Effects of anxiety on visuospatial pattern discrimination and decision-making processes: what can we learn from brain dynamics ?

Detection and discrimination of visuospatial input involve at least extracting, selecting and encoding relevant information and decision-making processes allowing selecting a response. These two operations are altered, respectively, by attentional mechanisms that change discrimination capacities, and by beliefs concerning the likelihood of uncertain events. Information processing is tuned by the attentional level that acts like a filter on perception, while decision-making processes are weighed by subjective probability of risk. In addition, it has been shown that anxiety could affect the detection of unexpected events through the modification of the level of arousal. Consequently, purpose of this study concerns whether and how decision-making and brain dynamics are affected by anxiety. To investigate these questions, the performance of women with either a high (12) or a low (12) STAI-T (State-Trait Anxiety Inventory, Spielberger, 1983) was examined in a decision-making visuospatial task where subjects have to recognize a target visual pattern from non-target patterns. The target pattern was a schematic image of furniture arranged in such a way as to give the impression of a living room. Non-target patterns were created by either the compression or the dilatation of the distances between objects. Target and non-target patterns were always presented in the same configuration. Preliminary behavioral results show no group difference in reaction time. In addition, visuo-spatial abilities were analyzed trough the signal detection theory for quantifying perceptual decisions in the presence of uncertainty (Green and Swets, 1966). This theory treats detection of a stimulus as a decision-making process determined by the nature of the stimulus and cognitive factors. Astonishingly, no difference in d' (corresponding to the distance between means of the distributions) and c (corresponds to the likelihood ratio) indexes was observed. Comparison of Event-related potentials (ERP) reveals that brain dynamics differ according to anxiety. It shows differences in component latencies, particularly a delay in anxious subjects over posterior electrode sites. However, these differences are compensated during later components by shorter latencies in anxious subjects compared to non-anxious one. These inverted effects seem indicate that the absence of difference in reaction time rely on a compensation of attentional level that tunes cortical activation in anxious subjects, but they have to hammer away to maintain performance.

Decision analysis for the genotype designation in low-template-DNA profiles

What genotype should the scientist specify for conducting a database search to try to find the source of a low-template-DNA (lt-DNA) trace? When the scientist answers this question, he or she makes a decision. Here, we approach this decision problem from a normative point of view by defining a decision-theoretic framework for answering this question for one locus. This framework combines the probability distribution describing the uncertainty over the trace's donor's possible genotypes with a loss function describing the scientist's preferences concerning false exclusions and false inclusions that may result from the database search. According to this approach, the scientist should choose the genotype designation that minimizes the expected loss. To illustrate the results produced by this approach, we apply it to two hypothetical cases: (1) the case of observing one peak for allele xi on a single electropherogram, and (2) the case of observing one peak for allele xi on one replicate, and a pair of peaks for alleles xi and xj, i ≠ j, on a second replicate. Given that the probabilities of allele drop-out are defined as functions of the observed peak heights, the threshold values marking the turning points when the scientist should switch from one designation to another are derived in terms of the observed peak heights. For each case, sensitivity analyses show the impact of the model's parameters on these threshold values. The results support the conclusion that the procedure should not focus on a single threshold value for making this decision for all alleles, all loci and in all laboratories.

A drug administration decision support system

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

Impact of voting advice applications on voters's decision-making

So-called online Voting Advice Applications (VAAs) have become very popular all over Europe. Millions of voters are using them as an assistance to make up their minds for which party they should vote. Despite this popularity there are only very few studies about the impact of these tools on individual electoral choice. On the basis of the Swiss VAA smartvote we present some first findings about the question whether VAAs do have a direct impact on the actual vote of their users. In deed, we find strong evidence that Swiss voters were affected by smartvote. However, our findings are somewhat contrary to the results of previous studies from other countries. Furthermore, the quality of available data for such studies needs to be improved. Future studies should pay attention to both: the improvement of the available data, as well as the explanation of the large variance of findings between the specific European countries.

A decision-making Fokker-Planck model in computational neuroscience

Minimal models for the explanation of decision-making in computational neuroscience are based on the analysis of the evolution for the average firing rates of two interacting neuron populations. While these models typically lead to multi-stable scenario for the basic derived dynamical systems, noise is an important feature of the model taking into account finite-size effects and robustness of the decisions. These stochastic dynamical systems can be analyzed by studying carefully their associated Fokker-Planck partial differential equation. In particular, we discuss the existence, positivity and uniqueness for the solution of the stationary equation, as well as for the time evolving problem. Moreover, we prove convergence of the solution to the the stationary state representing the probability distribution of finding the neuron families in each of the decision states characterized by their average firing rates. Finally, we propose a numerical scheme allowing for simulations performed on the Fokker-Planck equation which are in agreement with those obtained recently by a moment method applied to the stochastic differential system. Our approach leads to a more detailed analytical and numerical study of this decision-making model in computational neuroscience.

Decision making in a human population living sustainably

The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes.

Public particiation and the legitimacy of intergovernmental decision-making : a focus on the World Trade Organization

The legitimacy of the WTO's decision-making process has always been questioned, and many have advocated public participation mechanisms as a remedy. The present study considers the limits and potential of these mechanisms by advancing a conceptual framework, which distinguishes the four 'implementation parameters' of public participation: the goal, the object, the modalities, and the actors. It addresses the issue of legitimacy by considering to what extent, and by virtue of which legal developments, one can see implementing the democratic principle as a goal for public participation in the context of the WTO. By analyzing the institutional structure of the WTO and its different types of decisions, it then outlines how this goal should influence the object and modalities of public participation, which decision-making procedures should be opened to public participation, and how the mechanisms should be implemented in practice. Finally, it suggests speciflrc amendments to existing WTO affangements on public participation

Differential involvement of peroxisome-proliferator-activated receptors alpha and delta in fibrate and fatty-acid-mediated inductions of the gene encoding liver fatty-acid-binding protein in the liver and the small intestine.

Liver fatty-acid-binding protein (L-FABP) is a cytoplasmic polypeptide that binds with strong affinity especially to long-chain fatty acids (LCFAs). It is highly expressed in both the liver and small intestine, where it is thought to have an essential role in the control of the cellular fatty acid (FA) flux. Because expression of the gene encoding L-FABP is increased by both fibrate hypolipidaemic drugs and LCFAs, it seems to be under the control of transcription factors, termed peroxisome-proliferator-activated receptors (PPARs), activated by fibrate or FAs. However, the precise molecular mechanism by which these regulations take place remain to be fully substantiated. Using transfection assays, we found that the different PPAR subtypes (alpha, gamma and delta) are able to mediate the up-regulation by FAs of the gene encoding L-FABP in vitro. Through analysis of LCFA- and fibrate-mediated effects on L-FABP mRNA levels in wild-type and PPARalpha-null mice, we have found that PPARalpha in the intestine does not constitute a dominant regulator of L-FABP gene expression, in contrast with what is known in the liver. Only the PPARdelta/alpha agonist GW2433 is able to up-regulate the gene encoding L-FABP in the intestine of PPARalpha-null mice. These findings demonstrate that PPARdelta can act as a fibrate/FA-activated receptor in tissues in which it is highly expressed and that L-FABP is a PPARdelta target gene in the small intestine. We propose that PPARdelta contributes to metabolic adaptation of the small intestine to changes in the lipid content of the diet.

Spatial predictions of phylogenetic diversity in conservation decision making.

Considering genetic relatedness among species has long been argued as an important step toward measuring biological diversity more accurately, rather than relying solely on species richness. Some researchers have correlated measures of phylogenetic diversity and species richness across a series of sites and suggest that values of phylogenetic diversity do not differ enough from those of species richness to justify their inclusion in conservation planning. We compared predictions of species richness and 10 measures of phylogenetic diversity by creating distribution models for 168 individual species of a species-rich plant family, the Cape Proteaceae. When we used average amounts of land set aside for conservation to compare areas selected on the basis of species richness with areas selected on the basis of phylogenetic diversity, correlations between species richness and different measures of phylogenetic diversity varied considerably. Correlations between species richness and measures that were based on the length of phylogenetic tree branches and tree shape were weaker than those that were based on tree shape alone. Elevation explained up to 31% of the segregation of species rich versus phylogenetically rich areas. Given these results, the increased availability of molecular data, and the known ecological effect of phylogenetically rich communities, consideration of phylogenetic diversity in conservation decision making may be feasible and informative.

Involvement of the RNA-binding protein ARE/poly(U)-binding factor 1 (AUF1) in the cytotoxic effects of proinflammatory cytokines on pancreatic beta cells.

AIMS/HYPOTHESIS: Chronic exposure of pancreatic beta cells to proinflammatory cytokines leads to impaired insulin secretion and apoptosis. ARE/poly(U)-binding factor 1 (AUF1) belongs to a protein family that controls mRNA stability and translation by associating with adenosine- and uridine-rich regions of target messengers. We investigated the involvement of AUF1 in cytokine-induced beta cell dysfunction. METHODS: Production and subcellular distribution of AUF1 isoforms were analysed by western blotting. To test for their role in the control of beta cell functions, each isoform was overproduced individually in insulin-secreting cells. The contribution to cytokine-mediated beta cell dysfunction was evaluated by preventing the production of AUF1 isoforms by RNA interference. The effect of AUF1 on the production of potential targets was assessed by western blotting. RESULTS: MIN6 cells and human pancreatic islets were found to produce four AUF1 isoforms (p42>p45>p37>p40). AUF1 isoforms were mainly localised in the nucleus but were partially translocated to the cytoplasm upon exposure of beta cells to cytokines and activation of the ERK pathway. Overproduction of AUF1 did not affect glucose-induced insulin secretion but promoted apoptosis. This effect was associated with a decrease in the production of the anti-apoptotic proteins, B cell leukaemia/lymphoma 2 (BCL2) and myeloid cell leukaemia sequence 1 (MCL1). Silencing of AUF1 isoforms restored the levels of the anti-apoptotic proteins, attenuated the activation of the nuclear factor-κB (NFκB) pathway, and protected the beta cells from cytokine-induced apoptosis. CONCLUSIONS/INTERPRETATION: Our findings point to a contribution of AUF1 to the deleterious effects of cytokines on beta cell functions and suggest a role for this RNA-binding protein in the early phases of type 1 diabetes.

Sentinel lymph node involvement and a high Breslow index are independent factors of risk for early relapse of melanoma.

AIM: The clinical relevance of sentinel lymph node (SLN) analysis was evaluated prospectively and compared with other known risk factors of relapse in early stage melanoma. METHODS: Surgery was guided by lymphoscintigraphy, blue dye and gamma probe detection. SLN were analysed by haematoxylin eosin (HE) histochemistry and multimarker immunohistochemistry (IHC). Disease free survival (DFS) was evaluated with Kaplan-Meier plots according to different parameters and Cox analyses of variance. RESULTS: From 210 patients a total of 381 SLN were excised. Lymphoscintigraphy identified all excised SLN with only 2 false positive lymphatic lakes. Fifty patients (24%) had tumour positive SLN. With a mean follow-up of 31.3 months, 29 tumour recurrences were observed, 19 (38%) in 50 SLN positive and 10 (6%) in 160 SLN negative patients. Strong predictive factors for early relapse (p < 0.0005) were SLN positivity and a high Breslow index. CONCLUSION: SLN tumour positivity is an independent factor of high risk for early relapse with a higher power of discrimination than the Breslow index.

Decision-theoretic analysis of forensic sampling criteria using Bayesian decision networks

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.