Analyzing P300 Distractors for Target Reconstruction

P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and non-target stimulus categories during model training, which imparts bias into the model. Additionally, not all non-targets are created equal; some may contain visual features that resemble targets or may otherwise be visually salient. Current research has indicated that non-target distractors may elicit attenuated P300 responses based on the perceptual similarity of these distractors to the target category. To minimize this bias, and enable a more nuanced analysis, we use a generalized BCI approach that is fit to neither user nor task. We do not seek to improve the overall accuracy of the BCI with our generalized approach; we instead demonstrate the utility of our approach for identifying target-related image features. When combined with other intelligent agents, such as computer vision systems, the performance of the generalized model equals that of the user-specific models, without any user specific data.Comment: 4 pages, 3 figure

Decoding Neural Activity to Assess Individual Latent State in Ecologically Valid Contexts

There exist very few ways to isolate cognitive processes, historically defined via highly controlled laboratory studies, in more ecologically valid contexts. Specifically, it remains unclear as to what extent patterns of neural activity observed under such constraints actually manifest outside the laboratory in a manner that can be used to make an accurate inference about the latent state, associated cognitive process, or proximal behavior of the individual. Improving our understanding of when and how specific patterns of neural activity manifest in ecologically valid scenarios would provide validation for laboratory-based approaches that study similar neural phenomena in isolation and meaningful insight into the latent states that occur during complex tasks. We argue that domain generalization methods from the brain-computer interface community have the potential to address this challenge. We previously used such an approach to decode phasic neural responses associated with visual target discrimination. Here, we extend that work to more tonic phenomena such as internal latent states. We use data from two highly controlled laboratory paradigms to train two separate domain-generalized models. We apply the trained models to an ecologically valid paradigm in which participants performed multiple, concurrent driving-related tasks. Using the pretrained models, we derive estimates of the underlying latent state and associated patterns of neural activity. Importantly, as the patterns of neural activity change along the axis defined by the original training data, we find changes in behavior and task performance consistent with the observations from the original, laboratory paradigms. We argue that these results lend ecological validity to those experimental designs and provide a methodology for understanding the relationship between observed neural activity and behavior during complex tasks

Collaborative Brain-Computer Interface for Human Interest Detection in Complex and Dynamic Settings

Humans can fluidly adapt their interest in complex environments in ways that machines cannot. Here, we lay the groundwork for a real-world system that passively monitors and merges neural correlates of visual interest across team members via Collaborative Brain Computer Interface (cBCI). When group interest is detected and co-registered in time and space, it can be used to model the task relevance of items in a dynamic, natural environment. Previous work in cBCIs focuses on static stimuli, stimulus- or response- locked analyses, and often within-subject and experiment model training. The contributions of this work are twofold. First, we test the utility of cBCI on a scenario that more closely resembles natural conditions, where subjects visually scanned a video for target items in a virtual environment. Second, we use an experiment-agnostic deep learning model to account for the real-world use case where no training set exists that exactly matches the end-users task and circumstances. With our approach we show improved performance as the number of subjects in the cBCI ensemble grows, and the potential to reconstruct ground-truth target occurrence in an otherwise noisy and complex environment.Comment: 6 pages, 6 figure

Impact of the COVID-19 Global Pandemic on the Otolaryngology Fellowship Application Process

On March 11, 2020, the World Health Organization declared coronavirus disease 2019 a global pandemic. In addition to massive social disruption, this pandemic affected the traditional fellowship interview season for otolaryngology subspecialties, including head and neck surgical oncology, facial plastic and reconstructive surgery, laryngology, rhinology, neurotology, and pediatric otolaryngology. The impact on the fellowship interview process, from the standpoint of the institution and the applicant, necessitated the use of alternative interview processes. This change may alter the future of how interviews and the match proceed for years to come, with nontraditional methods of interviewing becoming a mainstay. While the impact this pandemic has on the fellowship match process is not yet fully realized, this commentary aims to discuss the challenges faced on both sides of the equation and to offer solutions during these unprecedented times

Effect of individual environmental heat stress variables on training and recovery in professional team sport

Context: Exercise in hot environments increases body temperature and thermoregulatory strain. However, little is known regarding the magnitude of effect that ambient temperature (Ta), relative humidity (RH), and solar radiation individually have on team-sport athletes. Purpose: To determine the effect of these individual heat-stress variables on team-sport training performance and recovery. Methods: Professional Australian Rules Football players (N = 45) undertook 8-wk preseason training producing a total of 579 outdoor field-based observations with Ta, RH, and solar radiation recorded at every training session. External load (distance covered, in m/min; percentage high-speed running [%HSR] >14.4 km/h) was collected via a global positioning system. Internal load (ratings of perceived exertion and heart rate) and recovery (subjective ratings of well-being and heart-rate variability [root mean square of the successive differences]) were monitored throughout the training period. Mixed-effects linear models analyzed relationships between variables using standardized regression coefficients. Results: Increased solar-radiation exposure was associated with reduced distance covered (−19.7 m/min, P 85% HRmax (3.9%, P a was associated with increased distance covered (19.7 m/min, P < .001) and %HSR (3.5%, P = .005). Conclusions: The authors show the importance of considering the individual factors contributing to thermal load in isolation for team-sport athletes and that solar radiation and RH reduce work capacity during team-sport training and have the potential to slow recovery between sessions.</p

Potential for improvement of population diet through reformulation of commonly eaten foods

Food reformulation: Reformulation of foods is considered one of the key options to achieve population nutrient goals. The compositions of many foods are modified to assist the consumer bring his or her daily diet more in line with dietary recommendations. Initiatives on food reformulation: Over the past few years the number of reformulated foods introduced on the European market has increased enormously and it is expected that this trend will continue for the coming years. Limits to food reformulation: Limitations to food reformulation in terms of choice of foods appropriate for reformulation and level of feasible reformulation relate mainly to consumer acceptance, safety aspects, technological challenges and food legislation. Impact on key nutrient intake and health: The potential impact of reformulated foods on key nutrient intake and health is obvious. Evaluation of the actual impact requires not only regular food consumption surveys, but also regular updates of the food composition table including the compositions of newly launched reformulated foods

Influenza Excess Mortality from 1950–2000 in Tropical Singapore

10.1371/journal.pone.0008096PLoS ONE412

Effectiveness of Pandemic H1N1-2009 Vaccination in Reducing Laboratory Confirmed Influenza Infections among Military Recruits in Tropical Singapore

10.1371/journal.pone.0026572PLoS ONE610