Collective Trauma,Implicit Memories,the Body,and Active Imagination in Jungian Analysis1

This presentation attempts to show the healing potential underlying the inclusion of the patient's body in the analytic process, while honouring and revisiting the understanding of the psyche-body connection described by Jung in his early work. In addition, the author offers reflections on the impact of collective trauma whose aftermath, among others, has been the disappearance of thousands of people, consequently breaking the family genealogy, leaving hundreds of children stripped of their roots and true identity. Referencing clinical material, the author describes how the process of translation and integration—from the sensory-perceptual to the conceptual-symbolic—can be halted on account of collective trauma occurring at an early stage in development. Moreover, it is shown how the potential of the archetype or image schema, linked to the somatic-affective early experiences encoded as implicit memories, can be recovered, when Embodied Active Imagination is included in the analytic work. The patient's bodily gestures and somatic experience may bridge the gap between the preverbal-implicit knowledge and the emergence of emotions and images that allow for the creation of a new symbolic narrative.     

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.     

Active school travel is associated with fewer suicide attempts among adolescents from low-and middle-income countries

Background/Objective: This study explored the association between active school travel (AST) and suicide attempts among adolescents in low- and middle-income countries (LMICs). Method: We used the data from the Global School-based Health Survey, including 127,097 adolescents aged 13-17 years from 34 LMICs. A self-reported survey was used to collect data on AST and suicide attempts as well as some variables. Multivariable logistic regression was performed to assess the association between AST and suicide attempts. A meta-analysis with random effects was undertaken to identify the difference in the association between AST and suicide attempts. Results: Across all the adolescents, the prevalence of AST was 37% and the prevalence of suicide attempts was 11.60%. Adolescents who engaged in AST were less likely to have suicide attempts irrespective of gender. The country-wise analysis indicated a large inconsistency in the association between AST and suicide attempt across the countries. Conclusions: AST would appear to be a protective factor for reducing suicide attempts among adolescents. However, the association between AST and suicide attempts varied greatly across the countries. Future studies should confirm the association between AST and suicide attempts.     

Human factors evaluation of an in-vehicle active traffic and demand management (ATDM) system

This research study focused on the evaluation of an emulated in-vehicle Active Traffic and Demand Management (ATDM) system on Interstate 66 in Northern Virginia. Traditional ATDM systems rely on infrastructure-mounted variable message signs (VMS) to provide information (speed limits, lane availability, etc.) to the traveling public. By providing information about dynamic roadway conditions on an in-vehicle device, the ATDM may improve driving safety and performance by allowing drivers to remain consistently aware of forthcoming traffic conditions and roadway requirements; even when external signage is inaccessible. This study represents an initial investigation of an emulated in-vehicle ATDM to provide developers with design guidance and ensure that unintended consequences, such as distraction, do not undermine the potential benefits.Twenty younger and 20 older participants, accompanied by a member of the research team, experienced the following ATDM features on an in-vehicle device (IVD) mounted to the dashboard: (1) dynamic speed limits, (2) dynamic lane use/shoulder control, (3) High Occupancy Vehicle (HOV) restrictions, and (4) roadway information from variable message signs. The IVD was equipped with auditory and visual alerts notifying the driver when relevant visual information was updated. Research questions addressed distraction and driver behavior associated with use of the system. Qualitative and quantitative participant data was acquired from the instrumented vehicle, various questionnaires, and researcher observation.Several key findings were uncovered: (1) The IVD, as tested, did not warrant classification as a source of distraction according to the NHTSA guidelines; v2) There was a significant difference in eye-glance durations to the IVD when comparing the VMS alerts to both the speed limit and lane management alerts; and (3) The speed limit alert motivated participants to alter their speed (per survey results and participant speed data).     

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.     

Socially emotional brain-inspired cognitive architecture framework for artificial intelligence

Artificial Intelligence of the next generation needs to interact with users socially, convincing them in its ability to understand human minds, including emotions. For this to happen, an artificial emotional intelligence is needed, capable of adequate, believable behavior in social emotional interactions. Building on previous developments, the present work extends the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA: Samsonovich, 2013, 2018), endowing it with fluents describing, in addition to appraisals, somatic markers, feelings, emotions, moods, emotional reactions and biases. Key building blocks that integrate them are moral schemas and semantic maps. The model describes interaction of three factors: plans and commitments, moral and ethical values, and somatic comfort. Learning in this framework includes self-organization of semantic maps that in turn may provide guidance for active humanlike learning. Implications for empirical studies and practical applications are discussed together with the expected impact.     

Translating the ICAP Theory of Cognitive Engagement Into Practice

ICAP is a theory of active learning that differentiates students’ engagement based on their behaviors. ICAP postulates that I nteractive engagement, demonstrated by co‐generative collaborative behaviors, is superior for learning to C onstructive engagement, indicated by generative behaviors. Both kinds of engagement exceed the benefits of A ctive or P assive engagement, marked by manipulative and attentive behaviors, respectively. This paper discusses a 5‐year project that attempted to translate ICAP into a theory of instruction using five successive measures: (a) teachers’ understanding of ICAP after completing an online module, (b) their success at designing lesson plans using different ICAP modes, (c) fidelity of teachers’ classroom implementation, (d) modes of students’ enacted behaviors, and (e) students’ learning outcomes. Although teachers had minimal success in designing Constructive and Interactive activities, students nevertheless learned significantly more in the context of Constructive than Active activities. We discuss reasons for teachers’ overall difficulty in designing and eliciting Interactive engagement.     

Training the brain: fact and fad in cognitive and behavioral remediation

Putatively safe and effective for improving cognitive performance in both health and disease, products purported to train the brain appeal to consumers and healthcare practitioners. In an increasingly health-centered society, these applications constitute a burgeoning commercial market. Sparse evidence coupled with lack of scientific rigor, however, leaves claims concerning the impact and duration of such brain training largely unsubstantiated. On the other hand, at least some scientific findings seem to support the effectiveness and sustainability of training for higher brain functions such as attention and working memory. In the present paper we provide a tectonic integration and synthesis of cognitive training approaches. Specifically, we sketch the relative merits and shortcomings of these programs, which often appeal to parents who must choose between side-effect-laden medication and other less conventional options. Here we examine how neuroplasticity allows the healthy as well the impaired to benefit from cognitive training programs. We evaluate the evidence and consider whether brain training can be a stand-alone treatment or an adjunct to pharmacotherapy, outline promising future prospects, and highlight what training outcomes are plausible in line with available data. Future research would determine whether the field of brain training realizes its potential to revolutionize education and rehabilitation or withers away engulfed in controversy.     

Can you tickle yourself if you swap bodies with someone else?

The effect of the body transfer illusion on the perceived strength of self- and externally-generated “tickle” sensations was investigated. As expected, externally generated movement produced significantly higher ratings of tickliness than those associated with self-generated movements. Surprisingly, the body transfer illusion had no influence on the ratings of tickliness, suggesting that highly surprising, and therefore hard to predict, experiences of body image and first-person perspective do not abolish the attenuation of tickle sensations. In addition, evidence was found that a version of the rubber hand illusion exists within the body transfer illusion. We situate our findings within the larger debate over sensory attenuation: (1) there is an attenuation of prediction errors that depends upon the context in which sensory input is predicted (i.e., efference copy), and (2) sensory attenuation is a necessary consequence of self-generated movement irrespective of context (i.e., active inference). The results support the notion of active inference.     

It’s how you say it – The extended Theory of Planned Behaviour explains active transport use in cardiac patients depending on the type of self-report in a hypothesis-generating study

Physical activity (PA) plays an essential part in the secondary prevention of persons with coronary heart disease (CHD). A substantial amount of PA can be gained through increasing the use of active transport modes (walking or cycling for at least 10 min/day) in CHD patients’ daily routine, benefiting the mortality and morbidity rate as well as the environment. The current study aims to investigate the utility of the Theory of Planned Behaviour (TPB) framework extended with habit strength, in understanding the behavioural intention and the behaviour of using active transport modes during the daily travel routine of CHD patients. A cross-sectional survey was conducted from 131 CHD patients. The behaviour was measured using three self-report methods; 1) scale measure, the walking or cycling frequency, 2) direct ATS (Active Travel Score, PA calculated by the directly reported aggregated time spent per day for walking or cycling for travel purposes), and 3) indirect ATS (PA calculated by combining the duration spent on trips by walking and cycling from the self-reported one-day travel diary). Additionally, the participants completed surveys on the direct measures of TPB constructs and habit strength. The results indicated that the TPB constructs explained a 38% variance in the intention to use active transport modes of CHD patients, by which the variance increased to 59% with the addition of habit strength. On the contrary, different behavioural measures were explained differently by TPB and habit strength. The scale measure of behaviour was best predicted (up to 21%) by TPB and habit strength. However, the direct and indirect measures of behaviour were poorly explained (up to 3% and 10% only, respectively). Habit strength moderated the relationship between behaviour (scale measure) and behavioural intention. Surprisingly, higher behavioural intention resulted in a lower behavioural frequency when the habit strength to be active is low. This suggests a limited control over the behaviour thus indicating the intention-behaviour gap. The current study findings highlight the inconsistent predictive utility of TPB across different types of behavioural self-report measures, targeted at the use of active transport modes in CHD patients. However, considering this study as hypothesis-generating, further research is necessary to replicate and extend these findings.