Anaesthetic impairment of immune function is mediated via GABA(A) receptors.

BACKGROUND: GABA(A) receptors are members of the Cys-loop family of neurotransmitter receptors, proteins which are responsible for fast synaptic transmission, and are the site of action of wide range of drugs. Recent work has shown that Cys-loop receptors are present on immune cells, but their physiological roles and the effects of drugs that modify their function in the innate immune system are currently unclear. We are interested in how and why anaesthetics increase infections in intensive care patients; a serious problem as more than 50% of patients with severe sepsis will die. As many anaesthetics act via GABA(A) receptors, the aim of this study was to determine if these receptors are present on immune cells, and could play a role in immunocompromising patients. PRINCIPAL FINDINGS: We demonstrate, using RT-PCR, that monocytes express GABA(A) receptors constructed of α1, α4, β2, γ1 and/or δ subunits. Whole cell patch clamp electrophysiological studies show that GABA can activate these receptors, resulting in the opening of a chloride-selective channel; activation is inhibited by the GABA(A) receptor antagonists bicuculline and picrotoxin, but not enhanced by the positive modulator diazepam. The anaesthetic drugs propofol and thiopental, which can act via GABA(A) receptors, impaired monocyte function in classic immunological chemotaxis and phagocytosis assays, an effect reversed by bicuculline and picrotoxin. SIGNIFICANCE: Our results show that functional GABA(A) receptors are present on monocytes with properties similar to CNS GABA(A) receptors. The functional data provide a possible explanation as to why chronic propofol and thiopental administration can increase the risk of infection in critically ill patients: their action on GABA(A) receptors inhibits normal monocyte behaviour. The data also suggest a potential solution: monocyte GABA(A) receptors are insensitive to diazepam, thus the use of benzodiazepines as an alternative anesthetising agent may be advantageous where infection is a life threatening problem.

Nash equilibria in multi-agent motor interactions.

Social interactions in classic cognitive games like the ultimatum game or the prisoner's dilemma typically lead to Nash equilibria when multiple competitive decision makers with perfect knowledge select optimal strategies. However, in evolutionary game theory it has been shown that Nash equilibria can also arise as attractors in dynamical systems that can describe, for example, the population dynamics of microorganisms. Similar to such evolutionary dynamics, we find that Nash equilibria arise naturally in motor interactions in which players vie for control and try to minimize effort. When confronted with sensorimotor interaction tasks that correspond to the classical prisoner's dilemma and the rope-pulling game, two-player motor interactions led predominantly to Nash solutions. In contrast, when a single player took both roles, playing the sensorimotor game bimanually, cooperative solutions were found. Our methodology opens up a new avenue for the study of human motor interactions within a game theoretic framework, suggesting that the coupling of motor systems can lead to game theoretic solutions.

Motor coordination: when two have to act as one.

Trying to pass someone walking toward you in a narrow corridor is a familiar example of a two-person motor game that requires coordination. In this study, we investigate coordination in sensorimotor tasks that correspond to classic coordination games with multiple Nash equilibria, such as "choosing sides," "stag hunt," "chicken," and "battle of sexes". In these tasks, subjects made reaching movements reflecting their continuously evolving "decisions" while they received a continuous payoff in the form of a resistive force counteracting their movements. Successful coordination required two subjects to "choose" the same Nash equilibrium in this force-payoff landscape within a single reach. We found that on the majority of trials coordination was achieved. Compared to the proportion of trials in which miscoordination occurred, successful coordination was characterized by several distinct features: an increased mutual information between the players' movement endpoints, an increased joint entropy during the movements, and by differences in the timing of the players' responses. Moreover, we found that the probability of successful coordination depends on the players' initial distance from the Nash equilibria. Our results suggest that two-person coordination arises naturally in motor interactions and is facilitated by favorable initial positions, stereotypical motor pattern, and differences in response times.

Development and evaluation of an alternative method for processing elastic-lidar return signals

A method for interpreting elastic-lidar return signals in heavily-polluted atmospheres is presented. It is based on an equation derived directly from the classic lidar equation, which highlights gradients of the atmospheric backscattering properties along the laser optical path. The method is evaluated by comparing its results with those obtained with the differential absorption technique. The results were obtained from locating and ranging measurements in pollutant plumes and contaminated environments around central México. © World Scientific Publishing Company.

Construction of nonparametric Bayesian models from parametric Bayes equations

We consider the general problem of constructing nonparametric Bayesian models on infinite-dimensional random objects, such as functions, infinite graphs or infinite permutations. The problem has generated much interest in machine learning, where it is treated heuristically, but has not been studied in full generality in non-parametric Bayesian statistics, which tends to focus on models over probability distributions. Our approach applies a standard tool of stochastic process theory, the construction of stochastic processes from their finite-dimensional marginal distributions. The main contribution of the paper is a generalization of the classic Kolmogorov extension theorem to conditional probabilities. This extension allows a rigorous construction of nonparametric Bayesian models from systems of finite-dimensional, parametric Bayes equations. Using this approach, we show (i) how existence of a conjugate posterior for the nonparametric model can be guaranteed by choosing conjugate finite-dimensional models in the construction, (ii) how the mapping to the posterior parameters of the nonparametric model can be explicitly determined, and (iii) that the construction of conjugate models in essence requires the finite-dimensional models to be in the exponential family. As an application of our constructive framework, we derive a model on infinite permutations, the nonparametric Bayesian analogue of a model recently proposed for the analysis of rank data.

Sensor data scheduling for linear quadratic Gaussian control with full state feedback

Networked control systems (NCSs) have attracted much attention in the past decade due to their many advantages and growing number of applications. Different than classic control systems, resources in NCSs, such as network bandwidth and communication energy, are often limited, which degrade the closed-loop system performance and may even cause the system to become unstable. Seeking a desired trade-off between the closed-loop system performance and the limited resources is thus one heated area of research. In this paper, we analyze the trade-off between the sensor-to-controller communication rate and the closed-loop system performance indexed by the conventional LQG control cost. We present and compare several sensor data schedules, and demonstrate that two event-based sensor data schedules provide better trade-off than an optimal offline schedule. Simulation examples are provided to illustrate the theories developed in the paper. © 2012 AACC American Automatic Control Council).

Comparison of the coherence properties of superradiance and laser emission in semiconductor structures

The coherence properties of a transient electron-hole state developing during superradiance emission in semiconductor laser structures have been studied experimentally using a Michelson interferometer and Young's classic double-slit configuration. The results demonstrate that, in the lasers studied, the first-order correlation function, which quantifies spatial coherence, approaches unity for superradiant emission and is 0.2-0.5 for laser emission. The supercoherence is due to long-range ordering upon the superradiant phase transition. © 2012 Kvantovaya Elektronika and Turpion Ltd.

No evidence for an item limit in change detection.

Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

Pneumatic and hydraulic microactuators: A review

The development of MEMS actuators is rapidly evolving and continuously new progress in terms of efficiency, power and force output is reported. Pneumatic and hydraulic are an interesting class of microactuators that are easily overlooked. Despite the 20 years of research, and hundreds of publications on this topic, these actuators are only popular in microfluidic systems. In other MEMS applications, pneumatic and hydraulic actuators are rare in comparison with electrostatic, thermal or piezo-electric actuators. However, several studies have shown that hydraulic and pneumatic actuators deliver among the highest force and power densities at microscale. It is believed that this asset is particularly important in modern industrial and medical microsystems, and therefore, pneumatic and hydraulic actuators could start playing an increasingly important role. This paper shows an in-depth overview of the developments in this field ranging from the classic inflatable membrane actuators to more complex piston-cylinder and drag-based microdevices. © 2010 IOP Publishing Ltd.

Design and characteristion of a hydraulic microactuator fabricated by lithography

To improve the force output of microactuators, this work focuses on actuators driven by pressurized gasses or liquids. Despite their well known ability to generate high actuation forces, hydraulic actuators remain uncommon in microsystems. This is both due to the difficulty of fabricating these microactuators with the existing micromachining processes and to the lack of adequate microseals. This paper describes how to overcome these limitations with a combination of anisotropic micromachining, UV definable polymers and low temperature bonding. The functionality of these actuators is proven by extensive measurements which showed that actuation forces of 0.1 N can be achieved for actuators with an active cross-section of 0.15 mm2. This is an order of magnitude higher than what is reported for classic MEMS actuators of similar size.

Electrorheologic liquid crystals in microsystems: model and measurements

Fluids with a controllable viscosity gained a lot of interest throughout the last years. One of the advantages of these fluids is that they allow to fabricate hydraulic components such as valves with a very simple structure. Although the properties of these fluids are very interesting for microsystems, their applicability is limited at microscale since the particles suspended in these fluids tend to obstruct microchannels. This paper investigates the applicability of electrorheologic Liquid Crystals (LCs) in microsystems. Since LC's do not contain suspended particles, they show intrinsic advantages over classic rheologic active fluids in microapplications. As a matter of fact, LC molecules are usually only a few nanometers long, and therefore, they can probably be used in systems with sub-micrometer channels or other nanoscale applications. This paper presents a novel model describing the electrorheologic behavior of these nanoscale molecules. This model is used to simulate a microvalve controlled by LC's. By comparing measurements and simulations performed on this microvalve it is possible to prove that the model developed in this paper is very accurate. In addition, these simulations and measurements revealed other remarkable properties of LC's, such as high bandwidths and high changes in flow resistance. © 2006 IEEE.

The use of liquid crystals as electrorheological fluids in microsystems: Model and measurements

Fluids with controllable flow properties have gained considerable interest in the past few years. Some of these fluids such as magnetorheologic fluids are now widely applied to active dampers and valves. Although these fluids show promising properties for microsystems, their applicability is limited to the microscale since particles suspended in these fluids tend to obstruct microchannels. This paper investigates the applicability of electrorheologic liquid crystals (LCs) in microsystems. Since LCs do not contain suspended particles, they show intrinsic advantages over classic rheologic fluids in micro-applications. This paper presents a novel physical model that describes the static and the dynamic behaviour of electrorheologic LCs. The developed model is validated by comparing simulations and measurements performed on a rectangular microchannel. This assessment shows that the model presented in this paper is able to simulate both static and dynamic properties accurately. Therefore, this model is useful for the understanding, simulation and optimization of devices using LCs as electrorheological fluid. In addition, measurements performed in this paper reveal remarkable properties of LCs, such as high bandwidths and high changes in flow resistance. © 2006 IOP Publishing Ltd.

Cortical substrates for exploratory decisions in humans.

Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration-exploitation' dilemma, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.