The lateral intraparietal area codes the location of saccade targets and not the dimension of the saccades that will be made to acquire them.

Activity in the lateral intraparietal area (LIP) represents a priority map that can be used to direct attention and guide eye movements. However, it is not known whether this activity represents the location of saccade targets or the actual eye movement made to acquire them. We recorded single neurons from rhesus macaques (Macaca mulatta) while they performed memory-guided delayed saccades to characterize the response profiles of LIP cells. We then separated the saccade target from the saccade end point by saccadic adaptation, a method that induces a change in the gain of the oculomotor system. We plotted LIP activity for all three epochs of the memory-guided delayed-response task (visual, delay period, and presaccadic responses) as a function of target location and saccade end point. We found that under saccadic adaptation the response profile for all three epochs was unchanged as a function of target location. We conclude that neurons in LIP reliably represent the locations of saccade targets, not the amplitude of the saccade required to acquire those targets. Although LIP transmits target information to the motor system, that information represents the location of the target and not the amplitude of the saccade that the monkey will make.

Setting the Standard: Using the ABA Burn Registry to Benchmark Risk Adjusted Mortality.

Reports of single center experience and studies of larger databases have identified several predictors of burn center mortality, including age, burn size, and inhalation injury. None of these analyses has been broad enough to allow benchmarking across burn centers. The purpose of this study was to derive a reliable, risk-adjusted, statistical model of mortality based on real-life experience at many burn centers in the U.S. We used the American Burn Association 2020 Full Burn Research Dataset, from the Burn Center Quality Platform (BCQP) to identify 130,729 subjects from July 2015 through June 2020 across 103 unique burn centers. We selected 22 predictor variables, from over 50 recorded in the dataset, based on completeness (at least 75% complete required) and clinical significance. We used gradient-boosted regression, a form of machine learning, to predict mortality and compared this to traditional logistic regression. Model performance was evaluated with AUC and PR curves. The CatBoost model achieved a test AUC of 0.980 with an average precision of 0.800. The logistic regression produced an AUC of 0.951 with an average precision of 0.664. While AUC, the measure most reported in the literature, is high for both models, the CatBoost model is markedly more sensitive, leading to a substantial improvement in precision. Using BCQP data, we can predict burn mortality allowing comparison across burn centers participating in BCQP.

Using a National Burn Registry to Develop a Model for Risk-Adjusted Length of Stay Benchmarking.

Length of stay (LOS) is a frequently reported outcome after a burn injury. LOS benchmarking will benefit individual burn centers as a way to measure their performance and set expectations for patients. We sought to create a nationwide, risk-adjusted model to allow for LOS benchmarking based on the data from a national burn registry. Using data from the American Burn Association's Burn Care Quality Platform, we queried admissions from 7/2015 to 6/2020 and identified 130,729 records reported by 103 centers. Using 22 predictor variables, comparisons of unpenalized linear regression and Gradient boosted (CatBoost) regressor models were performed by measuring the R2 and concordance correlation coefficient on the application of the model to the test dataset. The CatBoost model applied to the bootstrapped versions of the entire dataset was used to calculate O/E ratios for individual burn centers. Analyses were run on 3 cohorts: all patients, 10-20% TBSA, >20% TBSA. The CatBoost model outperformed the linear regression model with a test R2 of 0.67 and CCC of 0.81 compared with the linear model with R2=0.50, CCC=0.68. The CatBoost was also less biased for higher and lower LOS durations. Gradient-boosted regression models provided greater model performance than traditional regression analysis. Using national burn data, we can predict LOS across contributing burn centers while accounting for patient and center characteristics, producing more meaningful O/E ratios. These models provide a risk-adjusted LOS benchmarking using a robust data source, the first of its kind, for burn centers.

The dependence of visual scanning performance on saccade, fixation, and perceptual metrics.

We sought to understand the basis of performance variability and perceptual learning in saccadic visual search. Four subjects searched for a target based on its shape in a linear array of densely packed, regularly spaced items, a configuration used to simplify the analysis of performance and to minimize search strategy variability. We measured the dependence of performance-search speed-on the oculomotor variables of fixation duration and saccade amplitude, both within and across experimental sessions. We also measured perceptual span, the area in visual space in which subjects could identify the target above chance, with a modified version of the task using a gaze-contingent display with transiently appearing targets. The principal finding of this study was that both within and across sessions, saccade metrics accounted for much more of the variability and improvement in performance than did fixation duration. Increases in search speed were due primarily to subjects processing information from a greater area of the visual field, rather than processing information from a fixed area more quickly, though there was a small but consistent decrease in fixation duration across sessions. The increase in performance derived from an increase in perceptual span and not merely from an increase in subjects' efficiency in 'tiling' the search array with regions of visibility.

The dependence of visual scanning performance on search direction and difficulty.

Phillips and Edelman [Phillips, M. H., & Edelman, J. A. (2008). The dependence of visual scanning performance on saccade, fixation, and perceptual metrics. Vision Research, 48(7), 926-936] presented evidence that performance variability in a visual scanning task depends on oculomotor variables related to saccade amplitude rather than fixation duration, and that saccade-related metrics reflects perceptual span. Here, we extend these results by showing that even for extremely difficult searches trial-to-trial performance variability still depends on saccade-related metrics and not fixation duration. We also show that scanning speed is faster for horizontal than for vertical searches, and that these differences derive again from differences in saccade-based metrics and not from differences in fixation duration. We find perceptual span to be larger for horizontal than vertical searches, and approximately symmetric about the line of gaze.