Investigating the Genetic Profile of the Amyotrophic Lateral Sclerosis/Frontotemporal Dementia (ALS-FTD) Continuum in Patients of Diverse Race, Ethnicity and Ancestry

Preliminary evidence suggests that commonly used genetic tests may be less likely to identify a genetic etiology for ALS-FTD in patients of underrepresented race, ethnicity, and ancestry (REA), as compared to European REA. Patients of underrepresented REA may therefore be less likely to receive accurate and specific genetic counseling information and less likely to have access to gene-targeted therapies currently in clinical trials. We compiled outcome data from 1911 ALS-FTD patients tested at a commercial laboratory over a seven-year period for C9orf72 hexanucleotide repeat expansion (HRE) alone or C9orf72 and multigene sequencing panel testing. We compared the incidence of pathogenic (P), likely pathogenic (LP), and uncertain variants in C9orf72 and other ALS-FTD genes, as well as age at testing, in patients of different REA. The diagnostic rate in patients of European REA (377/1595, 23.64%) was significantly higher than in patients of underrepresented REA (44/316, 13.92%) (p < 0.001). Patients of European REA were more likely to have the C9orf72 HRE (21.3%) than patients of underrepresented REA (10.4%) (p < 0.001). The overall distribution of positive test outcomes in all tested genes was significantly different between the two groups, with relatively more P and LP variants in genes other than C9orf72 identified in patients of underrepresented REA. The incidence of uncertain test outcomes was not significantly different between patients of European and underrepresented REA. Patients with positive test outcomes were more likely to be younger than those with negative or uncertain outcomes. Although C9orf72 HRE assay has been advocated as the first, and in some cases, only genetic test offered to patients with ALS-FTD in the clinical setting, this practice may result in the reduced ascertainment of genetic ALS-FTD in patients of diverse REA.

Schizophrenia Patients Show Largely Similar Salience Signaling Compared to Healthy Controls in an Observational Task Environment

Recent evidence suggests that the aberrant signaling of salience is associated with psychotic illness. Salience, however, can take many forms in task environments. For example, salience may refer to any of the following: (1) the valence of an outcome, (2) outcomes that are unexpected, called reward prediction errors (PEs), or (3) cues associated with uncertain outcomes. Here, we measure brain responses to different forms of salience in the context of a passive PE-signaling task, testing whether patients with schizophrenia (SZ) showed aberrant signaling of particular types of salience. We acquired event-related MRI data from 29 SZ patients and 23 controls during the performance of a passive outcome prediction task. Across groups, we found that the anterior insula and posterior parietal cortices were activated to multiple different types of salience, including PE magnitude and heightened levels of uncertainty. However, BOLD activation to salient events was not significantly different between patients and controls in many regions, including the insula, posterior parietal cortices, and default mode network nodes. Such results suggest that deficiencies in salience processing in SZ may not result from an impaired ability to signal salience per se, but instead the ability to use such signals to guide future actions. Notably, no between-group differences were observed in BOLD signal changes associated with PE-signaling in the striatum. However, positive symptom severity was found to significantly correlate with the magnitudes of salience contrasts in default mode network nodes. Our results suggest that, in an observational environment, SZ patients may show an intact ability to activate striatal and cortical regions to rewarding and non-rewarding salient events. Furthermore, reduced deactivation of a hypothesized default mode network node for SZ participants with high levels of positive symptoms, following salient events, point to abnormalities in interactions of the salience network with other brain networks, and their potential importance to positive symptoms.

Boosting promotes advantageous risk-taking

Due to the prevalence and importance of choices with uncertain outcomes, it is essential to establish what interventions improve risky decision-making, how they work, and for whom. Two types of low-intensity behavioural interventions are promising candidates: nudges and boosts. Nudges guide people to better decisions by altering how a choice is presented, without restricting any options or modifying the underlying payoff matrix. Boosts, on the other hand, teach people decision strategies that focus their attention on key aspects of the choice, which allows them to make more informed decisions. A recent study compared these two types of interventions and found that boosts worked better for risky choices aimed at maximising gains, whereas nudges worked best for choices aimed at minimising losses. Though intriguing, these findings could not be easily interpreted because of a limitation in the items used. Here we replicate that study, with an extended item set. We find that boosts work by promoting risk-taking when it is beneficial, whereas nudges have a consistent (lesser) impact, regardless of whether risk-taking is beneficial or not. These results suggest that researchers and policymakers should consider the base rate risk propensity of the target population when designing decision-support systems.

Background Uncertainty Can Increase Risk Aversion in Decision Making

Here, we aim to investigate the effect of background uncertainty on decision making systematically. After reviewing the existing empirical studies, we argue that two types of uncertainty should be distinguished: a) ambiguity, i.e., uncertain outcomes without probability information, and b) risk, i.e., uncertainties involving probabilities regarding a negative outcome. We test the hypothesis that the type of uncertainty moderates the effect of background uncertainty on risk preferences. To test our hypothesis, we conducted four experimental studies. In this project we host all analyses scripts, data and linked preregistration of Study 3 and Study 4.

Curiosity or savouring? Information seeking is modulated by both uncertainty and valence

Curiosity is pervasive in our everyday lives, but we know little about the factors that contribute to this drive. In the current study, we assessed whether curiosity about uncertain outcomes is modulated by the valence of the information, i.e. whether the information is good or bad news. Using a lottery task in which outcome uncertainty, expected value and outcome valence (gain versus loss) were manipulated independently, we found that curiosity is overall higher for gains compared with losses and that curiosity increased with increasing outcome uncertainty for both gains and losses. These effects of uncertainty and valence did not interact, indicating that the motivation to reduce uncertainty and the motivation to maximize positive information represent separate, independent drives.

AI under great uncertainty: implications and decision strategies for public policy

Decisions where there is not enough information for a well-informed decision due to unidentified consequences, options, or undetermined demarcation of the decision problem are called decisions under great uncertainty. This paper argues that public policy decisions on how and if to implement decision-making processes based on machine learning and AI for public use are such decisions. Decisions on public policy on AI are uncertain due to three features specific to the current landscape of AI, namely (i) the vagueness of the definition of AI, (ii) uncertain outcomes of AI implementations and (iii) pacing problems. Given that many potential applications of AI in the public sector concern functions central to the public sphere, decisions on the implementation of such applications are particularly sensitive. Therefore, it is suggested that public policy-makers and decision-makers in the public sector can adopt strategies from the argumentative approach in decision theory to mitigate the established great uncertainty. In particular, the notions of framing and temporal strategies are considered.

Migration Decision-Making and Its Key Dimensions

Migration decisions are made in the context of personal needs and desires, and the individuals making these decisions face uncertain outcomes. Information about future opportunities is incomplete, and whether migration turns out to be a personal success or failure depends mostly on circumstances that are ex ante unknown and ex post not fully under the control of the individuals who migrate. This article elaborates on four dimensions of the complex process of migration decision-making: the formation of migration aspirations, the cognitive rules for searching and evaluating information about migratory options, the timing and planning horizons for preparing and realizing migratory decisions, and the locus of control and degree of agency in making migration decisions. We review the current state of evidence and identify opportunities for future empirical research that can help us to better understand these key dimensions of migration decision-making.

Entrepreneurial Beliefs and Agency under Knightian Uncertainty

At the centenary of Frank H. Knight’s Risk, Uncertainty, and Profit (1921), we explore the continuing relevance of Knightian uncertainty to the theory and practice of entrepreneurship. There are three challenges facing such assessment. First, RUP is complex and difficult to interpret. The key but neglected element of RUP is that Knight’s account is not solely about risk and uncertainty as states of nature, but about how an agent’s beliefs about uncertain outcomes and confidence in those beliefs guide their choices. Second, RUP is Knight’s only effort in this area. His subsequent career led elsewhere, so he did not engage with subsequent interpretations of this work. Third, much of the current literature emphasizes that decisions must be different under the two states of nature with a consequent misunderstanding of entrepreneurial agency. This paper addresses each challenge in sequence. First, we explicate Knight’s (1921) approach and explain why that approach is murky. Second, as a complement to Knight’s interpretation, we examine Frank P. Ramsey’s approach to subjective probabilities to help clarify Knight’s murky approach. What links Knight and Ramsey is a shared pragmatism about entrepreneurial agency under uncertainty that depends upon the beliefs about, and confidence in, their judgments of possible outcomes. This Knight-Ramsey approach does not require actor’s behaviors to be determined by the class of uncertain environment (whether risk, uncertainty, or ambiguity) they face. We focus on the response by the entrepreneur to the existence of uncertainty in all its forms. We argue that this reductive account provides a foundation to examine common problems in management, including managerial hubris, the interaction between entrepreneurs and venture capitalists, and the need for experimentation (such as prototyping and market research) in advance of new product and venture launches. Third, we critique current literature that favors epistemic purism about the ontology of risk and uncertainty and ignores Knight-Ramsey pragmatism in meeting uncertainty, such as using formal and informal institutions for uncertainty mitigation. Our account locates Frank Knight’s subtleties in entrepreneurial behavior firmly in the literature on entrepreneurial agency a century later.

A prominent role for precision composting in sustainable agriculture

Compost use in agriculture has the potential to increase the productivity and sustainability of food systems and to mitigate climate change. But the use of diverse compost types in unsuitable biophysical conditions cause uncertain outcomes for crop yields, soil organic carbon (SOC) and nitrous oxide (N2O) emissions. Here, we performed a global meta-analysis with over 2000 observations to determine whether a Precision Composting Strategy (PCS) that aligns suitable composts and application methods with target crop and environment can advance sustainable food production. Eleven key predictors of compost (carbon-to-nutrient ratios, pH, salt content), management (nitrogen supply) and biophysical settings (crop type, soil texture, SOC, pH, temperature, rainfall) determined 80% of the effect on crop yield, SOC, and N2O emissions. We estimate that a PCS could increase global cereal production by 354.5 Tg annually, approximately 1.7-times Africa’s current cereal yield. We further estimate that annual Carbon sequestration could increase by 170.4 Tg Carbon, approximately 20% of the global potential of croplands. This points to a central role of PCS in current and emerging agriculture consistent with the United Nations’ Sustainable Development Goals.

How Does Uncertainty Affect Voters' Preferences?

Rational voters care about outcomes, while parties campaign on policy proposals, the outcomes of which are never perfectly known. Can parties exploit this uncertainty to shape public opinion? This article presents a spatial preference model for policy proposals with uncertain outcomes. It reports the results of a large pre-registered survey experiment that involved presenting respondents with predictions about the effects of three policy proposals. The findings show that respondents update their attitudes to the proposals as their beliefs about outcomes change, and that parties are no less able to influence beliefs than non-partisan experts. Contrary to previous research, respondents discount outcome uncertainty by giving equal weight to conflicting optimistic and pessimistic predictions. The study shows that parties can shape public opinion by influencing voter beliefs, and that voters are not repelled by the uncertainty inherent in conflicting information.