Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that describes our (lack of) knowledge on its value, and model the effects of this uncertainty on EEG recordings with the help of an additive error term in the observation model. Before the Bayesian inference, the likelihood is marginalized over this error term. Thus, in the inversion we estimate only our primary unknown, the source distribution. We quantified the improvements in the source localization when the proposed Bayesian modelling was used in the presence of different skull conductivity errors and levels of measurement noise. Based on the results, BAE was able to improve the source localization accuracy, particularly when the unknown (true) skull conductivity was much lower than the expected standard conductivity value. The source locations that gained the highest improvements were shallow and originally exhibited the largest localization errors. In our case study, the benefits of BAE became negligible when the signal-to-noise ratio dropped to 20 dB.</p

Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability

The N-methyl-D -aspartate antagonist memantine has no neuroprotective effect during hypothermic circulatory arrest: A study in the chronic porcine model

AbstractBackground: Glutamate excitotoxicity has an important role in the development of brain injury after prolonged hypothermic circulatory arrest. The goal of the present study was to determine the potential efficacy of memantine, an N -methyl-D -aspartate receptor antagonist, to mitigate cerebral injury after hypothermic circulatory arrest. Methods: Twenty pigs (23-33 kg) were randomly assigned to receive memantine (5 mg/kg) or placebo in a blinded fashion before a 75-minute period of hypothermic circulatory arrest at 20°C. Hemodynamic, electroencephalographic, and metabolic monitoring were carried out. The intracerebral concentrations of glucose, lactate, glutamate, and glycerol were measured by means of enzymatic methods on a microdialysis analyzer. Daily behavioral assessment was performed until the animals died or were put to death on day 7. Histologic analysis of the brain was carried out in all animals. Results: In the memantine group, 5 of 10 animals survived 7 days compared with 9 of 10 in the placebo group. The median behavioral score at day 7 was 3.5 in the memantine group and 7.5 in the placebo group (P >.2). Among the surviving animals, medians were 9.0 and 8.0 on day 7 (P >.2), respectively. The medians of recovered electroencephalographic bursts were equal in both groups. The median of total histopathologic score was 16 in the memantine group and 14 in the placebo group (P >.2). There was a negative correlation between glutamate levels and electroencephalographic burst recovery (τ = –0.377, P =.043). A positive correlation was found between the highest individual glutamate value and histopathologic score (τ = 0.336, P =.045). Conclusions: The present study demonstrates that memantine has no neuroprotective effect after hypothermic circulatory arrest in the pig. In addition, we have shown the accuracy of cerebral glutamate measurements to predict histopathologic injury after hypothermic ischemia. (J Thorac Cardiovasc Surg 2001;121:957-70

Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity

textabstractElectroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that describes our (lack of) knowledge on its value, and model the effects of this uncertainty on EEG recordings with the help of an additive error term in the observation model. Before the Bayesian inference, the likelihood is marginalized over this error term. Thus, in the inversion we estimate only our primary unknown, the source distribution. We quantified the improvements in the source localization when the proposed Bayesian modelling was used in the presence of different skull conductivity errors and levels of measurement noise. Based on the results, BAE was able to improve the source localization accuracy, particularly when the unknown (true) skull conductivity was much lower than the expected standard conductivity value. The source locations that gained the highest improvements were shallow and originally exhibited the largest localization errors. In our case study, the benefits of BAE became negligible when the signal-to-noise ratio dropped to 20 dB

Prolonged mild hypothermia after experimental hypothermic circulatory arrest in a chronic porcine model

AbstractObjectives: We sought to evaluate the potential efficacy of prolonged mild hypothermia after hypothermic circulatory arrest. Methods: Twenty pigs, after a 75-minute period of hypothermic circulatory arrest, were randomly assigned to be rewarmed to 37°C (normothermia group) or to 32°C and kept at that temperature for 14 hours from the start of rewarming (hypothermia group). Results: The 7-day survival was 30% in the hypothermia group and 70% in the normothermia group (P =.08). The hypothermia group had poorer postoperative behavioral scores than the normothermia group. Prolonged hypothermia was associated with lower oxygen extraction and consumption rates and higher mixed venous oxygen saturation levels during the first hours after hypothermic circulatory arrest. Decreased cardiac index, lower pH, and higher partial pressure of carbon dioxide were observed in the hypothermia group. There was a trend for beneficial effect of prolonged hypothermia in terms of lower brain lactate levels until the 4-hour interval and of intracranial pressure until the 10-hour interval. Postoperatively, total leukocyte and neutrophil counts were lower, and creatine kinase BB was significantly increased in the hypothermia group. At extubation, the hypothermia group had higher oxygen extraction rates and lower brain tissue oxygen tension. Conclusions: A 14-hour period of mild hypothermia after 75-minute hypothermic circulatory arrest seems to be associated with poor outcome. However, the results of this study suggest that mild hypothermia may preserve its efficacy when it is used for no longer than 4 hours, but the potentials of a shorter period of postoperative mild hypothermia still require further investigation.J Thorac Cardiovasc Surg 2002;123:724-3

Effects of Warehouse Automation in Hospital Medication Supply Chain

This thesis examines the effects of technology and automation investments on the operational performance of hospital pharmacies. Until recently the hospital medication distribution and warehousing in Finland has largely relied on manual work and level of automation has remained low. During the last five years several hospitals and hospital pharmacies have made significant investments for electric medicine cabinets and picking and storage robotics. However, the studies on the effects of these investments remain limited. This thesis tries to fill this research gap, aiming to study that do the technology investments meet the stated objectives. The research focuses on hospital medication distribution; the flow of finished medicinal products from pharmaceutical factories to health care professionals and their patients. Hospital pharmacies are in a key role in this distribution network, acting as centralized warehouse and distribution hub. This thesis focuses on recognizing the key drivers for medication administration technologies investments in hospital pharmacies and on analysing the effects of picking and storage robotics on hospital pharmacy’s warehouse processes and performance. Based on the literature review on pharmaceutical supply chain management and warehouse performance evaluation, a framework for analyzing effects of the picking and storage robot implementation is created. The balanced approach includes three different perspectives with seven performance indicators: cost per order dispatched, medicine loss rate, inventory turnover, dispensing error rate, orders shipped on time, labour productivity and ward pharmacy services’ share of total working hours. The empirical part consists of a quantitative analysis of a specific case of introducing picking and storage robotics to HUS Pharmacy central warehouse in 2015. The study is conducted as before-after analysis, comparing the indicator values before and after the investment (2014-2017). Main drivers for the analysed picking and storage robot investment were to enhance medication safety via automated processes, bring personnel cost savings due to reduction of manual work and free pharmacists’ time for clinical pharmacy work. The findings imply that the investment has at least partially met these objectives. The main finding is that the introduction of the picking and storage robot seems to have increased the labour productivity by 15% through the automatization of manual tasks in the receiving, storage and picking phases of the HUS Pharmacy warehouse process. This increase in labour productivity enables cost savings, which can be realized either by cutting personnel or refocusing personnel time for more valuable tasks