视觉搜索过程中的眼跳及其机制

该文对视觉搜索过程中的眼跳及其时间进程、神经机制及相关的理论与模型等方面研究进行了回顾。发现内外源性眼跳得到了研究者的普遍关注,对眼运动记忆、返回抑制及眼跳时间进程的研究尚存在分歧。关于眼跳的神经机制,额叶眼动区与上丘分别被认为是眼跳的关键区与指令发出者。尽管不同的眼跳理论与模型对眼跳现象给出了各自的解释,但都不尽完善,尚需对这些理论进行整合或者提出新的解释模型。文章还对未来的研究进行了展望     

国外人格障碍五因素模型研究述评

近些年来,国外许多心理学家致力于将基础的人格理论和人格障碍研究相结合的工作,其中将五因素模型引入人格障碍的研究已经取得了很大进展。文章主要总结了这方面的研究成果,探讨了将五因素模型应用于临床诊断和干预的可能性,最后讨论了未来人格障碍的研究方向     

Modeling developmental transitions on the balance scale task

Periods of relatively stable, rule‐like behavior alternated with short transition periods characterize cognitive development on reasoning tasks like the balance scale task. Each transition gives rise to an improvement in behavior, until a phase is reached in which performance is flawless or improvement is not worthwhile given the necessary extra effort. Several computational models have been developed to capture the developmental phenomena associated with the balance scale task. These models, which originate from different computational traditions, explain the main phenomena of development. Recently, empirical phenomena have been reported that these models cannot easily accommodate. We propose a computational model that is implemented in ACT‐R and that is based on the evaluation of success of applied knowledge, combined with a mechanism to construct newknowledge by searching for differences between the left‐ and right‐hand sides of presented balance scale problems. This model accounts for the main empirical phenomena as well as for the recently reported empirical phenomena such as learning without feedback.     

An accumulator model for responses and response times in tests based on the proportional hazards model

Latent trait models for responses and response times in tests often lack a substantial interpretation in terms of a cognitive process model. This is a drawback because process models are helpful in clarifying the meaning of the latent traits. In the present paper, a new model for responses and response times in tests is presented. The model is based on the proportional hazards model for competing risks. Two processes are assumed, one reflecting the increase in knowledge and the second the tendency to discontinue. The processes can be characterized by two proportional hazards models whose baseline hazard functions correspond to the temporary increase in knowledge and discouragement. The model can be calibrated with marginal maximum likelihood estimation and an application of the ECM algorithm. Two tests of model fit are proposed. The amenability of the proposed approaches to model calibration and model evaluation is demonstrated in a simulation study. Finally, the model is used for the analysis of two empirical data sets.     

Comparing score tests and other local dependence diagnostics for the graded response model

Score tests for identifying locally dependent item pairs have been proposed for binary item response models. In this article, both the bifactor and the threshold shift score tests are generalized to the graded response model. For the bifactor test, the generalization is straightforward; it adds one secondary dimension associated only with one pair of items. For the threshold shift test, however, multiple generalizations are possible: in particular, conditional, uniform, and linear shift tests are discussed in this article. Simulation studies show that all of the score tests have accurate Type I error rates given large enough samples, although their small‐sample behaviour is not as good as that of Pearson's Χ² and M₂ as proposed in other studies for the purpose of local dependence (LD) detection. All score tests have the highest power to detect the LD which is consistent with their parametric form, and in this case they are uniformly more powerful than Χ² and M₂; even wrongly specified score tests are more powerful than Χ² and M₂ in most conditions. An example using empirical data is provided for illustration.     

Semi‐parametric proportional hazards models with crossed random effects for psychometric response times

The semi‐parametric proportional hazards model with crossed random effects has two important characteristics: it avoids explicit specification of the response time distribution by using semi‐parametric models, and it captures heterogeneity that is due to subjects and items. The proposed model has a proportionality parameter for the speed of each test taker, for the time intensity of each item, and for subject or item characteristics of interest. It is shown how all these parameters can be estimated by Markov chain Monte Carlo methods (Gibbs sampling). The performance of the estimation procedure is assessed with simulations and the model is further illustrated with the analysis of response times from a visual recognition task.     

Accuracy,Consensus, In-Group Bias,and Cultural Frame Shifting in the Context of National Character Stereotypes

We examined Finns’ and bilingual Swedish-Finns’ stereotypes regarding personality differences between Finns and Swedish-Finns and compared them with their respective self-ratings. Stereotype ratings by both groups converged on depicting Swedish-Finns as having a more desirable personality. In-group bias also influenced stereotypes. Contrary to predictions based on the Stereotype Content Model, out-group stereotypes were not compensatory. Consistent with the kernel of truth hypothesis of national stereotypes, Swedish-Finns’ aggregate self-ratings resembled their stereotype of personality differences between the two groups, and their personality self-ratings were more desirable than Finns’ self-ratings. Tentatively suggesting the occurrence of cultural frame shifting, the resemblance between Swedish-Finns’ self-ratings and their stereotype of Swedish-Finns was, although only marginally statistically significantly, somewhat stronger when the self-ratings were provided in Swedish.     

Change one can believe in: Adding learning to computational models of self-regulation

Theories of self-regulation describe motivation as a dynamic process of goal choice and goal striving. To facilitate those processes, individuals learn about themselves and their environment, which is an internal dynamic process. However, the precise nature of the relationship between these learning and motivational processes is not well specified. This article integrates formal models of learning, goal choice, and goal striving using a single information processing structure found in self-regulatory models of motivation. Results from two published studies ( and ) validate the model. In both cases, the integrated model accounts for findings that previous theories of self-regulation could not explain. Discussion focuses on additional tests to validate the model and on the value of incorporating formal models from the cognitive, learning, and motivational literatures to account for behavior in complex settings and over time.