Who knows what \u27healthy weight\u27 looks like?

Background: Obesity is a global epidemic. The World Health Organization (WHO) reports that worldwide obesity has nearly tripled since 1975. In 2016, more than 1.9 billion adults were overweight and had corresponding increases in well-recognised, associated chronic diseases. Aims: This study aimed to explore whether the general population is able to identify a healthy BMI and accurately perceive their own BMI using a visual scale. Method: A cross-sectional, population-based survey of 103 participants were shown a visual scale of computer-generated images representing different BMIs and asked to identify: (1) which images represented a healthy body weight; (2) which image best represented their body; and (3) whether they thought they were a healthy or unhealthy body size. Conclusion: Overweight participants were significantly less likely to correctly identify their own BMI on a visual scale (38.9 per cent,

Computations underlying sensorimotor learning

The study of sensorimotor learning has a long history. With the advent of innovative techniques for studying learning at the behavioral and computational levels new insights have been gained in recent years into how the sensorimotor system acquires, retains, represents, retrieves and forgets sensorimotor tasks. In this review we highlight recent advances in the field of sensorimotor learning from a computational perspective. We focus on studies in which computational models are used to elucidate basic mechanisms underlying adaptation and skill acquisition in human behavior.This work was supported by the Wellcome Trust, the Human Frontiers Science Program, the Royal Society (Noreen Murray Professorship in Neurobiology to D.M.W.) and the Canadian Institutes of Health Research.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.conb.2015.12.00

SB32-19/20: Resolution Amending Board on Member Organizations Bylaws to Address Student Groups Requiring Enrollment in an Academic Course

SB32-19/20: Resolution Amending Board on Member Organizations Bylaws to Address Student Groups Requiring Enrollment in an Academic Course Passed 21Y-1N-0A in the December 4, 2019 ASUM Senate Meeting

Q&A: Robotics as a tool to understand the brain.

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Computations underlying sensorimotor learning.

The study of sensorimotor learning has a long history. With the advent of innovative techniques for studying learning at the behavioral and computational levels new insights have been gained in recent years into how the sensorimotor system acquires, retains, represents, retrieves and forgets sensorimotor tasks. In this review we highlight recent advances in the field of sensorimotor learning from a computational perspective. We focus on studies in which computational models are used to elucidate basic mechanisms underlying adaptation and skill acquisition in human behavior.This work was supported by the Wellcome Trust, the Human Frontiers Science Program, the Royal Society (Noreen Murray Professorship in Neurobiology to D.M.W.) and the Canadian Institutes of Health Research.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.conb.2015.12.00

Towards real-time simulation of the sidescan sonar imaging process

peer-reviewedThis paper describes the functional theory and design of a modular simulator developed to generate physically representative spatio-temporal sidescan sonar echo data from a fractal model of the seafloor topography. The main contribution of this paper is in significantly reducing the computational bottleneck inherent in existing simulation models due to the size and resolution of the complex seafloor models required for acoustic reverberation modelling. Discovery of the individual faces within the footprint of the acoustic beam at each ping is considerably accelerated by successfully adapting and integrating an optimised mesh refinement scheme intended for interactive rendering of large-scale complex surfaces described by polygonal meshes. Operational features of the simulator permit direct visualisation of the sonar image formed from successive echo lines and synthetic images generated during simulation are presented.PUBLISHEDpeer-reviewe

Sex differences in plasma clozapine and norclozapine concentrations in clinical practice and in relation to body mass index and plasma glucose concentrations: a retrospective survey

Background Clozapine is widely prescribed and, although effective, can cause weight gain and dysglycemia. The dysmetabolic effects of clozapine are thought to be more prevalent in women with this gender on average attaining 17 % higher plasma clozapine concentrations than men. Methods We investigated the relationship between dose, body mass index (BMI), plasma glucose concentration, and plasma clozapine and N-desmethylclozapine (norclozapine) concentrations in 100 individuals with a severe enduring mental illness. Results Mean (10th/90th percentile) plasma clozapine concentrations were higher for women [0.49 (0.27–0.79) mg/L] compared with men [0.44 (0.26–0.70) mg/L] (F = 2.2; p = 0.035). There was no significant gender difference in the prescribed clozapine dose. BMI was significantly higher in women [mean (95 % CI) = 34.5 (26.0–45.3)] for females compared with 32.5 (25.2–41.0) for males. Overall, BMI increased by 0.7 kg/m 2 over a mean follow-up period of 210 days. A lower proportion, 41 % of women had a fasting blood glucose ≤6.0 mmol/L (<6.0 mmol/L is defined by the International Diabetes Federation as normal glucose handling), compared with 88 % of men (χ2  = 18.6, p < 0.0001). Conclusions We have shown that mean BMI and blood glucose concentrations are higher in women prescribed clozapine than in men. Women also tended to attain higher plasma clozapine concentrations than men. The higher BMI and blood glucose in women may relate to higher tissue exposure to clozapine, as a consequence of sex differences in drug metabolism

Attenuation of Self-Generated Tactile Sensations Is Predictive, not Postdictive

When one finger touches the other, the resulting tactile sensation is perceived as weaker than the same stimulus externally imposed. This attenuation of sensation could result from a predictive process that subtracts the expected sensory consequences of the action, or from a postdictive process that alters the perception of sensations that are judged after the event to be self-generated. In this study we observe attenuation even when the fingers unexpectedly fail to make contact, supporting a predictive process. This predictive attenuation of self-generated sensation may have evolved to enhance the perception of sensations with an external cause

Human decision making anticipates future performance in motor learning.

It is well-established that people can factor into account the distribution of their errors in motor performance so as to optimize reward. Here we asked whether, in the context of motor learning where errors decrease across trials, people take into account their future, improved performance so as to make optimal decisions to maximize reward. One group of participants performed a virtual throwing task in which, periodically, they were given the opportunity to select from a set of smaller targets of increasing value. A second group of participants performed a reaching task under a visuomotor rotation in which, after performing a initial set of trials, they selected a reward structure (ratio of points for target hits and misses) for different exploitation horizons (i.e., numbers of trials they might be asked to perform). Because movement errors decreased exponentially across trials in both learning tasks, optimal target selection (task 1) and optimal reward structure selection (task 2) required taking into account future performance. The results from both tasks indicate that people anticipate their future motor performance so as to make decisions that will improve their expected future reward