Why experimental variation in neuroimaging should be embraced.

In a perfect world, scientists would develop analyses that are guaranteed to reveal the ground truth of a research question. In reality, there are countless viable workflows that produce distinct, often conflicting, results. Although reproducibility places a necessary bound on the validity of results, it is not sufficient for claiming underlying validity, eventual utility, or generalizability.

The potential of gene drives in malaria vector species to control malaria in African environments.

Gene drives are a promising means of malaria control with the potential to cause sustained reductions in transmission. In real environments, however, their impacts will depend on local ecological and epidemiological factors. We develop a data-driven model to investigate the impacts of gene drives that causes vector population suppression.

Predicting Task Activation Maps from Resting-State Functional Connectivity using Deep Learning.

Recent work has shown that deep learning is a powerful tool for predicting brain activation patterns evoked through various tasks using resting state features. We replicate and improve upon this recent work to introduce two models, BrainSERF and BrainSurfGCN, that perform at least as well as the state-of-the-art while greatly reducing memory and computational footprints. Our performance analysis observed that low predictability was associated with a possible lack of task engagement derived from behavioral performance.

Cognitive tasks, anatomical MRI, and functional MRI data evaluating the construct of self-regulation.

We describe the following shared data from N = 103 healthy adults who completed a broad set of cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting state fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions.

Implementation of a Self-Audit Tool Improves Regulatory Compliance for Point-of-Care Respiratory Virus Testing in the Emergency Department.

Background: Point-of-care testing in the emergency department decreases wait times and supports evidence-based patient care. However, hurdles to successful implementation include management of interdisciplinary work flows and establishment of an effective quality control program. As COVID-19 testing is now integrated into screening protocols in emergency and urgent care settings, hospital systems must maintain flexible and adaptable respiratory virus testing to adapt to regional trends in transmission.