A primer on functional magnetic resonance imaging

Abstract In this manuscript, basic principles of functional magnetic resonance imaging (fMRI) are reviewed. In the first section, two intrinsic mechanisms of magnetic resonance image contrast related to the longitudinal and transverse components of relaxing spins and their relaxation rates, T 1 and T 2 , are described. In the second section, the biophysical mechanisms that alter the apparent transverse relaxation time, T * 2 , in blood oxygenation level dependent (BOLD) studies and the creation of BOLD activation maps are discussed. The physiological complexity of the BOLD signal is emphasized. In the third section, arterial spin labeling (ASL) measures of cerebral blood flow are presented. Arterial spin labeling inverts or saturates the magnetization of flowing spins to measure the rate of delivery of blood to capillaries. In the fourth section, calibrated fMRI, which uses BOLD and ASL to infer alterations of oxygen utilization during behavioral activation, is reviewed. The discussion concludes with challenges confronting studies of individual cases. Keywords Functional magnetic resonance imaging . Perfusion magnetic resonance imaging . Regional blood flow . Cerebral oxygen metabolism G. G. Brown ( ) Psychology Service (MC 116B), VA San Diego Healthcare System, 3350 La Jolla Village Drive

Quantification and parametric imaging of renal cortical blood flow in vivo based on Patlak graphical analysis

Quantification and parametric imaging of renal cortical blood flow in vivo based on Patlak graphical analysis. Patlak graphical analysis was applied to quantify renal cortical blood flow with N-13 ammonia and dynamic positron emission tomography. Measurements were made in a swine model of kidney transplantation with a wide range of normal and abnormal renal blood flows (N = 57 studies) and in 20 healthy human volunteers (N = 45 studies). Estimates of renal cortical blood flow by the Patlak method were compared to those from a two-compartment model for N-13 ammonia. In addition, estimates of renal cortical blood flow by the N-13 ammonia PET approach were compared in 10 normal human volunteers to estimates by the metabolically inert, freely diffusible O-15 water and a one-compartment model. Patlak graphical analysis estimates of renal cortical blood flow correlated linearly with the standard two-compartment model in pigs (y = -0.05 + 1.01x, r = 0.99) and in humans (y = 0.57 + 0.88x, r = 0.93). Estimates of renal cortical blood flow by O-15 water in human volunteers were also linearly correlated with those by N-13 ammonia and the Patlak graphical analysis (y = 0.71 + 0.84x, r = 0.86). Renal cortical blood flow estimates were highly reproducible both with N-13 ammonia and O-15 water measurements in humans. It is concluded that the Patlak graphical analysis with N-13 ammonia dynamic positron emission tomographic imaging renders accurate and reproducible estimates of renal cortical blood flow. Moreover, the graphical analysis approach is 1,000 times faster than the standard model fitting approach and suitable for generating parametric images of renal blood flow in the clinical setting

Anderson impurities in gapless hosts: comparison of renormalization group and local moment approaches

The symmetric Anderson impurity model, with a soft-gap hybridization vanishing at the Fermi level with power law r > 0, is studied via the numerical renormalization group (NRG). Detailed comparison is made with predictions arising from the local moment approach (LMA), a recently developed many-body theory which is found to provide a remarkably successful description of the problem. Results for the `normal' (r = 0) impurity model are obtained as a specific case. Particular emphasis is given both to single-particle excitation dynamics, and to the transition between the strong coupling (SC) and local moment (LM) phases of the model. Scaling characteristics and asymptotic behaviour of the SC/LM phase boundaries are considered. Single-particle spectra are investigated in some detail, for the SC phase in particular. Here, the modified spectral functions are found to contain a generalized Kondo resonance that is ubiquitously pinned at the Fermi level; and which exhibits a characteristic low-energy Kondo scale that narrows progressively upon approach to the SC->LM transition, where it vanishes. Universal scaling of the spectra as the transition is approached thus results. The scaling spectrum characteristic of the normal Anderson model is recovered as a particular case, and is captured quantitatively by the LMA. In all cases the r-dependent scaling spectra are found to possess characteristic low-energy asymptotics, but to be dominated by generalized Doniach-Sunjic tails, in agreement with LMA predictions.Comment: 26 pages, 14 figures, submitted for publicatio

Mathematical stories: Why do more boys than girls choose to study mathematics at AS-level in England?

Copyright @ 2005 Taylor & FrancisIn this paper I address the question: How is it that people come to choose mathematics and in what ways is this process gendered? I draw on the findings of a qualitative research study involving interviews with 43 young people all studying mathematics in post-compulsory education in England. Working within a post-structuralist framework, I argue that gender is a project and one that is achieved in interaction with others. Through a detailed reading of Toni and Claudia’s stories I explore the tensions for young women who are engaging in mathematics, something that is discursively inscribed as masculine, while (understandably) being invested in producing themselves as female. I conclude by arguing that seeing ‘doing mathematics’ as ‘doing masculinity’ is a productive way of understanding why mathematics is so male dominated and by looking at the implications of this understanding for gender and mathematics reform work.This work is funded by the ESR

The utilisation of health research in policy-making: Concepts, examples and methods of assessment

The importance of health research utilisation in policy-making, and of understanding the mechanisms involved, is increasingly recognised. Recent reports calling for more resources to improve health in developing countries, and global pressures for accountability, draw greater attention to research-informed policy-making. Key utilisation issues have been described for at least twenty years, but the growing focus on health research systems creates additional dimensions. The utilisation of health research in policy-making should contribute to policies that may eventually lead to desired outcomes, including health gains. In this article, exploration of these issues is combined with a review of various forms of policy-making. When this is linked to analysis of different types of health research, it assists in building a comprehensive account of the diverse meanings of research utilisation. Previous studies report methods and conceptual frameworks that have been applied, if with varying degrees of success, to record utilisation in policy-making. These studies reveal various examples of research impact within a general picture of underutilisation. Factors potentially enhancing utilisation can be identified by exploration of: priority setting; activities of the health research system at the interface between research and policy-making; and the role of the recipients, or 'receptors', of health research. An interfaces and receptors model provides a framework for analysis. Recommendations about possible methods for assessing health research utilisation follow identification of the purposes of such assessments. Our conclusion is that research utilisation can be better understood, and enhanced, by developing assessment methods informed by conceptual analysis and review of previous studies

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

A Dose-Dependent Relationship between Exposure to a Street-Based Drug Scene and Health-Related Harms among People Who Use Injection Drugs

While the community impacts of drug-related street disorder have been well described, lesser attention has been given to the potential health and social implications of drug scene exposure on street-involved people who use illicit drugs. Therefore, we sought to assess the impacts of exposure to a street-based drug scene among injection drug users (IDU) in a Canadian setting. Data were derived from a prospective cohort study known as the Vancouver Injection Drug Users Study. Four categories of drug scene exposure were defined based on the numbers of hours spent on the street each day. Three generalized estimating equation (GEE) logistic regression models were constructed to identify factors associated with varying levels of drug scene exposure (2–6, 6–15, over 15 hours) during the period of December 2005 to March 2009. Among our sample of 1,486 IDU, at baseline, a total of 314 (21%) fit the criteria for high drug scene exposure (>15 hours per day). In multivariate GEE analysis, factors significantly and independently associated with high exposure included: unstable housing (adjusted odds ratio [AOR] = 9.50; 95% confidence interval [CI], 6.36–14.20); daily crack use (AOR = 2.70; 95% CI, 2.07–3.52); encounters with police (AOR = 2.11; 95% CI, 1.62–2.75); and being a victim of violence (AOR = 1.49; 95 % CI, 1.14–1.95). Regular employment (AOR = 0.50; 95% CI, 0.38–0.65), and engagement with addiction treatment (AOR = 0.58; 95% CI, 0.45–0.75) were negatively associated with high exposure. Our findings indicate that drug scene exposure is associated with markers of vulnerability and higher intensity addiction. Intensity of drug scene exposure was associated with indicators of vulnerability to harm in a dose-dependent fashion. These findings highlight opportunities for policy interventions to address exposure to street disorder in the areas of employment, housing, and addiction treatment

Disrupted Functional Connectivity with Dopaminergic Midbrain in Cocaine Abusers

Background: Chronic cocaine use is associated with disrupted dopaminergic neurotransmission but how this disruption affects overall brain function (other than reward/motivation) is yet to be fully investigated. Here we test the hypothesis that cocaine addicted subjects will have disrupted functional connectivity between the midbrain (where dopamine neurons are located) and cortical and subcortical brain regions during the performance of a sustained attention task. Methodology/Principal Findings: We measured brain activation and functional connectivity with fMRI in 20 cocaine abusers and 20 matched controls. When compared to controls, cocaine abusers had lower positive functional connectivity of midbrain with thalamus, cerebellum, and rostral cingulate, and this was associated with decreased activation in thalamus and cerebellum and enhanced deactivation in rostral cingulate. Conclusions/Significance: These findings suggest that decreased functional connectivity of the midbrain interferes with the activation and deactivation signals associated with sustained attention in cocaine addicts

Effect of Convalescent Plasma on Organ Support-Free Days in Critically Ill Patients With COVID-19: A Randomized Clinical Trial

Importance: The evidence for benefit of convalescent plasma for critically ill patients with COVID-19 is inconclusive. Objective: To determine whether convalescent plasma would improve outcomes for critically ill adults with COVID-19. Design, Setting, and Participants: The ongoing Randomized, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia (REMAP-CAP) enrolled and randomized 4763 adults with suspected or confirmed COVID-19 between March 9, 2020, and January 18, 2021, within at least 1 domain; 2011 critically ill adults were randomized to open-label interventions in the immunoglobulin domain at 129 sites in 4 countries. Follow-up ended on April 19, 2021. Interventions: The immunoglobulin domain randomized participants to receive 2 units of high-titer, ABO-compatible convalescent plasma (total volume of 550 mL ± 150 mL) within 48 hours of randomization (n = 1084) or no convalescent plasma (n = 916). Main Outcomes and Measures: The primary ordinal end point was organ support-free days (days alive and free of intensive care unit-based organ support) up to day 21 (range, -1 to 21 days; patients who died were assigned -1 day). The primary analysis was an adjusted bayesian cumulative logistic model. Superiority was defined as the posterior probability of an odds ratio (OR) greater than 1 (threshold for trial conclusion of superiority >99%). Futility was defined as the posterior probability of an OR less than 1.2 (threshold for trial conclusion of futility >95%). An OR greater than 1 represented improved survival, more organ support-free days, or both. The prespecified secondary outcomes included in-hospital survival; 28-day survival; 90-day survival; respiratory support-free days; cardiovascular support-free days; progression to invasive mechanical ventilation, extracorporeal mechanical oxygenation, or death; intensive care unit length of stay; hospital length of stay; World Health Organization ordinal scale score at day 14; venous thromboembolic events at 90 days; and serious adverse events. Results: Among the 2011 participants who were randomized (median age, 61 [IQR, 52 to 70] years and 645/1998 [32.3%] women), 1990 (99%) completed the trial. The convalescent plasma intervention was stopped after the prespecified criterion for futility was met. The median number of organ support-free days was 0 (IQR, -1 to 16) in the convalescent plasma group and 3 (IQR, -1 to 16) in the no convalescent plasma group. The in-hospital mortality rate was 37.3% (401/1075) for the convalescent plasma group and 38.4% (347/904) for the no convalescent plasma group and the median number of days alive and free of organ support was 14 (IQR, 3 to 18) and 14 (IQR, 7 to 18), respectively. The median-adjusted OR was 0.97 (95% credible interval, 0.83 to 1.15) and the posterior probability of futility (O