The structure of executive functioning in 11 to 14 year olds with and without special educational needs

The structure and development of executive functioning (EF) have been intensively studied in typically developing populations, with little attention given to those with Special Educational Needs (SEN). This study addresses this by comparing the EF structure of 132 adolescents (11–14 years-old) with SEN and 138 adolescents not requiring additional support (Non-SEN peers). Participants completed verbal and non-verbal assessments of key components of EF: inhibition, working memory and switching. Confirmatory Factor Analysis on each group tested one-, two- and three-factor models of EF. In both groups, there was statistical support for the fit of one- and two-factor models with no model being clearly better than the others; there was little support for three-factor models. Parsimony suggests that the one-factor model best represents the structure of EF. In light of our results, the implications for the nature of EF in early adolescence in both SEN and Non-SEN groups are discussed.     

Age-related qualitative differences in post-error cognitive control adjustments

Detecting an error signals the need for increased cognitive control and behavioural adjustments. Considerable development in performance monitoring and cognitive control is evidenced by lower error rates and faster response times in multi-trial executive function tasks with age. Besides these quantitative changes, we were interested in whether qualitative changes in balancing accuracy and speed contribute to developmental progression during elementary school years. We conducted two studies investigating the temporal and developmental trajectories of post-error slowing in three prominent cognitive conflict tasks (Stroop, Simon, and flanker). We instructed children (8-, 10-, and 12-year-old) and adults to respond as fast and as accurately as possible and measured their response times on four trials after correct and incorrect responses to a cognitive conflict. Results revealed that all age groups had longer response times on post-error versus post-correct trials, reflecting post-error slowing. Critically, slowing on the first post-error trial declined with age, suggesting an age-related reduction in the orienting response towards errors. This age effect diminished on subsequent trials, suggesting more fine-tuned cognitive control adjustments with age. Overall, the consistent pattern across tasks suggests an age-related change from a relatively strong orienting response to more balanced cognitive control adaptations.     

父母心理控制对流动儿童道德推脱的影响:学校道德氛围感知的中介作用和性别的调节作用

以345名12～17岁初中阶段流动儿童为被试,采用问卷法考察学校道德氛围感知在流动儿童父母心理控制与道德推脱关系中的中介作用,以及性别的调节作用。结果表明:(1)父母心理控制正向预测流动儿童道德推脱;(2)学校道德氛围感知在父母心理控制和流动儿童道德推脱之间起到部分中介作用。(3)性别在父母心理控制与学校道德氛围感知间起调节作用,性别调节了中介模型的前半路径,具体而言,与男孩相较,女孩的学校道德氛围感知受到父母心理控制的影响作用更加显著。     

控制和外界客体社会效价对身体拥有感的影响

研究采用运动橡胶手错觉范式,操纵了“控制”和“社会效价”两个变量,通过行为实验探讨了控制和社会效价对身体拥有感的影响。结果发现,与“被动控制”条件相比,“主动控制”条件产生了更强的拥有感; 与“不利”条件相比,“有利”条件产生了更强的拥有感。且“控制”和“社会效价”的交互作用显著:无论哪种控制条件,有利条件下的拥有感都显著高于不利条件下的拥有感; 无论哪种效价条件,主动控制条件下的拥有感均显著高于被动控制条件下的拥有感。该结果表明,控制和社会效价是产生身体拥有感的条件。研究结果为提高假肢佩戴者对假肢的心理接纳程度提供了有益的训练途径。     

Effects of the function-specific instruction approach to neurofeedback training on frontal midline theta waves and golf putting performance

A recent meta-analysis has shown inconclusive results on the effectiveness of traditional electroencephalography (EEG) neurofeedback training (NFT) protocols in changing EEG activity and improving sports performance. To enhance the effectiveness of EEG NFT protocols, we explored a new approach to EEG NFT, namely the function-specific instruction (FSI) approach. The basic tenet underpinning effective verbal instruction is to induce mental states as the verbal instructions consider the meaning of the brainwave function in the target region and the EEG power magnitude. This study aimed to test whether a single session of FSI is efficacious in improving frontal midline theta (FMT) activity and putting performance. Method: Thirty-six skilled golfers with a handicap of 14.05 ± 9.43 were recruited. A consecutive sampling method was used to form three groups: an FSI group (n = 12), a traditional instruction (TI) group (n = 12), and a sham control (SC) group (n = 12). In the pre- and post-tests, each participant performed 40 putts from a distance of 3 m, and the number of holed putts was recorded. The participants were asked to perform 50 trials in a single session of NFT. Putting performance improved significantly from before to after NFT in the FSI group. Moreover, the FSI group demonstrated a significant decrease in FMT power, whereas the SC group demonstrated a significant increase in FMT power from before to after NFT. These findings suggest that the FSI approach is more effective in enhancing sustained attention and putting performance in skilled golfers than TI.     

认知控制的层级性：来自任务切换的脑电证据*

认知控制的主要研究范式之一是任务切换。以往研究发现切换代价受到认知控制层级性的调节, 但鲜有研究探索这一调节过程的动态神经机制。本研究通过嵌套的线索-任务切换范式考察不同层级任务切换代价的差异及其神经机制。在实验中, 要求被试完成高低两种层级任务, 低层级任务要求被试判断数字大小(或奇偶); 高层级任务则须先加工数字的某一语义特征(如当前数字是否是偶数), 然后进行大小判断。行为结果表明, 高层级任务切换代价显著大于低层级任务切换代价。线索锁时的脑电结果表明, 层级效应最早出现于P2成分, 切换效应(切换与重复之差)在CNV成分上受到任务层级的调控, 反映了在任务目标重构阶段给予高层级任务更多的选择性注意以及更高的主动性控制。目标锁时的脑电结果表明, 在N2及慢波(SP)成分上, 高层级任务切换与重复的波幅差异相比低层级任务显著更大, 反映了在抑制旧任务集与重构新反应集的过程中增强的反应性控制。这些结果为任务设置重构论和认知控制的层级性提供了新的证据。     

基于作答时间数据的改变点分析在检测加速作答中的探索——已知和未知项目参数

相对于传统的离散作答数据, 作答时间作为连续数据, 可以提供更多信息。改变点分析(change point analysis)技术在心理和教育领域是一个比较新的技术。本文一方面对改变点分析在心理测量领域的应用进行了一个综合的总结和分析; 另一方面, 将基于作答数据的两种改变点分析统计量推广到作答时间数据, 将改变点分析技术应用到测验异常作答模式：加速作答speededness的检测上。采用两种检验方法：似然比检验和Wald检验, 分别在已知和未知项目参数的条件下, 实现异常作答模式的检测。结果表明, 所采用的方法对于加速作答行为的检测具有很高的检验力, 同时能够很好的控制I类错误率。实证数据分析进一步表明本文中所使用的方法具有应用价值。     

An online hazard perception training course reduces heavy braking,speeding, and over-revving rates during everyday driving

In essence, driver training involves learning the skills required to drive safely and avoid dangerous events. However, in traditional on-road driver instruction, drivers virtually never accrue experience of the most significant types of events that they are learning to avoid: crashes. One means of providing this experience safely is to present novice drivers with video clips of real crashes, as part of structured learning exercises. A six-week automated online hazard perception training course for drivers, incorporating evidence-based training methods and over a hundred crash clips, was previously found to improve novice drivers’ hazard perception skill, which is known to be an important attribute for avoiding crashes. However, since hazard perception was measured using computer-based methods, the possibility remained that the training effect might not transfer to actual driving. We report a randomized control trial in which novice drivers were recruited to assess everyday driving behaviour objectively, using g-force triggered dashcams and GPS trackers installed in their vehicles. On-road data were collected for a one-month baseline period, and for a further two months after half of the sample completed the hazard perception training course. Drivers who completed the course significantly reduced their rate of heavy-braking events, their speeding behaviour, and their rate of over-revving events. These findings support the proposal that a relatively inexpensive and highly scalable hazard perception training intervention can improve on-road driving behaviour, with the clear potential to impact real-world driver safety.     

How to identify the take-over criticality in conditionally automated driving? An examination using drivers’ physiological parameters and situational factors

Autonomous vehicles and advanced driver assistance technology are growing exponentially, and vehicles equipped with conditional automation, which has features like Traffic Jam Pilot and Highway Assist, are already available in the market. And this could expose the driver to a stressful driving condition during the takeover mission. To identify stressful takeover situations and better interact with automated systems, the relationship and effect between drivers’ physiological responses, situational factors (e.g., takeover request [TOR] lead time, takeover frequencies, and scenario types), and takeover criticality were investigated.34 participants were involved in a series of takeover events in a simulated driving environment, which are varied by different TOR lead time conditions and driving scenes. The situational factors, drivers’ skin conductance (SC), heart rate (HR), gaze behaviors, and takeover criticality ratings were collected and analyzed. The results indicated that drivers had a higher takeover criticality rating when they experienced a shorter TOR lead time level or at first to fourth take-overs. Besides, drivers who encountered a dynamic obstacle reported higher takeover criticality ratings when they were at the same Time to collision (TTC). We also observed that the takeover situations of higher criticality have larger driver’s maximum HR, mean pupil size, and maximum change in the SC (relative to the initial value of a takeover stage). Those findings of situational factors and physiological responses can provide additional support for the designing of adaptive alert systems and environmental soothing technology in conditionally automated driving, which will improve the takeover performances and drivers’ experience.     

Towards autonomous artificial agents with an active self: Modeling sense of control in situated action

In this paper we present a computational modeling account of an active self in artificial agents. In particular we focus on how an agent can be equipped with a sense of control and how it arises in autonomous situated action and, in turn, influences action control. We argue that this requires laying out an embodied cognitive model that combines bottom-up processes (sensorimotor learning and fine-grained adaptation of control) with top-down processes (cognitive processes for strategy selection and decision-making). We present such a conceptual computational architecture based on principles of predictive processing and free energy minimization. Using this general model, we describe how a sense of control can form across the levels of a control hierarchy and how this can support action control in an unpredictable environment. We present an implementation of this model as well as first evaluations in a simulated task scenario, in which an autonomous agent has to cope with un-/predictable situations and experiences corresponding sense of control. We explore different model parameter settings that lead to different ways of combining low-level and high-level action control. The results show the importance of appropriately weighting information in situations where the need for low/high-level action control varies and they demonstrate how the sense of control can facilitate this.