Monte Carlo methods are revolutionizing the on-line analysis of data in fields as diverse as financial modeling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survival of the fittest, have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modeling, neural networks, optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practitioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris-XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning. Neil Gordon obtained a Ph.D. in Statistics from Imperial College, University of London in 1993. He is with the Pattern and Information Processing group at the Defence Evaluation and Research Agency in the United Kingdom. His research interests are in time series, statistical data analysis, and pattern recognition with a particular emphasis on target tracking and missile guidance.

/pdf/sequential-monte-carlo-methods-in-practice-3kfxeebn8e.pdf

Sequential Monte Carlo methods in practice

Information Theory and Reliable Communication

Population-based epidemiologic studies have uncovered the high prevalence and wide severity spectrum of undiagnosed obstructive sleep apnea, and have consistently found that even mild obstructive sleep apnea is associated with significant morbidity. Evidence from methodologically strong cohort studies indicates that undiagnosed obstructive sleep apnea, with or without symptoms, is independently associated with increased likelihood of hypertension, cardiovascular disease, stroke, daytime sleepiness, motor vehicle accidents, and diminished quality of life. Strategies to decrease the high prevalence and associated morbidity of obstructive sleep apnea are critically needed. The reduction or elimination of risk factors through public health initiatives with clinical support holds promise. Potentially modifiable risk factors considered in this review include overweight and obesity, alcohol, smoking, nasal congestion, and estrogen depletion in menopause. Data suggest that obstructive sleep apnea is associated with all these factors, but at present the only intervention strategy supported with adequate evidence is weight loss. A focus on weight control is especially important given the expanding epidemic of overweight and obesity in the United States. Primary care providers will be central to clinical approaches for addressing the burden and the development of cost-effective case-finding strategies and feasible treatment for mild obstructive sleep apnea warrants high priority.

Epidemiology of obstructive sleep apnea: a population health perspective.

International classification of sleep disorders-third edition: highlights and modifications.

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

https://www.zora.uzh.ch/id/eprint/77770/1/physiol_rev_93.pdf

About sleep's role in memory


 
 
 Hypnotics continue to be preferentially used in practice for the treatment of chronic insomnia, yet the comparative safety and efficacy of medication options are unclear. While several position statements and network meta-analyses have provided some guidance, none have provided a quantitative assessment of risk-benefit. In the present analysis, each therapeutic class commonly used for chronic insomnia is quantitatively ranked with respect to safety, efficacy, and risk-benefit.
 
 
 
 Safety data for FDA-approved hypnotics were extracted from the package insert adverse event tables and standardized to form a placebo-adjusted adverse event rate per 1000 (AEr). Efficacy data were extracted from randomized controlled trials identified in professional society position statements and published systematic reviews. The efficacy metric was computed from placebo adjusted pre-post change scores for self-reported sleep continuity (i.e., sleep latency [SL], wake after sleep onset [WASO], and total sleep time [TST]) and represented as a summed composite effect size score (SWT). Risk-benefit (R/B) was represented as a ratio between AEr and SWT. Comparative safety, efficacy, and risk-benefit metrics were calculated for five therapeutic classes: Benzodiazepines (BZs), non-benzodiazepine benzodiazepine receptor agonists (BZRAs), dual orexin receptor antagonists (DORAs), melatonin receptor agonists (MELAs), and sedating antidepressants (SADs).
 
 
 
 With respect to safety, MELAs had the lowest adverse event rate (AEr=43.1) and BZRAs had the highest rate (AEr=255.0). With respect to efficacy, BZs were the most efficacious (SWT=1.94, Mean ES=0.59) and MELAs were least efficacious (SWT=0.11, Mean ES=0.02). Overall, with respect to risk-benefit, SADs had the most favorable profile (R/B=69.5), while MELAs had the least favorable profile (R/B=395.7).
 
 
 
 The optimal selection of hypnotics requires consideration of both risk and benefit. Findings suggest that SADs can be considered the first-line pharmacotherapeutic option due to the superior risk-benefit profile. If treatment responses are inadequate or if SADs are contraindicated, risk-benefit rankings may serve as a decision tree as part of a medical algorithm protocol to guide treatment selection for patients with chronic insomnia.
 
 
 
 Sleep Research Society Mentor-Mentee Award (Cheung); K24AG055602 & R01AG054521 (Perlis)


0456 Comparative Safety and Efficacy of Hypnotics: A Quantitative Risk-Benefit Analysis

Effect Of Armodafinil On Cortical Activity And Working Memory In Patients With Residual Excessive Sleepiness Associated With CPAP-Treated OSA: A Multicenter FMRI Study

Nocturnal Dexmedetomidine in Nonintubated, Critically Ill Patients: Sleep or Sedation?

Spatiotemporal dynamic analysis of electroconvulsive therapy seizures

Principles and Practice of Geriatric Sleep Medicine: Geriatric psychopharmacology: an overview

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