Effects of training and display content on Level 2 driving automation interface usability

IntroductionLevel 2 driving automation features, such as adaptive cruise control (ACC) combined with lane centering, primarily communicate their operating statuses through the instrument cluster. It remains unclear how interface-specific training and display content influence the ability to understand Level 2 activity in production vehicles.MethodsEighty participants viewed videos recorded from the driver’s point of view in a variety of driving scenarios with Level 2 activity displayed in the instrument cluster of a 2017 Mercedes-Benz E-Class. Half viewed one of two instrument cluster layouts (simple or complex), and half received an orientation to the interface before the experiment. After each video, they were asked about the scenario they had just seen. We then examined what information in the displays participants used to identify Level 2 activity and the usability of the displays.ResultsTraining improved recognition accuracy of when lane centering was temporarily inactive and understanding of why it was inactive. Neither training nor display content affected the ability to recognize when ACC had adjusted the vehicle’s speed or detected a vehicle ahead, or when ACC initially did not detect a lead vehicle and understanding of why it had not detected it. Both factors influenced which sources of information participants used to determine Level 2 activity. Recognition accuracy of system activity improved when participants used valid sources of information. Training, but not display content, improved lane centering usability, but not ACC usability.DiscussionBasic training improves detection of notifications that potentially require further driver action, but not of those that display persistent status information. Training does not result in full understanding of all system notifications or functional limitations, which reinforces the need for intuitive, salient communication about system behavior and its limitations.     

Idiographic network analysis of discrete mood states prior to treatment

Idiographic network models based on time‐series data have received recent attention for their ability to model relationships among symptoms and behaviours as they unfold in time within a single individual (cf. Epskamp, Borsboom, & Fried, 2018; Fisher, Medaglia, & Jeronimus, 2018). Rather than examine the correlational relationships between variables in a sample of individuals, an idiographic network examines correlations within a single person, averaged over many time points. Because the approach averages over time, the data must be stationary (i.e. relatively consistent over time). If individuals experience varying states over time—different mixtures of symptoms and behaviours in one moment or another—then averaging over categorically different moments may undermine model accuracy. Fisher and Bosley (2019) address these concerns via the application of Gaussian finite mixture modelling to identify latent classes of time points in intraindividual time‐series data from a sample of adults with major depressive disorder and/or generalised anxiety disorder (n = 45). The present paper outlines an extension of this work, wherein network analysis is used to model within‐class covariation of symptoms. To illustrate this approach, network models were constructed for each intraindividual class identified by Fisher and Bosley (137 networks across the 45 participants, mean classes/person = ~3, range = 2–4 classes/person). We examine the relative consistency in symptom organisation between each individual's multiple mood state networks and assess emergent group‐level patterns. We highlight opportunities for enhanced treatment personalisation and review nomothetic patterns relevant to transdiagnostic conceptualisations of psychopathology. We address opportunities for integrating this approach into clinical practice and outline potential shortcomings.     

变量间的网络分析模型及其应用

变量间的网络分析模型近年来被广泛应用于心理学研究。不同于将潜变量作为观测变量的共同先导因素的潜变量模型, 网络分析模型将观测变量作为初级指标, 采用图论的方法建立观测变量之间的关系网络, 其中变量为网络的节点, 而变量间的关系是节点之间的连线。因此网络分析可以突显观测变量之间的联系以及观测变量相互影响而形成的系统。通过变量网络中基于各个节点特征的指标(如中心性)以及基于整体结构特征的指标(如小世界性), 网络分析为研究各种心理现象提供了新的可视化的描述方式和理解视角。近10年来, 网络分析的方法已在人格心理学、社会心理学和临床心理学等领域得到一定的应用。未来研究应继续发展和完善网络分析模型的理论和方法, 使之运用到更多的数据类型和更广的研究领域中。     

孤独症谱系障碍者视觉定向与视觉搜索的特点及神经机制

定向网络是注意网络的重要组成部分, 主要包括视觉定向与视觉搜索两大任务。对于这两大注意任务, 正常个体在神经机制上存在较大的重叠, 然而, 孤独症个体却表现出截然相反的行为证据。研究者从非社会信息的注意视角发现, 一般而言, 在视觉定向上, 孤独症个体注意转移不存在缺陷, 而注意脱离存在困难, 但该结论仍有争议; 在视觉搜索上, 孤独症个体存在视觉搜索优势, 但该优势发生的阶段及原因仍需进一步探究。未来研究应进一步考察孤独症个体在视觉定向任务中左右视野的不对称性、视觉搜索优势的内在机制及两大注意任务之间的相互关系。     

瞳孔是心灵的窗口吗?——瞳孔在心理学研究中的应用及测量

瞳孔大小是眼动研究中一个重要的参数指标, 在一定程度上能够反映人的心理活动并影响他人的心理与行为。一方面, 瞳孔变化受到自上而下的知觉与注意、情绪与动机、心理努力、社会认知与发展等因素的影响, 另一方面, 大瞳孔能引起他人更多的积极评价和积极行为。瞳孔的神经机制(蓝斑-去甲肾上腺素系统)和自适应增益理论解释了瞳孔与心理之间存在紧密联系的原因。瞳孔测量(pupillometry)作为一种有效的眼动追踪方法有助于理解瞳孔与心理的关系, 研究者在测量瞳孔时需要关注无关变量(如亮度、注视位置), 原始数据处理(如基线校正、眨眼处理)及瞳孔指标选取(如瞳孔直径、震颤频率)等问题, 未来研究应继续探讨瞳孔与其他心理之间的关系, 并探索更有效地处理和使用瞳孔指标的方法。     

价值观的稳定性与可变性：基于认知神经科学的视角

价值观的稳定性和可变性一直是该领域争论的焦点所在。近些年来, 研究者开始从认知神经科学的角度来探讨导致价值观稳定性差异的机制问题。已有的神经反应证据表明, 当某种价值观是基于道义主义的绝对规则来进行认知建构的, 或与自我概念在表征上存在一致性时, 其更倾向于保持稳定的状态; 若非如此, 便可能会在外界影响(如他人劝说)下发生重要程度上的改变。未来需要进一步丰富和完善认识价值观稳定性与可变性关系的认知神经加工模型, 并探索价值观长效改变背后的认知神经机制, 以促进理论研究在价值观教育中的实践和应用。     

青少年的同伴选择与同伴影响：基于学业投入与学业成就的纵向社会网络分析

以756名中学生为研究对象,对学业投入、学业成就、同伴团体进行追踪测量,探讨青少年同伴团体的学业投入及学业成就是否存在同伴选择与同伴影响效应。结果表明：（1）在1年的追踪时间中,青少年学业投入的发展呈下降趋势,初始水平与下降速度负相关,学业成就的发展呈上升趋势,初始水平与上升速度无显著相关;（2）学业投入与学业成就存在同伴选择效应,青少年倾向选择与自己学业投入及学业成就相似的个体构建同伴团体;（3）青少年的学业投入及学业成就与同伴逐渐趋近相似,即同伴影响效应显著。     

Predatory aggression in the mink (Mustela vison): Roles of serotonin and food satiation

5-Hydroxytrypotophan at a dose of 50 mg/kg intraperitoneally (i.p.) sharply increased neural serotonin (5-HT) levels in mink and considerably inhibited that animal's predatory attack on rats. Intraperitoneal injection of 5-HT (10 and 20 mg/kg) did not influence such rat-killing. Neural levels of 5-HT or 5-hydroxyindoleacetic acid (5-HIAA) and subsequent aggression by the predator did not change to any great degree after ingestion of a single meal. Abundance of natural mink food for 3 days was associated with an increased level of 5-HIAA in the lateral hypothalamus and the amygdala as well as with an increased latency to attack and to kill rats. 5-HT seems to represent an endogenous factor that inhibits predatory attack by the mink; this effect appears to function through increased metabolism of 5-HT in some brain regions, which is evident after abundant intake of tryptophan with the natural diet.