The role of midfrontal theta oscillations across the development of cognitive control in preschoolers and school‐age children

The development of cognitive control enables children to better resist acting based on distracting information that interferes with the current action. Cognitive control improvement serves different functions that differ in part by the type of interference to resolve. Indeed, resisting to interference at the task‐set level or at the response‐preparation level is, respectively, associated with cognitive flexibility and inhibition. It is, however, unknown whether the same neural mechanism underlies these two functions across development. Studies in adults have revealed the contribution of midfrontal theta (MFT) oscillations in interference resolution. This study investigated whether MFT is involved in the resolution of different types of interference in two age groups identified as corresponding to different latent structures of executive functions. Preschool (4–6 years) and school children (6–8 years) were tested with a task involving interference at the response level and/or the task‐set level while (electroencephalogram) EEG was recorded. Behaviorally, response time and accuracy were affected by task‐set. Both age groups were less accurate when the interference occurred at the task‐set level and only the younger group showed decreased accuracy when interference was presented at the response‐preparation level. Furthermore, MFT power was increased, relative to the baseline, during the resolution of both types of interference and in both age groups. These findings suggest that MFT is involved in immature cognitive control (i.e., preschool and school‐ages), by orchestrating its different cognitive processes, irrespective of the interference to resolve and of the level of cognitive control development (i.e., the degree of differentiation of executive functions).     

Mapping differential responses to cognitive training using machine learning

We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self‐organizing maps (SOMs)—a type of simple artificial neural network—to represent multivariate cognitive training data, and then tested whether the way tasks are represented changed as a result of training. The patterns of change we observed in the SOM weight matrices implied that the processes drawn upon to perform WM tasks changed following training. This was then combined with K‐means clustering to identify distinct groups of children who respond to the training in different ways. Firstly, the K‐means clustering was applied to an independent large sample (N = 616, M_age = 9.16 years, range = 5.16–17.91 years) to identify subgroups. We then allocated children who had been through cognitive training (N = 179, M_age = 9.00 years, range = 7.08–11.50 years) to these same four subgroups, both before and after their training. In doing so, we were able to map their improvement trajectories. Scores on a separate measure of fluid intelligence were predictive of a child's improvement trajectory. This paper provides an alternative approach to analysing cognitive training data that go beyond considering changes in individual tasks. This proof‐of‐principle demonstrates a potentially powerful way of distinguishing task‐specific from domain‐general changes following training and of establishing different profiles of response to training.     

Willingness of people who are blind to accept autonomous vehicles: An empirical investigation

Attitudes of a sample of 211 UK people who are blind concerning autonomous vehicles (AVs), and the determinants of the willingness of people who are blind to travel in AVs, were examined. Participants answered an open-ended question regarding their attitudes towards level 5 AVs and the results were analysed using a semi-automated structural topic modelling procedure. (Level 5 AVs are fully autonomous anywhere, and do not require controlled areas in which to operate.) Four “topics” emerged from the exercise: (i) “hope” for future independence and freedom to travel offered by AVs to people who are blind, (ii) scepticism that AVs will ever be configured to meet the needs of people who are blind, (iii) concerns over safety, and (iv) the affordability of AVs. The four topics were employed as mediating variables in a structural equation model designed to explain the respondents’ willingness to travel in an AV. A number of covariates were presumed to influence the four mediating topics, including a participant’s desire for independence, comorbidity, locus of control, and level of generalised anxiety. Three of the mediating variables exerted significant influences on willingness to travel in an AV, i.e., hope for future independence, misgivings about safety, and affordability. Scepticism about AVs did not have a significant effect. Several implications for AV design and for the creation of public information messages promoting AVs are suggested. In particular, public information campaigns should emphasise the freedom to travel that AVs will provide for people who are blind; reassurances concerning safety; and the inevitability of AVs appearing on the roads of economically developed countries.     

Toward ethical cognitive architectures for the development of artificial moral agents

New technologies based on artificial agents promise to change the next generation of autonomous systems and therefore our interaction with them. Systems based on artificial agents such as self-driving cars and social robots are examples of this technology that is seeking to improve the quality of people’s life. Cognitive architectures aim to create some of the most challenging artificial agents commonly known as bio-inspired cognitive agents. This type of artificial agent seeks to embody human-like intelligence in order to operate and solve problems in the real world as humans do. Moreover, some cognitive architectures such as Soar, LIDA, ACT-R, and iCub try to be fundamental architectures for the Artificial General Intelligence model of human cognition. Therefore, researchers in the machine ethics field face ethical questions related to what mechanisms an artificial agent must have for making moral decisions in order to ensure that their actions are always ethically right. This paper aims to identify some challenges that researchers need to solve in order to create ethical cognitive architectures. These cognitive architectures are characterized by the capacity to endow artificial agents with appropriate mechanisms to exhibit explicit ethical behavior. Additionally, we offer some reasons to develop ethical cognitive architectures. We hope that this study can be useful to guide future research on ethical cognitive architectures.     

Buying an electric car: A rational choice or a norm-directed behavior?

The diffusion of electric cars can contribute to more sustainability in the transport sector, but diffusion rates in most countries are still low. We investigated motives for electric car adoption in German households from an environmental psychology perspective. The public debate focuses on rational aspects such as the purchase price or new technological demands (e.g., limited range and a new charging system). Psychological research on energy-related investment decisions in households confirms the relevance of rational motives, but additionally points to the importance of norm-directed motives (moral and social norms). We investigated the relevance of different motives in an online questionnaire with n = 220 members of German households interested in buying a new car. The questionnaire included possible rational and norm-related predictors of electric car adoption. We tested three action models to explain adoption intention: An adjusted technology acceptance model (TAM), an adjusted norm activation model (NAM), and an integrative model with predictors from both models. We analyzed the hypothesized models with path analyses. All models explained a substantial share of variance in adoption intention. The explained share of variance in the NAM was higher than in the TAM and comparably high to the integrative model. The results demonstrate the important role of moral and social motives for households’ investment decisions. Additionally, the technology’s perceived usefulness was an important rational motive. We discuss the context dependency of the results, as household members might have little knowledge about the new technology during the early stages of a technology’s diffusion process. The results strongly suggest broadening political support schemes, such as informational and image campaigns, as a way to more effectively foster electric car diffusion. More comprehensive assessments appear to be necessary in future analyses of electric car adoption as well as energy-related investment decisions.     

Life skills development in physical education: A self-determination theory-based investigation across the school term

ObjectivesGrounded in self-determination theory (SDT), the main aim of this study was to examine the longitudinal associations between teacher autonomy support, students’ basic psychological need satisfaction and life skills development in physical education (PE).DesignThis study employed a two-wave longitudinal research design.MethodStudents (N = 266, Mage = 12.94 years, SD = 0.70) completed measures assessing perceived autonomy-supportive teaching, need satisfaction (autonomy, competence, and relatedness), and life skills development in PE (teamwork, goal setting, social skills, problem solving and decision making, emotional skills, leadership, time management, and interpersonal communication). Data collections took place during week 6 (timepoint 1; T1) and week 15 (timepoint 2; T2) of the autumn school term.ResultsCross-lagged panel analyses showed that T1 teacher autonomy support did not significantly predict students’ three basic psychological needs, total need satisfaction or life skills development at T2. Students’ T1 total need satisfaction positively predicted their development of all eight life skills at T2. Additionally, students’ T1 autonomy satisfaction positively predicted their teamwork, social skills, emotional skills, leadership, and interpersonal communication skills at T2, T1 competence satisfaction positively predicted students’ teamwork skills at T2, and students’ T1 relatedness satisfaction positively predicted their social skills at T2.ConclusionsProviding partial support for SDT, the findings highlighted that satisfaction of students’ three basic psychological needs had some positive effects on students’ life skills development in PE. As such, a climate that satisfies students’ basic psychological needs should help to develop their life skills in PE.     

工作反刍及其“双刃剑”效应

工作反刍指在没有要求其出现的情境下, 有意识的、重复发生的工作方面的相关想法, 分为工作相关情感反刍与工作相关问题解决沉思两个维度。工作反刍对个体健康、工作及幸福感的影响有“双刃剑”效应。持续性认知理论、压力认知激活模型与认知资源视角理论, 可以解释该效应的内在机制。未来研究应分析影响双刃剑效应的边界条件, 寻求减少消极效应、增加积极效应的途径, 拓展其双刃剑效应心理机制的分析视角和该效应的作用层面。     

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。     

面孔识别的自我群体偏向

面孔认知研究表明, 人们识别和再认自己所属群体(如种族、性别、年龄)面孔的成绩显著好于识别其他群体面孔的成绩。近年来围绕面孔识别的这种自我群体偏向进行了实验研究, 研究者提出了知觉经验说和社会认知论两种理论来解释其认知加工机制, 而类别化-个性化模型和双路径模型则是将两种理论分别加以整合提出的新解释。研究者还对面孔识别自我群体偏向的神经机制进行了研究, 探讨了评价者、评价对象和评价任务等因素对自我群体偏向的影响。提升面孔识别自我群体偏向研究的生态效度, 构建整合性理论模型以及加强跨文化和本土研究是未来研究的重要方向。