A Unifying Model for Discordant and Concordant Results in Human Neuroimaging Studies of Facial Viewpoint Selectivity.

Recognizing faces regardless of their viewpoint is critical for social interactions. Traditional theories hold that view-selective early visual representations gradually become tolerant to viewpoint changes along the ventral visual hierarchy. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest a three-stage architecture including an intermediate face-selective patch abruptly achieving invariance to mirror-symmetric face views. Human studies combining neuroimaging and multivariate pattern analysis (MVPA) have provided convergent evidence of view selectivity in early visual areas. However, contradictory conclusions have been reached concerning the existence in humans of a mirror-symmetric representation like that observed in macaques. We believe these contradictions arise from low-level stimulus confounds and data analysis choices. To probe for low-level confounds, we analyzed images from two face databases. Analyses of image luminance and contrast revealed biases across face views described by even polynomials-i.e., mirror-symmetric. To explain major trends across neuroimaging studies, we constructed a network model incorporating three constraints: cortical magnification, convergent feedforward projections, and interhemispheric connections. Given the identified low-level biases, we show that a gradual increase of interhemispheric connections across network-layers is sufficient to replicate view-tuning in early processing stages and mirror-symmetry in later stages. Data analysis decisions-pattern dissimilarity measure and data recentering-accounted for the inconsistent observation of mirror-symmetry across prior studies. Pattern analyses of human fMRI data (of either sex) revealed biases compatible with our model. The model provides a unifying explanation of MVPA studies of viewpoint selectivity and suggests observations of mirror-symmetry originate from ineffectively normalized signal imbalances across different face views.

A simple optical flow model explains why certain object viewpoints are special.

A core challenge in perception is recognizing objects across the highly variable retinal input that occurs when objects are viewed from different directions (e.g. front versus side views). It has long been known that certain views are of particular importance, but it remains unclear why. We reasoned that characterizing the computations underlying visual comparisons between objects could explain the privileged status of certain qualitatively special views. We measured pose discrimination for a wide range of objects, finding large variations in performance depending on the object and the viewing angle, with front and back views yielding particularly good discrimination. Strikingly, a simple and biologically plausible computational model based on measuring the projected three-dimensional optical flow between views of objects accurately predicted both successes and failures of discrimination performance. This provides a computational account of why certain views have a privileged status.

Pressing ethical issues relating to clinical pig organ transplantation studies.

Clinical pig heart transplant experiments have been undertaken, and further clinical experiments and/or clinical trials of gene-edited pig organ xenotransplantation are anticipated. The ethical issues relating to xenotransplantation have been discussed for decades but with little resolution. Consideration of certain ethical issues is more urgent than others, and the need to attain consensus is important. These issues include: (i) patient selection criteria for expanded access and/or clinical trials; (ii) appropriate protection of the patient from xenozoonoses, that is, infections caused by pig microorganisms transferred with the organ graft, (iii) minimization of the risk of a xenozoonosis to bystanders, and (iv) the need for additional public perception studies. We discuss why it is important and urgent to achieve consensus on these ethical issues prior to carrying out further expanded access experiments or initiating formal clinical trials. The ways forward on each issue are proposed.

The importance of multisensory-motor learning on subsequent visual recognition.

Speed of visual object recognition is facilitated after active manual exploration of objects relative to passive visual processing alone. Manual exploration allows viewers to select important information about object structure that may facilitate recognition. Viewpoints where the objects' axis of elongation is perpendicular or parallel to the line of sight are selected more during exploration, recognized faster than other viewpoints, and afford the most information about structure when object movement is controlled by the viewer. Prior work used virtual object exploration in active and passive viewing conditions, limiting multisensory structural object information. Adding multisensory information to encoding may change accuracy of overall recognition, viewpoint selection, and viewpoint recognition. We tested whether the known active advantage for object recognition would change when real objects were studied, affording visual and haptic information. Participants interacted with 3D novel objects during manual exploration or passive viewing of another's object interactions. Object recognition was tested using several viewpoints of rendered objects. We found that manually explored objects were recognized more accurately than objects studied through passive exploration and that recognition of viewpoints differed from previous work.

Harnessing ChatGPT for Thematic Analysis: Are We Ready?

ChatGPT (OpenAI) is an advanced natural language processing tool with growing applications across various disciplines in medical research. Thematic analysis, a qualitative research method to identify and interpret patterns in data, is one application that stands to benefit from this technology. This viewpoint explores the use of ChatGPT in three core phases of thematic analysis within a medical context: (1) direct coding of transcripts, (2) generating themes from a predefined list of codes, and (3) preprocessing quotes for manuscript inclusion. Additionally, we explore the potential of ChatGPT to generate interview transcripts, which may be used for training purposes. We assess the strengths and limitations of using ChatGPT in these roles, highlighting areas where human intervention remains necessary. Overall, we argue that ChatGPT can function as a valuable tool during analysis, enhancing the efficiency of the thematic analysis and offering additional insights into the qualitative data. While ChatGPT may not adequately capture the full context of each participant, it can serve as an additional member of the analysis team, contributing to researcher triangulation through knowledge building and sensemaking.

Safety, Efficiency, and Mental Workload in Simulated Teledriving of a Vehicle as Functions of Camera Viewpoint.

Teleoperation services are expected to operate on-road and often in urban areas. In current teleoperation applications, teleoperators gain a higher viewpoint of the environment from a camera on the vehicle's roof. However, it is unclear how this viewpoint compares to a conventional viewpoint in terms of safety, efficiency, and mental workload. In the current study, teleoperators (n = 148) performed driving tasks in a simulated urban environment with a conventional viewpoint (i.e., the simulated camera was positioned inside the vehicle at the height of a driver's eyes) and a higher viewpoint (the simulated camera was positioned on the vehicle roof). The tasks required negotiating road geometry and other road users. At the end of the session, participants completed the NASA-TLX questionnaire. Results showed that participants completed most tasks faster with the higher viewpoint and reported lower frustration and mental demand. The camera position did not affect collision rates nor the probability of hard braking and steering events. We conclude that a viewpoint from the vehicle roof may improve teleoperation efficiency without compromising driving safety, while also lowering the teleoperators' mental workload.

Viewpoint Selection for 3D-Games with f-Divergences.

In this paper, we present a novel approach for the optimal camera selection in video games. The new approach explores the use of information theoretic metrics f-divergences, to measure the correlation between the objects as viewed in camera frustum and the ideal or target view. The f-divergences considered are the Kullback-Leibler divergence or relative entropy, the total variation and the χ2 divergence. Shannon entropy is also used for comparison purposes. The visibility is measured using the differential form factors from the camera to objects and is computed by casting rays with importance sampling Monte Carlo. Our method allows a very fast dynamic selection of the best viewpoints, which can take into account changes in the scene, in the ideal or target view, and in the objectives of the game. Our prototype is implemented in Unity engine, and our results show an efficient selection of the camera and an improved visual quality. The most discriminating results are obtained with the use of Kullback-Leibler divergence.

Honoring the gift: The transformative potential of transplant-declined human organs.

For decades, transplantation has been a life-saving treatment for those fortunate enough to gain access. Nevertheless, many patients die waiting for an organ and countless more never make it onto the waitlist because of a shortage of donor organs. Concurrently, thousands of donated organs are declined for transplant each year because of concerns about poor outcomes post-transplant. The decline of any donated organ-even if medically justified-is tragic for both the donor family and potential recipients. In this Personal Viewpoint, we discuss the need for a new mindset in how we honor the gift of organ donation. We believe that the use of transplant-declined human organs in translational research has the potential to hasten breakthrough discoveries in a multitude of scientific and medical areas. More importantly, such breakthroughs will allow us to properly value every donated organ. We further discuss the many practical challenges that such research presents and offer some possible solutions based on experiences in our own research laboratories. Finally, we share our perspective on what we believe are the necessary next steps to ensure a future where every donated organ realizes its full potential to impact the lives of current and future patients.

Information design to support growth, quality, and equity of the US transplant system.

The Organ Procurement and Transplantation Network, an arm of the Health Resources and Services Administration, has a contract with the United Network for Organ Sharing since 1986 to provide central oversight of organ donation and transplants in the United States. The United Network for Organ Sharing has recently come under scrutiny, prompting a review by the National Academies of Sciences, Engineering, and Medicine as summarized in its recent report and also by the US Senate Finance Committee. The national news services have opined about organ donation ethics, access to transplantation particularly for medically underserved populations, and management of organ transplantation data. These critiques raise important concerns that deserve our best response as a transplant community. Broadly, we suggest that the data management approach of the Organ Procurement and Transplantation Network be replaced with a patient-centric omnichannel network in which all donor and recipient data exist in a single longitudinal record that can be used by all applications. A more comprehensive and standardized approach to donor data collection would drive quality improvement across organ procurement organizations and help address inequities in transplantation. Finally, a substantial increase in organ donation would be prompted by considering organ donors as a public health resource, meriting transparent publicly available data collection with respect to organ donor referral, screening, and management.

My view on your actions: Dynamic changes in viewpoint-dependent auditory ERP attenuation during action observation.

It has been suggested that during action observation, a sensory representation of the observed action is mapped onto one's own motor system. However, it is largely unexplored what this may imply for the early processing of the action's sensory consequences, whether the observational viewpoint exerts influence on this and how such a modulatory effect might change over time. We tested whether the event-related potential of auditory effects of actions observed from a first- versus third-person perspective show amplitude reductions compared with externally generated sounds, as revealed for self-generated sounds. Multilevel modeling on trial-level data showed distinct dynamic patterns for the two viewpoints on reductions of the N1, P2, and N2 components. For both viewpoints, an N1 reduction for sounds generated by observed actions versus externally generated sounds was observed. However, only during first-person observation, we found a temporal dynamic within experimental runs (i.e., the N1 reduction only emerged with increasing trial number), indicating time-variant, viewpoint-dependent processes involved in sensorimotor prediction during action observation. For the P2, only a viewpoint-independent reduction was found for sounds elicited by observed actions, which disappeared in the second half of the experiment. The opposite pattern was found in an exploratory analysis concerning the N2, revealing a reduction that increased in the second half of the experiment, and, moreover, a temporal dynamic within experimental runs for the first-person perspective, possibly reflecting an agency-related process. Overall, these results suggested that the processing of auditory outcomes of observed actions is dynamically modulated by the viewpoint over time.

The management of healthcare employees' job satisfaction: optimization analyses from a series of large-scale surveys.

BACKGROUND: Measuring employees' satisfaction with their jobs and working environment have become increasingly common worldwide. Healthcare organizations are not extraneous to the irreversible trend of measuring employee perceptions to boost performance and improve service provision. Considering the multiplicity of aspects associated with job satisfaction, it is important to provide managers with a method for assessing which elements may carry key relevance. Our study identifies the mix of factors that are associated with an improvement of public healthcare professionals' job satisfaction related to unit, organization, and regional government. Investigating employees' satisfaction and perception about organizational climate with different governance level seems essential in light of extant evidence showing the interconnection as well as the uniqueness of each governance layer in enhancing or threatening motivation and satisfaction. METHODS: This study investigates the correlates of job satisfaction among 73,441 employees in healthcare regional governments in Italy. Across four cross sectional surveys in different healthcare systems, we use an optimization model to identify the most efficient combination of factors that is associated with an increase in employees' satisfaction at three levels, namely one's unit, organization, and regional healthcare system. RESULTS: Findings show that environmental characteristics, organizational management practices, and team coordination mechanisms correlates with professionals' satisfaction. Optimization analyses reveal that improving the planning of activities and tasks in the unit, a sense of being part of a team, and supervisor's managerial competences correlate with a higher satisfaction to work for one's unit. Improving how managers do their job tend to be associated with more satisfaction to work for the organization. CONCLUSIONS: The study unveils commonalities and differences of personnel administration and management across public healthcare systems and provides insights on the role that several layers of governance have in depicting human resource management strategies.

Understanding the contemporary high obesity rate from an evolutionary genetic perspective.

The topic of obesity is gaining increasing popularity globally. From an evolutionary genetic perspective, it is believed that the main cause of the high obesity rate is the mismatch between environment and genes after people have shifted toward a modern high-calorie diet. However, it has been debated for over 60 years about how obesity-related genes become prevalent all over the world. Here, we review the three most influential hypotheses or viewpoints, i.e., the thrifty gene hypothesis, the drifty gene hypothesis, and the maladaptation viewpoint. In particular, genome-wide association studies in the recent 10 years have provided rich findings and evidence to be considered for a better understanding of the evolutionary genetic mechanisms of obesity. We anticipate this brief review to direct further studies and inspire the future application of precision medicine in obesity treatment.

Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges.

Emergency medicine and its services have reached a breaking point during the COVID-19 pandemic. This pandemic has highlighted the failures of a system that needs to be reconsidered, and novel approaches need to be considered. Artificial intelligence (AI) has matured to the point where it is poised to fundamentally transform health care, and applications within the emergency field are particularly promising. In this viewpoint, we first attempt to depict the landscape of AI-based applications currently in use in the daily emergency field. We review the existing AI systems; their algorithms; and their derivation, validation, and impact studies. We also propose future directions and perspectives. Second, we examine the ethics and risk specificities of the use of AI in the emergency field.

Low Adoption of Video Consultations in Post-COVID-19 General Practice in Northern Europe: Barriers to Use and Potential Action Points.

In the wake of the COVID-19 pandemic, video consultation was introduced in general practice in many countries around the world as a solution to provide remote health care to patients. It was assumed that video consultation would find widespread adoption in post-COVID-19 general practice. However, adoption rates remain low across countries in Northern Europe, suggesting that barriers to its use exist among general practitioners and other practice staff. In this viewpoint, we take a comparative approach, reflecting on similarities and differences in implementation conditions of video consultations in 5 Northern European countries' general practice settings that might have created barriers to its use within general practice. We convened at a cross-disciplinary seminar in May 2022 with researchers and clinicians from 5 Northern European countries with expertise in digital care in general practice, and this viewpoint emerged out of dialogues from that seminar. We have reflected on barriers across general practice settings in our countries, such as lacking technological and financial support for general practitioners, that we feel are critical for adoption of video consultation in the coming years. Furthermore, there is a need to further investigate the contribution of cultural elements, such as professional norms and values, to adoption. This viewpoint may inform policy work to ensure that a sustainable level of video consultation use can be reached in the future, one that reflects the reality of general practice settings rather than policy optimism.

Use of Consumer Wearables in Health Research: Issues and Considerations.

As wearable devices, which allow individuals to track and self-manage their health, become more ubiquitous, the opportunities are growing for researchers to use these sensors within interventions and for data collection. They offer access to data that are captured continuously, passively, and pragmatically with minimal user burden, providing huge advantages for health research. However, the growth in their use must be coupled with consideration of their potential limitations, in particular, digital inclusion, data availability, privacy, ethics of third-party involvement, data quality, and potential for adverse consequences. In this paper, we discuss these issues and strategies used to prevent or mitigate them and recommendations for researchers using wearables as part of interventions or for data collection.

Viewpoint-Agnostic Taekwondo Action Recognition Using Synthesized Two-Dimensional Skeletal Datasets.

Issues of fairness and consistency in Taekwondo poomsae evaluation have often occurred due to the lack of an objective evaluation method. This study proposes a three-dimensional (3D) convolutional neural network-based action recognition model for an objective evaluation of Taekwondo poomsae. The model exhibits robust recognition performance regardless of variations in the viewpoints by reducing the discrepancy between the training and test images. It uses 3D skeletons of poomsae unit actions collected using a full-body motion-capture suit to generate synthesized two-dimensional (2D) skeletons from desired viewpoints. The 2D skeletons obtained from diverse viewpoints form the training dataset, on which the model is trained to ensure consistent recognition performance regardless of the viewpoint. The performance of the model was evaluated against various test datasets, including projected 2D skeletons and RGB images captured from diverse viewpoints. Comparison of the performance of the proposed model with those of previously reported action recognition models demonstrated the superiority of the proposed model, underscoring its effectiveness in recognizing and classifying Taekwondo poomsae actions.

Viewpoint Planning for Range Sensors Using Feature Cluster Constrained Spaces for Robot Vision Systems.

The efficient computation of viewpoints for solving vision tasks comprising multi-features (regions of interest) represents a common challenge that any robot vision system (RVS) using range sensors faces. The characterization of valid and robust viewpoints is even more complex within real applications that require the consideration of various system constraints and model uncertainties. Hence, to address some of the challenges, our previous work outlined the computation of valid viewpoints as a geometrical problem and proposed feature-based constrained spaces (C-spaces) to tackle this problem efficiently for acquiring one feature. The present paper extends the concept of C-spaces to consider multi-feature problems using feature cluster constrained spaces (GC-spaces). A GC-space represents a closed-form, geometrical solution that provides an infinite set of valid viewpoints for acquiring a cluster of features satisfying diverse viewpoint constraints. Furthermore, the current study outlines a generic viewpoint planning strategy based on GC-spaces for solving vision tasks comprising multi-feature scenarios effectively and efficiently. The applicability of the proposed framework is validated on two different industrial vision systems used for dimensional metrology tasks.

Feasibility of Using Q-Sort to Map Conditional Participation in Physical Activity in Adolescents With Autism Spectrum Disorder.

BACKGROUND: Participation in physical activity among adolescents with autism is often conditional. However, there is a lack of methods for identifying these specific conditions. Therefore, the purpose of this study was to develop and investigate the feasibility of a Q-sort tool to map individual-specific conditions for participation in physical activity among adolescents with autism and to identify different viewpoints regarding conditions for such participation. METHOD: An exploratory mixed-methods design was employed to investigate the feasibility of using Q methodology and the Q-sort procedure to identify what individual-specific conditions are important for participation in physical activity for adolescents with autism. RESULTS: The adolescents ranked the statements with varying levels of ease. Two viewpoints were identified: Autonomous participation without surprises and Enjoyment of activity in a safe social context. CONCLUSION: Q-sort is a feasible method for mapping conditions for participation, which can guide the development of tailored physical activity interventions.

Room-size illusion and recovery of the true appearance.

It is widely known among photographers that photographing a room with a wide-angle lens exaggerates the size of the room; nevertheless, such images are commonly found on hotel-reservation web sites. The present paper points out that the size exaggeration is a kind of optical illusion caused by an inappropriate viewpoint from which the image is seen, and presents a method we developed for removing the illusion and thus recovering the true appearance of the room. This method requires only a single image together with the lens center at which the image is taken. From this information, we can generate images that would be obtained if we stand at the same point as the camera and pan around the original scene, changing the view direction. The validity of the method is shown by examples. Possible applications to size-exaggerated images posted on web sites are also discussed.

The neural coding of face and body orientation in occipitotemporal cortex.

Face and body orientation convey important information for us to understand other people's actions, intentions and social interactions. It has been shown that several occipitotemporal areas respond differently to faces or bodies of different orientations. However, whether face and body orientation are processed by partially overlapping or completely separate brain networks remains unclear, as the neural coding of face and body orientation is often investigated separately. Here, we recorded participants' brain activity using fMRI while they viewed faces and bodies shown from three different orientations, while attending to either orientation or identity information. Using multivoxel pattern analysis we investigated which brain regions process face and body orientation respectively, and which regions encode both face and body orientation in a stimulus-independent manner. We found that patterns of neural responses evoked by different stimulus orientations in the occipital face area, extrastriate body area, lateral occipital complex and right early visual cortex could generalise across faces and bodies, suggesting a stimulus-independent encoding of person orientation in occipitotemporal cortex. This finding was consistent across functionally defined regions of interest and a whole-brain searchlight approach. The fusiform face area responded to face but not body orientation, suggesting that orientation responses in this area are face-specific. Moreover, neural responses to orientation were remarkably consistent regardless of whether participants attended to the orientation of faces and bodies or not. Together, these results demonstrate that face and body orientation are processed in a partially overlapping brain network, with a stimulus-independent neural code for face and body orientation in occipitotemporal cortex.