The interaction of perfectionism, perceived weight status, and self-esteem to predict bulimic symptoms: the role of 'benign' perfectionism

The present study sought to replicate an interactive model of global perfectionism, perceived weight status, and self-esteem in predicting bulimic symptom development in a sample of young women [Bardone-Cone, et al. (2006). Predicting bulimic symptoms: An interactive model of self-efficacy, perfectionism, and perceived weight status. Behaviour Research and Therapy, 44, 27-42; Vohs, K. D., et al. (1999). Perfectionism, perceived weight status, and self-esteem interact to predict bulimic symptoms: A model of bulimic symptom development. Journal of Abnormal Psychology, 108, 695-700; Vohs, K. D., et al. (2001). Perfectionism, body dissatisfaction, and self-esteem: An interactive model of bulimic symptom development. Journal of Social and Clinical Psychology, 20, 476-497]. The aim was to investigate the role of 'problematic' and 'benign' perfectionism within this model, using data from 95 female university students over a 3-month period. Contrary to hypotheses, multivariate analyses revealed a significant three-way interaction only between 'benign' perfectionism, perceived weight status and self-esteem in predicting change in bulimic symptoms over a 3-month period. The predictive effect of the interaction between 'benign' perfectionism and perceived weight status on bulimic symptoms was strongest for women with high self-esteem, for whom feeling overweight and having perfectionistic attitudes preceded increased bulimic symptoms. These findings suggest that high self-esteem is insufficient to protect against the development of bulimic symptoms when both the perception of oneself as being overweight, and high levels of perfectionistic standards, are present. It would appear that the role of perfectionism within the context of disordered eating is complex.     

A computational model of event segmentation from perceptual prediction

People tend to perceive ongoing continuous activity as series of discrete events. This partitioning of continuous activity may occur, in part, because events correspond to dynamic patterns that have recurred across different contexts. Recurring patterns may lead to reliable sequential dependencies in observers' experiences, which then can be used to guide perception. The current set of simulations investigated whether this statistical structure within events can be used 1) to develop stable internal representations that facilitate perception and 2) to learn when to update such representations in a self-organizing manner. These simulations demonstrate that experience with recurring patterns enables a system to accurately predict upcoming stimuli within an event, to identify boundaries between such events based on transient increases in prediction error, and to use such boundaries to improve prediction about subsequent activities.     

Situated language understanding as filtering perceived affordances

We introduce a computational theory of situated language understanding in which the meaning of words and utterances depends on the physical environment and the goals and plans of communication partners. According to the theory, concepts that ground linguistic meaning are neither internal nor external to language users, but instead span the objective-subjective boundary. To model the possible interactions between subject and object, the theory relies on the notion of perceived affordances: structured units of interaction that can be used for prediction at multiple levels of abstraction. Language understanding is treated as a process of filtering perceived affordances. The theory accounts for many aspects of the situated nature of human language use and provides a unified solution to a number of demands on any theory of language understanding including conceptual combination, prototypicality effects, and the generative nature of lexical items. To support the theory, we describe an implemented system that understands verbal commands situated in a virtual gaming environment. The implementation uses probabilistic hierarchical plan recognition to generate perceived affordances. The system has been evaluated on its ability to correctly interpret free-form spontaneous verbal commands recorded from unrehearsed game play between human players. The system is able to "step into the shoes" of human players and correctly respond to a broad range of verbal commands in which linguistic meaning depends on social and physical context. We quantitatively compare the system's predictions in response to direct player commands with the actions taken by human players and show generalization to unseen data across a range of situations and verbal constructions.     

基于统计的汉语隐喻生成模型及其系统实现

隐喻是一种在语篇中普遍存在的语言现象.用计算机模拟隐喻这一带有创造性的人类语言,对隐喻计算化乃至自然语言处理的研究都具有十分重要的意义.本文介绍了一个汉语隐喻自动生成系统.在对大规模语料库进行统计研究的基础上,建立基于向量空间的模型,进行了词义相似度和词义相关度的计算,并构建了支持三种输入模式的隐喻句生成系统.实验结果表明,该系统初步实现了生成汉语隐喻句的目的,并具有一定的自学习功能.     

内隐学习的人工神经网络模型

近年来,人工神经网络模型常被用来模拟各种心理活动,从而为心理学的一些相关理论提供丰富的证据,内隐学习也不例外。基于权重调整来学习正确反应的人工神经网络模型和内隐学习的两大本质特征间有着极为相应的匹配,因此,人工神经网络模型特别适用于内隐学习研究。到目前为止,针对两种较为普遍的内隐学习任务,已经相应地出现了两种使用较为广泛的神经网络模型——自动联系者和简单循环网络     

图表加工的理论模型

图表作为一种以图形和表格记录、展示和传递信息的表征方式已得到广泛应用。图表加工是指人们对图表所呈现信息的认知加工。文章首先说明并简要评述图表加工的规则模型、认知过程模型和计算模型,然后介绍2004年提出的层次框架模型,最后进行小结并指出未来的研究方向     

汉语双字词的心理词典存储—来自发展性阅读障碍个案的证据

研究探讨了发展性阅读障碍个案S汉字命名过程选择性错误的产生机制。汉字命名、词汇判断和组词实验有三个主要发现,个案S在汉字命名过程中产生大量的选择性错误,选择性错误在复合词中发生的前后位置没有显著差异;S在词汇判断过程中,混淆词汇中两个词素的先后顺序;S对产生选择性错误的汉字组词的数量显著少于控制组,且其产生选择性错误的复合词的频率显著高于他组出的其他词汇频率。研究以Zhou&Marslen-Wilson(2000)的复合词的多水平平行结构心理词典模型为基础讨论了这些发现的理论意义,并着重分析了汉字命名过程中词素频率和词汇意义结构之间的交互作用。     

大五人格与绩效：团队水平的研究

众多研究表明,大五人格能够有效预测工作情境中的个体绩效。随着团队研究的广泛开展,团队人格特征与团队绩效的关系也得到了重视。本文在简单回顾个体水平的研究结果的基础上,着重介绍团队大五人格特征与团队绩效以及关系绩效之间关系的研究;阐述从个体特质到团队特征的整合方法和依据;最后指出现有研究存在的以及未来研究需要关注的四个问题     

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