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1. chinaXiv:201802.00674 [pdf]

金庸小说人物的大五人格—基于文心系统的15部金庸小说分析

崔馨月; 郑苑仪; 王贝依; 郭荣慧; 丁照云; 朱廷劭
分类: 心理学 >> 人格心理学

[目的]从心理学的角度全面分析金庸小说人物人格与创作阶段、性别之间的关系。[方法]本文通过创作阶段对金庸15部小说进行划分,采用基于数据挖掘的文学智能分析方法,通过中文心理分析系统对人物对话进行处理,得到人物的大五人格预测分数。[结果] 女性人物的神经质倾向高于男性人物;创作阶段影响小说人物的尽责性、外向性倾向。[局限]仅仅对小说中的人物进行了分析,没有和金庸本人生平经历和创作时代特点相结合。[结论]本文从心理学人格理论出发探讨金庸小说的人物描写特点,丰富了“金学”的研究成果,为研究金庸的人物刻画风格与偏好提供了新的视角。

提交时间: 2018-02-12 点击量127下载量85 评论 0

2. chinaXiv:201709.00120 [pdf]

贝叶斯因子及其在JASP中的实现

胡传鹏; 孔祥祯; Eric-Jan Wagenmakers; Alexander Ly; 彭凯平
分类: 心理学 >> 心理统计

统计推断在科学研究中起到关键作用,然而当前科研中最常用的经典统计方法——零假设检验(Null hypothesis significance test, NHST)却因难以理解而被部分研究者误用或滥用。有研究者提出使用贝叶斯因子(Bayes factor)作为一种替代和(或)补充的统计方法。贝叶斯因子是贝叶斯统计中用来进行模型比较和假设检验的重要方法,其可以解读为对零假设H0或者备择假设H1的支持程度。其与NHST相比有如下优势:同时考虑H0和H1并可以用来支持H0、不“严重”地倾向于反对H0、可以监控证据强度的变化以及不受抽样计划的影响。目前,贝叶斯因子能够很便捷地通过开放的统计软件JASP实现,本文以贝叶斯t检验进行示范。贝叶斯因子的使用对心理学研究者来说具有重要的意义,但使用时需要注意先验分布选择的合理性以及保持数据分析过程的透明与公开。

提交时间: 2018-01-27 点击量5649下载量1769 评论 0

3. chinaXiv:201801.00308 [pdf]

多项式加工树模型在社会心理学中的应用

刘媛媛; 丁一; 彭凯平; 胡传鹏
分类: 心理学 >> 社会心理学

多项式加工树(multinomial processing tree, MPT)从理论模型出发,使用多项式模型来拟合行为数据并估计理论模型中各个加工过程发生的可能性。该模型能够有效分离和量化不同心理过程,广泛应用于社会认知研究之中,如刻板印象、道德判断等。本文首先介绍该模型的基本原理及其实现,并以道德判断为例说明其在社会心理学中的最新应用。最后,总结其对社会心理学研究的意义,即可以作为一种方法提高研究的效度和精度,具有较高的实用价值,并指出其潜在不足。

提交时间: 2018-01-17 点击量714下载量124 评论 0

4. chinaXiv:201801.00701 [pdf]

唤醒度对自我优势的调节

钱浩悦; 王治国; 李超; 高湘萍
分类: 心理学 >> 实验心理学

最近的研究表明自我偏向被情绪状态所调节。但是,这种调节背后的原因是效价还是唤醒度还不清楚。在实验1中,我们测了四种情绪下的自我偏向效应大小。结果显示,在高唤醒度条件下自我偏向较高,且自我偏向与唤醒度成正比。实验2的结果显示,警觉线索的出现会提高唤醒度,进而提升自我偏向效应。这些结果表明唤醒度能够调节自我偏向性加工。

提交时间: 2018-01-12 点击量106下载量38 评论 0

5. chinaXiv:201712.02153 [pdf]

大尺度脑网络交互支持内外部指向的认知

辛斐; 谢超 ; 雷旭
分类: 心理学 >> 心理学其他学科

大量神经成像研究表明,人脑的高级认知功能不是由单个脑区负责的,而是通过多个与认知活动相关的脑区构成的特异性脑网络的协同活动来实现的。其中,额顶控制网络动态调控默认网络和背侧注意网络之间的信息交互,受到了很多研究者的关注。背侧注意网络主要负责外部自上而下的注意导向、视觉空间知觉等功能,默认网络主要负责内部注意指向的和自我参照的认知加工。根据当前任务对个体注意指向的要求,额顶控制网络灵活地选择与默认网络或背侧注意网络耦合或解耦合,从而更高效地分配注意资源。目前,在三个大尺度脑网络的脑区分布、功能分工和交互关系上仍存在争议有待进一步揭示。未来研究需要对三个脑网络进行更精确的功能定义,进一步探索网络内部各个亚网络的功能角色,同时借助效应连接的手段考察网络内部和网络间信息传递的方向性和动态性,从而更深入理解默认网络、背侧注意网络和额顶控制网络在内外部注意指向的认知活动中信息交互的神经机制。

提交时间: 2017-12-29 点击量753下载量161 评论 0

6. chinaXiv:201712.00001 [pdf]

孤独症脑自发活动动态性及其整合的异常机制

鲁彬; 陈骁; 李乐; 沈杨千; 陈宁轩; 梅婷; 周会霞; 刘靖; 严超赣
分类: 心理学 >> 医学心理学

孤独症谱系障碍(Autism Spectrum Disorder, ASD)是一种病因未明,发病率较高的神经发育疾病。目前大多数静息态功能磁共振(Resting-state fMRI, R-fMRI)研究仅考察了ASD患者脑活动的静态特征,忽视了动态特征。近期研究发现,不同R-fMRI局部指标的动态性之间存在一致性。本研究基于ASD公开数据库,使用滑动时间窗方法系统计算了716名ASD患者和755名健康对照被试的主流R-fMRI局部指标的动态性及R-fMRI局部指标之间的一致性动态特征,并考察了这些指标与ASD行为指标之间的关系。我们发现ASD患者在外侧额叶呈现出动态性显著升高,该现象几乎在所有指标的动态性中都有体现。我们也发现ALFF的动态性在默认网络关键脑区,如后扣带回/楔前叶呈现下降。在进一步考察了这些指标之间的一致性动态特征后,发现ASD患者的平均一致性动态特征显著低于健康对照组被试,表现出显著下降的功能整合能力。我们的结果表明ASD患者存在着脑自发活动动态性及其整合的异常。

提交时间: 2017-11-30 点击量927下载量493 评论 0

7. chinaXiv:201711.00276 [pdf]

DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging

Chao-Gan Yan; Xin-Di Wang; Xi-Nian Zuo; Yu-Feng Zang
分类: 心理学 >> 应用心理学

Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

提交时间: 2017-11-06 点击量210下载量177 评论 0

8. chinaXiv:201711.00277 [pdf]

Linear trend of resting-state fMRI time series

Xin-Di Wang; Chao-Gan Yan; Yu-Feng Zang
分类: 心理学 >> 应用心理学

Although爈inear trend removing has often been implemented as a routine preprocessing step in resting-state functional magnetic resonance imaging (RS-fMRI) data analysis, the爏patial distribution爋f the magnitude of linear trend is still unclear. Further, it is interesting whether there will be any difference of the linear trend magnitude between different resting-states. For the first aim, we analyzed 5 RS-fMRI datasets from 5 different scanners (namely Beijing-Simens-3T, Cambridge-Siemens-3T, CCBD-GE750-3T, Milwaukee-GE-3T, and Oulu-GE-1.5T). One-sample t-tests on the regression coefficient (i.e., the magnitude of linear trend) were performed for each datasets. For the second aim, we used 2 datasets in each of which different states were compared, one containing eyes-open resting-state (EO-RS) vs. eyes-closed resting-state (EC-RS) and the other containing two steady-state tasks, i.e.,爎eal-time finger force feedback�RT-FFF) and sham finger force feedback (S-FFF) tasks. Paired t-tests were performed between EO-RS and EC-RS, and between RT-FFF and S-FFF. One-sample t-tests showed that the spatial pattern of linear trend of RS-fMRI time series were quite different between different manufactures. The 3T SIEMENS scanners showed positive linear trend in almost all part of the brain, while GE scanners showed primarily negative linear trend in most part of the brain. Paired t-tests showed some differences between paired conditions; differences between EO-RS and EC-RS were mainly in cuneus and eyeballs, and differences between RT-FFF and S-FFF were found in the thalamus, anterior cingulate gyrus, and right sensorimotor cortex. The current study indicated that, while the manufacturer-dependent linear trend of RS-fMRI time series were mostly scanner-related noise, the linear trend may also be physiological noise (eyeballs) or even physiologically meaningful, especially during steady-state tasks.

提交时间: 2017-11-06 点击量164下载量138 评论 0

9. chinaXiv:201711.00278 [pdf]

PRN: a preprint service for catalyzing R-fMRI and neuroscience related studies

Chao-Ganyan; Qingyang Li; Lei Gao
分类: 心理学 >> 实验心理学

Sharing drafts of scientific manuscripts on preprint hosting services for early exposure and pre-publication feedback is a well-accepted practice in fields such as physics, astronomy, or mathematics. The field of neuroscience, however, has yet to adopt the preprint model. A reason for this reluctance might partly be the lack of central preprint services for the field of neuroscience. To address this issue, we announce the launch of Preprints of the R-fMRI Network (PRN), a community funded preprint hosting service. PRN provides free-submission and free hosting of manuscripts for resting state functional magnetic resonance imaging (R-fMRI) and neuroscience related studies. Submissions will be peer viewed and receive feedback from readers and a panel of invited consultants of the R-fMRI Network. All manuscripts and feedback will be freely available online with citable permanent URL for open-access. The goal of PRN is to supplement the “peer reviewed” journal publication system – by more rapidly communicating the latest research achievements throughout the world. We hope PRN will help the field to embrace the preprint model and thus further accelerate R-fMRI and neuroscience related studies, eventually enhancing human mental health.

提交时间: 2017-11-06 点击量175下载量135 评论 0

10. chinaXiv:201711.00275 [pdf]

Reliability of sleep deprivation-associated spontaneous brain activity and behavior

Lei Gao; Lijun Bai; Yuchen Zhang; Xi-jian Dai; Rana Netra; Youjiang Min; Fuqing燴hou; Honghan Gong; Ming Zhang; Yijun Liu
分类: 心理学 >> 应用心理学

Recent studies have indicated that sleep deprivation (SD) alters intrinsic low-frequency connectivity in the resting brain, mainly focusing on the default mode network (DMN) and its anticorrelated network (ACN). These networks hold key functions in segregating internally and externally directed awareness. However, far less attention has been paid to investigation of the altered amplitude of these low-frequency fluctuations (ALFF) at the whole-brain level and more importantly by what extent the sleep-deprived resting brain pattern can be reproducible and predict individual behavioral performance. The aim of this study was to characterize more clearly the influence of sleep on the whole brain level of ALFF changes and its relation with the performance of a lexical decision task in the sleep deprivation. Sixteen healthy participants underwent fMRI three times: once after a normal night of sleep in the rested wakefulness (RW) state and two following approximately 24 h of total SD separated by an interval of two weeks (SD1 and SD2). Our behavioral results showed that sleep stabilizes performance whereas two sleep deprivation even at an interval of two weeks consistently deteriorates it. Sleep deprivation attenuated the ALFF mainly in the bilateral orbitofrontal cortex (OFC), bilateral dorsolateral prefrontal cortex (DLPFC) and right inferior parietal lobule (IPL). By contrast, the enhanced ALFF emerged in the left sensorimotor cortex (SMA), visual cortex and left fusiform gyrus. Conjunction analysis of SD1 and SD2 versus the control maps and voxel-wise ICC analysis revealed that these SD induced ALFF changes showed a significantly high reliability (ICC>0.5). Particularly, the attenuation of the right IPL presents a significant negative relation with the behavior performance and can be reproducible for two SD at an interval of two weeks. Our results suggest that ALFF is a stable measure in study of SD, and the right IPL may represent a stable biomarker that responds to sleep loss.

提交时间: 2017-11-06 点击量155下载量136 评论 0

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