Normative Developmental Trajectories of Aggressive Behaviors in African American,American Indian,Asian American,Caucasian, and Hispanic Children and Early Adolescents

The current 5-year accelerated longitudinal investigation modeled the developmental trajectories of aggressive behaviors in 10,107 predominantly minority (>70%; African American, American Indian, Asian American, and Hispanic) children and early adolescents (Kindergarten through 8th grade, 49% female youth) from lower to lower-middle socioeconomic strata. Based on a two-part latent growth model, findings suggest that the probability and frequency of aggressive behavior use decreases slightly (linear) through the elementary school years and then increases as children move into middle school (quadratic). Though mean level differences were found across ethnic and racial groups, socioeconomic strata, and particularly by sex at initial status, rates of change over time across all groups were invariant. Findings suggest that potential socialization differences, if any, occur pre-Kindergarten in all groups.     

The boundaries between attachment and personality: Associations across three levels of the attachment network

This research examined the associations between measures of sociotropic and autonomous personality, romantic attachment anxiety and avoidance, and corresponding attachment ratings across a range of different specific relationships with people whom participants regularly interacted (including romantic partners, friends, family members, and colleagues). Analyses using hierarchical linear modeling showed that sociotropy and autonomy were directly associated with respective ratings of relationship-specific anxiety and avoidance within non-romantic relationships. In contrast, domain-specific romantic attachment predicted relationship-specific attachment with romantic (but not non-romantic) partners, and, as hypothesized, mediated the associations between sociotropy and autonomy and relationship-specific attachment within this domain. Implications for the operationalization of sociotropy and autonomy as broad-bandwidth (personality-level) measures that assess more global summaries of regularities in the same dual dimensions identified in the attachment literature (i.e., attachment anxiety and avoidance) are discussed.     

犯罪行为决策的理论与研究方法

犯罪行为是犯罪人决策的结果。犯罪行为决策研究旨在通过运用认知心理学的有关原理,说明犯罪行为实施之前的行为决策过程及影响因素,其成果能为国家制定刑事政策与犯罪预防政策等提供理论依据。犯罪行为决策的理论模型主要可分为犯罪理性模型、犯罪期望效用模型和犯罪前景理论模型。犯罪行为决策的研究方法主要采用心理物理法、过程追踪法、访谈法、投射测验法和犯罪统计法等。展望未来,应进一步探讨犯罪行为决策的理性与非理性问题,并加强对犯罪行为决策的验证性研究。     

信息保持、短时存贮与执行控制的脑模型

工作记忆的脑机制是认知神经科学研究的重要问题。研究者在分析大量脑成像研究数据的基础上,创建了许多解释工作记忆神经基础的模型。Smith和Jonides发展了工作记忆成分结构模型和贮存与执行加工分离模型。Postle和D’Esposito建构了工作记忆相对表征混合模型,D’Esposito, Postle和Rypma阐述了工作记忆加工阶段动态模型。Fletcher和Henson提出工作记忆额叶分区整合理论。该文通过对上述模型或理论的评价,总结了工作记忆脑成像研究中存在的问题,展望了该研究领域的发展趋势。     

Model theory of deduction: a unified computational approach

One of the most debated questions in psychology and cognitive science is the nature and the functioning of the mental processes involved in deductive reasoning. However, all existing theories refer to a specific deductive domain, like syllogistic, propositional or relational reasoning.
Our goal is to unify the main types of deductive reasoning into a single set of basic procedures. In particular, we bring together the microtheories developed from a mental models perspective in a single theory, for which we provide a formal foundation. We validate the theory through a computational model (UNICORE) which allows fine-grained predictions of subjects' performance in different reasoning domains.
The performance of the model is tested against the performance of experimental subjects—as reported in the relevant literature—in the three areas of syllogistic, relational and propositional reasoning. The computational model proves to be a satisfactory artificial subject, reproducing both correct and erroneous performance of the human subjects. Moreover, we introduce a developmental trend in the program, in order to simulate the performance of subjects of different ages, ranging from children (3–6) to adolescents (8–12) to adults (>21). The simulation model performs similarly to the subjects of different ages.
Our conclusion is that the validity of the mental model approach is confirmed for the deductive reasoning domain, and that it is possible to devise a unique mechanism able to deal with the specific subareas. The proposed computational model (UNICORE) represents such a unifying structure.     

Contrasting Acquisition-Focused and Performance-Focused Models of Acquired Behavior

What is encoded during a learning experience? In a learning situation, a training (acquisition) phase is often followed by a test phase. Acquisition-focused models (most associative models) emphasize information processing that occurs during training and assume that only summary statistics (associative values) are retained to influence behavior during testing. Performance-focused models (a k a "computational" models) emphasize information processing that occurs at test and often assume fairly comprehensive memory of prior experiences. In this article, we contrast these two families of models. We note that neither family can claim unique support from the various learning phenomena commonly cited as favoring one or the other position. Within each family, there are highly diverse models that preclude blanket generalizations. However, the acquisition-focused view that subjects retain only summary statistics suggests unrealistically impoverished memories relative to the fairly veridical memories that clearly are formed. But this oversimplifying assumption of acquisition-focused associative theories is exactly what has made them superior to performance-focused models to date in stimulating research.     

Fronto-parietal mirror neuron system modeling: Visuospatial transformations support imitation learning independently of imitator perspective

Although the human mirror neuron system (MNS) is critical for action observation and imitation, most MNS investigations overlook the visuospatial transformation processes that allow individuals to interpret and imitate actions observed from differing perspectives. This problem is not trivial since accurately reaching for and grasping an object requires a visuospatial transformation mechanism capable of precisely remapping fine motor skills where the observer’s and imitator’s arms and hands may have quite different orientations and sizes. Accordingly, here we describe a novel neural model to investigate the dynamics between the fronto-parietal MNS and visuospatial processes during observation and imitation of a reaching and grasping action. Our model encompasses i) the inferior frontal gyrus (IFG) and inferior parietal lobule (IPL), regions that are postulated to produce neural drive and sensory predictions, respectively; ii) the middle temporal (MT) and middle superior temporal (MST) regions that are postulated to process visual motion of a particular action; and iii) the superior parietal lobule (SPL) and intra-parietal sulcus (IPS) that are hypothesized to encode the visuospatial transformations enabling action observation/imitation based on different visuospatial viewpoints. The results reveal that when a demonstrator executes an action, an imitator can reproduce it with similar kinematics, independently of differences in anthropometry, distance, and viewpoint. As with prior empirical findings, similar model synaptic activity was observed during both action observation and execution along with the existence of both view-independent and view-dependent neural populations in the frontal MNS. Importantly, this work generates testable behavioral and neurophysiological predictions. Namely, the model predicts that i) during observation/imitation the response time increases linearly as the rotation angle of the observed action increases but remain similar when performing both clockwise and counterclockwise rotation and ii) IPL embeds essentially view-independent neurons while SPL/IPS includes both view-independent and view-dependent neurons. Overall, this work suggests that MT/MST visuomotion processes combined with the SPL/IPS allow the MNS to observe and imitate actions independently of demonstrator-imitator spatial relationships.     

On scaling models applied to data from several groups

Statistical methods are presented to facilitate a more complete analysis of results obtained when a scaling model is applied to data from two or more groups. These methods can be used to (a) compare the corresponding estimated latent distributions obtained using the scaling model applied to the different groups, (b) compare the corresponding estimated item reliabilities (or item response error rates) for the different groups, and (c) test whether the scaling model applied to the several groups can be replaced by a more parsimonious scaling model that includes various homogeneity constraints (i.e., constraints that describe which parameters in the model are the same for the several groups). Various kinds of scaling models are considered here in the multiple-group context.Support for this research was provided in part by the National Science Foundation, to Clogg by Grant No. SES-7823759 and to Goodman by Grant No. SES-8303838. Clogg and Goodman were Fellows at the Center for Advanced Study in the Behavioral Sciences when part of the research was done, with financial support provided in part by National Science Foundation grant BNS-8011494 to the Center. The authors are indebted to Mark P. Becker and James W. Shockey for helpful comments.     

Bayes modal estimation in item response models

This article describes a Bayesian framework for estimation in item response models, with two-stage prior distributions on both item and examinee populations. Strategies for point and interval estimation are discussed, and a general procedure based on the EM algorithm is presented. Details are given for implementation under one-, two-, and three-parameter binary logistic IRT models. Novel features include minimally restrictive assumptions about examinee distributions and the exploitation of dependence among item parameters in a population of interest. Improved estimation in a moderately small sample is demonstrated with simulated data.This research was supported by a grant from the Spencer Foundation, Chicago, IL. Comments and suggestions on earlier drafts by Charles Lewis, Frederic Lord, Rosenbaum, James Ramsey, Hiroshi Watanabe, the editor, and two anonymous referees are gratefully acknowledged.     

Extended similarity trees

Proximity data can be represented by an extended tree, which generalizes traditional trees by including marked segments that correspond to overlapping clusters. An extended tree is a graphical representation of the distinctive features model. A computer program (EXTREE) that constructs extended trees is described and applied to several sets of conceptual and perceptual proximity data.This research was supported in part by a National Science Foundation Pre-doctoral Fellowship to the first author.A magnetic tape containing both the EXTREE program described in the article and ADDTREE/P program for fitting additive trees can also be obtained from the above address. Requests for the program should be accompanied by a check for $25 made out to Teachers College, to cover the costs of the tape and postage.