Electroencephalographic Measures of Delirium in the Perioperative Setting: A Systematic Review.

Postoperative delirium (POD) is frequent in older adults and is associated with adverse cognitive and functional outcomes. In the last several decades, there has been an increased interest in exploring tools that easily allow the early recognition of patients at risk of developing POD. The electroencephalogram (EEG) is a widely available tool used to understand delirium pathophysiology, and its use in the perioperative setting has grown exponentially, particularly to predict and detect POD.

Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias.

The clock drawing test (CDT) is a neuropsychological assessment tool to screen an individual's cognitive ability. In this study, we developed a Fair and Interpretable Representation of Clock drawing test (FaIRClocks) to evaluate and mitigate classification bias against people with less than 8 years of education, while screening their cognitive function using an array of neuropsychological measures. In this study, we represented clock drawings by a priorly published 10-dimensional deep learning feature set trained on publicly available data from the National Health and Aging Trends Study (NHATS).

FaIRClocks: Fair and Interpretable Representation of the Clock Drawing Test for mitigating classifier bias against lower educational groups.

The clock drawing test (CDT) is a neuropsychological assessment tool to evaluate a patient's cognitive ability. In this study, we developed a ir and nterpretable epresentation of drawing tests () to evaluate and mitigate bias against people with lower education while predicting their cognitive status. We represented clock drawings with a 10-dimensional latent embedding using Relevance Factor Variational Autoencoder (RF-VAE) network pretrained on publicly available clock drawings from the National Health and Aging Trends Study (NHATS) dataset.

Metacognition and Causal Inference in Audiovisual Speech.

In multisensory environments, our brains perform causal inference to estimate which sources produce specific sensory signals. Decades of research have revealed the dynamics which underlie this process of causal inference for multisensory (audiovisual) signals, including how temporal, spatial, and semantic relationships between stimuli influence the brain's decision about whether to integrate or segregate. However, presently, very little is known about the relationship between metacognition and multisensory integration, and the characteristics of perceptual confidence for audiovisual signals.