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.     

Lessons Learned Conducting Dialectical Behavior Therapy via Telehealth in the Age of COVID-19

Given the severity and suicide risk of patients typically treated by Dialectical Behavior Therapy (DBT) and the absence of guidelines regarding delivery of DBT via telehealth, it is crucial that the DBT treatment community gather and rapidly disseminate information about effective strategies for delivering DBT via telehealth. The current study surveyed DBT providers (N = 200) to understand challenges and lessons learned as they transitioned to conducting DBT via telehealth during the COVID-19 pandemic. Open-ended responses to challenges and lessons-learned were coded. Most frequently noted challenges were Therapy-Interfering Behaviors and elements related to the provision of Individual Therapy and Skills Training Group. The majority of providers offered advice for implementing group skills training, avoiding or overcoming therapist burnout, and emphasized continued adherence to treatment principles, even in the context of this new treatment modality. Overall, this qualitative study marks a starting point on identifying best practices delivering DBT via telehealth for which it is anticipated that clinical recommendations in this area will evolve, informed by clinician, researcher, and consumer input.     

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.     

Perfectionism: The good,the bad,and the creative

The influence of adaptive and maladaptive perfectionism on creativity was examined. Initially, six measures of creativity were administered, including creative self-perceptions, behavior, and performance measures. Adaptive perfectionism was weakly positively related to creativity, whereas maladaptive perfectionism was unrelated to creativity across five of the six measures. A follow-up study assessed whether initial findings could be generalized to an everyday problem-solving task. Results indicated that adaptive perfectionism was related to higher quality but not originality of solutions. Further, a curvilinear relationship in the shape of an inverted “U” occurred between adaptive perfectionism and four of eight creativity measures. Overall, adaptive perfectionism was consistently, albeit weakly, related to creativity across various types of measures, whereas maladaptive perfectionism was not related to creativity.     

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.