国外关于右脑的语言功能研究的进展

对国外有关右脑语言功能的研究作了简要概述,对研究中达成的共识和存在的分歧作了初步介绍;在此基础上,对有关右脑的语言功能研究意义和趋势作了概括和预测。从而为国内相关研究提供借鉴和启示。     

文昌信仰的神谕性训诫研究——以文昌劝善书为中心

劝善书产生于北宋时期,是一种宣传伦理道德、劝诫世人行善去恶并建立道德规范的指导书.文昌信仰是由产生于远古的星宿信仰、晋朝武将张恶子信仰等合流的一种民间信仰.文昌劝善书是以文昌信仰为基础所造做的劝善书,成为明清时期劝善书的主流.本文主要以一些明清时期重要文昌劝善书为例,探讨文昌神谕性的训诫及其对社会的影响.     

青少年孤独感与人格五因素的关系:人际关系能力的中介作用

该研究采用小五人格问卷、中学生孤独感问卷和人际关系能力问卷,以784名青少年为被试,考察青少年孤独感的特点及其与人格五因素、人际关系能力的关系。结果发现:(1)青少年的孤独感存在显著的性别差异,男生显著高于女生;(2)在孤独感各维度中,除同伴关系评价与开放性的相关不显著外,其他维度与人格各维度及人际关系能力间均相关显著;(3)人格的情绪性和开放性显著正向预测孤独感,外向性、宜人性和人际关系能力显著负向预测孤独感;(4)在外向性、情绪性及开放性与孤独感的关系中,人际关系能力起部分中介作用,而在宜人性与孤独感的关系中,人际关系能力起完全中介作用。     

伦理管理"如何可能"之策新探

企业伦理管理"如何可能"问题是伦理管理的技术性或工具性实现难题,尽管美国经验可资借鉴,但我国实践中仍存在许多操作难题,研究也以宏观层面和中观层面的解决之策为主,缺乏可操作性较强的"术"的层面的策略研究成果,因此,有必要对伦理管理"如何可能"之术作进一步探讨.以此为基点,策略可分为伦理管理目标能见度提高策略和伦理管理运行机制的效力提升策略.     

Brain activation detection by neighborhood one-class SVM

Brain activation detection is an important problem in fMRI data analysis. In this paper, we propose a data-driven activation detection method called neighborhood one-class SVM (NOC-SVM). Based on the probability distribution assumption of the one-class SVM algorithm and the neighborhood consistency hypothesis, NOC-SVM identifies a voxel as either an activated or non-activated voxel by a weighted distance between its near neighbors and a hyperplane in a high-dimensional kernel space. The proposed NOC-SVM are evaluated by using both synthetic and real datasets. On two synthetic datasets with different SNRs, NOC-SVM performs better than K-means and fuzzy K-means clustering and is comparable to POM. On a real fMRI dataset, NOC-SVM can discover activated regions similar to K-means and fuzzy K-means. These results show that the proposed algorithm is an effective activation detection method for fMRI data analysis. Furthermore, it is stabler than K-means and fuzzy K-means clustering.     

Multi-aspect data analysis for investigating human computation mechanism

In the paper, we present a multi-aspect data analysis approach for investigating human computation mechanism. Multi-aspect analysis in multiple human brain data sources is an important methodology in Brain Informatics, which emphasizes on a systematic way for investigating human information processing mechanisms, including measuring, collecting, modeling, transforming, managing, and mining multiple human brain data obtained from various cognitive experiments by using powerful equipments, such as fMRI and EEG. After giving an outline of Brain Informatics methodology, we describe how to design cognitive experiments of mental arithmetic task with multiple difficulty levels for obtaining multiple EEG and fMRI data sources, and how to analyze such data for investigating the spatiotemporal characteristics and flow of human computation processing. Such an investigation can be regarded as a case study using Brain Informatics methodology. Experimental results show the usefulness of our approach.     

语音信息对中国英语学习者语义加工的影响及其脑机制

本研究采用经典的句尾畸义词诱发N400的ERP实验范式探讨了中国英语学习者在进行英文阅读时语音的影响及其相关脑机制。实验包括两类畸义语句:1.同音畸义:句尾词有畸义,但语音和相应正常语义句尾词相同;2.非同音畸义:句尾词有畸义,且语音和相应正常语义句尾词不同。行为数据显示:在错误率上同音畸义显著地高于非同音畸义。ERP显示:无论在早期(N100)还是晚期(N400)脑电成份上,同音畸义和非同音畸义的ERP振幅都有明显差异。本研究从行为和脑电两个方面一致揭示中国英语学习者阅读英文时受到了语音的影响。