Linguistic characteristics of neurotic, borderline and psychotic personality organization

Thirty patients were subjected to a Structural Interview by means of which 10 of them received the diagnosis NPO (Neurotic Personality Organization), 10 BPO (Borderline Personality Organization) and 10 PPO (Psychotic Personality Organization). About 2500 words and groups of words were extracted from the patients' utterances for analysis. The word-frequencies thus found were analyzed by a PLS discriminant analysis which yielded two significant principal components (main dimensions) explaining 57% of the variance. This analysis showed that the three groups of patients are well separated from one another and that there is a definite correlation between personality organization and linguistic variables. The main features of the BPO-patients in this study seem to be that they refer to positions outside themselves and their language is impersonal; we see this as an exemple of a vacillating identity. The NPO-group is characterized by an intense and rich language, signs of a more advanced symbolizing ability, deixis and high level defenses. The language of the PPO-patients is poor and its predominant feature is a lack of words; in our interpretation this indicates foreclosure and a lack of identity.     

柯林斯语义层次网络模型的实验研究

应用语义验证法对柯林斯与奎利安的语义层次网络模型进行研究,结果表明:(1)柯林斯等人的语义层次网络模型不完全适用于人脑的信息加工;(2)被试对主语所指称客体的熟悉程度是决定语义验证时间的一个重要因素;(3)被试提取概念各属性的时间并非完全由属性储存的位置决定的。     

Priming autobiographical memories: How recalling the past may affect everyday forms of autobiographical remembering

This study investigated the idea that when one recalls past episodes, that the content of those memories will activate additional episodic memories with like content, and such memories will then have the potential of surfacing in subsequent acts of involuntary and voluntary recall. We tested the episodic content priming hypothesis in two experiments. In Experiment 1, priming group participants first recalled memories about specific activities or events and then they were subsequently engaged in a word-cue voluntary autobiographical memory task. The results showed that priming group participants produced more episodic memories involving the primed content on this task than control participants occupied in the same task. In Experiment 2, episodic content priming was further tested on a measure of involuntary autobiographical memory (i.e., the vigilance task). The results on this task also revealed support for the episodic content priming hypothesis, including after a delay of 24 h.     

Determination of visual figure and ground in dynamically deforming shapes

Figure/ground assignment - determining which part of the visual image is foreground and which background - is a critical step in early visual analysis, upon which much later processing depends. Previous research on the assignment of figure and ground to opposing sides of a contour has almost exclusively involved static geometric factors - such as convexity, symmetry, and size - in non-moving images. Here, we introduce a new class of cue to figural assignment based on the motion of dynamically deforming contours. Subjects viewing an animated, deforming shape tended to assign figure and ground so that articulating curvature extrema - i.e., "hinging" vertices - had negative (concave) contour curvature. This articulating-concavity bias is present when all known static cues to figure/ground are absent or neutral in each of the individual frames of the animation, and even seems to override a number of well-known static cues when they are in opposition to the motion cue. We propose that the phenomenon reflects the visual system's inbuilt expectations about the way shapes will deform - specifically, that deformations tend to involve rigid parts articulating at concavities.     

Multilevel Modeling with Correlated Effects

When there exist omitted effects, measurement error, and/or simultaneity in multilevel models, explanatory variables may be correlated with random components, and standard estimation methods do not provide consistent estimates of model parameters. This paper introduces estimators that are consistent under such conditions. By employing generalized method of moments (GMM) estimation techniques in multilevel modeling, the authors present a series of estimators along a robust to efficient continuum. This continuum depends on the assumptions that the analyst makes regarding the extent of the correlated effects. It is shown that the GMM approach provides an overarching framework that encompasses well-known estimators such as fixed and random effects estimators and also provides more options. These GMM estimators can be expressed as instrumental variable (IV) estimators which enhances their interpretability. Moreover, by exploiting the hierarchical structure of the data, the current technique does not require additional variables unlike traditional IV methods. Further, statistical tests are developed to compare the different estimators. A simulation study examines the finite sample properties of the estimators and tests and confirms the theoretical order of the estimators with respect to their robustness and efficiency. It further shows that not only are regression coefficients biased, but variance components may be severely underestimated in the presence of correlated effects. Empirical standard errors are employed as they are less sensitive to correlated effects when compared to model-based standard errors. An example using student achievement data shows that GMM estimators can be effectively used in a search for the most efficient among unbiased estimators. This research was supported by the National Academy of Education/Spencer Foundation and the National Science Foundation, grant number SES-0436274. We thank the editor, associate editor, and referees for detailed feedback that helped improve the paper.     

Signal Detection Models with Random Participant and Item Effects

The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis with aggregated data is not consistent. In fact, mnemonic ability is underestimated, even in the large-sample limit. We present two hierarchical Bayesian models that simultaneously account for participant and item variability. We show how these models provide for accurate estimation of participants’ mnemonic ability as well as the memorability of items. The model is benchmarked with a simulation study and applied to a novel data set. This research is supported by NSF grants SES-0095919 and SES-0351523, NIH grant R01-MH071418, a University of Missouri Research Leave grant and fellowships from the Spanish Ministry of Education and the University of Leuven, Belgium.     

One REBTers Model for Business Consulting

Organizational consulting offers opportunities to diversify one’s practice and increase one’s income, all the while reducing the frustrations associated with working with insurance and managed care companies. This paper describes one REBT therapist’s conception of the “personality” of any organization, a list of potential services to offer businesses, and a few practical suggestions to successfully transfer from the clinical office into the organizational world.     

国外有关学习时间分配决策能力的研究概述

学习时间分配决策是记忆监控的核心内容之一。文章围绕学习时间分配决策能力的新近研究,重点介绍了如下问题：（1）儿童学习时间分配决策能力的发展;（2）学习时间分配决策机制的探讨,特别对最新的理论模型——学习层次模型和最近学习区假设进行了比较详细的介绍;（3）对今后研究发展的趋势进行了展望。     

组织学习整合理论模型

如何提高组织学习能力、如何创建学习型组织、学习型社会,这已经成为我国企业和社会发展需要迫切解决的问题。文章从定义的根本假设、组织学习层次、组织学习过程、内部推动因素四个方面对文献进行了综述,在此基础上提出了组织学习的界定以及整合的组织学习模型,它包括：个体、团队、组织层、组织间四个学习层次,获得和产生、解释、整合、制度化四个心理和社会互动过程,反馈学习（feedback）和前馈学习(feed forward)两个信息或知识流动过程。最后提出了今后研究的方向。