Deficits in executed and imagined aiming performance in brain-injured children

Motor disorders are a frequent consequence of acquired brain injury (ABI) in children and much effort is currently invested in alleviating these deficits. The aim of the present study was to test motor imagery (MI) capabilities in children with ABI (n=25) and an age- and gender-matched control group (n=25). A computerized Virtual Radial Fitts Task (VRFT) was used to investigate the speed-accuracy trade-offs (or Fitts' law) that occur as target size is varied for both executed and imagined performance. In the control group, the speed for accuracy trade-off for both executed and imagined performance conformed to Fitts' law. In the ABI group, only executed movements conformed to Fitts' law. These findings suggest that children with ABI show an inferior ability to imagine the time needed to complete goal-directed movements with differential difficulty levels.     

初中生家庭功能类型与其价值观形成的关系探讨

采用亲密度与适应性量表中文版（FACESⅡ-CV）和价值观自测问卷对259名绍兴市区初中生进行了调查,结果发现：（1）亲密度高、情感联系强的家庭更容易形成符合社会规范的价值观,而情感联系弱的家庭容易形成自我中心的价值观;（2）适应性强、应变功能高的无规律型家庭有利于自律、内控的自我导向价值观的形成,并对从众型和冷漠型价值观的形成具有抑制作用;（3）家庭亲密度与适应性功能水平和踏实型价值观类型存在显著的正相关,适应性功能水平与功利型和冷漠型价值观类型存在显著的负相关。     

A Deep Inference System for the Modal Logic S5

We present a cut-admissible system for the modal logic S5 in a formalism that makes explicit and intensive use of deep inference. Deep inference is induced by the methods applied so far in conceptually pure systems for this logic. The system enjoys systematicity and modularity, two important properties that should be satisfied by modal systems. Furthermore, it enjoys a simple and direct design: the rules are few and the modal rules are in exact correspondence to the modal axioms. Presented by Heinrich Wansing     

Putting the system back into systems change: a framework for understanding and changing organizational and community systems

Systems change has emerged as a dominant frame through which local, state, and national funders and practitioners across a wide array of fields approach their work. In most of these efforts, change agents and scholars strive to shift human services and community systems to create better and more just outcomes and improve the status quo. Despite this, there is a dearth of frameworks that scholars, practitioners, and funders can draw upon to aid them in understanding, designing, and assessing this process from a systemic perspective. This paper provides one framework--grounded in systems thinking and change literatures--for understanding and identifying the fundamental system parts and interdependencies that can help to explain system functioning and leverage systems change. The proposed framework highlights the importance of attending to both the deep and apparent structures within a system as well as the interactions and interdependencies among these system parts. This includes attending to the dominant normative, resource, regulative, and operational characteristics that dictate the behavior and lived experiences of system members. The value of engaging critical stakeholders in problem definition, boundary construction, and systems analysis are also discussed. The implications of this framework for systems change researchers and practitioners are discussed.     

个人目标取向、课堂目标结构及文化因素与学业求助策略的关系研究

本研究以982名初中学生为被试,采用验证性因素分析和多元回归方法对个人目标取向、课堂目标结构及文化因素与学业求助策略的关系进行研究。结果表明:(1)个人目标取向可以区分出任务取向、趋向型自我取向和逃避型自我取向,它们对学业求助的影响是不同的,只有逃避型自我取向的学生才倾向于作不利于学习的执行性求助。(2)课堂目标结构对学业求助有影响 ,在任务取向的课堂里 ,学生倾向于作工具性求助。(3)文化因素对学业求助有影响。认同中国求助格言的学生愿意作工具性求助,在意他人评价的学生倾向于回避求助或作执行性求助。(4)个人目标取向、课堂目标结构和文化因素对不同年级学生学业求助的影响模式不同。     

The effect of context during word perception in schizophrenic patients

Hospitalized chronic and acute schizophrenics were compared with age- and social-status-matched controls on word perception tests to measure the effect of context on recognition thresholds. In Experiment 1 the method of J. Morton (1964, British Journal of Psychology, 55, 165-180) was adopted to see how related and unrelated contexts influenced word recognition thresholds when both context and stimulus word were presented visually. Experiment 2 was an auditory analog of Experiment 1 and in addition the chronic schizophrenics were selected on the basis of a presence or absence of auditory hallucinations. The influence of context on perceptual thresholds was quite normal in all schizophrenics. However, analysis of the incorrect responses elicited showed that some schizophrenic subjects do produce bizarre or irrelevant responses or perseveration to a greater extent than their controls. These results are explained in terms of automatic and strategic modes of information processing. The automatic processes responsible for the adjustment of perceptual thresholds operate normally in schizophrenics but response production which demands strategic selection and editing of responses is prone to malfunction which results in the observed deviations in the normal use of language.     

Some contributions to efficient statistics in structural models: Specification and estimation of moment structures

Current practice in structural modeling of observed continuous random variables is limited to representation systems for first and second moments (e.g., means and covariances), and to distribution theory based on multivariate normality. In psychometrics the multinormality assumption is often incorrect, so that statistical tests on parameters, or model goodness of fit, will frequently be incorrect as well. It is shown that higher order product moments yield important structural information when the distribution of variables is arbitrary. Structural representations are developed for generalizations of the Bentler-Weeks, Jöreskog-Keesling-Wiley, and factor analytic models. Some asymptotically distribution-free efficient estimators for such arbitrary structural models are developed. Limited information estimators are obtained as well. The special case of elliptical distributions that allow nonzero but equal kurtoses for variables is discussed in some detail. The argument is made that multivariate normal theory for covariance structure models should be abandoned in favor of elliptical theory, which is only slightly more difficult to apply in practice but specializes to the traditional case when normality holds. Many open research areas are described.     

Do complex models increase prediction of complex behaviours? Predicting driving ability in people with brain disorders

Prediction of complex behavioural tasks via relatively simple modelling techniques, such as logistic regression and discriminant analysis, often has limited success. We hypothesized that to more accurately model complex behaviour, more complex models, such as kernel-based methods, would be needed. To test this hypothesis, we assessed the value of six modelling approaches for predicting driving ability based on performance on computerized sensory–motor and cognitive tests (SMCTests?) in 501 people with brain disorders. The models included three models previously used to predict driving ability (discriminant analysis, DA; binary logistic regression, BLR; and nonlinear causal resource analysis, NCRA) and three kernel methods (support vector machine, SVM; product kernel density, PK; and kernel product density, KP). At the classification level, two kernel methods were substantially more accurate at classifying on-road pass or fail (SVM 99.6%, PK 99.8%) than the other models (DA 76%, BLR 78%, NCRA 74%, KP 81%). However, accuracy decreased substantially for all of the kernel models when cross-validation techniques were used to estimate prediction of on-road pass or fail in an independent referral group (SVM 73–76%, PK 72–73%, KP 71–72%) but decreased only slightly for DA (74–75%) and BLR (75–76%). Cross-validation of NCRA was not possible. In conclusion, while kernel-based models are successful at modelling complex data at a classification level, this is likely to be due to overfitting of the data, which does not lead to an improvement in accuracy in independent data over and above the accuracy of other less complex modelling techniques.     

Thought sequences

Abstract

Thought sequences are ordered series of verbal-like expressions that pass spontaneously through one's mind and which are characterised by well-demarcated beginnings and ends. The present paper notes the significance of and interest in thought sequences and presents a framework for their analysis. Given the scope of the enterprise, different levels of analysis are noted which set the boundaries for the present investigation, and define guidelines for further research. Here, the focus of interest is the structural (as distinct from either functional or computational) relationships between pairs of consecutive expressions. The informational bases for these relationships are reviewed and a typology of them is drawn. The typology reveals marked internal structure and it suggests that the variety of couplings of thought sequences constitutes a space spanned by a small number of variables. Methodological issues regarding the use of introspection in cognitive research are also discussed.