Speed and Accuracy of Static Image Discrimination by Rats

When discriminating dynamic noisy sensory signals, human and primate subjects achieve higher accuracy when they take more time to decide, an effect attributed to accumulation of evidence over time to overcome neural noise. We measured the speed and accuracy of twelve freely behaving rats discriminating static, high contrast photographs of real-world objects for water reward in a self-paced task. Response latency was longer in correct trials compared to error trials. Discrimination accuracy increased with response latency over the range of 500-1200ms. We used morphs between previously learned images to vary the image similarity parametrically, and thereby modulate task difficulty from ceiling to chance. Over this range we find that rats take more time before responding in trials with more similar stimuli. We conclude that rats' perceptual decisions improve with time even in the absence of temporal information in the stimulus, and that rats modulate speed in response to discrimination difficulty to balance speed and accuracy

Improving population-level refractive error monitoring via mixture distributions

Introduction: Sampling and describing the distribution of refractive error in populations is critical to understanding eye care needs, refractive differences between groups and factors affecting refractive development. We investigated the ability of mixture models to describe refractive error distributions. Methods: We used key informants to identify raw refractive error datasets and a systematic search strategy to identify published binned datasets of community-representative refractive error. Mixture models combine various component distributions via weighting to describe an observed distribution. We modelled raw refractive error data with a single-Gaussian (normal) distribution, mixtures of two to six Gaussian distributions and an additive model of an exponential and Gaussian (ex-Gaussian) distribution. We tested the relative fitting accuracy of each method via Bayesian Information Criterion (BIC) and then compared the ability of selected models to predict the observed prevalence of refractive error across a range of cut-points for both the raw and binned refractive data. Results: We obtained large raw refractive error datasets from the United States and Korea. The ability of our models to fit the data improved significantly from a single-Gaussian to a two-Gaussian-component additive model and then remained stable with ≥3-Gaussian-component mixture models. Means and standard deviations for BIC relative to 1 for the single-Gaussian model, where lower is better, were 0.89 ± 0.05, 0.88 ± 0.06, 0.89 ± 0.06, 0.89 ± 0.06 and 0.90 ± 0.06 for two-, three-, four-, five- and six-Gaussian-component models, respectively, tested across US and Korean raw data grouped by age decade. Means and standard deviations for the difference between observed and model-based estimates of refractive error prevalence across a range of cut-points for the raw data were −3.0% ± 6.3, 0.5% ± 1.9, 0.6% ± 1.5 and −1.8% ± 4.0 for one-, two- and three-Gaussian-component and ex-Gaussian models, respectively. Conclusions: Mixture models appear able to describe the population distribution of refractive error accurately, offering significant advantages over commonly quoted simple summary statistics such as mean, standard deviation and prevalence

Alcohol Consumption and Incident Cataract Surgery in Two Large UK Cohorts

PURPOSE: To examine the association of alcohol consumption and type of alcoholic beverage with incident cataract surgery in two large cohorts. DESIGN: Longitudinal observational study PARTICIPANTS: We included 469,387 participants of UK Biobank with a mean age of 56 years, and 23,162 participants of EPIC-Norfolk with a mean age of 59 years. METHODS: Self-reported alcohol consumption at baseline was ascertained by a touchscreen questionnaire in UK Biobank and a food-frequency questionnaire in EPIC-Norfolk. Cases were defined as participants undergoing cataract surgery in either eye as ascertained via data linkage to National Health Service procedure statistics. We excluded participants with cataract surgery up to 1 year after the baseline assessment visit or those with self-reported cataract at baseline. Cox proportional hazards models were used to examine the associations of alcohol consumption with incident cataract surgery, adjusted for age, sex, ethnicity, Townsend deprivation index, body mass index, smoking and diabetes status. MAIN OUTCOME MEASURES: Incident cataract surgery RESULTS: There were 19,011 (mean cohort follow-up of 95 months) and 4,573 (mean cohort follow-up of 193 months) incident cases of cataract surgery in UK Biobank and EPIC-Norfolk, respectively. Compared to non-drinkers, drinkers were less likely to undergo cataract surgery in UK Biobank (HR 0.89, 95% CI 0.85-0.93) and EPIC-Norfolk (HR 0.90, 95% CI 0.84-0.97) after adjusting for covariables. Among alcohol consumers, greater alcohol consumption was associated with a reduced risk of undergoing cataract surgery in EPIC-Norfolk (P<0.001), while a U-shaped association was observed in the UK Biobank. Compared with non-drinkers, sub-group analysis by type of alcohol beverage showed the strongest protective association with wine consumption; the risk of incident cataract surgery was 23% and 14% lower among those in the highest category of wine consumption in EPIC-Norfolk and UK Biobank, respectively. CONCLUSION: Our findings suggest a lower risk of undergoing cataract surgery with low to moderate alcohol consumption. The association was particularly apparent with wine consumption. We cannot exclude the possibility of residual confounding and further studies are required to determine whether this association is causal in nature

No straight lines – young women’s perceptions of their mental health and wellbeing during and after pregnancy: a systematic review and meta-ethnography

Background: Young mothers face mental health challenges during and after pregnancy including increased rates of depression compared to older mothers. While the prevention of teenage pregnancy in countries such as the United States and the United Kingdom has been a focus for policy and research in recent decades, the need to understand young women’s own experiences has been highlighted. The aim of this meta-ethnography was to examine young women’s perceptions of their mental health and wellbeing during and after pregnancy to provide new understandings of those experiences. Methods: A systematic review and meta-ethnographic synthesis of qualitative research was conducted. Seven databases were systematically searched and forward and backward searching conducted. Papers were included if they were from Organisation for Economic Co-operation and Development countries and explored mental health and wellbeing experiences of young mothers (age under 20 in pregnancy; under 25 at time of research) as a primary research question – or where evidence about mental health and wellbeing from participants was foregrounded. Nineteen papers were identified and the Critical Appraisal Skills Programme checklist for qualitative research used to appraise the evidence. Following the seven-step process of meta-ethnography, key constructs were examined within each study and then translated into one another. Results: Seven translated themes were identified forming a new line of argument wherein mental health and wellbeing was analysed as relating to individual bodily experiences; tied into past and present relationships; underpinned by economic insecurity and entangled with feelings of societal surveillance. There were ‘no straight lines’ in young women’s experiences, which were more complex than dominant narratives around overcoming adversity suggest. Conclusions: The synthesis concludes that health and social care professionals need to reflect on the operation of power and stigma in young women’s lives and its impact on wellbeing. It adds to understanding of young women’s mental health and wellbeing during and after pregnancy as located in physical and structural factors rather than individual capacities alone

Concurrent acute illness and comorbid conditions poorly predict antibiotic use in upper respiratory tract infections: a cross-sectional analysis

<p>Abstract</p> <p>Background</p> <p>Inappropriate antibiotic use promotes resistance. Antibiotics are generally not indicated for upper respiratory infections (URIs). Our objectives were to describe patterns of URI treatment and to identify patient and provider factors associated with antibiotic use for URIs.</p> <p>Methods</p> <p>This study was a cross-sectional analysis of medical and pharmacy claims data from the Pennsylvania Medicaid fee-for-service program database. We identified Pennsylvania Medicaid recipients with a URI office visit over a one-year period. Our outcome variable was antibiotic use within seven days after the URI visit. Study variables included URI type and presence of concurrent acute illnesses and chronic conditions. We considered the associations of each study variable with antibiotic use in a logistic regression model, stratifying by age group and adjusting for confounders.</p> <p>Results</p> <p>Among 69,936 recipients with URI, 35,786 (51.2%) received an antibiotic. In all age groups, acute sinusitis, chronic sinusitis, otitis, URI type and season were associated with antibiotic use. Except for the oldest group, physician specialty and streptococcal pharyngitis were associated with antibiotic use. History of chronic conditions was not associated with antibiotic use in any age group. In all age groups, concurrent acute illnesses and history of chronic conditions had only had fair to poor ability to distinguish patients who received an antibiotic from patients who did not.</p> <p>Conclusion</p> <p>Antibiotic prevalence for URIs was high, indicating that potentially inappropriate antibiotic utilization is occurring. Our data suggest that demographic and clinical factors are associated with antibiotic use, but additional reasons remain unexplained. Insight regarding reasons for antibiotic prescribing is needed to develop interventions to address the growing problem of antibiotic resistance.</p

Evaluation of the dual mTOR / PI3K inhibitors Gedatolisib (PF-05212384) and PF-04691502 against ovarian cancer xenograft models

We are grateful to Wyeth/Pfizer (ONC-EU-150) and to the Scottish Funding Council (SRDG HR07005) for support of this study.This study investigated the antitumour effects of two dual mTOR/PI3K inhibitors, gedatolisib (WYE-129587/PKI-587/PF-05212384) and PF-04691502 against a panel of six human patient derived ovarian cancer xenograft models. Both dual mTOR/PI3K inhibitors demonstrated antitumour activity against all xenografts tested. The compounds produced tumour stasis during the treatment period and upon cessation of treatment, tumours re-grew. In several models, there was an initial rapid reduction of tumour volume over the first week of treatment before tumour stasis. No toxicity was observed during treatment. Biomarker studies were conducted in two xenograft models; phospho-S6 (Ser235/236) expression (as a readout of mTOR activity) was reduced over the treatment period in the responding xenograft but expression increased to control (no treatment) levels on cessation of treatment. Phospho-AKT (Ser473) expression (as a readout of PI3K) was inhibited by both drugs but less markedly so than phospho-S6 expression. Initial tumour volume reduction on treatment and regrowth rate after treatment cessation was associated with phospho-S6/total S6 expression ratio. Both drugs produced apoptosis but minimally influenced markers of proliferation (Ki67, phospho-histone H3). These results indicate that mTOR/PI3K inhibition can produce broad spectrum tumour growth stasis in ovarian cancer xenograft models during continuous chronic treatment and this is associated with apoptosis.Publisher PDFPeer reviewe

Effect of educational outreach on general practice prescribing of antibiotics and antidepressants: a two-year randomised controlled trial

Objective. Prescribing of broad spectrum antibiotics and antidepressants in general practice often does not accord with guidelines. The aim was to determine the effectiveness of educational outreach in improving the prescribing of selected antibiotics and antidepressants, and whether the effect is sustained for two years. Design. Single blind randomized trial. Setting. Twenty-eight general practices in Leicestershire, England. Intervention. Educational outreach visits were undertaken, tailored to barriers to change, 14 practices receiving visits for reducing selected antibiotics and 14 for improving antidepressant prescribing. Main outcome measures. Number of items prescribed per 1000 registered patients for amoxicillin with clavulanic acid (co-amoxiclav) and quinolone antibiotics, and average daily quantities per 1000 patients for lofepramine and fluoxetine antidepressants, measured at the practice level for six-month periods over two years. Results. There was no effect on the prescribing of co-amoxiclav, quinolones, or fluoxetine, but prescribing of lofepramine increased in accordance with the guidelines. The increase persisted throughout two years of follow-up. Conclusion. A simple, group-level educational outreach intervention, designed to take account of identified barriers to change, can have a modest but sustained effect on prescribing levels. However, outreach is not always effective. The context in which change in prescribing practice is being sought, the views of prescribers concerning the value of the drug, or other unrecognised barriers to change may influence the effectiveness of outreach

A Common Cortical Circuit Mechanism for Perceptual Categorical Discrimination and Veridical Judgment

Perception involves two types of decisions about the sensory world: identification of stimulus features as analog quantities, or discrimination of the same stimulus features among a set of discrete alternatives. Veridical judgment and categorical discrimination have traditionally been conceptualized as two distinct computational problems. Here, we found that these two types of decision making can be subserved by a shared cortical circuit mechanism. We used a continuous recurrent network model to simulate two monkey experiments in which subjects were required to make either a two-alternative forced choice or a veridical judgment about the direction of random-dot motion. The model network is endowed with a continuum of bell-shaped population activity patterns, each representing a possible motion direction. Slow recurrent excitation underlies accumulation of sensory evidence, and its interplay with strong recurrent inhibition leads to decision behaviors. The model reproduced the monkey's performance as well as single-neuron activity in the categorical discrimination task. Furthermore, we examined how direction identification is determined by a combination of sensory stimulation and microstimulation. Using a population-vector measure, we found that direction judgments instantiate winner-take-all (with the population vector coinciding with either the coherent motion direction or the electrically elicited motion direction) when two stimuli are far apart, or vector averaging (with the population vector falling between the two directions) when two stimuli are close to each other. Interestingly, for a broad range of intermediate angular distances between the two stimuli, the network displays a mixed strategy in the sense that direction estimates are stochastically produced by winner-take-all on some trials and by vector averaging on the other trials, a model prediction that is experimentally testable. This work thus lends support to a common neurodynamic framework for both veridical judgment and categorical discrimination in perceptual decision making

Changes of Mind in an Attractor Network of Decision-Making

Attractor networks successfully account for psychophysical and neurophysiological data in various decision-making tasks. Especially their ability to model persistent activity, a property of many neurons involved in decision-making, distinguishes them from other approaches. Stable decision attractors are, however, counterintuitive to changes of mind. Here we demonstrate that a biophysically-realistic attractor network with spiking neurons, in its itinerant transients towards the choice attractors, can replicate changes of mind observed recently during a two-alternative random-dot motion (RDM) task. Based on the assumption that the brain continues to evaluate available evidence after the initiation of a decision, the network predicts neural activity during changes of mind and accurately simulates reaction times, performance and percentage of changes dependent on difficulty. Moreover, the model suggests a low decision threshold and high incoming activity that drives the brain region involved in the decision-making process into a dynamical regime close to a bifurcation, which up to now lacked evidence for physiological relevance. Thereby, we further affirmed the general conformance of attractor networks with higher level neural processes and offer experimental predictions to distinguish nonlinear attractor from linear diffusion models