Subjects: Psychology >> Experimental Psychology submitted time 2023-11-15
Abstract： Emotions surface during interaction between individuals. Thus, an accurate recognition of facial expressions is essential in the realm of social interactions. In recent years, numerous studies have revealed that individuals not only depend on facial configuration information for identifying facial expressions but also place considerable emphasis on contextual information extracted from external cues beyond the face. People’s behavior frequently unfolds within intricate social group dynamics, wherein individuals often perceive and interpret the facial expressions of their fellow group members during interaction. However, the impact of group information on facial expression recognition, being an essential social contextual factor, remains somewhat unclear. Hence, three experiments were conducted to investigate the influence exerted by group information on the recognition of facial expressions.
The stimuli used in the study were happy, fearful, and neutral face images selected from the NimStim set, including 15 pictures (seven females) of each of the aforementioned emotions. Group information was manipulated following the presentation of a fixation cross through perceptual cues. Subsequently, during the facial expression recognition phase, participants were instructed to recognize the facial expressions exhibited by target individuals. In the first experiment, participants were instructed to rate the intensity of target facial expressions on a six-emotion scale, and the surrounding facial expressions were always congruent with the target facial expressions. A total of 29 college students (16 females, mean age 20.00 ± 1.80 years) were recruited to participate in this experiment. In Experiments 2 and 3, we manipulated the emotional congruency between the surrounding faces and the target faces during the facial expression recognition phase. Additionally, we controlled for variations in physical characteristics across different experimental conditions. The task requirement of Experiment 2 was the same as those of Experiment 1. However, in Experiment 3, participants were instructed to judge the target facial expressions by pressing corresponding keys on the keyboard as quickly and accurately as possible. A total of 26 college students (14 females, mean age 21.15 ± 1.99 years) participated in Experiment 2, and 32 college students (15 females, mean age 21.20 ± 1.60 years) participated in Experiment 3.
Results revealed the following: (1) Compared with emotion-incongruent conditions, emotional congruency between target faces and surrounding faces resulted in shorter RTs and higher accuracy. (2) Group information regulated the influence of surrounding facial expressions on target facial expression recognition. Specifically, under group conditions, participants tended to recognize target facial expressions according to the emotional state of the surrounding faces. When the target facial expressions in line with the expectations established by the participants that group members have congruent emotional state, the recognition of target facial expressions was faster and more accurate than incongruent conditions. However, under nongroup conditions, participants recognized target facial expressions without reference to the emotional states of the surrounding faces. (3) Participants exhibited a faster and more accurate recognition of happy faces, indicating the recognition advantage effect for happy facial expressions.
Results revealed that group information influenced facial expression recognition, individuals recognized facial expressions based on the social relationship between the interactions, and understanding social interaction plays an important role in the process of emotion perception.
Subjects: Psychology >> Social Psychology submitted time 2023-09-27
Abstract： In recent years, social transformation and economic development in China have changed people’s behaviour, lifestyles, and values and have directly affected individuals’ mental state and behaviour. However, due to the limitations of research methods, previous studies have explored target variables from a single dimension. They have lacked exploration of the multidimensional structure of complex variables and have been unable to directly compare cross-scale data. Therefore, social and cultural psychology research needs to incorporate a systems science perspective to study and understand the structure and pattern of social changes.
This study introduces a new approach for exploring social change from the perspective of pattern-representational similarity analysis (RSA). Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS)-Longitudinal Data (1998～2018), we demonstrate the process of the construction of representation similarity matrices and provide examples of multivariable-unidimensional pattern analysis (time, space, mental space), multivariable cross-dimensional pattern analysis (mental space-time, mental space-space, mental space-time-space), cross-scale model analysis (region-country), conceptual model analysis, and coupling analysis between RSA and traditional methods.
This study finds that the pattern and level of economic development moderates the similarity between regional mental health change patterns and the overall pattern of elderly individuals. In addition, the cultural looseness-tightness concept model and the interregional pattern of mental health among elderly individuals have significant similarities. These results show that RSA analysis can explore the relationship between variables from the perspective of patterns and can make direct quantitative comparisons of cross-scale data.
Overall, this study introduces different methods for the application of RSA in social change research through demonstrative examples. The exploration of psychological and behavioural changes in social change from a pattern perspective paves the way for future exploration.
Subjects: Psychology >> Social Psychology Subjects: Psychology >> Developmental Psychology submitted time 2023-05-17
Abstract： Perception of groups develops from an early age. Previous studies focused on groups with perceptual-salient cues like gender and race. As highlighted in the intuitive theories of social categorization, children perceive social groups as natural kinds or serving functional roles of social obligation. However, the priority ofthese two aspects affecting children’s group perception is yet to be explored. Our current research summarized these two aspects into physical-type and societal-type cues. Physical-type cues are identified by perceptual-salient attributes related to people like color, gender, and socioeconomic status (SES). Societal-type cues reflect shared attitudes, beliefs, and values among group members, such as common interests, group belongings, and norms. It has previously been found that children start to endorse prescriptive norms around age five. Therefore, we assume that children’s preferences for societal-type cues will increase across ages 3 to 8, with a critical period of 5 to 6 years of age. Study 1 was tested online. A total of 215 children (108 males) ages 3 to 8 were recruited. Three physical-type and three societal-type cues were paired under nine experimental conditions. Two tasks were conducted in random order between the participants: The Triad ClassificationTask and the Exclusion Task. Both tasksrequired participantsto categorize targets based on one of the two given cues (each represented by one cue-type). In the Triad Classification Task, children needed to select one target from two peers, and in the Exclusion Task, they needed to exclude one target. Study 2 tested 3- to 8-year-old children offline (3- to 4-year-olds: 32 children; 5- to 6-year-olds: 21 children; 7- to 8-year-olds: 20 children). Six cues were combined into two experimental conditions(gender × color × norm vs. SES × common interest × belonging). Children were tested using the Opening Social Categorization Task, in which they categorized eight targets into two groups, and reported the reasons for categorization. Results of the two studies demonstrated that 3-to 8-year-olds could apply physical-type and societal-type cuesto group perception. Specifically, childrenrely more on societal-type cues than physical-type cues as they grow up. The 3- to 4-year-olds preferred societal-type cues in social categorization tasks with two choices (Study 1), and physical-type cues in tasks offering three choices(Study 2). Children aged 5 to 8 displayed preferencesforsocietal-type cuesin the tasks of Study 1, whereasshowed no cue preferences in Study 2. Therefore, for young children (3- to 6- year-olds), their preferencesforsocietal-type cues were sensitive to the number of cues provided in the social categorization tasks, and offline versus online measurements. Moreover, children’s cue-type preferences differed significantly between 3- to 4-year-olds (preferred physical-type cues) and 7- to 8-year-olds(preferredsocietal-type cues). Thus, the critical period for developing a preference for societal cues was 5 to 6 years of age. Thisstudy constructs a new framework of physical-type and societal-type cues to understand children’ssocial categorization and group perception. These two types of cues reflect children’s perceptual and conceptual foundation in theirsocial categorization. Across ages, children’s ability to apply physical-type and societal-type cuessupportsthe intuitive theory of social categorization that children are naturally perceived as groups from two aspects. Physical and societal aspects may be the basic dimensions of group perception. Future research could extend the present findingsto othersocial categories, and more importantly, provide more neurobiological evidence for children’s biases toward societal-type cues.
Subjects: Psychology >> Cognitive Psychology submitted time 2022-01-13
Abstract：
Facial attractiveness plays a crucial role in important social decisions (e.g., mate selection, job search, social exchange, etc.). Previous studies on facial attractiveness emphasized the evolutionary approach to interpret the effect of facial features on facial attractiveness while rarely paid attention to the cognitive representation of facial attractiveness. In recent years, the study of dynamic faces has gathered increasing research interest. Furthermore, it has been found that motion can improve facial attractiveness, but the mechanism is not clear. This project will adopt behavioral experiments, combined with eye-tracking technology and statistical methodology like structural equation modeling, to explore the holistic representation of facial attractiveness. From the perspective of holistic processing, attention, and vitality, this project will shed light on the enhancement mechanism of dynamic facial attractiveness. This project will deepen our understanding of facial attractiveness and human’s high-level intelligence required for aesthetic perception. Also, the research results of this project will have potential applications for daily interpersonal interaction, artificial intelligence, and so on.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Developmental Psychology submitted time 2021-07-21
Abstract： Representing the numerical value of symbolic fraction is central to the conceptual learning of symbolic fraction. The representation of symbolic fraction has been hypothesized to be built on non-symbolic magnitude representation (e.g., representing the magnitude of a set, or the proportion between two magnitudes) that exists since human early infancy. The supportive evidence includes that non-symbolic magnitude representation, especially the non-symbolic representation for the proportion between quantities, is correlated with the representation for symbolic fraction in behavioral and brain neural responses. However, further research is needed to determine the unique and causal relation between non-symbolic magnitude representation and symbolic fraction representation, and to clarify the specific cognitive mechanism underlying symbolic fraction representation.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2021-06-19
Abstract： Visual working memory (VWM) is a limited-capacity cognitive system that is responsible for temporarily storing up to three or four items, maintaining their availability for current cognitive processing. Although VWM capacity is limited, the limit is not fixed. Factors such as the complexity, statistical regularity, real-world spatial regularity, and perceptual grouping principles of memory objects can modulate this capacity. However, the potential influence of higher-order conceptual regularities, such as categorical relationships among memory objects, remains an open and controversial issue. The effect of object category on VWM capacity, if any, has two possibilities: a mixed-category advantage and a same-category advantage. The first is consistent with the neural resource theory, by which the ability to simultaneously process multiple items is limited by the extent to which those items are represented by nonoverlapping neural representations. The same-category advantage is consistent with a prediction yielded by an ideal-observer analysis of VWM, based on the rate-distortion theory. Although the mixed-category advantage is predicted by the neural resource theory, almost all current supporting evidence solely involves faces. On the other hand, although the same-category advantage is consistent with the ideal-observer prediction, there is still lack of direct evidence to support the generalization of this prediction from low-level to high-level features. Hence, in the present study, we used behavioral and electrophysiological methods to explore this issue. Here, we report two behavioral experiments and one event-related-potentials (ERPs) experiment that assess whether category knowledge affects VWM capacity. The experiments were carried out on 60 undergraduate students. A 2 (memory load: two or four) × 2 (category: same or different) × 2 (posture: high similar or low similar) within-subject design was used in this experiment 1. The results showed that category knowledge modulates the capacity of the VWM and leads to a same-category advantage. In experiment2, we changed the presentation of MIs from simultaneous to successive and replicated the findings from Experiment 1, demonstrating that category knowledge leads to larger memory capacity in the same-category rather than in the different-category condition, even if the MIs are sequentially presented. In Experiment 3, in addition to Cowan’s K, the electrophysiological index CDA was measured to further explore the processing mechanism underlying the same-category advantage. Our electrophysiology results show for the first time that same-category objects can induce a smaller contralateral delay activity (an index of VWM capacity) than different-category objects. The CDA results combined with behavioral results indicated that category knowledge can help compact the representations of same-category objects and therefore enlarge the total information capacity of VWM. In conclusion, our data clearly demonstrate an advantageous same-category effect on the capacity of VWM, which indicates that categorical relationships among objects play an important role in expanding the capacity of VWM by enabling the grouping of same-category objects. This suggests that VWM capacity is not fixed but can be flexible depending on the type of information to be remembered. Moreover, our data also suggest that the ideal-observer prediction can be extended from low-level to high-level features.
Subjects: Psychology >> Statistics in Psychology submitted time 2021-05-08
Abstract： In the fields of psychology, education, and clinical science, researchers have devoted increased attention to the dynamic changes and personalized modeling of individuals' behaviors, minds, and treatment effects over time. Intensive longitudinal data is a set of measures collected at multiple time points with higher frequency over shorter periods. Thus, it can be used in the analysis of the dynamics and mechanisms of within-person processes. In recent years, intensive longitudinal design has become one of the most prominent and promising approaches in psychological research. However, many of these researches still rely on traditional data analysis methods. Many models have been proposed to analyze intensive longitudinal data, including top-down approaches (e.g., dynamic structural equation model, DSEM) and bottom-up approaches (e.g., group iterative multiple model estimation, GIMME). Both of the methods can conveniently model autoregressive and cross-lagged effects in intensive longitudinal data.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2021-04-25
Abstract： 在心理学研究中，以下两种情况下研究者可能需要对零效应进行评估：第一，推断某种效应不存在；第二，意外出现不显著结果，需要区分到底是效应不存在还是当前数据未能提供足够的证据。然而，常用的原假设显著性检验（Null hypothesis significance test, NHST）无法直接评估零效应。近年来，等价检验、贝叶斯估计和贝叶斯因子三种方法逐渐被用于评估零效应：在频率统计框架下，等价检验通过检验效应是否在最小感兴趣区内（Smallest effect size of interest, SESOI），通过p值来推断效应是否为零；在贝叶斯统计框架下，贝叶斯估计通过对比后验分布的最高密度区间和实际等价区的重叠情况，推断效应是否为零；而贝叶斯因子则是通过评估当前数据对原假设和备择假设的相对支持程度，推断当前数据对原假设的相对支持程度。文章通过分析两个真实的数据，展示三种方法的实际应用。三种方法各有其特点：等价检验在逻辑上是对NHST的拓展，易于从传统统计中延伸使用；贝叶斯因子的解读较符合直觉，逻辑上清晰；贝叶斯估计则具有较强的灵活性，可拓展于更多的研究问题。以上三种评估零效应的方法，可能能够帮助心理学研究者在实际研究中进行合理的统计推断和研究决策。
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2020-10-27
Abstract： In the research of psychology, education, and organizational behavior, researchers often encounter multilevel data with hierarchical structures (e.g., participants may cluster within communities, classes, or clinics). Ignoring the hierarchical structures of data may lead to a violation of the independence assumption of some models, resulting in biased parameter estimates. Therefore, researchers often need to conduct multilevel modeling to solve the statistical problems caused by non-independent observations. However, due to the limitation of objective conditions, in real studies, the sample sizes of level 1 and/or level 2 are often small in hierarchical data. Traditional frequentist-based maximum likelihood (ML) approach, which relies on large-sample theory, might lead to problems in parameter estimation and model convergence in multilevel modeling with small samples. In contrast, Bayesian approach is often more advantageous in small samples, but it is also more susceptible to the subjective specification of priors. To investigate the potentially detrimental effects of inaccurate prior information on Bayesian approaches and compare their performance to the traditional approaches, we conducted a series of simulations under the multilevel model framework with different dependent variable types (i.e., continuous normal, continuous non-normal, and binary dependent variables), sample sizes and intraclass correlation coefficients (ICCs). In sum, the results revealed the devastating impacts of inaccurate prior information on Bayesian estimation, especially in the cases of larger ICC, smaller level 2 sample size, and smaller prior variance. When the dependent variable was non-normal or binary, these negative effects were more obvious. The present study investigated the impacts of inaccurate prior information on Bayesian estimation and provided advice on the specification of priors. We hope that it could contribute to strengthening the theoretical and practical understanding of prior specifications.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2020-10-23
Abstract： Behavioral oscillations are periodic changes of behavioral performance which result from rhythmic mental processes. Through behavioral methods that have high temporal resolutions, prior studies have provided a unique perspective to investigate the temporal dynamics of visual attention. Phenomena of behavioral oscillations were observed in many types of attentional tasks. There was much evidence supporting that attentional sampling showed periodic changes mainly at two different rhythms: α (8-13 Hz) band which reflects attentional suppression and θ (4-8 Hz) band which reflects attentional shift. These results help revealing the temporal dynamics of attention and provide a new approach for the controversy between serial- and parallel-search theories of attention. Some potential factors, including task difficulty and cue validity, were found to be able to influence the rhythmic characteristics of behavioral oscillations. Behavioral oscillations showed consistent rhythms with neural oscillations in some attentional tasks, suggesting that they might involve similar mental processes. To systematically reveal the temporal dynamics of attention, future studies are needed to investigate the specific patterns of behavioral oscillations under various attentional control processes, as well as in multimodal attentional tasks. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2020-10-17
Abstract： P-value is the most widely used statistical index for inference in science. Unfortunately, researchers in psychological science may not be able to interpret p-value correctly, resulting in possible mistakes in statistical inference. Our specific goal was to estimate how nonsignificant results were interpreted in the empirical studies published in Chinese Journals. Frist, We randomly selected 500 empirical research papers published in 2017 and 2018 in five Chinese prominent journals (Acta Psychological Sinica, Psychological Science, Chinese Journal of Clinical Psychology, Psychological Development and Education, Psychological and Behavioral Studies). Secondly, we screened the abstracts of the selected articles and judged whether they contained negative statements. Thirdly, we categorized each negative statement into 4 categories (Correct-frequentist, Incorrect-frequentist: whole population, Incorrect-frequentist: current sample, Difficult to judge). Finally, we calculated Bayes factors based on the t values and sample size associated with the nonsignificant results to investigate whether empirical data provide enough evidence in favor of null hypothesis. Our survey revealed that: (1) 36% of these abstracts (n = 180) mentioned nonsignificant results; (2) there were 236 negative statements in the article that referred to nonsignificant results in abstracts, and 41% negative statements misinterpreted nonsignificant results; (3) 5.1% (n = 2) nonsignificant results can provide strong evidence in favor of null hypothesis (BF01 > 10). The results suggest that Chinese researchers need to enhance their understanding of nonsignificant results and use more appropriate statistical methods to extract information from non-significant results.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2020-05-14
Abstract： Psychological researches focus on describing, explaining and predicting behavior, and having a good understanding of the association between variables is an essential part of this process. Regression analysis, a method to evaluate the relationship between variables, is widely used in psychological studies. However, due to its highly focus on the interpretation of sample data, the traditional ordinary least squares regression has several drawbacks, such as over-fitting problem and limitation on dealing with multicollinearity, which may undermine the generalizability of the model. These drawbacks have an inevitable influence on the promotion and prediction of the model conclusion. With the rapid development of methodology, Least absolute shrinkage and selection operator (Lasso) regression has been emerged to better compensate for the limitations of traditional methods. By introducing a penalty term in the model and shrinking the regression coefficients to zero, Lasso regression can achieve a higher accuracy of model prediction and model generalizability with the cost of a certain estimation bias. Besides, Lasso regression can also effectively deal with the multicollinearity problem. Therefore, it has been widely used in medicine, economics, neuroscience and other fields. In psychology, due to the limitations of computer computing power, researchers used to mainly rely on hypothesis testing to understand the association among variables to verify theories. Now, with the rapid development of machine learning, a shift from focusing on interpretation of the regression coefficients to improving the prediction of the model has emerged and become more and more important. Therefore, based on fundamental theories and real data analysis, the aim of this paper is to introduce the principles, implementation steps and advantages of the Lasso regression. With the help of statistic science, it is promising that more and more applied researchers will be called upon to focus on the emerging statistical tools to promote the development of psychology.
Subjects: Psychology >> Cognitive Psychology submitted time 2020-04-24
Abstract： "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2020-01-14
Abstract： Human perception to near-threshold visual stimuli is not always reliable. To investigate variability of visual perception and its neural mechanism, some researchers focus on the influences of prestimulus ongoing alpha oscillations (8~13 Hz) on visual perception. Recently, studies found that decrease of prestimulus alpha power associated with improvement of observers’ detection rate, but no such effect on perception accuracy was found. In addition, phase of prestimulus alpha was reported to predict whether an observer can detect the following visual stimulus or not. Thus, power of prestimulus alpha is considered to reflect the excitability of visual cortex; decrease of alpha power indicates increase of cortical excitability, which results in higher detection rate of near-threshold stimuli. Nevertheless, phase of prestimulus alpha might play a role in regulating the time of excitation and inhibition of the cortex, and the different brain states (excitation or inhibition) at stimulus onset would lead to different perceptions of the stimulus.
Peer Review Status:Awaiting Review
Subjects: Psychology >> Cognitive Psychology submitted time 2020-01-08
Abstract： Feature-based attention (FBA) is the ability that observers can direct their attention to a specific feature dimension or value. In the attentional focus, FBA can modulate the response of neurons in visual cortex: it selectively increases the responses of neurons encoding attended features while suppresses the responses of neurons encoding distracting features. Many studies found that this attentional modulation can spread outside the focus of attention, but the underlying mechanism of the global modulation of FBA (enhancement or suppression) is still controversial. The global enhancement mechanism and the global suppression mechanism are different in time courses and may play distinctive roles in visual information processing. Compared to the global enhancement mechanism, the global suppression mechanism seems more likely to be influenced by experimental designs and parameters. Future studies are needed to investigate under what conditions the global suppression mechanism takes effect and to further disassociate these two global mechanisms in the process of feature-based attention.
Subjects: Psychology >> Statistics in Psychology submitted time 2019-04-15
Abstract： The recent replication crisis in psychology has motivated many researchers to reform the methods they used in research, reporting effect sizes (ES) and their confidence intervals (CIs) becomes a new standard in mainstream journals. However, a practical tutorial for calculating CIs is still lacking. In this primer, we introduced theoretical basis of CIs of the two most widely-used effect size, Cohen's d and η2, in plain language. The CIs of both Cohen's d and η2 are calculated under the condition that the alternative hypothesis (H1) is true, and both rely on the estimation of non-centrality parameters of non-central distributions by using iterative approximations. More specifically, non-central t-distribution for Cohen's d and non-central F-distribution for η2. Then, we illustrated how to calculate them in R and JASP with real data. This practical primer may help Chinese psychological researchers understand the CIs better and report CIs in their own research. "
Peer Review Status:Awaiting Review
Subjects: Psychology >> Statistics in Psychology submitted time 2019-03-01
Abstract： Measurement invariance (MI) is a pre-requisite for comparison between groups under the framework of latent variables. But in traditional multi-group factor analysis, scalar invariance is almost unachievable in practice. The Bayesian approximate MI proposed by Muthén and Asparouhov (2013) compensates for this limitation to some extent by providing a zero-mean, small-variance prior for the differences in measurement parameters. It allows for small differences between groups and avoids the problem caused by strict restrictions in classical method, such as poor model fitting, awkward model modifications and higher Type I error rate. These strengths make this new approach a more suitable method in the practical research. Throughout the paper we summarized the principles and advantages of the approximate MI approach, and a real data set was analyzed to demonstrate the validity and practical usefulness of this approach using Mplus. "
Peer Review Status:Awaiting Review
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