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The British Journal of Anaesthesia organisation is a registered charity comprised of two interlinked missions: provision of impactful publications and funding the generation and dissemination of research to the wider anaesthetic community. This centenary editorial highlights our charitable activity that covers funding of research infrastructure, meeting support and funding of a diverse portfolio of international research grants. [ABSTRACT FROM AUTHOR]

Closed-loop systems are able to make their own decisions and to try to reach and maintain a preset target. As a result, they might help the anaesthetist to optimise the titration of drug administration without any overshoot, controlling physiological functions and guiding monitoring variables. Thanks to the development of fast computer technology and more reliable pharmacological effect measures, the study of automation in anaesthesia has regained popularity. This short review focuses on the most recently developed and tested feedback systems in anaesthesia. Various new approaches for controlling the administration of intravenous and inhaled hypnotic–anaesthetic drugs have recently been published. For analgesics, a framework for further research has been presented in the literature. For other drugs, such as muscle relaxants and haemodynamic agents, only short reviews can be found. Until now, most of these systems have had to be under development. The challenge is now fully to establish the safety, efficacy, reliability and utility of closed-loop anaesthesia so that it can be adopted in the clinical setting. Besides, their role in optimising the controlled variables and control models, these systems have to be tested in extreme circumstances in order to test their robustness. [Copyright &y& Elsevier]

Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain states using the unscented Kalman filter applied to estimate parameters of the Jansen–Rit cortical population model is evaluated through the application of propofol-based anesthetic state monitoring. In particular, 15 subjects underwent propofol anesthesia induction from awake to anesthetised while behavioral responsiveness was monitored and frontal electroencephalographic signals were recorded. The unscented Kalman filter Jansen–Rit model approach applied to frontal electroencephalography achieved reasonable testing performance for classification of the anesthetic brain state (sensitivity: 0.51; chance sensitivity: 0.17; nearest neighbor sensitivity 0.75) when compared to approaches based on linear (autoregressive moving average) modeling (sensitivity 0.58; nearest neighbor sensitivity: 0.91) and a high performing standard depth of anesthesia monitoring measure, Higuchi Fractal Dimension (sensitivity: 0.50; nearest neighbor sensitivity: 0.88). Moreover, it was found that the unscented Kalman filter based parameter estimates of the inhibitory postsynaptic potential amplitude varied in the physiologically expected direction with increases in propofol concentration, while the estimates of the inhibitory postsynaptic potential rate constant did not. These results combined with analysis of monotonicity of parameter estimates, error analysis of parameter estimates, and observability analysis of the Jansen–Rit model, along with considerations of extensions of the Jansen–Rit model, suggests that the Jansen–Rit model combined with unscented Kalman filtering provides a valuable reference point for future real-time brain state tracking studies. This is especially true for studies of more complex, but still computationally efficient, neural models of anesthesia that can more accurately track the anesthetic brain state, while simultaneously inferring underlying physiological changes that can potentially provide useful clinical information. [ABSTRACT FROM AUTHOR]