Relating Human Error-Based Learning to Modern Deep RL Algorithms.

In human error-based learning, the size and direction of a scalar error (i.e., the "directed error") are used to update future actions.

Meckel's diverticulectomy: a multi-centre 19-year retrospective study.

Background: Meckels diverticulum (MD) causes a number of acute surgical pathologies and can contain ectopic tissue with the surgical aim to resect all ectopic mucosa. This has traditionally implied a small bowel resection (BR); though contemporary literature has demonstrated Meckel's diverticulectomy to be safe. The aim of this study was to determine optimal resection strategy, and assess MD histopathological features and their relationship to outcomes.

Mask wearing in community settings reduces SARS-CoV-2 transmission.

The effectiveness of mask wearing at controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been unclear. While masks are known to substantially reduce disease transmission in healthcare settings [D. K.

To stitch or not to stitch: the skin closure of laparoscopic port sites, a meta-analysis.

Background: Previous meta-analyses examining skin closure methods for all surgical wounds have found suture to have significantly decreased rates of wound dehiscence compared to tissue adhesive; however, this was not specific to laparoscopic wounds alone. This study aims to determine the best method of skin closure in patients undergoing laparoscopic abdominopelvic surgery in order to minimize wound complications and pain, while maximize cosmesis, time and cost efficiency.

Methods: A comprehensive search of EMBASE, Medline, Pubmed, and CENTRAL was conducted from inception to 1st May 2020 for randomized controlled trials (RCTs).

Gradient Regularization as Approximate Variational Inference.

We developed Variational Laplace for Bayesian neural networks (BNNs), which exploits a local approximation of the curvature of the likelihood to estimate the ELBO without the need for stochastic sampling of the neural-network weights. The Variational Laplace objective is simple to evaluate, as it is the log-likelihood plus weight-decay, plus a squared-gradient regularizer. Variational Laplace gave better test performance and expected calibration errors than maximum a posteriori inference and standard sampling-based variational inference, despite using the same variational approximate posterior.

Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe.

European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe.

Synaptic plasticity as Bayesian inference.

Learning, especially rapid learning, is critical for survival. However, learning is hard; a large number of synaptic weights must be set based on noisy, often ambiguous, sensory information. In such a high-noise regime, keeping track of probability distributions over weights is the optimal strategy.

Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference.

Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise variability, transient overshoots and oscillations, that have so far escaped a common, principled theoretical account. We developed a unifying model for these phenomena by training a recurrent excitatory-inhibitory neural circuit model of a visual cortical hypercolumn to perform sampling-based probabilistic inference. The optimized network displayed several key biological properties, including divisive normalization and stimulus-modulated noise variability, inhibition-dominated transients at stimulus onset and strong gamma oscillations.

With or without you: predictive coding and Bayesian inference in the brain.

Two theoretical ideas have emerged recently with the ambition to provide a unifying functional explanation of neural population coding and dynamics: predictive coding and Bayesian inference. Here, we describe the two theories and their combination into a single framework: Bayesian predictive coding. We clarify how the two theories can be distinguished, despite sharing core computational concepts and addressing an overlapping set of empirical phenomena.

Active dendritic integration as a mechanism for robust and precise grid cell firing.

Understanding how active dendrites are exploited for behaviorally relevant computations is a fundamental challenge in neuroscience. Grid cells in medial entorhinal cortex are an attractive model system for addressing this question, as the computation they perform is clear: they convert synaptic inputs into spatially modulated, periodic firing. Whether active dendrites contribute to the generation of the dual temporal and rate codes characteristic of grid cell output is unknown.

The Hamiltonian Brain: Efficient Probabilistic Inference with Excitatory-Inhibitory Neural Circuit Dynamics.

Probabilistic inference offers a principled framework for understanding both behaviour and cortical computation. However, two basic and ubiquitous properties of cortical responses seem difficult to reconcile with probabilistic inference: neural activity displays prominent oscillations in response to constant input, and large transient changes in response to stimulus onset. Indeed, cortical models of probabilistic inference have typically either concentrated on tuning curve or receptive field properties and remained agnostic as to the underlying circuit dynamics, or had simplistic dynamics that gave neither oscillations nor transients.

Zipf's Law Arises Naturally When There Are Underlying, Unobserved Variables.

Zipf's law, which states that the probability of an observation is inversely proportional to its rank, has been observed in many domains. While there are models that explain Zipf's law in each of them, those explanations are typically domain specific. Recently, methods from statistical physics were used to show that a fairly broad class of models does provide a general explanation of Zipf's law.

The ergonomics of laparoscopic surgery: a quantitative study of the time and motion of laparoscopic surgeons in live surgical environments.

Background: Laparoscopic surgery presents multiple ergonomic difficulties for the surgeon, requiring awkward body postures and prolonged static muscle loading that increases risk of musculoskeletal strain and injury. This prospective study quantitatively measures the biomechanical movements of surgeons during laparoscopic procedures to determine at-risk movements from prolonged static muscle loading and repetitive motions that may lead to injury.

Methods: A total of 150 video recordings of 18 surgeons, standing at the patient's left, were captured from three fixed camera positions during live gynecological laparoscopic surgery.

Myobacterium bovis peri-prosthetic hip infection with successful prosthesis retention following intravesical BCG therapy for bladder carcinoma.

Systemic dissemination and peri-prosthetic infection of Mycobacterium bovis (M. bovis) following intravesical Bacillus Calmette-Guerin (BCG) therapy presents a rare but significant complication of treatment for non-muscle invasive bladder carcinoma. We present a patient with Mycobacterium bovis infection of a prosthetic hip nine months following BCG therapy for bladder cancer.

Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making.

Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear.

Preoperative Mechanical Bowel Preparation for Abdominal, Laparoscopic, and Vaginal Surgery: A Systematic Review.

Study Objective: Mechanical bowel preparation (MBP) continues to be widely used in gynecologic surgery, with the aim of reducing postoperative complications and improving the viewing and handling conditions in the surgical field. It is reported that MBP is an unpleasant patient experience and may be associated with adverse effects such as dehydration and electrolyte imbalance. This review evaluates the use of preoperative MBP compared with no MBP in adult patients undergoing open abdominal, laparoscopic, or vaginal surgery.

A feasibility study determining surgical ergonomics in a live surgical setting.

Study Objective: To identify the biomechanical movements of laparoscopic surgeons during laparoscopic gynecologic procedures, and to determine whether such movements can be assessed and measured both temporally and biomechanically.

Design: Prospective descriptive kinematic study (Canadian Task Force classification II-3).

Setting: A tertiary referral hospital in Sydney, Australia.

Cell signalling mechanisms for insect stress tolerance.

Insects successfully occupy most environmental niches and this success depends on surviving a broad range of environmental stressors including temperature, desiccation, xenobiotic, osmotic and infection stress. Epithelial tissues play key roles as barriers between the external and internal environments and therefore maintain homeostasis and organismal tolerance to multiple stressors. As such, the crucial role of epithelia in organismal stress tolerance cannot be underestimated.

The use of a combined enrichment-filtration technique for the isolation of Campylobacter spp. from clinical samples.

A combined non-selective enrichment-filtration technique was investigated for the isolation of Campylobacter spp. from clinical samples. In total, 479 samples were tested by direct culture, enrichment subculture and enrichment-filtration.