Socio-Motor Improvisation in Schizophrenia: A Case-Control Study in a Sample of Stable Patients

Improvising is essential for human development and is one of the most important characteristics of being human. However, how mental illness affects improvisation remains largely unknown. In this study we focused on socio-motor improvisation in individuals with schizophrenia, one of the more debilitating mental disorder. This represents the ability to improvise gestures during an interaction to promote sustained communication and shared attention. Using a novel paradigm called the mirror game and recently introduced to study joint improvisation, we recorded hand motions of two people mirroring each other. Comparing Schizophrenia patients and healthy controls skills during the game, we found that improvisation was impaired in schizophrenia patients. Patients also exhibited significantly higher difficulties to being synchronized with someone they follow but not when they were leaders of the joint improvisation game. Considering the correlation between socio-motor synchronization and socio-motor improvisation, these results suggest that synchronization does not only promote affiliation but also improvisation, being therefore an interesting key factor to enhance social skills in a clinical context. Moreover, socio-motor improvisation abnormalities were not associated with executive functioning, one traditional underpinning of improvisation. Altogether, our results suggest that even if both mental illness and improvisation differ from normal thinking and behavior, they are not two sides of the same coin, providing a direct evidence that being able to improvise in individual situations is fundamentally different than being able to improvise in a social context.

Few-Shot Object Detection on Remote Sensing Images via Shared Attention Module and Balanced Fine-Tuning Strategy

Few-shot object detection is a recently emerging branch in the field of computer vision. Recent research studies have proposed several effective methods for object detection with few samples. However, their performances are limited when applied to remote sensing images. In this article, we specifically analyze the characteristics of remote sensing images and propose a few-shot fine-tuning network with a shared attention module (SAM) to adapt to detecting remote sensing objects, which have large size variations. In our SAM, multi-attention maps are computed in the base training stage and shared with the feature extractor in the few-shot fine-tuning stage as prior knowledge to help better locate novel class objects with few samples. Moreover, we design a new few-shot fine-tuning stage with a balanced fine-tuning strategy (BFS), which helps in mitigating the severe imbalance between the number of novel class samples and base class samples caused by the few-shot settings to improve the classification accuracy. We have conducted experiments on two remote sensing datasets (NWPU VHR-10 and DIOR), and the excellent results demonstrate that our method makes full use of the advantages of few-shot learning and the characteristics of remote sensing images to enhance the few-shot detection performance.

Putting Policy First

The vast potential of Twitter means that it can be used as a tool for policy information. This chapters shows that a majority of senators adopt a policy-wonk style for their rhetorical agenda. While institutions and constituent expectations constrain the issues senators may act on, what they communicate in their rhetorical agenda is an opportunity to gain agency over their policy messaging. Senators with policy-focused constituencies, particularly committee leaders and Democrats with policy coalitions, act as legislative entrepreneurs by taking advantage of Twitter’s expansive network to link their legislative activity and policy-focused rhetorical agenda with a diverse constituency of followers networked by shared attention to issue priorities. Additionally, this chapter introduces the concept of a dual process of policy prioritization where lawmakers not only have to decide to become a policy wonk but also make a second decision about which policies define their time in office.

Eye contact marks the rise and fall of shared attention in conversation

Conversation is the platform where minds meet: the venue where information is shared, ideas cocreated, cultural norms shaped, and social bonds forged. Its frequency and ease belie its complexity. Every conversation weaves a unique shared narrative from the contributions of independent minds, requiring partners to flexibly move into and out of alignment as needed for conversation to both cohere and evolve. How two minds achieve this coordination is poorly understood. Here we test whether eye contact, a common feature of conversation, predicts this coordination by measuring dyadic pupillary synchrony (a corollary of shared attention) during natural conversation. We find that eye contact is positively correlated with synchrony as well as ratings of engagement by conversation partners. However, rather than elicit synchrony, eye contact commences as synchrony peaks and predicts its immediate and subsequent decline until eye contact breaks. This relationship suggests that eye contact signals when shared attention is high. Furthermore, we speculate that eye contact may play a corrective role in disrupting shared attention (reducing synchrony) as needed to facilitate independent contributions to conversation.

A SPECULATION ON THE POTENTIAL SUPPORT OF BIO-INSPIRED DESIGN TO BIOLOGICALISATION IN MANUFACTURING

The paper investigates to what extent the knowledge accumulated in the field of Bio-Inspired Design might benefit the process of biologicalisation in manufacturing. According to visions making inroads in the manufacturing field, the latter will not be limited to the consideration and the analysis of biological principles as a source of inspiration for solving technical and organizational problems. In fact, the process of biologicalisation in manufacturing foresees the development of bio-integrated and bio-intelligent systems. In light of these expected developments, Bio-Inspired Design’s might fail to support the whole transition to take place in the manufacturing field. Methodological limitations still to overcome represent an important barrier in this perspective too. While a transfer of knowledge from the design to the manufacturing domain seems unlikely, the authors individuate aspects that encourage cross-fertilization between Bio-Inspired Design and biologicalisation in manufacturing. These include the need to include biologists in engineering teams, the objective of sustainable development, and a shared attention to the evolution of (Design for) Additive Manufacturing.

Eye Contact Marks The Rise And Fall of Shared Attention in Conversation

Conversation is the platform where minds meet —the venue where information is shared, ideas co-created, cultural norms shaped, and social bonds forged. Its frequency and ease belie its complexity. Every conversation weaves a unique shared narrative from the contributions of independent minds, requiring partners to flexibly move into and out of alignment as needed for conversation to both cohere and evolve. How two minds achieve this coordination is poorly understood. Here we test whether eye contact, a common feature of conversation, predicts this coordination by measuring dyadic pupillary synchrony (a corollary of shared attention) during natural conversation. We find that eye contact is positively correlated with synchrony as well as ratings of engagement by conversation partners. However, rather than elicit synchrony, eye contact commences as synchrony peaks and predicts its immediate and subsequent decline until eye contact breaks. This relationship suggests that eye contact signals when shared attention is high. Further, we speculate that eye contact may play a corrective role in disrupting shared attention (reducing synchrony) as needed to facilitate independent contributions to conversation.

Human-social interaction robots to improve shared attention in children with autism

The purpose of the current research is utilization of robots specifically human robots which has filled dramatically in numerous territories, including treatment. In this investigation, a humanoid robot was utilized to improve open consideration in kids with autism. One of the difficulties of this methodology is that infection makes unique conditions for the patient that the presence of the advisor and some other unfamiliar item isn't effortlessly acknowledged. The second challenge is to choose suitable calculations and strategies for following the head and understudy of the eye in youngsters with mental imbalance. One of the attributes of which is compulsory and uncontrolled developments of the head and eyes to the sides. The third issue is the treatment and exploration techniques. The treatment cycle and the planned tests ought not to reason exorbitant incitement in the youngster. In order to beat the referenced difficulties, notwithstanding the high-obstruction ongoing student following calculation, without the utilization of business equipment. Fluffy choice tree has been utilized to join clinical and designing data during treatment, lastly the idea of intuitive treatment for the improvement of medically introverted youngsters has been presented.

Improving Joint Attention in Children with Autism: A VR-AR Enabled Game Approach

Autism Spectrum Disease (ASD) can be referred to as one type of neurodevelopmental disorder, causing communication or behavioral disabilities in multiple severity levels. These challenges cause difficulties in communication, interaction, problem-solving, etc. Though having no persistent cure for ASD, several treatments and intervention strategies prevail for their behavioral development. These treatments include social skill training, sensory integration, and occasional therapy, etc. Many of these researches highly emphasize joint attention, which is the common issue of most autism cases. Joint or shared attention is highly essential for language and communication skill development. In this work, we proposed a game-based approach to improving the joint attention of children with autism. This approach focuses on the efficiency of skilling up their shared attention by interacting with digital models through problem-solving. We integrate AR (Augmented Reality) and VR (Virtual Reality) technologies for solving this issue. Using these technologies, we have designed an interactive multi-staged game module, including several types of real-life alike problems. Problem-solving and interacting with these mascots can help children build up learning and communication skills, which sometimes real-life interaction may find challenging. Again, eye screening and health can be issues in the device-centric scheme. An analytical survey has been presented in this work, confirming that all these health issues have been carefully considered. Implementation and outperforming results of this work will give a clear stand about the effectiveness of this module. Besides, we present sufficient analytics confirming that this module can also be efficient for normal children.

A longitudinal study of early pretense: Metarepresentational or not

The metarepresentational aspect of early pretend play (make-believe activities where children create or participate in creating a new situation different from a real one) has been theoretically debated. In the present longitudinal study of N = 83 children, we tested for predictive relations of shared attention at 12–18 months, implicit false belief (FB) at 18 months, and pretend production at 18 months, as well as comprehension at 24 months. We also tested for long-term predictive relations of pretense production and comprehension with theory of mind (ToM) at the age of 4–5 years. Only pretense production directed toward others (but not self) was specifically related to infancy measures of shared attention. Early pretense, either production or comprehension, was not related to implicit FB or later ToM measures. The findings are discussed in terms of different theoretical accounts of early pretense.