Quantitative Electroencephalography (EEG) Predicting Acute Neurologic Deterioration in the Pediatric Intensive Care Unit: A Case Series.

Introduction: Continuous neurologic assessment in the pediatric intensive care unit is challenging. Current electroencephalography (EEG) guidelines support monitoring status epilepticus, vasospasm detection, and cardiac arrest prognostication, but the scope of brain dysfunction in critically ill patients is larger. We explore quantitative EEG in pediatric intensive care unit patients with neurologic emergencies to identify quantitative EEG changes preceding clinical detection. Methods: From 2017 to 2020, we identified pediatric intensive care unit patients at a single quaternary children's hospital with EEG recording near or during acute neurologic deterioration. Quantitative EEG analysis was performed using Persyst P14 (Persyst Development Corporation). Included features were fast Fourier transform, asymmetry, and rhythmicity spectrograms, "from-baseline" patient-specific versions of the above features, and quantitative suppression ratio. Timing of quantitative EEG changes was determined by expert review and prespecified quantitative EEG alert thresholds. Clinical detection of neurologic deterioration was defined pre hoc and determined through electronic medical record documentation of examination change or intervention. Results: Ten patients were identified, age 23 months to 27 years, and 50% were female. Of 10 patients, 6 died, 1 had new morbidity, and 3 had good recovery; the most common cause of death was cerebral edema and herniation. The fastest changes were on "from-baseline" fast Fourier transform spectrograms, whereas persistent changes on asymmetry spectrograms and suppression ratio were most associated with morbidity and mortality. Median time from first quantitative EEG change to clinical detection was 332 minutes (interquartile range: 201-456 minutes). Conclusion: Quantitative EEG is potentially useful in earlier detection of neurologic deterioration in critically ill pediatric intensive care unit patients. Further work is required to quantify the predictive value, measure improvement in outcome, and automate the process.

Spatial updating in human parietal cortex.

Single neurons in monkey parietal cortex update visual information in conjunction with eye movements. This remapping of stimulus representations is thought to contribute to spatial constancy. We hypothesized that a similar process occurs in human parietal cortex and that we could visualize it with functional MRI. We scanned subjects during a task that involved remapping of visual signals across hemifields. We observed an initial response in the hemisphere contralateral to the visual stimulus, followed by a remapped response in the hemisphere ipsilateral to the stimulus. We ruled out the possibility that this remapped response resulted from either eye movements or visual stimuli alone. Our results demonstrate that updating of visual information occurs in human parietal cortex.

Straight to the Source: Detecting Aggregate Objects in Astronomical Images with Proper Error Control.

The next generation of telescopes, coming on-line in the next decade, will acquire terabytes of image data each night. Collectively, these large images will contain billions of interesting objects, which astronomers call sources. One critical task for astronomers is to construct from the image data a detailed source catalog that gives the sky coordinates and other properties of all detected sources. The source catalog is the primary data product produced by most telescopes and serves as an important input for studies that build and test new astrophysical theories. To construct an accurate catalog, the sources must first be detected in the image. A variety of effective source detection algorithms exist in the astronomical literature, but few if any provide rigorous statistical control of error rates. A variety of multiple testing procedures exist in the statistical literature that can provide rigorous error control over pixelwise errors, but these do not provide control over errors at the level of sources, which is what astronomers need. In this paper, we propose a technique that is effective at source detection while providing rigorous control on source-wise error rates. We demonstrate our approach with data from the Chandra X-ray Observatory Satellite. Our method is competitive with existing astronomical methods, even finding two new sources that were missed by previous studies, while providing stronger performance guarantees and without requiring costly follow up studies that are commonly required with current techniques.

Remapping in human visual cortex.

With each eye movement, stationary objects in the world change position on the retina, yet we perceive the world as stable. Spatial updating, or remapping, is one neural mechanism by which the brain compensates for shifts in the retinal image caused by voluntary eye movements. Remapping of a visual representation is believed to arise from a widespread neural circuit including parietal and frontal cortex. The current experiment tests the hypothesis that extrastriate visual areas in human cortex have access to remapped spatial information. We tested this hypothesis using functional magnetic resonance imaging (fMRI). We first identified the borders of several occipital lobe visual areas using standard retinotopic techniques. We then tested subjects while they performed a single-step saccade task analogous to the task used in neurophysiological studies in monkeys, and two conditions that control for visual and motor effects. We analyzed the fMRI time series data with a nonlinear, fully Bayesian hierarchical statistical model. We identified remapping as activity in the single-step task that could not be attributed to purely visual or oculomotor effects. The strength of remapping was roughly monotonic with position in the visual hierarchy: remapped responses were largest in areas V3A and hV4 and smallest in V1 and V2. These results demonstrate that updated visual representations are present in cortical areas that are directly linked to visual perception.

Thresholding of statistical maps in functional neuroimaging using the false discovery rate.

Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a long-standing problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures for multiple hypothesis testing (e.g., Bonferroni) tend to not be sensitive enough to be useful in this context. This paper introduces to the neuroscience literature statistical procedures for controlling the false discovery rate (FDR). Recent theoretical work in statistics suggests that FDR-controlling procedures will be effective for the analysis of neuroimaging data. These procedures operate simultaneously on all voxelwise test statistics to determine which tests should be considered statistically significant. The innovation of the procedures is that they control the expected proportion of the rejected hypotheses that are falsely rejected. We demonstrate this approach using both simulations and functional magnetic resonance imaging data from two simple experiments.