Accounting for model error in strong-constraint 4DVar data assimilation

The strong constraint formulation of four-dimensional variational data assimilation (4DVar) assumes that the model used in the process perfectly describes the true dynamics of the system. However, this assumption often does not hold and the use of an erroneous model in strong constraint 4DVar can lead to a sub-optimal estimation of the initial conditions. We show how the presence of model error can be correctly accounted for in strong constraint 4D-Var by allowing for errors in both the observations and the model when considering the statistics of the innovation vector. We demonstrate that when these combined model error and observation error statistics are used in place of the standard observation error statistics in the strong constraint formulation of 4DVar, a statistically more accurate estimate of the initial state is obtained. The calculation of the combined model error and observation error statistics requires the specification of model error covariances, which in practice are often unknown. We present a method to estimate the combined statistics from innovation data that does not require explicit specification of the model error covariances. Numerical experiments using the linear advection equation and a simple nonlinear coupled model demonstrate the success of the new methods in reducing the error in the estimate of the initial state, even in the case when only the uncorrelated part of the model error is accounted for

Regulating Craving by Anticipating Positive and Negative Outcomes: A Multivariate Pattern Analysis and Network Connectivity Approach

During self-control, we may resist short-term temptations in order to reach a favorable future (e.g., resisting cake to stay healthy). The neural basis of self-control is typically attributed to “cold,” unemotional cognitive control mechanisms which inhibit affect-related regions via the prefrontal cortex (PFC). Here, we investigate the neural underpinnings of regulating cravings by mentally evoking the positive consequences of resisting a temptation (e.g., being healthy) as opposed to evoking the negative consequences of giving in to a temptation (e.g., becoming overweight). It is conceivable that when using these types of strategies, regions associated with emotional processing [e.g., striatum, ventromedial prefrontal cortex (vmPFC)] are involved in addition to control-related prefrontal and parietal regions. Thirty-one participants saw pictures of unhealthy snacks in the fMRI scanner and, depending on the trial, regulated their craving by thinking of the positive consequences of resisting, or the negative consequences of not resisting. In a control condition, they anticipated the pleasure of eating and thus, allowed the craving to occur (now-condition). In line with previous studies, we found activation of a cognitive control network during self-regulation. In the negative future thinking condition, the insula was more active than in the positive condition, while there were no activations that were stronger in the positive (> negative) future thinking condition. However, additionally, multivariate pattern analysis showed that during craving regulation, information about the valence of anticipated emotions was present in the vmPFC, the posterior cingulate cortex (PCC) and the insula. Moreover, a network including vmPFC and PCC showed higher connectivity during the positive (> negative) future thinking condition. Since these regions are often associated with affective processing, these findings suggest that “hot,” affective processes may, at least in certain circumstances, play a role in self-control

The kinetics of antibody binding to Plasmodium falciparum VAR2CSA PfEMP1 antigen and modelling of PfEMP1 antigen packing on the membrane knobs

<p>Abstract</p> <p>Background</p> <p>Infected humans make protective antibody responses to the PfEMP1 adhesion antigens exported by <it>Plasmodium falciparum </it>parasites to the erythrocyte membrane, but little is known about the kinetics of this antibody-receptor binding reaction or how the topology of PfEMP1 on the parasitized erythrocyte membrane influences antibody association with, and dissociation from, its antigenic target.</p> <p>Methods</p> <p>A Quartz Crystal Microbalance biosensor was used to measure the association and dissociation kinetics of VAR2CSA PfEMP1 binding to human monoclonal antibodies. Immuno-fluorescence microscopy was used to visualize antibody-mediated adhesion between the surfaces of live infected erythrocytes and atomic force microscopy was used to obtain higher resolution images of the membrane knobs on the infected erythrocyte to estimate knob surface areas and model VAR2CSA packing density on the knob.</p> <p>Results</p> <p>Kinetic analysis indicates that antibody dissociation from the VAR2CSA PfEMP1 antigen is extremely slow when there is a high avidity interaction. High avidity binding to PfEMP1 antigens on the surface of <it>P. falciparum</it>-infected erythrocytes in turn requires bivalent cross-linking of epitopes positioned within the distance that can be bridged by antibody. Calculations of the surface area of the knobs and the possible densities of PfEMP1 packing on the knobs indicate that high-avidity cross-linking antibody reactions are constrained by the architecture of the knobs and the large size of PfEMP1 molecules.</p> <p>Conclusions</p> <p>High avidity is required to achieve the strongest binding to VAR2CSA PfEMP1, but the structures that display PfEMP1 also tend to inhibit cross-linking between PfEMP1 antigens, by holding many binding epitopes at distances beyond the 15-18 nm sweep radius of an antibody. The large size of PfEMP1 will also constrain intra-knob cross-linking interactions. This analysis indicates that effective vaccines targeting the parasite's vulnerable adhesion receptors should primarily induce strongly adhering, high avidity antibodies whose association rate constant is less important than their dissociation rate constant.</p

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

A 20-year experiment on the effects of deer and hare on eastern hemlock regeneration

Eastern hemlock (Tsuga canadensis (L.) Carrière) is a shade-tolerant, slow-growing tree once common in forests across the Great Lakes region. It was heavily exploited in the late 19th and early 20th centuries and now experiences limited regeneration across much of its range. This failure to regenerate has been ascribed to poor seedbed conditions, insufficient canopy openings, warmer climate, and browsing by white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)) or snowshoe hare (Lepus americanus Erxleben, 1777). To test whether deer or hare limit hemlock regeneration, we studied >2000 hemlock seedlings inside and adjacent to experimental deer exclosures at 59 sites randomly distributed across hemlock and hemlock-component stands in northern Wisconsin and the western Upper Peninsula of Michigan in the United States. We monitored local deer and hare abundance, seedling growth, and seedling survival for 20 years. Two First Nations reservations showed lower deer density and greater survival and growth of unprotected seedlings than three national forests of the United States. Cohorts of hemlock seedlings protected from deer survived at a rate four times higher than those exposed to deer (59.3% vs. 15.0%) and shared a combined height 5.2 times greater. Hare densities significantly affected seedling survival only within exclosures. This extensive, long-term study identifies deer as the primary factor constraining hemlock regeneration in the region.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

GraphVar 2.0: a user-friendly toolbox for machine learning on functional connectivity measures

International audienceBackground:We previously presented GraphVar as a user-friendly MATLAB toolbox for comprehensive graph analyses of functional brain connectivity. Here introduce a comprehensive extension of the toolbox allowing users to seamlessly explore easily customizable decoding models across functional connectivity measures as well as additional features.New Method: GraphVar 2.0 provides machine learning (ML) model construction, validation and exploration. Machine learning can be performed across any combination of graph measures and additional variables, allowing for a flexibility in neuroimaging applications.Results: In addition to previously integrated functionalities, such as network construction and graph-theoretical analyses of brain connectivity with a high-speed general linear model (GLM), users can now perform customizable ML across connectivity matrices, graph measures and additionally imported variables. The new extension also provides parametric and nonparametric testing of classifier and regressor performance, data export, figure generation and high quality export.Comparison with existing methods: Compared to other existing toolboxes, GraphVar 2.0 offers (1) comprehensive customization, (2) an all-in-one user friendly interface, (3) customizable model design and manual hyperparameter entry, (4) interactive results exploration and data export, (5) automated queue system for modelling multiple outcome variables within the same session, (6) an easy to follow introductory review.Conclusions: GraphVar 2.0 allows comprehensive, user-friendly exploration of encoding (GLM) and decoding (ML) modelling approaches on functional connectivity measures making big data neuroscience readily accessible to a broader audience of neuroimaging investigators

Anticipating the good and the bad : a study on the neural correlates of bivalent emotion anticipation and their malleability via attentional deployment

In everyday life, we often deliberate about affective outcomes of decisions which can be described as ambivalent; i.e. positive and negative at the same time. For example, when looking forward to meet a dear friend at her/his favorite concert although one dislikes the music that is being performed. Thus, anticipation of bivalent emotions and their volitional regulation is an important ingredient of everyday choices. However, previous studies investigating neural substrates involved in anticipating emotional events mostly focused on anticipating either negative emotions (punishment) or positive emotions (reward) in isolation, thus inducing either of them separately. Furthermore, these studies rather focused on the effortful down-regulation of affect (i.e. reducing negative or positive affect), whereas such conflict situations may also require us to deploy attention on and thereby upregulate anticipated emotions in order to resolve a decision conflict (e.g., by focusing on positive consequences while orienting away from negative consequences of that same situation). To address this gap, we performed a series of three fMRI-experiments using simple visual and auditory stimuli in order to (i) determine the neural correlates involved when anticipating a bivalent affective outcome that is both positive and negative at the same time – related to a conflict situation and (ii) investigate their malleability during anticipation via voluntary emotion regulation using attentional focusing. In these studies, we (i) demonstrate that brain areas involved in anticipating positive (ventral striatum) and negative (anterior insula) emotional events are co-activated when anticipating the occurrence of both punishment and reward at the same time and (ii) provide evidence that attention on either the positive or the negative correlates with a shift in activations of these co-activated neural networks and associated anticipated emotions towards either the positive (increased activity in ventral striatum, ventromedial prefrontal cortex, posterior cingulate cortex) or the negative (increased activity in insula) aspect of the upcoming bivalent outcome. In summary, we provide self-report and neural evidence for the assumption that affective brain systems associated with the processing of bivalent anticipated emotions can be voluntarily controlled by cognitive emotion regulation strategies