation and quasi-experimental study on children and adolescents, focusing on: (1) the developmental trajectory and outcome types of children with PTSD. (2) What is the mechanism of prognosis for PTSD among children? (3) Whether school-based intervention services can promote the recovery of children with PTSD and reduce the risk of their transition to other physical and mental disorders? (4) According to the characteristics of Chinese children, how to develop early health service plans focusing on reducing traumatic events and promoting the recovery ability of children with PTSD? This study will identify the long-term trajectory types and mechanisms of Child PTSD prognosis in China, reduce the risk of children's PTSD to other physical and mental diseases through the joint intervention program based on the school setting, verify the effect of comprehensive intervention services on promoting the recovery of children's PTSD, and provide evidence for children's PTSD intervention and personalized diagnosis and treatment. Simultaneously, multiple theories were integrated to build the early-warning model, to interpret prognosis mechanism and comprehensive intervention strategy. Based on the "long tail theory", the early-warning model explore the trajectory and trait of the PTSD children. The prognosis mechanism of Child PTSD, incorporated the basic essence of the stress model and the resilience model, will reveal the developmental mechanism of Child PTSD. The process-based intergrated intervention strategy synthesized the characteristics of the long term effect, psychological environmental mechanism and task-shifting model. And this strategy could provide theoretical guidance for the school-based interventions of Child PTSD in the Chinese context.

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    The sustainability of altruistic behaviors and its formation mechanism in organizations: From the perspective of proactive motivation
    YU Kun, WANG Zheyuan, PENG Xiongliang, WANG Pei, ZHAO Zejun, YAN Yidan, CAO Peiyue
    2022, 30 (10):  2164-2176.  doi: 10.3724/SP.J.1042.2022.02164
    Abstract ( 887 )   HTML ( 56 )  
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    With the rapid development of the economy and society, the critical role of the sustainability of altruism is more salient for organizations and their employees to have a better adaptation and greater prosperity. Although altruistic behaviors are very critical to modern organizations, there are several severe deficiencies in the understanding of the nature of altruistic behaviors and the investigation of its formation mechanism in the current altruism literature. First, researchers have long believed that altruism behaviors are static trait-like behaviors, and behavioral differences mainly exist at the interpersonal level. Therefore, most of the previous research in this area focused on the exploration of interpersonal differences in the static value of altruistic behaviors. This deficiency not only keeps previous research from accurately reflecting the characteristics of long-term trajectories of altruistic behavior but may also cover up the possible outliers in the short-term volatility of altruistic behavior, which may lead to the misjudgment that treating the static value of altruistic behavior as the “ideal” altruistic behavior which is stable and sustainable. Second, the existing investigation of altruistic behavior via a dynamic theoretical lens or using dynamic methods generally lacks systematic integration. A key problem is that, although scholars generally believe that altruistic behaviors have features of both long-term trends and short-term volatility, most of the existing studies were based on narrower research frameworks and independently discussed either short-term volatility or long-term trend of altruistic behavior, respectively. If the above two issues remain unsolved, it will lead to our incomplete understanding of the antecedents and forming mechanism of altruistic behavior. Therefore, based on the model of proactive motivation, this paper attempts to construct a theoretical framework of the sustainability of altruistic behaviors, examining the short-term volatility and long-term trends of altruistic behavior simultaneously, and exploring individual and leadership antecedents and forming mechanisms of the sustainability of altruistic behavior. Specifically, using a mixed-method of longitudinal survey and experience sampling method, this study firstly aims to clarify the nature of the sustainability of altruistic behaviors, to uncover the relationship between the short-term volatility and long-term trend of altruistic behavior, and by which to enrich our understanding of the sustainability of altruistic behavior. Secondly, we aim to explore how employee antecedents (belief in a justice world and perceived overqualification) and leader antecedents (ethical leadership and abusive supervision) impact the goal-setting (short-term volatility) and goal-striving (long-term trend) of altruistic behavior via “energized to” path (state gratitude, psychological entitlement, and heroism), “reason to” path (organizational concern and impression management motives), and “can do” path (reciprocal cognition and career adaptability). To sum up, based on the model of proactive motivation, this paper facilitates the literature on altruistic behavior by filling an important research gap regarding the sustainability of altruistic behavior and advancing the knowledge on antecedents and forming mechanisms of the sustainability of altruistic behavior. Moreover, the findings of the current research would also provide practical suggestions for the construction of sustainable reciprocal teams and organizations.

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    Be your own leader: The multi-level motivational mechanisms of individual self-leadership
    LUO Wenhao, WANG Yao
    2022, 30 (10):  2177-2193.  doi: 10.3724/SP.J.1042.2022.02177
    Abstract ( 1040 )   HTML ( 59 )  
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    Currently, business organizations are continuously promoting changes in organizational structure and methods of work. Meanwhile, employees are also increasingly pursuing their own values and goals. Therefore, individual self-leadership has become an important and evolving research topic in organizational management research. Individual self-leadership not only contributes to organizational development and personal performance improvement but is also closely related to self-growth in uncertain times. It is thus necessary to investigate the driving factors and mechanisms of self-leadership. A literature review of extant studies found that the current concept of self-leadership is mostly based on classical control theory, emphasizing the process of self-control and influence. However, its relatively broad content means that it has been difficult to accurately reflect new meanings of self-leadership. At the same time, empirical research on the antecedents of individual self-leadership has been limited to a single level, without considering multi-level interactions. More importantly, existing research fails to fully address the motivational processes behind the antecedents of self-leadership.

    With this practical and theoretical background, this study aims to initially answer the core scientific question of "how does individual self-leadership form" through three closely related theoretical studies. Firstly, the present study defines and expands the conceptualization of individual self-leadership, and develops a reliable and valid scale for it. On the one hand, the concept of individual self-leadership has undergone substantive changes in this period of new management practice; on the other hand, the existing definition and measurement of self-leadership have been criticized because it is too broad and has insufficient reliability and validity. To this end, this study intends to reconceptualize self-leadership by building on a grounded analysis of new management practices. Furthermore, through conducting qualitative interviews and following a scale development process, Study 1 aims to develop and validate a new scale for individual self-leadership. Secondly, starting from the intrinsic motivation-driven nature of self-leadership, Study 2 theoretically investigates the influence of individual cognitive characteristics and team leadership style on the formation of individual self-leadership. Specifically, this study initially proposes that employees' belief in leadership co-creation promotes individual self-leadership by inspiring their personal goal strivings, and team empowering leadership promotes self-leadership by satisfying employees' psychological need for autonomy. Further, team leaders’ empowering leadership behaviors will also strengthen the impact of employees’ beliefs in leadership co-creation on self-leadership, resulting in a cross-level moderation model. Finally, Study 3 examines the influence mechanism of organizational contexts and team self-leadership on individual self-leadership, so as to develop a trickle-down effect model. Specifically, this study proposes that organizational shared vision and autonomy support climate can work together to enhance team self-leadership, which can further motivate individual self-leadership. In addition, the positive effect of team self-leadership on individual self-leadership will be enhanced in the context of high task interdependence and high adoption of telecommuting. To sum up, the integrated framework developed in this study emphasizes the multi-level influences and the motivational processes underlying the formation of individual self-leadership. It also echoes recent discussions on the paradoxical feature of self-leadership.

    Our research is expected to make theoretical contributions to the self-leadership literature in the following ways. This research enriches and expands the concept of self-leadership, better reflecting the changes in management practices, and also provides a clearer concept and scale with accepted reliability and validity for subsequent studies. On this basis, the theoretical exploration of the formation mechanism of individual self-leadership provides a foundation for developing a multi-level theoretical framework of self-leadership, thereby helping to deepen the understanding of self-leadership in the academic world and management practice. However, given the conceptual nature of the current study, we call for further empirical examinations of self-leadership and its formation mechanisms. Future studies could also consider the role of self-leadership in digitalization transformation and artificial intelligence-driven contexts.

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    How does decision making process signal social status? A maximizing decision making perspective
    LUAN Mo, WU Shuang
    2022, 30 (10):  2194-2205.  doi: 10.3724/SP.J.1042.2022.02194
    Abstract ( 946 )   HTML ( 56 )  
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    Social status signaling is a fundamental motive that drives consumer behavior. Previous research on consumer psychology largely focuses on how social status can be signaled by the characteristics of products, but rarely explores how consumer decision process, another pivotal element of consumer decision-making, affects social status inference. Decision process is a vital part of consumer behavior. Similar to product characteristics, it is easy to observe and easy to control. The current research aims to build a social status inference model based on information about the maximizing decision process. We will systematically examine the following three questions. First, does maximizing, as a decision-making process, signal consumers’ social status? If so, how? We propose a moderated mediation model with perceived agency as the mediating mechanism and subjective decision experience and social mobility belief as boundary conditions. Building upon research on social status inference, our research will address the lack of focus on purchasing process in past research and broaden the scope of research on social status inference. Building upon research on maximizing, we will examine how maximizing influences social status inference by observers, which extends research on maximizing to an interpersonal level. Second, does the motivation to signal social status drive consumers to maximize? Individuals may adopt a maximizing decision strategy to signal social status. We will approach the question from a social status perspective and examine whether need for social status explains why consumers maximize during decision making. Third, how does consumers’ maximizing decision process influence their observers’ subsequent consumption behavior through social status inference? We will examine how perceived agency and social status inference serially mediate the effect of maximizing on consumers’ influence, reflected by observers’ advice seeking, reliance on consumers’ reviews, and purchase decisions. We will test the serial mediation model in two domains: reviews generated by consumers and advertisements generated by companies. The current research will study maximizing at an interpersonal level by examining how maximizing influences the attitude and behavior of observers. Furthermore, our research will help companies and marketers understand how decision process, described in user reviews, affect status inference and observers’ subsequent consumption. As a result, companies and marketers can nudge consumers to provide more descriptions about their decision process in the review, thereby helping with word-of-mouth marketing. Our research will also help companies and marketers understand how decision process related to product design and manufacturing, described in advertisements, affects status inference and consumers’ subsequent consumption. As a result, companies and marketers can design more effective advertisements by providing more information about the decision process. In conclusion, our research will provide a new perspective for research on social status inference, expand the scope of research on maximizing and shed new light on the underlying causes of maximizing.

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    Regular Articles
    The internal mechanisms of attentional templates in facilitating visual search
    WANG Zile, ZHANG Qi
    2022, 30 (10):  2206-2218.  doi: 10.3724/SP.J.1042.2022.02206
    Abstract ( 723 )   HTML ( 63 )  
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    Attentional templates can facilitate the target search process by enhancing relevant information and suppressing irrelevant information during the search task. According to the results of recent studies on the internal mechanism of attentional templates, the main findings are summarized in terms of the information relied on in the establishment of attentional templates (establishment process), the relationship between attentional templates and memory (stored process), and the mechanism of attentional templates promoting search (function mechanism).

    Firstly, the semantic information and visual feature information cannot be well separated in the current experimental studies, so it is not clear whether it was based on semantic or visual feature information in the process of establishing the attentional templates. Secondly, in some earlier studies, researchers equate attentional templates with working memory, believing that attentional templates are stored in working memory. However, recent studies have found that attentional templates can be stored in both the working and long-term memory. But the number of templates stored in working memory is still controversial. Some researchers believe that simultaneously searching for two items is worse than searching for one item, as shown by evidence for storing only one template in the working memory. Similar results may be found when two templates are stored in the working memory, such as the following possibilities: when two templates were stored in the working memory simultaneously, each template receive fewer resources compared to storing only one template due to the limited resources of the working memory; when two templates were activated at the same time, the information in the online state will interfere with each other, resulting in poorer performance of searching for two items simultaneously than searching for one item; when two templates are switched to each other, the switch takes time, and the simultaneous memory representation will be damaged, which will also reduce the efficiency of searching for two items at the same time than that of searching for one item. Finally, there are differences in the mechanism of different types of attentional templates. The target template and the template for rejection may promote the search through different mechanisms. The right posterior temporal cortex, anterior superior parietal lobule, bilaterally at the occipital pole and lateral occipital cortex play an important role in promoting the search of the target through the target template. The activation of posterior parietal cortex and the area of posterior parietal cortex bordering precuneus are associated with the templates for rejection in filtering task-irrelevant information.

    Furthermore, we know very little about how template information is transmitted and used during visual search. The mechanisms by which templates facilitate search may also vary across populations, and that some findings in normal individuals may not be universally applicable. As well as the controversial in active attentional suppression hypothesis and search and destroy hypotheses for explaining the mechanism of template for rejection in the suppression of distractors. Therefore, future research should pay attention to how the internal information is transmitted during the establishment of attentional templates, the neural mechanisms of attentional templates in different populations, and resolve theoretical disputes about the suppression mechanism of rejection templates.

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    The processing mechanism of category-specific attentional control settings in attentional capture
    WU Xia, WANG Junzhe, WANG Yun, CHEN Ying, YANG Haibo
    2022, 30 (10):  2219-2227.  doi: 10.3724/SP.J.1042.2022.02219
    Abstract ( 474 )   HTML ( 25 )  
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    Attentional capture refers to the phenomenon that task-related stimuli unconsciously capture attention and get priority processing in attentional orientation. Attentional control Settings (ACS) can guide attention to task-related stimuli, and then preferentially process it. When target is defined as a category composed of multiple objects, the attention system will form category-specific attentional control settings (cACS). Investigating the mechanism of cACS in attentional capture can not only expand and enrich previous theoretical research, but also provide basis and guidance for real life.

    The present study reviewed the characteristics of cACS. Firstly, related to the processing stage of cACS, some previous studies claimed it occurred at an early stage, while others thought it happened at a late stage. Two-stage hypothesis combined these two views and postulated that different cACS can guide attention independently at the early stage, and then integrate into one single cACS at the late stage. In addition, cACS can also be preactivated in the preattentive stage to improve the subsequent search efficiently.

    Secondly, relative to the processing weight of cACS, the attributes (e.g., color, size, shape or motion) of category, the size of items in category and the abstraction of categorical hierarchy were proven to be the impact factors of the processing weight of cACS. Specifically, the processing weight of cACS was lower than the feature-specific attentional control settings (fACS). The weight of color-specific cACS was larger than that of other cACSs. The weight of cACS was reduced along with a larger size of items in category. And the weight of superordinate-level cACS was lower than that of subordinate-level cACS.

    Thirdly, relative to the involved brain regions of cACS, we summarized the previous functional brain imaging research and found object-selective cortex (OSC) involved the processing of extracting cACS stored in long-term memory and selecting target/inhibiting distractor.

    Finally, we summarized the neural mechanisms of cACS in attentional capture. Firstly, cACS can preactivate in the early preattentive stage of processing to promote the detection of categorical stimuli (as the involvement of OSC). When the visual stimulus is occurred, cACS can compare the current stimulus to the definition of target (as the index of N1 and P1 components), the frontal parietal network (PFC, LIP, etc.) involve in the category judgment process, and the left superior temporal sulcus (lSTS) participate in the integration of top-down and bottom-up processing. The stimulus that matches target definition can induce attentional capture (as the index of N2pc component), while the stimulus that mismatches the target definition can elicit attentional inhibition (as the index of PD component). When cACS engage in visual search task, the processing weight of attention is affected by different attributes (color, shape, etc.), item size within category, category hierarchy. In addition, if the target is defined as multiple cACS (e.g., a digit with warm color), the different dimensions of cACS (e.g., symbol and color ) will affect attentional capture independently at the early stage, and then these two independent cACS can be integrated into one cACS in the late stage. In the late stage, the consolidation in working memory (as the index of CDA component) and the behavioral response (as the index of accuracy and response time and the involvement of SMA and precuneus) are involved.

    Future studies can focus on the categorical rejection template for distractors, the various effects of different types of cACS in attentional capture, and the mechanism of artificial cACS.

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    Serial dependence effect: A novel “history effect”
    LIU Wang-Juan, DING Xian-Feng, CHENG Xiao-Rong, FAN Zhao
    2022, 30 (10):  2228-2239.  doi: 10.3724/SP.J.1042.2022.02228
    Abstract ( 1084 )   HTML ( 40 )  
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    Serial dependence effect (SDE) refers to a stable and systematic attractive bias in which cognitive processing of the current stimuli is pulled toward the stimuli presented moments ago. Existing studies have revealed many factors modulating serial dependence effects. The first one is attention. Only stimuli that are consciously perceived can produce serial dependence effects. Secondly, sensory uncertainty of stimuli also affects serial dependence effects. Particularly, previous studies had found that stimuli with higher sensory uncertainty produced higher SDE intensity. The physical characteristics of stimuli also affect serial dependence effects. In addition, the spatial and temporal distances between the neighboring stimuli also have a tuning effect on serial dependence effects. All these distinctive features and special effects (caused perception bias, but did not influence reaction times) showed that the serial dependence effect is a brand new "history effect" (the influence of past stimuli on the current stimulus).

    The cognitive and neural mechanisms of serial dependence effects have received much attention. There are currently several mainstream views since 2014. The earliest view, i.e., the “continuity field” theory, believes that serial dependence is an effect purely at the perceptual level and occurs before the stage at which sensory signals are transformed into conscious representations. Some researchers also believe that serial dependence effects occur at the perceptual level and further they are modulated by neural feedback signals from higher levels. Another view attributes serial dependence effects to dynamic biases in working memory, while some researchers believe that serial dependence effects stem from decision-making processes. Finally, some researchers propose that serial dependence effects may exist at multiple cognitive processing stages and cannot be explained by a single mechanism. Recently, empirical progress had been made upon the neural mechanism of serial dependence effects. For example, Electroencephalogram (EEG) studies had revealed electrophysiological signals that can represent serial dependence effects starting from early stages of perceptual processing in adaptation paradigms. Evidence from fMRI studies also demonstrated an attractive bias at the level of early sensory representation imposed by previous perceptions. The latest research had discovered abnormal serial dependence effects in patients with brain injury. In addition, it was found that the dorsal premotor cortex had significant influence on visual movement-based serial dependence. The underlying mechanism of serial dependence effects is being uncovered gradually.

    Since been proposed, the serial dependence effect is thought to be a mechanism that promotes stability for visual processing by integrating visual input along the temporal dimension. However, some results are still controversial. Thus, there is still large space left for studies on serial dependence effects. In the future research, it is necessary to tackle the origin of serial dependence effects with multiple strategies, including innovation of experimental paradigms, data analysis approaches, and various cognitive neuroscience technologies. Further, future studies can focus on the modulating factors on serial dependence effects, and provide explanations to inconsistent results and individual differences of serial dependence effects in previous studies. Finally, it is also important to note that any psychological experimental design involving sequential visual stimuli in the future will have to consider the potential effects of serial dependence that may exist between past and current stimuli.

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    Unitization improves associative memory: The role of familiarity and recollection processes
    LIU Zejun, LIU Wei
    2022, 30 (10):  2240-2253.  doi: 10.3724/SP.J.1042.2022.02240
    Abstract ( 550 )   HTML ( 25 )  
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    Dual-process theory holds that memory are based on two processes: familiarity and recollection. Familiarity refers to the feeling of knowing something or someone without the retrieval of additional information. In contrast, recollection includes remembering contextual information about the learning episode. While there is agreement that item memory can be supported by both processes, associative memory is generally thought to be supported by recollection only. However, recent research suggested that familiarity can also contribute to associative memory when the to-be-associated stimuli are unitized during encoding. Graf and Schacter (1989) defined this manipulation as unitization. Subsequently, a large number of behavioral studies, ERP studies, fMRI studies, and studies of older adults began to examine the effect of unitizaiton on associative memory and its processing. The results consistently showed that both top-down unitizaiton and bottom-up unitizaiton increased the contribution of familiarity to associative memory. However, some issues have been overlooked in these studies.

    First, the vast majority of studies have considered only the effect of single-modality unitization on associative memory, while only a very small number of studies have compared the effect of different unitization on associative memory. A review of these studies reveals that conceptual unitization has a higher level of unitization than perceptual unitization and interactive imagery task, and that interactive imagery task may have a higher level of unitization than conceptual definition task. However, no studies directly compared the level of unitization between conceptual unitization and conceptual definition task, and between perceptual unitization and interactive imagery/conceptual definition tasks.

    Second, limited by experimental material selection and memory load, most studies have not matched the level of unitization between the studied and rearranged pairs. Liu et al. (2020) first introduced the variable of unitization-congruence, and three studies consistently revealed that unitization-congruence does moderate the effect of unitization on associative memory. This finding not only help resolve the current debates in the literature concerning the influence of unitization on associative memory, but also reveal the optimal condition to benefit associative recognition from unitization—when item pairs with high level of unitization at encoding are rearranged into item pairs with lower level of unitization at retrieval.

    Again, while it is widely accepted that unitization can facilitate the contribution of familiarity to associative memory, there is disagreement about the effect of unitization on the memory of the individual items that comprise the association. The ‘benefits-only’ account argues that unitization facilitates associative memory without impairing item memory, whereas the ‘benefits and costs’ account argues that unitization facilitates associative memory at the expense of item memory. A review of existing studies suggests that limited cognitive resources and semantic relatedness between the old and new words may be important in explaining these two accounts.

    Finally, there are three apparently different hypotheses about the mechanisms by which unitization occurs, namely, the item hypothesis, the schema hypothesis, and the semantic elaboration hypothesis. Combining the effects of unitization on associative and item memory, the item hypothesis seems more reasonable.

    In summary, we can not only compare the facilitation effect of different unitization on associative memory but also explore its lifelong development pattern in further study, provided that unitization-congruence needs to be taken into account.

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    Neural mechanisms of successful episodic memory aging
    ZHENG Zhiwei, XIAO Fengqiu, SHAO Qi, ZHAO Xiaofeng, HUANG Yan, LI Juan
    2022, 30 (10):  2254-2268.  doi: 10.3724/SP.J.1042.2022.02254
    Abstract ( 727 )   HTML ( 28 )  
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    Healthy aging is generally associated with a decline in episodic memory. Usually, older adults show more significant declines in associative memory than in item memory. Most previous cognitive aging studies of episodic memory focus on mean changes in memory performance with age and thus assume that older adults are a homogenous group. However, older adults demonstrate notable individual differences in episodic memory. While most older adults show a normal or pathological decline in episodic memory, some indicate successful episodic memory aging. Therefore, it is essential to investigate the neural mechanisms of individual differences in episodic memory aging to demystify the determinants of successful memory aging. This helps reveal the neural basis of human cognitive function and is insightful for developing effective interventions to improve memory function in older adults and delay cognitive aging. To date, four critical theories have been proposed to explain why some older adults exhibit successful memory aging: brain maintenance, neural dedifferentiation, cognitive reserve, and neural compensation. The brain maintenance account claims that the ability of some older adults to demonstrate successful memory aging may be explained by individual differences in brain preservation. In line with this prediction, individuals who demonstrate a relative lack of senescent brain changes and more youth-like brain activation patterns show higher levels of memory performance. The neural dedifferentiation view states that individuals with higher functional specificity of brain regions and networks may have superior episodic memory. The concept of cognitive reserve states that individual differences in cognitive operations or processes shaped by lifetime exposures allow some individuals to maintain cognitive function in the face of brain aging or pathology. The above concepts may reflect the optimization process of the selective optimization with compensation (SOC) model. Specifically, brain maintenance may reflect the results of the optimization, whereas cognitive reserve may reflect the approach for conducting the optimization process. The neural compensation hypothesis, which reflects the compensation process of the SOC model, states that some older adults can compensate for age-related neural decline or pathology to preserve high levels of cognitive and behavioral output. Based on these theories and the SOC model, we speculate that some older adults display successful memory aging because they have higher cognitive reserve shaped by several lifestyle factors throughout their lifespans. These factors include education, occupation, physical activity, cognitively stimulating activities, and other lifestyle aspects. Older adults with higher cognitive reserve can optimize the function of the brain regions and networks related to episodic memory and more successfully compensate for age-related neural decline. Ultimately, the benefits of the optimization and compensation processes are reflected in maintaining a higher level of brain function (e.g., the fidelity of neural representation or functional segregation of brain networks). Nevertheless, there are still debates regarding how to define the concept of cognitive reserve operationally, how cognitive reserve and compensation relate to one another, and how lifestyle factors affect brain maintenance, cognitive reserve, and neural compensation in older adults. Future research should incorporate more longitudinal studies to investigate the relationship between these theories and their impact factors, which would be beneficial for understanding the neural mechanisms of successful memory aging and providing support for improving brain and cognitive health in older adults.

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    The regulatory mechanism of transcutaneous vagus nerve stimulation on inhibition control
    WANG Rong, CHEN Xiaoyi, DU Xue, JIANG Jun
    2022, 30 (10):  2269-2277.  doi: 10.3724/SP.J.1042.2022.02269
    Abstract ( 596 )   HTML ( 19 )  
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    Transcutaneous vagal nerve stimulation (tVNS) is a new, safe and non-invasive brain nerve stimulation regulation technology. It applies intermittent pulse electrical stimulation to the vagus nerve branches in the human outer ear, allowing electrical signals noninvasively transmitted into the brain through the vagus nerve pathway, so as to regulate on cerebral cortical activity and related neurobiochemical markers. Previous studies have found that tVNS has a positive regulatory effect on inhibitory control.

    At present, there are two views on how tVNS regulates inhibitory control. One is that tVNS regulates the locus coeruleus-norepinephrine system (LC-NE), and then the activity of the LC-NE system directly regulates the performance in inhibitory control tasks. The other is that tVNS promotes the release of the neurotransmitter g-aminobutyric acid (GABA), and the changes of GABA concentration plays an important regulatory effect on the inhibitory control. After summarizing and reviewing the behavioral and physiological regulation effects of tVNS on inhibitory control, we further elucidated the neurobiochemical mechanism of tVNS regulating inhibitory control and the problems of previous literatures. We suggested that future research should further clarify the regulation effect and mechanism of tVNS on inhibitory control, and provide reliable theoretical basis and data support for basic research and clinical application of tVNS.

    In the future, we can further construct studies from the following three aspects. Firstly, the parameter settings of tVNS should be continuously optimized, because of the results of previous studies are difficult to compare due to the differences in experimental tasks, stimulation modes and subject groups. To determine the optimal parameter, researchers should standardize the operation process of tVNS, and conduct a systematic comparative study on the setting of related stimulation parameters such as stimulation position, intensity, pulse width, frequency. Secondly, tVNS has great potential in promoting the recovery of inhibitory control functions, and thus future study should more focus on the regulation of tVNS on inhibitory control in healthy population, and strengthen the discussion and research on groups with impaired or declined inhibitory function. Finally, tVNS is not only a scientific research tool but also a promising and valuable intervention technology to explore the long-term positive effects of tVNS on inhibitory control in delaying cognitive aging, promoting cognitive development and treating neurological and psychiatric diseases. Therefore, future research can explore the long-term positive effect of tVNS on inhibitory function, and how to maintain or enhance this long-term positive effect.

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    Neural mechanisms underlying the effect of low socioeconomic status on self-regulation
    HU Xiaoyong, DU Tangyan, LI Lanyu, WANG Tiantian
    2022, 30 (10):  2278-2290.  doi: 10.3724/SP.J.1042.2022.02278
    Abstract ( 833 )   HTML ( 55 )  
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    In the historical stage of solidly promoting common prosperity, low-income groups are the key support groups to promote common prosperity. How to improve the self-development ability of low-income groups is an important way to achieve common prosperity. One of the core abilities of self-development ability is self-regulation ability. Self-regulation is the ability to monitor and regulate cognition, emotion and behavior in order to achieve goals and adapt to the changing environment, it includes three independent and interactive components: cognition, emotion and behavior. Self-regulation has a strong and extensive impact on individual development and plays a role in various fields such as achievement, interpersonal communication and health. It not only promotes positive behavior, but also prevents bad behavior. Self-regulation is regarded as the key to human success and happiness. Improving the self-regulation ability of low-income groups is conducive to increasing human capital, increasing income, reducing medical and health care costs, and then conducive to the realization of common prosperity.

    However, many studies have found that people who live in low socioeconomic conditions have poor self-regulation ability. In order to improve their self-regulation ability, we must deeply investigate the mechanism of low socioeconomic status affecting self-regulation. Because the brain is the main channel for the environment to affect individual psychology and behavior, neuroscience methods can observe specific behavioral, cognitive and emotional brain processes, and then provide unique information, which plays an irreplaceable role: low socioeconomic status changes the structure and function of dorsolateral prefrontal cortex(DLPFC), cingulate gyrus, ventromedial prefrontal cortex(vmPFC), amygdala, hippocampus and ventral striatum(VS), and then affects various components of self-regulation (cognitive regulation, emotional regulation and behavioral regulation). Specifically, low socioeconomic status affects the structure and function of dorsolateral prefrontal cortex(DLPFC) and dorsal anterior cingulate cortex (dACC), and then affects cognitive regulation. Amygdala, ventromedial prefrontal cortex(vmPFC) and hippocampus are three key brain regions in the process of emotion regulation affected by low socioeconomic status. Ventral striatum (VS) may be the physiological basis of low socioeconomic status affecting behavioral regulation. Since behavioral regulation is the result of cognitive regulation and emotional regulation playing a role in the interrelated balance, the neural mechanism of low socioeconomic status affecting behavioral regulation may also involve brain regions related to cognitive regulation and emotional regulation.

    In order to make the research findings in this field give full play to the value of practice and policy, future research should be strengthened in the following aspects: First, for each step of the potential "causal chain" of "low socioeconomic status - brain structure and function - self-regulation - adverse consequences", there is an urgent need for more research and more in-depth investigation. Low socioeconomic status does not necessarily lead to adverse consequences, the influence of low socioeconomic status on self-regulation and its neural mechanism also have complex paths. Second, connect neurobiology with developmental psychology, and reveal the unique impact mechanism of low socioeconomic status on self-regulation at different development stages. Living in low socioeconomic conditions in a specific development stage may have a unique impact on different aspects of self-regulation. Third, in the long run, promoting the self-regulation ability of people who live in low socioeconomic conditions is the key to improving human capital and the core of realizing common prosperity. Future research should explore the adaptive response and advantageous response of people who live in low socioeconomic conditions at the neural and behavioral levels from the perspective of adaptation, which is conducive to the development of systematic, sustainable and effective self-regulation intervention schemes on the basis of mechanism research, so as to make the intervention design better adapt to the needs and potential of people who live in low socioeconomic conditions.

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    Can Instructors' eye gaze promote video learning?
    KUANG Ziyi, CHENG Meixia, LI Wenjing, WANG Fuxing, HU Xiangen
    2022, 30 (10):  2291-2302.  doi: 10.3724/SP.J.1042.2022.02291
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    The eye gaze of instructors is an important but easily overlooked element in video-based learning environments. The importance of the potential roles of eye gaze can be explained by several theories, such as parasocial theory and social agent theory. These theories suggest that an instructor’s eye gaze in video-based learning environments can promote learning. Other theories such as cognitive theory of multimedia learning and cognitive load theory suggest that an instructor’s eye gaze may hinder learning. While these theories predict the effect of an instructor’s eye gaze differently, in this review article we found inconsistencies in several empirical studies. First, the retention and transfer tests are mainly used to gauge the learning outcome. On retention tests, 9 (60%) of 15 studies show that eye gaze in the video can improve students' retention test, and 6 studies (40%) show that eye gaze can hinder students' performance on retention tests. The median effect size for the eye gaze facilitated retention test was d = 0.41. The median effect sizes for the guided gaze and direct gaze facilitated retention tests were d = 0.28 and d = 0.42. On the transfer test, 6 (40%) of 15 studies show that eye gaze in the video can improve students' transfer test, 1 study (7%) shows that eye gaze can reduce students’ performance on a transfer test, and 8 studies (53%) show that eye gaze can hinder students' performance on transfer tests. The median effect size for the eye gaze facilitated transfer tests was d = 0.39. The median effect sizes for the guided gaze and direct gaze facilitated transfer tests were d = 0.24 and d = 0.42. The above study showed a small facilitative effect of eye gaze on retention and transfer tests. Second, in terms of attentional processing, previous studies have focused on the learner's fixation times on learning materials. 6 (38%) of 16 studies show that eye gaze in the video can increase students' fixation times on learning material, 7 studies (44%) show that eye gaze can reduce students’ fixation times on learning material, and 6 studies (38%) show that eye gaze can hinder students' fixation times on learning material. The median effect size for the eye gaze facilitated fixation times on learning material was d = 0.06. The median effect sizes for the guided gaze and direct gaze facilitated fixation times were d = 0.19 and d =﹣0.14.The above studies suggest that the effect of eye gaze on attentional processing is relatively weak. Third, in terms of subjective experience, parasocial interactions and cognitive load were mainly explored. For the parasocial interaction, 5 (56%) of 9 studies show that eye gaze in the video can improve students' parasocial interaction, and 4 studies (44%) show that eye gaze can hinder students' retention test. The median effect size for the eye gaze facilitated parasocial interaction was d = 0.35. The median effect sizes for the guided gaze and direct gaze facilitated parasocial interaction were d = 0.04 and d = 0.37. Regarding cognitive load, 3 (33%) of 9 studies show that eye gaze in the video can reduce students' cognitive load, and 6 studies (44%) show that eye gaze can increase students' cognitive load. The median effect size for the eye gaze facilitated cognitive load was d =﹣0.02. The median effect sizes for the guided gaze and direct gaze facilitated cognitive load were d = -0.03 and d = 0.09. The above study showed a small facilitative effect of eye gaze on parasocial interaction, but a very weak effect on cognitive load. In addition, the above findings support the parasocial interaction theory, social agency theory, and signaling principle, but not the cognitive theory of multimedia learning or the cognitive load theory. Future research needs to consider the moderating role of the type of eye gaze, facial expressions, prior knowledge experience, and the nature of the learned material. Further exploration is needed for the cognitive processing of eye gaze affecting learning and the related cognitive neural activity.

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    Early screening and diagnosis of autism spectrum disorder assisted by artificial intelligence
    YUAN Yuzhuo, LUO Fang
    2022, 30 (10):  2303-2320.  doi: 10.3724/SP.J.1042.2022.02303
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    Symptoms of Autistic Spectrum Disorders (ASD) can manifest as early as infancy, and the earlier detection and intervention can lead to better therapeutic results. The traditional screening and diagnosis of autism comes from professionals, which is highly subjective and time-consuming, leading to misdiagnosis or missing the optimal intervention time. In recent years, with the rapid development of artificial intelligence and the accumulation of clinical data on autism, intelligent recognition methods for autism and its early symptoms have developed rapidly. This paper summarizes the research on intelligent recognition of autistic infants in the past decade, and divides the research into six sub-areas based on the data types used in the research: 1) recognition based on classical task behavior data; 2) recognition based on facial expression and emotional data; 3) recognition based on eye gaze data; 4) recognition based on brain image data; 5) recognition based on motor control and movement pattern data; 6) recognition based on multimodal data. The current technology is to use non-contact vision system and sensory devices to collect infants’ behavioral data, such as facial expression, head and limb movement, eye movement, brain image. Researchers usually develop risk behavior detection algorithms and build machine learning or deep learning models for automatic recognition according to task objectives and data characteristics. At present, it can reach the precision of scale tools and manual evaluation. The current modeling trend is to use a multimodal fusion framework to build prediction models based on the complementary relationship between multimodal information, feature transformation and representation patterns of autistic infants, which is expected to further improve the recognition accuracy. In the future, researchers should focus on building an intelligent medical screening and diagnosis system for early autism, developing screening tools for infants and young children, establishing a refined diagnosis method for autism combined with brain imaging technology, and building an intelligent recognition model for autistic infants by integrating multimodal data. In addition, to carry out high-quality intelligent recognition research, a large-scale database of autism and high-risk infants and corresponding behavioral characteristic database should be established as soon as possible, and risk behaviors were marked in coarse and fine granularity according to the early behavioral diagnostic criteria of autism. Currently, in the face of the contradiction between the large demand for model training data and the lack of autistic samples, researchers can first try to use small sample learning methods, such as model fine-tuning, data augmentation, transfer learning.

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    Application of machine learning in early identification and diagnosis of autistic children
    HOU Tingting, CHEN Xiao, KONG Depeng, SHAO Xiujun, LIN Fengxun, LI Kaiyun
    2022, 30 (10):  2321-2337.  doi: 10.3724/SP.J.1042.2022.02321
    Abstract ( 1349 )   HTML ( 84 )  
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    In recent years, autism spectrum disorder has gradually become a major global public health problem due to complex etiology and large group, and its prevalence rate has been rising all over the world. A series of explorations and discussions, which focused on effective intervention, have been conducted in this field. Early detection, early diagnosis and early intervention have been determined as the consensus of autistic children education and rehabilitation. However, both the limitations of traditional identification and diagnosis methods and the lack of professionals mostly caused the miss of the well-timed intervention in autistic children. However, traditional identification and diagnosis methods often have some limitations (e.g., strong subjectivity, time-consuming) and face the situation that lack of professionals and higher requirements for professional clinical ability, which seriously affect the early intervention of autistic children and even make them miss the best opportunity of education and rehabilitation; Furthermore, which brings huge psychological and economic burden to autistic children and their families. In order to improve this situation, machine learning has made great achievement in recent years. With its advantages of objectivity, accuracy, simplicity and flexibility, machine learning has been gradually applied in the early prediction, screening, diagnosis and evaluation of autism. Previous studies were mostly conducted on the basis of traditional machine learning algorithms (e.g., support vector machines, naive bayes and random forest) or deep learning algorithms (e.g.,, convolutional neural network, artificial neural network and multilayer perceptions), and the analysis of EEG signals, behavioral data and genetic data could support for establishing predictive or classification models which contribute to predict, identify and diagnose autistic children. Compared with the traditional classification, this method could not only improve the efficiency and reduce the pressure of professionals, but also automatically extract and sort out subtle and potentially critical information from a large amount of data. Moreover, it could gain insight into the inherent laws of complex problems, build a multimodal classification model, complement each other's advantages, and improve the classification accuracy. However, machine learning has limitations in the selection of research objects, the extraction and collection of classified data, and the application of theoretical models. To solve the above problems, first of all, future research should clarify the pathology, etiology and course factors of autism in the early stage of development, and promote the construction of a tracking database of pathophysiological information of pregnant women and newborn. The data collection of the health information of pregnant women and their family could know about related genetic and environmental teratogenic factors and try to transfer "passive waiting" to "active defense" and avoid obstacles as soon as possible. Secondly, it is very important to sort out the criteria and basis for selecting classification indicators and improve the fineness of indicators. For example, the appropriate classification indicators, which adapt to autistic children come from different age groups and different disability degree groups, should be determined. Following studies should gradually detectestable, widely adaptable and higher accurate indicators. The build of a more scientific and stable standardized classification index system could promote the internal order of classification indexes. Finally, the actual needs and worries of different audiences should be carefully investigated. The problems such as sample representativeness, model applicability, algorithm accuracy and stability should be solved as well. The extension of propaganda about theoretical research achievements is needed; Meanwhile, more efforts should be taken to accelerate the transformation from theoretical achievements of intelligent autism identification and diagnosis to practice.

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    Psychological challenge and its explanation of first-generation college students: A perspective from cultural mismatch theory
    LI Yusu, ZHANG Kun, BI Yanling, ZHANG Baoshan
    2022, 30 (10):  2338-2355.  doi: 10.3724/SP.J.1042.2022.02338
    Abstract ( 1319 )   HTML ( 68 )  
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    As a critical institution for promoting and nurturing the adequate development of college students, universities should provide equal opportunities for the growth of students from difference life circumstances. In the current higher education, first-generation college students(neither parent has a college degree) confront additional background-specific obstacles in campus adjustment, academic performance and interpersonal interactions, and they underperformed relative to non-first-generation college students (at least one parent has a college degree). Cultural mismatch theory provides an alternative explanation for the disadvantages of first-generation college students from the perspective of disparate experiences between their interdependent self-values and values of independence typical of higher education.

    Cultural mismatch theory proposes that one barrier to effectively addressing social class achievement disparities in universities is the unresolved clash between two cultural norms of the individual and institution level. At the individual level, through social contexts such as family, community and school, students from different social class backgrounds develop a cultural model of self that is compatible with their class. Specifically, first-generation students, who are from lower social class backgrounds, are often dominated by an interdependent model of self. In contrast, non-first-generation students, who are from middle-and upper-class backgrounds, are more often dominated by an independent model of self. At the institution level, institutions of higher education are built and organized according to taken for granted, individualistic cultural norms represented by independence, unwritten codes. Given the variation in the models of self that students bring with them to college, and the different cultural norms they afford, students’ cultural norms can either match or mismatch the college environment.

    Two models (normative well-being model and critical cultural wealth model) were introduced to better understand the effect of cultural mismatch on first-generation college students. By combining these models, we broaden and develop a more comprehensive framework from which to understand first-generation college students’ campus experiences. The framework presented here describes students’ academic performance and psychological well-being using the following four dimensions: individual personality traits, campus cultural tendencies, psychological processes and school-family conflict. These dimensions are collectively may be used as a framework to capture the academic difficulties, self-cognition, and social pressure.

    Interventions informed by this theory can help first-generation college students to make sense of the source of additional challenges they face, equip them with the right kinds of tools and strategies. Interventions for mitigating social disparities in education are multifaceted and complicated, including both values affirmation intervention and difference education intervention. A common assumption in these interventions is that first-generation college students need psychological resources, including the critical insight that people who have background like theirs deserve to attend college and can thrive there. Values affirmation intervention demonstrates one key process through which motivational education improves individual self-integrity and perception of self-worth, that is, by affirming one’s core values. Difference education intervention provides first-generation college students a contextual theory from the experiences of senior students with similar backgrounds, in this format, it can improve disadvantaged students’ campus fit and academic performance.

    The theory of cultural mismatch is of great theoretical significance and practical value in promoting the all-round development of university students, mitigating the achievement gap between social classes and improving the equity of current higher education. Several directions (e.g., role of personality factors, the shaping of a multiple self, advocacy for a diverse cultural environment in higher education, self-development in the face of social change, the role of unique cultural attributes) for future research are discussed.

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    The impact of partner choice on cooperative behavior and its mechanisms
    TANG Hui, LI Xinyu, WEI Yifan, LI Xiaocai, CHEN Liuyan, ZHANG Yao
    2022, 30 (10):  2356-2371.  doi: 10.3724/SP.J.1042.2022.02356
    Abstract ( 1391 )   HTML ( 98 )  
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    Partner choice refers to the individual’s behavior of choosing or refusing to engage in partnerships with other individuals based on whether they can bring benefits to him/her. Partner choice is an independent mechanism that promotes cooperative behavior. The theory of reciprocity based on partner control condition has dominated the discussion of non-kin cooperation for a long time. In contrast to the partner control condition, under which individuals focus on how to avoid being exploited by a defector to facilitate cooperation (e.g., the “tit-for-tat” strategy), under the partner choice condition, individuals can focus on both avoiding exploitation by leaving a defector and finding a better partner to get more substantial benefits. Briefly, it comprises three main aspects. First, partner choice itself can promote cooperation through leaving defectors and choosing partners; only partner choice is enough to bring about cooperative behaviors. Second, individuals can seek reliable cooperators to promote higher-level cooperation based not only on simple behaviors of others but also on stable information at the trait level (such as generosity, moral character, etc.). Third, in terms of internal mechanisms, in the process of partner choice, individuals may promote cooperation primarily through the punishment mechanism of walking away from uncooperative individuals (i.e., ostracism), the reward mechanism of seeking better cooperators, the assortative matching mechanism, and the competition mechanism of winning partners by developing competitive altruism. The punishment and reward mechanisms concern individual behavior, while the assortative matching and competition mechanisms involve the entire social system. In partner choice, individuals focus on finding more cooperative partners that leads to greater benefits rather than punishing others. Therefore, the promotion of cooperative behavior by partner choice needs to be explained more with the reward mechanism, the assortative matching mechanism and the competition mechanism.

    In the future, studies should investigate various aspects of partner choice. First, tools should be developed to measure partner choice ability from the perspectives of behavioral and cognitive ability and to explore the timing and constraints of partner replacement from the perspective of rule or system design. Second, the ecological validity of partner choice research should be improved by adding the cost of “quitting” in the experimental paradigm, allowing individuals to use a wider range of information to select partners, and using a gambling paradigm that can produce mutualistic cooperation. Third, studies should further explore the internal mechanisms of the promotion of cooperative behavior by partner choice. Under the condition of partner choice, individuals may see cooperation as their goal, rather than as the means to obtain material benefits. In addition, partner choice may not only involve the judgment of a partner’s generosity and morality, but also may involve the evaluation of common ground with a partner in their goals, behavioral norms, skills, and personality traits. Fourth, studies should solve the problem of low cooperation tendency under the condition of static network or partner control in light of partner choice, such as by exploring the proportion of dynamic network in an individual's interpersonal network that can best promote cooperative behavior in a static network. Finally, indigenous research should be carried out to explore partner choice and cooperation issues in the context of Chinese culture.

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    You get what you pay for? The mechanisms and moderators of price-quality effect
    ZHAO Na, QIN Xuezhe, LIU Yaqian, SUN Ling
    2022, 30 (10):  2372-2380.  doi: 10.3724/SP.J.1042.2022.02372
    Abstract ( 1114 )   HTML ( 39 )  
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    Decades of research have established that price is one important extrinsic clue to judge the quality of product. The price-quality effect refers to the tendency to use clues such as price to judge product quality, which is one of the main findings in the marketing literature. However, previous studies also showed that price, as an extrinsic clue, was not always a good indicator of product. It is largely affected by individual’s subjective psychological state, such as attitudes, emotions and values. Though branch of studies explored the key role of price-quality effect in consumption psychology and consumption behavior, the answer to the question of why price quality effect occur is still not clear enough.

    There are several theories that can explain the price-quality effect, including selective information processing theory, reference-dependent model, and assimilation-contrast theory. The selective information processing theory states that the evidential bases for judgments are often scattered and complex. Consumers often simplify the judgment evaluation process by focusing selectively on the hypothesis-consistent evidence while neglecting the hypothesis-inconsistent evidence. The reference-dependent model demonstrated how people trade-off between satisfaction and expectation during the consumption. Assimilation/contrast explains this phenomena from the perspective of consuming experiences. Meanwhile, there are also a large number of studies have examined the neural mechanisms in the judgment of price-quality effect. However, these studies mainly focused on eating behavior which the external validity needs to be further verified.

    Meanwhile, the price-quality effect was moderated by several factors, such as product characteristics, individual differences, group and social-culture contexts. Generally speaking, consumers are more easily judge the quality from its price of luxury product than common ones. Also, there are many individual differences moderated the relationship between price and quality, such as emotion, construct level, familiarity of product and need for closure. The relationship also moderated by interpersonal factors such as interpersonal relationship, group identity and group norms. The relationship of price and quality also varied by different culture. These moderators also have interactive effects on price-quality effect.

    Although the current research have made fruitful results focused on the price-quality effect, the future studies still should pay attention to the following issues. Firstly, we suggested that the future study should pay more attention to the dynamic relationship between price and quality throughout the life cycle of the product. Every product has its life cycles and there are different relationships between price and quality in different cycles. Studies show that the price in judging the quality of product weights more in the start stage of a new product and weights less in the last stage. Secondly, it is promising to examine the price-quality effect from the perspective of the native cultures. In a “face culture” context, products also stand for individual’s ability and social status. From this perspective, Renqing, Guanxi and other native icons play important role in price-quality judgement. Thirdly, the different patterns of price-quality between online and offline should be taken into consideration as well. In offline consumption, due to the limitation of physical space, there is relatively little information for consumers to refer. Hence, price clues account for a large proportion in quality evaluation. However, there are more reference clues for online consumption behavior, which reducing the weight of price in quality evaluation. Finally, future research also needs to consider whether the relationship between price and quality is linear. When the price quality effect is used as the basis for business pricing, the sales amount may increase in the short term, but its follow-up effect should also be taken into account, which aimed to avoid the “one hammer trading”.

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