The incidence of unacceptable movement with motor evoked potentials during craniotomy for aneurysm clipping.

OBJECTIVE: To review the experience at a single institution with motor evoked potential (MEP) monitoring during intracranial aneurysm surgery to determine the incidence of unacceptable movement. METHODS: Neurophysiology event logs and anesthetic records from 220 craniotomies for aneurysm clipping were reviewed for unacceptable patient movement or reason for cessation of MEPs. Muscle relaxants were not given after intubation. Transcranial MEPs were recorded from bilateral abductor hallucis and abductor pollicis muscles. MEP stimulus intensity was increased up to 500 V until evoked potential responses were detectable. RESULTS: Out of 220 patients, 7 (3.2%) exhibited unacceptable movement with MEP stimulation-2 had nociception-induced movement and 5 had excessive field movement. In all but one case, MEP monitoring could be resumed, yielding a 99.5% monitoring rate. CONCLUSIONS: With the anesthetic and monitoring regimen, the authors were able to record MEPs of the upper and lower extremities in all patients and found only 3.2% demonstrated unacceptable movement. With a suitable anesthetic technique, MEP monitoring in the upper and lower extremities appears to be feasible in most patients and should not be withheld because of concern for movement during neurovascular surgery.

Bayesian Emulation for Sequential Modeling, Inference and Decision Analysis

The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

Usage analysis of tier 2 public computers: Perkins & Bostock libraries first floor - May 2016

A spring 2016 report about public computer usage on the first floor of Perkins and Bostock libraries. This report includes data from survey questions, an observational study, and transaction logs. The report also includes recommendations for changes based on the data collected.