Precise Hypotheses Research Articles

Omics and the metabolic function of insect-microbial symbioses.

Omic studies of metabolic interactions between insects and their microbial symbionts enable us to construct precise hypotheses, especially regarding the metabolic services provided by microbial partners and the identity of metabolites exchanged between microorganisms and the insect host. Valuable sources of information include the complement of metabolism-related genes in the microbial partners, and differences in the abundance of transcripts, proteins or metabolites, either between microbe-bearing organs and the whole body or between insects bearing and lacking microbial symbionts. Hypotheses generated from omic data can, most productively, be tested by experiments using reverse genetics for precise manipulation of the gene expression.

Global Mental Health and Adolescent Anxiety: Kin, Care and Struggle in New Mexico.

While recent developments within the field of global mental health have illuminated the reality of serious mental health difficulties worldwide, particularly in low-income settings, research that focuses on children and adolescents remains underdeveloped. This is especially the case with respect to ethnographic studies of lived experience of adolescents diagnosed with serious mental health conditions. Drawing from an interdisciplinary study of adolescents in New Mexico who were afflicted with a broad range of disorders according to contemporary research diagnostic criteria, this article focuses on anxiety-related conditions with respect to subjective experience and social-ecological contexts of living with such conditions. We offer preliminary observations regarding the value of linking ethnographic and research diagnostic data to address questions of resilience, endurance, capacity and struggle. These observations are intended as the basis for the formulation of more precise hypotheses about adolescent anxiety, kin, and care under conditions of structural violence marked by psychological, residential, and intergenerational adversity.

The Virtues of Nonviolent Struggle

There is an emerging consensus in the study of mass-based political resistance that successful nonviolent campaigns leave in their wake political conditions suitable for democracy and stability. The following paper subjects this claim to closer scrutiny. Using theory grounded in the study of conflict, revolution, and democratic transition, we make the case that a resistance campaign’s duration is an important driver of its downstream effects. Sudden victory is likely to leave important questions about the balance of capabilities between and within interest groups unanswered. It may also create a destabilizing legitimacy deficit for the entity endowed with the status of incumbency once calm is restored. Further complicating matters, we argue, is the fact that the benefits of struggling en route to victory are not distributed equally across violent and nonviolent movements. To test our precise hypotheses on these points, we examine four post-campaign outcome variables in a large-N framework: levels of democracy, electoral manipulation, coup detat attempts, and violent conflict. With the aid of flexible modeling and sensitivity analysis, we make the case that campaign duration significantly moderates the long-term political effects of mass-based nonviolent resistance, with harder-fought victories yielding more positive outcomes.

How camouflage works.

For camouflage to succeed, an individual has to pass undetected, unrecognized or untargeted, and hence it is the processing of visual information that needs to be deceived. Camouflage is therefore an adaptation to the perception and cognitive mechanisms of another animal. Although this has been acknowledged for a long time, there has been no unitary account of the link between visual perception and camouflage. Viewing camouflage as a suite of adaptations to reduce the signal-to-noise ratio provides the necessary common framework. We review the main processes in visual perception and how animal camouflage exploits these. We connect the function of established camouflage mechanisms to the analysis of primitive features, edges, surfaces, characteristic features and objects (a standard hierarchy of processing in vision science). Compared to the commonly used research approach based on established camouflage mechanisms, we argue that our approach based on perceptual processes targeted by camouflage has several important benefits: specifically, it enables the formulation of more precise hypotheses and addresses questions that cannot even be identified when investigating camouflage only through the classic approach based on the patterns themselves. It also promotes a shift from the appearance to the mechanistic function of animal coloration.This article is part of the themed issue 'Animal coloration: production, perception, function and application'.

Strategic Retirement in Comparative Perspective: Supreme Court Justices in Presidential Regimes

AbstractStudents of judicial behavior debate whether justices time their retirement to allow for the nomination of like-minded judges. We formalize the assumptions of strategic retirement theory and derive precise hypotheses about the conditions that moderate the effect of partisan incentives on judicial retirements. The empirical implications are tested with evidence for Supreme Court members under democracies and dictatorships in six presidential regimes between 1900 and 2004. The theory of strategic retirement finds limited support in the United States and elsewhere. We conclude that researchers should emphasize “sincere” motivations for retirement, progressive political ambitions, and—crucial in weakly institutionalized legal systems—political pressures.

Performance Gaps and Managerial Decisions: A Bayesian Decision Theory of Managerial Action

An extensive literature finds that managerial decisions matter for the performance of public organizations, yet little attention has been devoted to why managers make the decisions that they do. This article builds a theory of public management decision making based on the simple assumption that managers are concerned with performance and the performance gaps of their organization. Using a logic borrowed from bounded rationality and Bayesian decision theory, we theorize a set of prior expectations. Whether the organization meets these expectations or fails to do so is then used to specify a series of precise hypotheses about when managers make a variety of decisions including when to seek additional information, take risks, decentralize the organization, determine goals, or select a managerial strategy as well as other managerial actions. The logic of the theory can easily be extended to decisions about selecting goals or managerial strategy. We then extend the basic theory by considering multiple goals, hierarchy, and alternative theoretical approaches.

The Evolution of Interactivity - New Insights into Innovation System Change and the Role of the State

The theoretical framework of innovation systems has been intensively studied over the last decades. The analysis of the network of interactions between institutions, actors, and processes appeared promising to derive valid hypotheses about the necessary preconditions and accelerating factors for and throughout the emergence of innovation. Few studies, however, succeeded to transform the theoretical framework into a model and even fewer took into account the evolutionary (time-related) character of such a complex system. This article follows two main questions: The first question is of a theoretical or methodological nature and is focused on how innovation systems can be designed in a way that makes them a workable model for future research. The main challenge lies in the generation of precise hypotheses that enable the researcher to trace technological evolution and the surrounding environment over time. This implies that the underlying theoretical assumptions of innovation systems have to be operationalized. This paper follows on the existing approaches and compares their merit to extract a promising concept. This concept is being coupled with existing theoretical assumptions on innovation policy to tackle the second question in this article about how to measure the political actors' influence on the innovation process. In essence, it becomes evident that innovation systems demand different political support in different development phases. These differences mainly refer to the level of intervention (from local to international) and types of interventions (e.g., direct investment, regulatory or systemic interventions). The article shows where in the system's development process certain types of political interventions are likely to be necessary and when private entrepreneurs and market mechanisms do not need this (or any) type of support. Finally, it sheds light on the influence of system-external events on the innovation system's development. It is shown that a consequential impact on the development can be spotted mainly under the influence of external macro events. Interestingly, these influences are on the one hand translated into the system via political action and on the other hand impact quite differently on the respective innovation systems, based on the system's state of evolution.

Optimization Models for Reaction Networks: Information Divergence, Quadratic Programming and Kirchhoff’s Laws

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.

Single-Neuron Correlates of Atypical Face Processing in Autism

People with autism spectrum disorder (ASD) show abnormal processing of faces. A range of morphometric, histological, and neuroimaging studies suggest the hypothesis that this abnormality may be linked to the amygdala. We recorded data from single neurons within the amygdalae of two rare neurosurgical patients with ASD. While basic electrophysiological response parameters were normal, there were specific and striking abnormalities in how individual facial features drove neuronal response. Compared to control patients, a population of neurons in the two ASD patients responded significantly more to the mouth, but less to the eyes. Moreover, we found a second class of face-responsive neurons for which responses to faces appeared normal. The findings confirm the amygdala's pivotal role in abnormal face processing by people with ASD at the cellular level and suggest that dysfunction may be traced to a specific subpopulation of neurons with altered selectivity for the features of faces.

Comments on: An updated review of Goodness-of-Fit tests for regression models

We discuss the following two particular aspects of the paper of Gonzalez-Manteiga and Crujeiras ( 10.1007/s11749-013-0327-5 ): First, what changes if the null hypothesis is non- or semiparametric? For example, Rodriguez-Poo et al. (A practical test for misspecification in regression: functional form, separability, and distribution. Econom. Theory, 2013, under revision) considered optimal rates of adaptive nonparametric tests when the null model is semiparametric. A second, though related question is, how serious are the bandwidth and calibration problems? Sperlich (On the choice of regularization parameters in specification testing: a critical discussion. Empir. Econ., 2013, forthcoming) has shown that the unsolved bandwidth selection problems, in particular when calibrating, render nonparametric specification tests useless in practice. Two additional questions are only raised briefly and concern (a) the computational aspects, and (b) the problem that asymptotically, nonparametric omnibus tests might reject almost any null hypothesis as probably no parametric or semiparametric model is 100 % correct. But it is maybe a reasonable and useful approximation. To this aim we recall the idea of testing the problem of so-called ‘precise hypotheses’ as outlined in Dette (Ann. Stat. 27:1012–1040, 1999) for nonparametric goodness-of-fit tests.

The Neuropsychology of Sex Offenders

Typically, neuropsychological studies of sex offenders have grouped together different types of individuals and different types of measures. This is why results have tended to be nonspecific and divergent across studies. Against this background, the authors undertook a review of the literature regarding the neuropsychology of sex offenders, taking into account subgroups based on criminological theories. They also conducted a meta-analysis of the data to demonstrate the cognitive heterogeneity of sex offenders statistically. Their main objective was to test the hypothesis to the effect that the neuropsychological deficits of sex offenders are not broad and generalized compared with specific subgroups of participants based on specific measures. In all, 23 neuropsychological studies reporting data on 1,756 participants were taken into consideration. As expected, a highly significant, broad, and heterogeneous overall effect size was found. Taking subgroups of participants and specific cognitive measures into account significantly improved homogeneity. Sex offenders against children tended to obtain lower scores than did sex offenders against adults on higher order executive functions, whereas sex offenders against adults tended to obtain results similar to those of non-sex offenders, with lower scores in verbal fluency and inhibition. However, it is concluded that neuropsychological data on sex offenders are still too scarce to confirm these trends or to test more precise hypotheses. For greater clinical relevance, future neuropsychological studies should consider specific subgroups of participants and measures to verify the presence of different cognitive profiles.

Leopard spot variation: What dialects have to say about variation, change and acquisition

AbstractIn this work I intend to discuss some general properties of dialectal variation which have import on the theory of language acquisition. I will first briefly discuss whether dialectal variation is qualitatively different from typological variation, a prediction made by a theory which assumes that there exist macro‐ and microparameters, as dialectal variation should only display microparameters. As this is not the case, I argue against the idea of a hierarchical order of parameters that the child has to set progressively in language acquisition, and in favor of an idea of a constellation of abstract properties connected by the fact that they share some primitive components that cluster to form what we call “formal features” in a way similar to how articulatory features cluster to combine phonemes. The second part of the article deals with what is indeed peculiar to dialectal variation, namely the type of distribution called “leopard spots” by traditional dialectologists and puts forth the idea that it can be used to formulate more precise hypotheses on the structure of functional items inside a framework like the cartographic/nano‐syntax one.

Full Bayesian Analysis for a Model of Tail Dependence

The family of the asymmetric logistic copulas appears naturally in modeling tail dependence. Within this family, some well-known models, as independence and logistic dependence, define precise hypotheses, having zero posterior probability for an absolute continuous posterior distribution. We show that the e-value associated to the Full Bayesian Significance Test has a good performance in non standard dependence problems, obtaining posterior estimates and predictive distributions. The analysis proposed is illustrated with two examples: (1) monthly sea level maxima at Newlyn and Sheerness, England (1990–2005) and (2) AIDS rates related to an educational indicator in U.S. Census Bureau (2007). We validate the inferences obtained through simulated data.

Abnormal repetitive behaviours: shared phenomenology and pathophysiology

Self-injurious behaviour (SIB) is a devastating problem observed in individuals with various neurodevelopmental disorders, including specific genetic syndromes as well as idiopathic intellectual and developmental disability. Although an increased prevalence of SIB has been documented in specific genetic mutations, little is known about the neurobiological basis of SIB. This makes vulnerability assessment and pharmacological treatment incredibly challenging. Here we review evidence that SIB and other repetitive, invariant behaviours, such as stereotypy, compulsions and tics, share many phenotypic similarities, are often co-morbidly expressed and have common inducing conditions. This argues for shared or overlapping pathophysiology. As much more is known about the neurobiology of these related disorders, this should make the neurobiology of SIB a more tractable problem. Stereotypy, compulsions and tics are diagnostic for disorders that have received focused neurobiological investigation (autism, obsessive compulsive disorder, Tourette syndrome, respectively). In addition, animal models of these repetitive behaviours have been well characterised. Collectively, these studies have found that cortical basal ganglia circuitry dysfunction mediates repetitive behaviour. Moreover, these studies provide more detailed information and potentially testable hypotheses about specific aspects of the circuitry that may be operative in SIB. We can use available information from clinical and animal models to make more precise hypotheses regarding the particular pathophysiology driving SIB. The results of testing such hypotheses should generate pharmacological strategies that may prove efficacious in reducing SIB.

De Rham Theory for Tame Stacks and Schemes with Linearly Reductive Singularities

We prove that the Hodge-de Rham spectral sequence for smooth proper tame Artin stacks in characteristic p (as defined by Abramovich, Olsson, and Vistoli) which lift mod p degenerates. We push the result to the coarse spaces of such stacks, thereby obtaining a degeneracy result for schemes which are etale locally the quotient of a smooth scheme by a finite linearly reductive group scheme. Given a scheme X smooth and proper over a field k, the cohomology of the algebraic de Rham complex ΩX/k is an important invariant of X, which, when k = C, recovers the singular cohomology of X(C). When the Hodge-de Rham spectral sequence E 1 = H (ΩX/k)⇒ H (ΩX/k) degenerates, the invariants dimkH (ΩX/k) break up into sums of the finer invariants dimkH (ΩX/k). The degeneracy of this spectral sequence for smooth proper schemes in characteristic 0 was first proved via analytic methods. It was not until much later that Faltings [Fa] gave a purely algebraic proof by means of p-adic Hodge Theory. Soon afterwards, Deligne and Illusie [DI] gave a substantially simpler algebraic proof by showing that the degeneracy of the Hodge-de Rham spectral sequence in characteristic 0 is implied by its degeneracy for smooth proper schemes in characteristic p that lift mod p2. Their method therefore extends de Rham Theory to the class of smooth proper schemes in positive characteristic which lift. A version of de Rham Theory also exists for certain singular schemes. Steenbrink showed [St, Thm 1.12] that if k is a field of characteristic 0, M a proper k-scheme with quotient singularities, and j : M0 ↪→ M its smooth locus, then the hypercohomology spectral sequence E 1 = H (j∗Ω s M0/k)⇒ H (j∗Ω • M0/k) degenerates and H(j∗Ω • M0/k) agrees with H n(M(C),C) when k = C. As we explain in this paper, a version of this theorem is true in positive characteristic as well: if k has characteristic p and M is proper with quotient singularities by groups whose orders are prime to p, then the above spectral sequence degenerates for s+ t < p provided a certain liftability criterion is satisfied (see Theorem 1.15 for precise hypotheses). As a warm-up for the rest of the paper, we begin by showing how Steenbrink’s result can be reproved using the theory of stacks. The idea is as follows. Every scheme M as above is the coarse space of a smooth Deligne-Mumford stack X whose stacky structure is supported at the singular locus of M . We show that the de Rham cohomology H(ΩX/k) of the stack agrees with H(j∗Ω • M0/k). After checking that the method of Deligne-Illusie extends to Deligne-Mumford stacks, we recover Steenbrink’s result as a consequence of the degeneracy of the Hodge-de Rham spectral sequence for X. The above extends de Rham Theory to the class of schemes with quotient singularities by groups whose orders are prime to the characteristic, but in positive characteristic this class of schemes contains certain “gaps” and it is natural to ask if de Rham Theory can be 2010 Mathematics Subject Classification. 14A20, 14F40.

Constructive Verification, Empirical Induction, and Falibilist Deduction: A Threefold Contrast

This article explores some open questions related to the problem of verification of theories in the context of empirical sciences by contrasting three epistemological frameworks. Each of these epistemological frameworks is based on a corresponding central metaphor, namely: (a) Neo-empiricism and the gambling metaphor; (b) Popperian falsificationism and the scientific tribunal metaphor; (c) Cognitive constructivism and the object as eigen-solution metaphor. Each of one of these epistemological frameworks has also historically co-evolved with a certain statistical theory and method for testing scientific hypotheses, respectively: (a) Decision theoretic Bayesian statistics and Bayes factors; (b) Frequentist statistics and p-values; (c) Constructive Bayesian statistics and e-values. This article examines with special care the Zero Probability Paradox (ZPP), related to the verification of sharp or precise hypotheses. Finally, this article makes some remarks on Lakatos’ view of mathematics as a quasi-empirical science.

A Role for Medical Anthropology in Complex Systems Approaches to Health Disparities?

The recent article by Diez Roux1 calls for the application of complex systems approaches to specific health disparities research. Methodologically, the author argues that virtual worlds (i.e., complex modeling and computer simulations) can help identify how lower processes scale up and interact with higher-level factors to manifest in patterns of health and disease at the population level. Such approaches can elucidate underlying leverage points that have caused policy resistance. While Diez Roux is correct that systems approaches demand interdisciplinary cooperation, her focus on virtual worlds minimizes an area of formidable value to systems-based health disparities research: the social sciences. Specifically, a discipline such as medical anthropology—whose practitioners immerse themselves in the beliefs, values, and norms of human groups to understand the concepts and causes of health and disease2—would seem to have an intuitive role to play in systems thinking. Any public health researcher interested in exploring health disparities in a discreet community would benefit from the involvement of anthropologists who have undertaken ethnography in that population.3 Anthropologists can help shape more precise research questions and hypotheses based on an understanding of how people on the ground construct their worldviews in relation to variables of interest (e.g., access to healthy foods, physical activity, sources of stress, peer family norms). Their perspectives can provide deeper conceptualization of how those variables are imbued by class, race, and gender, and the degree to which they might interrelate. Medical anthropologists would also be uniquely positioned to help translate knowledge about leverage points that emerge from systems-based modeling into culturally sensitive practice at the community level, which could further reduce policy resistance. Ultimately, Diez Roux's forceful charge to apply systems approaches to health disparities research is a much-needed message in a complex world fraught with chronic, infectious, and other diseases. But, in trying to understand and influence the complicated systems that affect human health, we should take care not to overestimate the power of technology or underestimate the valuable perspective of those devoted to the study of human beings.

The Attentional Routing Circuit: Receptive Field Modulation Through Nonlinear Dendritic Interactions

AbstractWe present a model of attentional routing called the Attentional Routing Circuit (ARC) that extends an existing model of spiking neurons with dendritic nonlinearities. Specifically, we employ the Poirazi et al. (2003) pyramidal neuron in a population coding framework. ARC demonstrates that the dendritic nonlinearities can be exploited to result in selective routing, with a decrease in the number of cells needed by a factor of ~5 as compared with a linear dendrite model.Routing of attended information occurs through the modulation of feedforward visual signals by a cortical control signal specifying the location and size of the attended target. The model is fully specified in spiking single cells. Our approach differs from past work on shifter circuits by having more efficient control, and using a more biologically detailed substrate. Our approach differs from existing models that use gain fields by providing precise hypotheses about how the control signals are generated and distributed in a hierarchical model in spiking neurons. Further, the model accounts for numerous experimental findings regarding the timing, strength and extent of attentional modulation in ventral stream areas, and the perceived contrast enhancement of attended stimuli.To further demonstrate the plausibility of ARC, it is applied to the attention experiments of Womelsdorf et al. (2008) and tested in detail. For the simulations, the model has only two free parameters that influence its ability to match the experimental data, and without fitting, we show that it can account for the experimental observations of changes in receptive field (RF) gain and position with attention in macaques. In sum, the model provides an explanation of RF modulation as well as testable predictions about nonlinear cortical dendrites and attentional changes of receptive field properties.

Population-Based Resequencing of Experimentally Evolved Populations Reveals the Genetic Basis of Body Size Variation in Drosophila melanogaster

Body size is a classic quantitative trait with evolutionarily significant variation within many species. Locating the alleles responsible for this variation would help understand the maintenance of variation in body size in particular, as well as quantitative traits in general. However, successful genome-wide association of genotype and phenotype may require very large sample sizes if alleles have low population frequencies or modest effects. As a complementary approach, we propose that population-based resequencing of experimentally evolved populations allows for considerable power to map functional variation. Here, we use this technique to investigate the genetic basis of natural variation in body size in Drosophila melanogaster. Significant differentiation of hundreds of loci in replicate selection populations supports the hypothesis that the genetic basis of body size variation is very polygenic in D. melanogaster. Significantly differentiated variants are limited to single genes at some loci, allowing precise hypotheses to be formed regarding causal polymorphisms, while other significant regions are large and contain many genes. By using significantly associated polymorphisms as a priori candidates in follow-up studies, these data are expected to provide considerable power to determine the genetic basis of natural variation in body size.

Introduction to the Special Topic Embodied and Grounded Cognition

Introduction: In the last 10–15 years, the embodied and grounded (E and G) cognition approach has become widespread in all fields related to cognitive (neuro) science, and a lot of evidence has been collected. The approach proposes that cognitive activity is grounded in sensory–motor processes and situated in specific contexts and situations. This special topic had two aims: first, give an idea of the field in its broadness. Second, focus on some challenges for E and G theories. The first important challenge is to account for understanding abstract concepts and words. Evidence on the representation of concrete concepts is compelling, whereas evidence on abstract concepts is still scarce and limited to restricted domains. A second important challenge concerns the role of computational models. E and G theories of cognition need to formulate more precise hypotheses, and models help to constrain and specify in more detail the predictions and the claims advanced.