东莨菪碱所致记忆障碍的脑内突触机制

研究问题是东莨菪碱所致记忆障碍的脑内突触机制,在东莨菪碱所致记忆障碍模型上定量分析屯小鼠海马ＣＡ３区ＧｒａｙＩ突触界面结构参数的变化。     

Fitting multivariage normal finite mixtures subject to structural equation modeling

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the differences between the components in the mixture. Within the general model, individual parameters can be subjected to equality, nonlinear and simple bounds constraints. Confidence intervals are based on the inverse of the Hessian and on the likelihood profile. Several illustrations are given and results of a simulation study concerning the confidence intervals are reported.     

Education and Understanding Structural Causes for Group Inequalities

Group inequalities in the United States are most often attributed to the characteristics of the individuals who belong to these groups; thinking about structural causes of group inequalities is rare. This paper reviews cognitive, cultural, and systemic reasons for this bias. The efficacy of education as a way to increase structural thinking was investigated in two studies of college students' causal thinking about group inequalities. Both studies involved a course on intergroup relations that covered structural sources of racial or ethnic inequalities. Results supported hypotheses that the course would increase structural thinking about racial or ethnic inequality, and that structural thinking would generalize to inequalities not explicitly covered in the course. Both course content and active learning pedagogy were related to structural thinking about inequalities. Active learning was also related to applying structural thinking to targets of change.     

Experimental analysis of academic performance in a classroom setting

We evaluated the effects of specific stimulus prompts on accuracy of academic performance with adolescents who displayed academic problems in a public special education classroom. We conducted analyses of instructional strategies within a multielement design with two students who had mild disabilities. Differential effects of the strategies on reading comprehension were not apparent on demand (independent-level) tasks but were apparent on high-demand (instructional-level) tasks. These results suggested that the application of experimental analysis methodologies to instructional variables may facilitate the identification of stimulus prompts associated with accurate academic performance.     

Multilevel covariance structure analysis of sibling substance use and intrafamily conflict

Conventional covariance structure analysis, such as factor analysis, is often applied to data that are obtained in a hierarchical fashion, such as siblings observed within families. A more appropriate specification is demonstrated which explicitly models the within-level and between-level covariance matrices of sibling substance use and intrafamily conflict. Participants were 267 target adolescents (mean age=13.11 years) and 318 siblings (mean age=15.03 years). The level of homogeneity within sibling clusters, and heterogeneity among families, was sufficient to conduct a multilevel covariance structure analysis (MCA). Parental and family-level variables consisting of marital status, socioeconomic status, marital discord, parent use, and modeling of substances were used to explain heterogeneity among families. Marital discord predicted intrafamily conflict, and parent marital status and modeling of substances predicted sibling substance use. Advantages and uses of hierarchical designs and conventional covariance structure software for multilevel data are discussed.     

Linear structural equations with latent variables

An interdependent multivariate linear relations model based on manifest, measured variables as well as unmeasured and unmeasurable latent variables is developed. The latent variables include primary or residual common factors of any order as well as unique factors. The model has a simpler parametric structure than previous models, but it is designed to accommodate a wider range of applications via its structural equations, mean structure, covariance structure, and constraints on parameters. The parameters of the model may be estimated by gradient and quasi-Newton methods, or a Gauss-Newton algorithm that obtains least-squares, generalized least-squares, or maximum likelihood estimates. Large sample standard errors and goodness of fit tests are provided. The approach is illustrated by a test theory model and a longitudinal study of intelligence.This investigation was supported in part by a Research Scientist Development Award (KO2-DA00017) and a research grant (DA01070) from the U. S. Public Health Service.     

Development of Adolescent Problem Behavior

The developmental model of adolescent antisocial behavior advanced by Patterson and colleagues (e.g., Patterson, Reid, & Dishion, 1992) appears to generalize the development of a diverse set of problem behaviors. Structural equation modeling methods were applied to 18-month longitudinal data from 523 adolescents. The problem behavior construct included substance use, antisocial behavior, academic failure, and risky sexual behavior. Families with high levels of conflict were less likely to have high levels of parent–child involvement. Such family conditions resulted in less adequate parental monitoring of adolescent behavior, making associations with deviant peers more likely. Poor parental monitoring and associations with deviant peers were strong predictors of engagement in problem behavior. These constructs accounted for 46% of the variance in problem behavior. Although association with deviant peers was the most proximal social influence on problem behavior, parental monitoring and family factors (conflict and involvement) were key parenting practices that influenced this developmental process.     

Classical test theory based and factor analytic structural models for analyzing change: A note on differences and similarities

This note is concerned with differences and similarities between structural models for analyzing change, which are conceptualized within two different modelling traditions: the one based on the classical test theory, and that within the factor-analytic approach. It is shown that these two possibilities lead to models for studying change, which are indistinguishable when using for data analytic purposes structural modeling programs, such as LISREL, EQS, COSAN, LISCOMP, RAMONA, EzPATH, SAS PROC CALIS. The reason for this data-analytic equivalence of the two conceptually different types of models is the confounding of their differences in the corresponding implied covariance matrix structures.     

On the need for structurally competent counselling and psychotherapy: Neoliberal ideology,disability and the psy disciplines

This article highlights and problematises the psy disciplines' articulations with neoliberalism, with a particular focus upon disability and upon counselling and psychotherapy. Recent years have witnessed burgeoning scholarly interest in the potential complicities of the psy professions in a neoliberal agenda of individualisation, pathologisation and responsibilisation of human suffering. Such complicities are, in state therapy settings, driven by a growing need for these professions to offer cost-effective, evidence-based interventions to secure funding in an increasingly competitive market. Whilst the entwining of neoliberal ideology with therapy practices may be innocuous for some, it is contended that disabled people may be at particular risk of harm. A case is then made for training and practice to foreground structural competency, an awareness of how therapy encounters and client concerns are shaped by socio-structural factors, including, but not limited to, politics and political ideology. This would require not only an appreciation of the sociopolitical context in which therapy unfolds and its indubitable shaping of subjectivities, but also greater recognition of disability as a source of social inequity and oppression, as opposed to an individual phenomenon. Moreover, structural competency would require theoretical and demographic diversity in training and practice, which, in turn, would necessitate identifying and addressing barriers to inclusion for disabled people. Points raised are deemed of particular importance given the emergence of long COVID.     

A multi-analyses approach of inductive/deductive asymmetry in the affective priming paradigm

Rapidly evaluating our environment's beneficial and detrimental features is critical for our successful functioning. A classic paradigm used to investigate such fast and automatic evaluations is the affective priming (AP) paradigm, where participants classify valenced target stimuli (e.g., words) as good or bad while ignoring the valenced primes (e.g., words). We investigate the differential impact that verbs and adjectives used as primes and targets have on the AP paradigm. Based on earlier work on the Linguistic Category Model, we expect AP effect to be modulated by non-evaluative properties of the word stimuli, such as the linguistic category (e.g., if the prime is an adjective and the target is a verb versus the reverse). A reduction in the magnitude of the priming effect was predicted for adjective–verb prime-target pairs compared to verb–adjective prime-target pairs. Moreover, we implemented a modified crowdsourcing of statistical analyses implementing independently three different statistical approaches. Deriving our conclusions on the converging/diverging evidence provided by the different approaches, we show a clear deductive/inductive asymmetry in AP paradigm (exp. 1), that this asymmetry does not require a focus on the evaluative dimension to emerge (exp. 2) and that the semantic-based asymmetry weakly extends to valence (exp. 3).