The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction

Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID), uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP) model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex

Governing software: networks, databases and algorithmic power in the digital governance of public education

This article examines the emergence of ‘digital governance’ in public education in England. Drawing on and combining concepts from software studies, policy and political studies, it identifies some specific approaches to digital governance facilitated by network-based communications and database-driven information processing software that are being discursively promoted in education by cross-sectoral intermediary organizations. Such intermediaries, including National Endowment for Science, Technology and the Arts, Demos, the Innovation Unit, the Education Foundation and the Nominet Trust, are increasingly seeking to participate in new digitally mediated forms of educational governance. Through their promotion of network-based pedagogies and database-driven analytics software, these organizations are seeking to delegate educational decision-making to socio-algorithmic forms of power that have the capacity to predict, govern and activate learners' capacities and subjectivities

Human α2β1HI CD133+VE epithelial prostate stem cells express low levels of active androgen receptor

Stem cells are thought to be the cell of origin in malignant transformation in many tissues, but their role in human prostate carcinogenesis continues to be debated. One of the conflicts with this model is that cancer stem cells have been described to lack androgen receptor (AR) expression, which is of established importance in prostate cancer initiation and progression. We re-examined the expression patterns of AR within adult prostate epithelial differentiation using an optimised sensitive and specific approach examining transcript, protein and AR regulated gene expression. Highly enriched populations were isolated consisting of stem (α(2)β(1)(HI) CD133(+VE)), transiently amplifying (α(2)β(1)(HI) CD133(-VE)) and terminally differentiated (α(2)β(1)(LOW) CD133(-VE)) cells. AR transcript and protein expression was confirmed in α(2)β(1)(HI) CD133(+VE) and CD133(-VE) progenitor cells. Flow cytometry confirmed that median (±SD) fraction of cells expressing AR were 77% (±6%) in α(2)β(1)(HI) CD133(+VE) stem cells and 68% (±12%) in α(2)β(1)(HI) CD133(-VE) transiently amplifying cells. However, 3-fold lower levels of total AR protein expression (peak and median immunofluorescence) were present in α(2)β(1)(HI) CD133(+VE) stem cells compared with differentiated cells. This finding was confirmed with dual immunostaining of prostate sections for AR and CD133, which again demonstrated low levels of AR within basal CD133(+VE) cells. Activity of the AR was confirmed in prostate progenitor cells by the expression of low levels of the AR regulated genes PSA, KLK2 and TMPRSS2. The confirmation of AR expression in prostate progenitor cells allows integration of the cancer stem cell theory with the established models of prostate cancer initiation based on a functional AR. Further study of specific AR functions in prostate stem and differentiated cells may highlight novel mechanisms of prostate homeostasis and insights into tumourigenesis

Losing Confidence in Luminosity

A mental state is luminous if, whenever an agent is in that state, they are in a position to know that they are. Following Timothy Williamson’s Knowledge and Its Limits, a wave of recent work has explored whether there are any non-trivial luminous mental states. A version of Williamson’s anti-luminosity appeals to a safety- theoretic principle connecting knowledge and confidence: if an agent knows p, then p is true in any nearby scenario where she has a similar level of confidence in p. However, the relevant notion of confidence is relatively underexplored. This paper develops a precise theory of confidence: an agent’s degree of confidence in p is the objective chance they will rely on p in practical reasoning. This theory of confidence is then used to critically evaluate the anti-luminosity argument, leading to the surprising conclusion that although there are strong reasons for thinking that luminosity does not obtain, they are quite different from those the existing literature has considered. In particular, we show that once the notion of confidence is properly understood, the failure of luminosity follows from the assumption that knowledge requires high confidence, and does not require any kind of safety principle as a premis

Risk in the "Red Zone": Outcomes for Children Admitted to Ebola Holding Units in Sierra Leone Without Ebola Virus Disease.

We collected data on 1054 children admitted to Ebola Holding Units in Sierra Leone and describe outcomes of 697/1054 children testing negative for Ebola virus disease (EVD) and accompanying caregivers. Case-fatality was 9%; 3/630 (0.5%) children discharged testing negative were readmitted EVD-positive. Nosocomial EVD transmission risk may be lower than feared

Belief, Credence and Statistical Evidence

According to the Rational Threshold View, a rational agent believes p if and only if her credence in p is equal to or greater than a certain threshold. One of the most serious challenges for this view is the problem of statistical evidence: statistical evidence is often not sufficient to make an outright belief rational, no matter how probable the target proposition is given such evidence. This indicates that rational belief is not as sensitive to statistical evidence as rational credence. The aim of this paper is twofold. First, we argue that, in addition to playing a decisive role in rationalizing outright belief, non-statistical evidence also plays a preponderant role in rationalizing credence. More precisely, when both types of evidence are present in a context, non-statistical evidence should receive a heavier weight than statistical evidence in determining rational credence. Second, based on this result, we argue that a modified version of the Rational Threshold View can avoid the problem of statistical evidence. We conclude by suggesting a possible explanation of the varying sensitivity to different types of evidence for belief and credence based on the respective aims of these attitudes

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

Baseline characteristics of people experiencing homelessness with a recent drug overdose in the PHOENIx pilot randomised controlled trial

Background: Drug-related deaths in Scotland are the highest in Europe. Half of all deaths in people experiencing homelessness are drug related, yet we know little about the unmet health needs of people experiencing homelessness with recent non-fatal overdose, limiting a tailored practice and policy response to a public health crisis. Methods: People experiencing homelessness with at least one non-fatal street drug overdose in the previous 6 months were recruited from 20 venues in Glasgow, Scotland, and randomised into PHOENIx plus usual care, or usual care. PHOENIx is a collaborative assertive outreach intervention by independent prescriber NHS Pharmacists and third sector homelessness workers, offering repeated integrated, holistic physical, mental and addictions health and social care support including prescribing. We describe comprehensive baseline characteristics of randomised participants. Results: One hundred and twenty-eight participants had a mean age of 42 years (SD 8.4); 71% male, homelessness for a median of 24 years (IQR 12–30). One hundred and eighteen (92%) lived in large, congregate city centre temporary accommodation. A quarter (25%) were not registered with a General Practitioner. Participants had overdosed a mean of 3.2 (SD 3.2) times in the preceding 6 months, using a median of 3 (IQR 2–4) non-prescription drugs concurrently: 112 (87.5%) street valium (benzodiazepine-type new psychoactive substances); 77 (60%) heroin; and 76 (59%) cocaine. Half (50%) were injecting, 50% into their groins. 90% were receiving care from Alcohol and Drug Recovery Services (ADRS), and in addition to using street drugs, 90% received opioid substitution therapy (OST), 10% diazepam for street valium use and one participant received heroin-assisted treatment. Participants had a mean of 2.2 (SD 1.3) mental health problems and 5.4 (SD 2.5) physical health problems; 50% received treatment for physical or mental health problems. Ninety-one per cent had at least one mental health problem; 66% had no specialist mental health support. Participants were frail (70%) or pre-frail (28%), with maximal levels of psychological distress, 44% received one or no daily meal, and 58% had previously attempted suicide. Conclusions: People at high risk of drug-related death continue to overdose repeatedly despite receiving OST. High levels of frailty, multimorbidity, unsuitable accommodation and unmet mental and physical health care needs require a reorientation of services informed by evidence of effectiveness and cost-effectiveness. Trial registration UK Clinical Trials Registry identifier: ISRCTN 10585019