睡眠影响记忆巩固的同步EEG-fMRI研究

默认网络是静息状态活动较强的大脑结构, 它包含的海马和内侧前额叶两个脑区是记忆巩固的关键部位, 同时静息态也被证明伴随有记忆巩固现象, 我们推测默认网络是睡眠依赖记忆巩固的核心结构。本研究拟借助同步EEG-fMRI在时空分辨率上的优势, 研究默认网络参与睡眠依赖记忆巩固的神经机制。包括：1)发掘默认网络活动的电生理指标, 应用EEG源定位和跨频段耦合分析, 揭示记忆巩固的动态过程; 2)应用滑动时间窗和模块分析, 研究默认网络参与静息态和睡眠过程记忆巩固的异同, 揭示记忆在昼夜更迭中得以强化的神经机制; 3)通过多模态信息融合, 揭示记忆类型和睡眠阶段等因素对睡眠依赖记忆巩固的影响。本研究的开展对阐明睡眠依赖记忆巩固的神经机制具有深刻的理论意义, 并最终可能为治疗学习记忆相关障碍提供全新的思路。     

相似性词汇同时性加工与相继性加工的比较

为考查同时性学习与相继性学习在相似性材料学习中的特点,本研究以57名大学一年级学生为被试,用英语单词记忆测验考查了相似性英语新单词的同时性学习和相继性学习的差异。结果发现,对于相似性英语新单词来说,同时性学习的效果明显优于相继性学习效果。这表明,两种不同的学习方式在信息处理过程和信息加工水平上存在不同。     

Trust and trustworthiness in a sequential bargaining game

We use a two‐person extensive form bargaining game to explore individuals' trusting and reciprocal behavior and how those relate to their scores on a trust survey. In keeping with prior research, we find that the ‘self‐interested’ outcome is rejected by a majority of individuals. People who score high on the trust survey are both trusting and are also trustworthy, in that they reciprocate others' trust. But people with low‐trust scores often exhibit trust but are not trustworthy. These ‘inconsistent trusters’ seem to be interested in exploiting the trust and trustworthiness of others in increasing their own payoff. Copyright © 2003 John Wiley & Sons, Ltd.     

Blocking incidental frustration during bargaining

The current study examined the effects of an intervention aimed at blocking the transfer of frustration from a previous experience (i.e. recall task) to a subsequent and unrelated task (i.e. ultimatum bargaining task). Participants who went through the intervention were more likely to accept unfair offers in the ultimatum bargaining task than those who did not go through the intervention. These results show that participants who were blocked from transferring their feelings of frustration from the recall task to the subsequent bargaining task (no-transfer condition) more likely accepted unfair offers than those who inadvertently transferred their feelings of frustration (transfer condition). The effect of conditions on accept-reject decisions in the ultimatum bargaining was mediated by reported feelings of frustration.     

A method for increasing empirical discriminability and eliminating top‐row preference in photo arrays

It is important to consider the two parameters of signal detection theory, discriminability and response bias, when evaluating eyewitness identification from simultaneous lineups. On the basis of the diagnostic feature‐detection hypothesis, we tested a method for increasing discriminability that encourages eyewitnesses to carefully rank each lineup member based on match to their memory for a perpetrator. This procedure increased empirical discriminability and also eliminated a response bias that is largely overlooked in the literature: Participants were biased to choose from the top row of the six‐pack (2 × 3) lineup commonly used in the United States. We argue that suspect position in the simultaneous lineup is an important variable to consider for researchers and the criminal justice system. We also encourage researchers to test the ranking procedure to determine if such a simple set of instructions could be utilized by police to help eyewitnesses correctly sort innocent versus guilty suspects.     

同声传译过程中的工作记忆与双语控制研究

同声传译是一项受时间限制的高度复杂的双语活动,译员在接收原语输入的同时要进行译入语输出。同传中译员要经过原语接收、理解、转换、译入语表达等一系列过程。近年来有研究者开始尝试同声传译过程中的工作记忆研究,认为工作记忆是同传作业的关键因素,并提出工作记忆在同传中的扩展模型。本文主要就同声传译的关键特征与多任务处理模型、工作记忆在同传中的作用机制和译入语提取时的双语控制机制等问题进行简要介绍,并提出了进一步的研究思路。     

数学学习困难儿童的编码加工特点:基于PASS理论的研究

同时加工和继时加工是PASS模型中的两类编码加工,二者在数学学习中发挥重要作用。使用基于PASS理论的认知评估系统（DN：CAS）单纯型数学困难、混合型数学困难和正常小学生进行两类编码加工的测评,比较研究发现,两类困难学生的两类编码加工水平均显著低于正常儿童,两类困难学生间的同时加工差异不显著,而混合型困难学生的继时加工水平显著低于单纯型困难学生。较低的同时加工水平似乎是两类数学困难的共同特征,继时加工水平的差异则似可作为单纯型与混合型困难的区分指标之一。     

Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units

A new methodology is proposed for the simultaneous reduction of units, variables, and occasions of a three-mode data set. Units are partitioned into a reduced number of classes, while, simultaneously, components for variables and occasions accounting for the largest common information for the classification are identified. The model is a constrained three-mode factor analysis and it can be seen as a generalization of the REDKM model proposed by De Soete and Carroll for two-mode data. The least squares fitting problem is mathematically formalized as a constrained problem in continuous and discrete variables. An iterative alternating least squares algorithm is proposed to give an efficient solution to this minimization problem in the crisp and fuzzy classification context. The performances of the proposed methodology are investigated by a simulation study comparing our model with other competing methodologies. Different procedures for starting the proposed algorithm have also been tested. A discussion of some interesting differences in the results follows. Finally, an application to real data illustrates the ability of the proposed model to provide substantive insights into the data complexities.