Computational models of the “active self” and its disturbances in schizophrenia

The notion that self-disorders are at the root of the emergence of schizophrenia rather than a symptom of the disease, is getting more traction in the cognitive sciences. This is in line with philosophical approaches that consider an enactive self, constituted through action and interaction with the environment. We thereby analyze different definitions of the self and evaluate various computational theories lending to these ideas. Bayesian and predictive processing are promising approaches for computational modeling of the “active self”. We evaluate their implementation and challenges in computational psychiatry and cognitive developmental robotics. We describe how and why embodied robotic systems provide a valuable tool in psychiatry to assess, validate, and simulate mechanisms of self-disorders. Specifically, mechanisms involving sensorimotor learning, prediction, and self-other distinction, can be assessed with artificial agents. This link can provide essential insights to the formation of the self and new avenues in the treatment of psychiatric disorders.     

Intraindividual variability in driving simulator parameters of healthy drivers of different ages

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.     

Different level automation technology acceptance: Older adult driver opinion

The increase in the number of older adult drivers in developed countries has raised safety concerns due to the decline in their sensory, motor, perceptual, and cognitive abilities which can limit their driving capabilities. Their driving safety could be enhanced by the use of modern Automated Driver Assistance Systems (ADASs) and might totally resolved by full driving automation. However, the acceptance of these technologies by older adult drivers is not yet well understood. Thus, this study investigated older adult drivers’ intention to use six ADASs and full driving automation through two questionnaires with 115 and 132 participants respectively in Rhode Island, USA. A four-dimensional model referred to as the USEA model was used for exploring older adult drivers’ technology acceptance. The USEA model included perceived usefulness, perceived safety, perceived ease of use, and perceived anxiety. Path Analysis was applied to evaluate the proposed model. The results of this study identified the important factors in older adult drivers’ intention to use ADASs and full driving automation, which could assist stakeholders in improving technologies for use by older drivers.     

Bridging ears and eyes when learning spoken words: On the effects of bilingual experience at 30 months

From the very first moments of their lives, infants selectively attend to the visible orofacial movements of their social partners and apply their exquisite speech perception skills to the service of lexical learning. Here we explore how early bilingual experience modulates children's ability to use visible speech as they form new lexical representations. Using a cross‐modal word‐learning task, bilingual children aged 30 months were tested on their ability to learn new lexical mappings in either the auditory or the visual modality. Lexical recognition was assessed either in the same modality as the one used at learning (‘same modality’ condition: auditory test after auditory learning, visual test after visual learning) or in the other modality (‘cross‐modality’ condition: visual test after auditory learning, auditory test after visual learning). The results revealed that like their monolingual peers, bilingual children successfully learn new words in either the auditory or the visual modality and show cross‐modal recognition of words following auditory learning. Interestingly, as opposed to monolinguals, they also demonstrate cross‐modal recognition of words upon visual learning. Collectively, these findings indicate a bilingual edge in visual word learning, expressed in the capacity to form a recoverable cross‐modal representation of visually learned words.     

Evaluating the effectiveness of Didi ride-hailing security measures: An integration model

Security is one of the most critical factors influencing individuals’ mobility. Ensuring security along ride-hailing trips is also a fundamental challenge to service providers. After two cases of rape and homicide, Didi has rectified measures again to meet passengers’ need for security. However, there are few scientific findings concerning the impact of Didi rectified measures on personal perception of security. This study aims to explore critical latent factors that affect individuals’ intentions to use or reuse ride-hailing after the rectification of security measures. This paper examines individuals’ usage intentions by integrating and expanding both the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB). Research results suggest that perceived security, security risk, and government credibility are correlated with the intentions to use or reuse ride-hailing. Importantly, perceived security and security risk both have a direct impact on behavioral intentions from a different perspective. In contrast, government credibility has an indirect effect. Hence, a mediating effect test is conducted. Government credibility could indirectly influence behavioral intention by affecting trust. Finally, this study verifies that the effectiveness of security measures could be evaluated and improved by studying the influence of latent factors on the intentions to use or reuse ride-hailing.     

Driver conflict response during supervised automation: Do hands on wheel matter?

Securing appropriate driver responses to conflicts is essential in automation that is not perfect (because the driver is needed as a fall-back for system limitations and failures). However, this is recognized as a major challenge in the human factors literature. Moreover, in-depth knowledge is lacking regarding mechanisms affecting the driver response process. The first aim of this study was to investigate how driver conflict response while using highly reliable (but not perfect) supervised automation differ for drivers that (a) crash or avoid a conflict object and (b) report high trust or low trust in automation to avoid the conflict object. The second aim was to understand the influence on the driver conflict response of two specific factors: a hands-on-wheel requirement (with vs. without), and the conflict object type (garbage bag vs. stationary vehicle). Seventy-six participants drove with highly reliable but supervised automation for 30 min on a test track. Thereafter they needed to avoid a static object that was revealed by a lead-vehicle cut-out. The driver conflict response was assessed through the response process: timepoints for driver surprise reaction, hands-on-wheel, driver steering, and driver braking. Crashers generally responded later in all actions of the response process compared to non-crashers. In fact, some crashers collided with the conflict object without even putting their hands on the wheel. Driver conflict response was independent of the hands-on-wheel requirement. High-trust drivers generally responded later than the low-trust drivers or not at all, and only high trust drivers crashed. The larger stationary vehicle triggered an earlier surprise reaction compared to the garbage bag, while hands-on-wheel and steering response were similar for the two conflict object types. To conclude, crashing is associated with a delay in all actions of the response process. In addition, driver conflict response does not change with a hands-on-wheel requirement but changes with trust-level and conflict object type. Simply holding the hands on the wheel is not sufficient to prevent collisions or elicit earlier responses. High trust in automation is associated with late response and crashing, whereas low trust is associated with appropriate driver response. A larger conflict object trigger earlier surprise reactions.     

Safety of micro-mobility: Riders’ psychological factors and risky behaviors of cargo TTWs in China

Cargo two- or three-wheeled vehicles (TTWs), as a new form of micro-mobility, have become a popular mode of urban cargo transportation in China. Cargo TTW riders’ psychological factors and risky behaviors lead to a number of accidents. A questionnaire is designed by comprehensively considering these factors and behaviors of cargo TTW riders that includes eleven risk factors to quantitatively analyze the risky behaviors based on structural equation modeling (SEM). One thousand three hundred nineteen participants reported using cargo TTWs on a questionnaire distributed across the country. The characteristics of riding behavior data are analyzed to verify the three-layer risk theoretical framework of “Psychological factors (Personality traits/specific factors) - Psychological acceptability of risks (confidence/perception/attitude) - Risky behaviors”. The results show that anger has a strong direct effect on riding violations, while normlessness and altruism have a direct effect on riding errors. Workload has a weak but direct effect on risky behaviors, and riding feedback has a weak and mixed effect. In addition, high-risk groups are identified by analysis of variance (ANOVA) with rider population attributes. These quantitative analyses can help guide safety countermeasures to mitigate accidents involving cargo TTWs.     

An adaptive network model covering metacognition to control adaptation for multiple mental models

Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.     

De l’estime de soi et du sentiment d’auto-efficacité à la motivation au travail : le rôle médiateur du sens du travail chez les alternants en France

The purpose of this study was to test the links between self-esteem, the feeling of self-efficacy and the different forms of motivation. It also aimed to understand the mediating effect of the meaning of work between the variables. French work-integrated learning students (n = 471) completed a self-administered online questionnaire. The results showed significant links between self-esteem, perceived self-efficacy, work meaning, and different dimensions of motivation (extrinsic, intrinsic, and amotivation). In addition, the meaning of work played a mediating role in the relationship between self-esteem, perceived self-efficacy, and dimensions of motivation. This study showed the central mechanism of work meaning in work motivation.     

Dynamiques représentationnelles et identitaires au cours de la socialisation professionnelle de jeunes recrues LGBT

This article examines the ways in which representational and identity transformations work during the socialization in the workplace of young LGBT hires, linked to discrimination perceived in their workplace environment as well as their impact on professional goals. Working within the theoretical framework of active socialization, the study is based on the IMIS method and proposes a detailed analysis of two cases recently entering the transportation workplace. The results show that, depending on how severe the perceived discrimination is in the workplace, previous experiences of homophobia encountered in other environments and already built self-image are reactivated in different ways, leading to a more or less important reconstruction of professional and identity representations, as well as the future goals of the individual. These elements are discussed from the point of view of interactions between environments and possible interventions by valuing diversity and accompanying the integration of young hires into organizations.