A circuit mechanism for irrationalities in decision-making and NMDA receptor hypofunction: behaviour, computational modelling, and pharmacology

Decision-making biases can be systematic features of normal behaviour, or deficits underlying neuropsychiatric symptoms. We used behavioural psychophysics, spiking-circuit modelling and pharmacological manipulations to explore decision-making biases in health and disease. Monkeys performed an evidence integration task in which they showed a pro-variance bias (PVB): a preference to choose options with more variable evidence. The PVB was also present in a spiking circuit model, revealing a neural mechanism for this behaviour. Because NMDA receptor (NMDA-R) hypofunction is a leading hypothesis for neuropathology in schizophrenia, we simulated behavioural effects of NMDA-R hypofunction onto either excitatory or inhibitory neurons in the model. These were tested experimentally using the NMDA-R antagonist ketamine, yielding changes in decision-making consistent with lowered cortical excitation/inhibition balance from NMDA-R hypofunction onto excitatory neurons. These results provide a circuit-level mechanism that bridges across explanatory scales, from the synaptic to the behavioural, in neuropsychiatric disorders where decision-making biases are prominent. Significance People can make apparently irrational decisions because of underlying features in their decision circuitry. Deficits in the same neural circuits may also underlie debilitating cognitive symptoms of neuropsychiatric patients. Here, we reveal a neural circuit mechanism explaining an irrationality frequently observed in healthy humans making binary choices – the pro-variance bias. Our circuit model could be perturbed by introducing deficits in either excitatory or inhibitory neuron function. These two perturbations made specific, dissociable predictions for the types of irrational decisionmaking behaviour produced. We used the NMDA-R antagonist ketamine, an experimental model for schizophrenia, to test if these predictions were relevant to neuropsychiatric pathophysiology. The results were consistent with impaired excitatory neuron function, providing important new insights into the pathophysiology of schizophrenia

A circuit mechanism for decision-making biases and NMDA receptor hypofunction

Decision-making biases can be features of normal behaviour, or deficits underlying neuropsychiatric symptoms. We used behavioural psychophysics, spiking-circuit modelling and pharmacological manipulations to explore decision-making biases during evidence integration. Monkeys showed a pro-variance bias (PVB): a preference to choose options with more variable evidence. The PVB was also present in a spiking circuit model, revealing a potential neural mechanism for this behaviour. To model possible effects of NMDA receptor (NMDA-R) antagonism on this behaviour, we simulated the effects of NMDA-R hypofunction onto either excitatory or inhibitory neurons in the model. These were then tested experimentally using the NMDA-R antagonist ketamine, a pharmacological model of schizophrenia. Ketamine yielded an increase in subjects' PVB, consistent with lowered cortical excitation/inhibition balance from NMDA-R hypofunction predominantly onto excitatory neurons. These results provide a circuit-level mechanism that bridges across explanatory scales, from the synaptic to the behavioural, in neuropsychiatric disorders where decision-making biases are prominent

End of the road? The career intentions of under-represented STEM students in higher education

Background The analogy of the leaky pipeline has been used to describe STEM education, with lower student diversity from compulsory to post-compulsory education and beyond. Although extensive research has explored the views and experiences of school-aged children about STEM, fewer studies have examined the career intentions of STEM students at university, especially those from under-represented backgrounds (e.g., racial/ethnic minority, women and working class students). This paper draws on a large qualitative study that interviewed 110 under-represented STEM undergraduates in the UK. We focus on students’ STEM career intentions and the likely directions of their post-degree trajectories, drawing on the lenses of science identity and Social Cognitive Career Theory. Results Three pathways were identified. The first group plans to pursue a career in or from STEM. While social inequalities may persist, the potential impact of these challenges may be neutralised by the personal drive and passion of STEM career-oriented students, who seem committed to drive into an STEM future. The second group stated intentions for non-STEM-related careers, leaving the STEM pipeline. The reasons students gave for their imminent departure from STEM are the better financial reward on offer in some non-STEM sectors, especially in finance and business, as well as wider social inequalities and stereotypes. The third group was undecided, those who are uncertain or unclear about their futures. Students described a general lack of direction or clear career pathway, from a complete lack of career ideas to an overload of options. Conclusions We conclude with a reminder that the STEM pipeline is far from secured or equitable, despite apparent progress in participation and representation. We reiterate the importance of fostering a diverse, inclusive and supportive learning environment that maximises the participation, strengths and potential of all students, especially those from under-represented backgrounds. While it is not uncommon for STEM students to pursue careers outside of STEM, we need to be wary that those who exit the STEM pipeline are not forced off the road by social inequalities and exclusions

Atmospheric science: the self-cleansing ability of prehistoric air

Isotopic data from an ice core have been used to estimate atmospheric oxidant levels during past climate transitions — pointing to relatively unexplored climate feedbacks as drivers of atmospheric composition

Are autistic traits measured equivalently in individuals with and without an Autism Spectrum Disorder?:An invariance analysis of the Autism Spectrum Quotient Short Form

It is common to administer measures of autistic traits to those without autism spectrum disorders (ASDs) with, for example, the aim of understanding autistic personality characteristics in non-autistic individuals. Little research has examined the extent to which measures of autistic traits actually measure the same traits in the same way across those with and without an ASD. We addressed this question using a multi-group confirmatory factor invariance analysis of the Autism Quotient Short Form (AQ-S: Hoekstra et al. in J Autism Dev Disord 41(5):589-596, 2011) across those with (n = 148) and without (n = 168) ASD. Metric variance (equality of factor loadings), but not scalar invariance (equality of thresholds), held suggesting that the AQ-S measures the same latent traits in both groups, but with a bias in the manner in which trait levels are estimated. We, therefore, argue that the AQ-S can be used to investigate possible causes and consequences of autistic traits in both groups separately, but caution is due when combining or comparing levels of autistic traits across the two group

Cloud impacts on photochemistry: Building a climatology of photolysis rates from the Atmospheric Tomography mission

Abstract. Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J values) throughout the remote Pacific and Atlantic Ocean basins. J values control tropospheric ozone and methane abundances, and thus clouds have been included for more than three decades in tropospheric chemistry modeling. ATom made four profiling circumnavigations of the troposphere capturing each of the seasons during 2016–2018. This work examines J values from the Pacific Ocean flights of the first deployment, but publishes the complete Atom-1 data set (29 July to 23 August 2016). We compare the observed J values (every 3 s along flight track) with those calculated by nine global chemistry–climate/transport models (globally gridded, hourly, for a mid-August day). To compare these disparate data sets, we build a commensurate statistical picture of the impact of clouds on J values using the ratio of J-cloudy (standard, sometimes cloudy conditions) to J-clear (artificially cleared of clouds). The range of modeled cloud effects is inconsistently large but they fall into two distinct classes: (1) models with large cloud effects showing mostly enhanced J values aloft and or diminished at the surface and (2) models with small effects having nearly clear-sky J values much of the time. The ATom-1 measurements generally favor large cloud effects but are not precise or robust enough to point out the best cloud-modeling approach. The models here have resolutions of 50–200 km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average scattered sunlight over a mixed cloud field, but only out to scales of tens of kilometers. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements. NERC ACSIS LTSM projec

COPD diagnosis related to different guidelines and spirometry techniques

The aim was to compare the diagnosis of COPD among smokers according to different international guidelines and to compare the outcome when using slow (SVC) and forced vital capacity (FVC)

Patients’ willingness to attend the NHS cardiovascular health checks in primary care: A qualitative interview study

Background: The NHS Cardiovascular Health Check (NHSHC) programme was introduced in England in 2009 to reduce cardiovascular disease mortality and morbidity for all patients aged 40 to 74 years old. Programme cost-effectiveness was based on an assumed uptake of 75% but current estimates of uptake in primary care are less than 50%. The purpose of this study was to identify factors influencing patients’ willingness to attend an NHSHC. For those who attended, their views, experiences and their future willingness to engage in the programme were explored. Method: Telephone or face-to-face interviews were conducted with patients who had recently been invited for an NHSHC by a letter from four general practices in Torbay, England. Patients were purposefully sampled (by gender, age, attendance status). Interviews were audio recorded, transcribed verbatim and analysed thematically. Results: 17 attendees and 10 non-attendees were interviewed. Patients who attended an NHSHC viewed it as worthwhile. Proactive attitudes towards their health, a desire to prevent disease before they developed symptoms, and a willingness to accept screening and health check invitations motivated many individuals to attend. Non-attendees cited not seeing the NHSHC as a priority, or how it differed from regular monitoring already received for other conditions as barriers to attendance. Some non-attendees actively avoided GP practices when feeling well, while others did not want to waste health professionals’ time. Misunderstandings of what the NHSHC involved and negative views of what the likely outcome might be were common. Conclusion: While a minority of non-attendees simply had made an informed choice not to have an NHSHC, improving the clarity and brevity of invitational materials, better advertising, and simple administrative interventions such as sending reminder letters, have considerable potential to improve NHSHC uptake

Parametric study of EEG sensitivity to phase noise during face processing

<b>Background: </b> The present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model. <b>Results: </b> Our results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces. <b>Conclusion: </b> Our results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses

Gene expression profiling of human whole blood samples with the Illumina WG-DASL assay

<p>Abstract</p> <p>Background</p> <p>Microarray-based gene expression analysis of peripheral whole blood is a common strategy in the development of clinically relevant biomarker panels for a variety of human diseases. However, the results of such an analysis are often plagued by decreased sensitivity and reliability due to the effects of relatively high levels of globin mRNA in whole blood. Globin reduction assays have been shown to overcome such effects, but they require large amounts of total RNA and may induce distinct gene expression profiles. The Illumina whole genome DASL assay can detect gene expression levels using partially degraded RNA samples and has the potential to detect rare transcripts present in highly heterogeneous whole blood samples without the need for globin reduction. We assessed the utility of the whole genome DASL assay in an analysis of peripheral whole blood gene expression profiles.</p> <p>Results</p> <p>We find that gene expression detection is significantly increased with the use of whole genome DASL compared to the standard IVT-based direct hybridization. Additionally, globin-probe negative whole genome DASL did not exhibit significant improvements over globin-probe positive whole genome DASL. Globin reduction further increases the detection sensitivity and reliability of both whole genome DASL and IVT-based direct hybridization with little effect on raw intensity correlations. Raw intensity correlations between total RNA and globin reduced RNA were 0.955 for IVT-based direct hybridization and 0.979 for whole genome DASL.</p> <p>Conclusions</p> <p>Overall, the detection sensitivity of the whole genome DASL assay is higher than the IVT-based direct hybridization assay, with or without globin reduction, and should be considered in conjunction with globin reduction methods for future blood-based gene expression studies.</p