TL;DR: A working hypothesis is formed that epistasis is a ubiquitous component of the genetic architecture of common human diseases and that complex interactions are more important than the independent main effects of any one susceptibility gene.
Abstract: There is increasing awareness that epistasis or gene-gene interaction plays a role in susceptibility to common human diseases In this paper, we formulate a working hypothesis that epistasis is a ubiquitous component of the genetic architecture of common human diseases and that complex interactions are more important than the independent main effects of any one susceptibility gene This working hypothesis is based on several bodies of evidence First, the idea that epistasis is important is not new In fact, the recognition that deviations from Mendelian ratios are due to interactions between genes has been around for nearly 100 years Second, the ubiquity of biomolecular interactions in gene regulation and biochemical and metabolic systems suggest that relationship between DNA sequence variations and clinical endpoints is likely to involve gene-gene interactions Third, positive results from studies of single polymorphisms typically do not replicate across independent samples This is true for both linkage and association studies Fourth, gene-gene interactions are commonly found when properly investigated We review each of these points and then review an analytical strategy called multifactor dimensionality reduction for detecting epistasis We end with ideas of how hypotheses about biological epistasis can be generated from statistical evidence using biochemical systems models If this working hypothesis is true, it suggests that we need a research strategy for identifying common disease susceptibility genes that embraces, rather than ignores, the complexity of the genotype to phenotype relationship
TL;DR: It is argued here that functional neuroimaging data—which I restrict to the haemodynamic techniques of fMRI and PET—can inform psychological theorizing, provided one assumes a “systematic” function–structure mapping in the brain.
Abstract: I argue here that functional neuroimaging data--which I restrict to the haemodynamic techniques of fMRI and PET--can inform psychological theorizing, provided one assumes a "systematic" function-structure mapping in the brain. In this case, imaging data simply comprise another dependent variable, along with behavioural data, that can be used to test competing theories. In particular, I distinguish two types of inference: function-to-structure deduction and structure-to-function induction. With the former inference, a qualitatively different pattern of activity over the brain under two experimental conditions implies at least one different function associated with changes in the independent variable. With the second type of inference, activity of the same brain region(s) under two conditions implies a common function, possibly not predicted a priori. I illustrate these inferences with imaging studies of recognition memory, short-term memory, and repetition priming. I then consider in greater detail what is meant by a "systematic" function-structure mapping and argue that, particularly for structure-to-function induction, this entails a one-to-one mapping between functional and structural units, although the structural unit may be a network of interacting regions and care must be taken over the appropriate level of functional/structural abstraction. Nonetheless, the assumption of a systematic function-structure mapping is a "working hypothesis" that, in common with other scientific fields, cannot be proved on independent grounds and is probably best evaluated by the success of the enterprise as a whole. I also consider statistical issues such as the definition of a qualitative difference and methodological issues such as the relationship between imaging and behavioural data. I finish by reviewing various objections to neuroimaging, including neophrenology, functionalism, and equipotentiality, and by observing some criticisms of current practice in the imaging literature.
TL;DR: In this paper, a new scheme of hypothesis classification is proposed to facilitate and clarify the proper use of statistical hypothesis testing in empirical research, based on the explicated, sound relationship between the research and statistical hypotheses.
TL;DR: The conclusion is that developmental relationships are the foundational metric with which to judge the quality and forecast the impact of interventions for at-risk children and youth.
Abstract: Developmental relationships are characterized by reciprocal human interactions that embody an enduring emotional attachment, progressively more complex patterns of joint activity, and a balance of power that gradually shifts from the developed person in favor of the developing person. The working hypothesis of this article is that developmental relationships constitute the active ingredient of effective interventions serving at-risk children and youth across settings. In the absence of developmental relationships, other intervention elements yield diminished or minimal returns. Scaled-up programs and policies serving children and youth often fall short of their potential impact when their designs or implementation drift toward manipulating other ‘‘inactive’’ ingredients (e.g., incentive, accountability, curricula) instead of directly promoting developmental relationships. Using empirical studies as case examples, this study demonstrates that the presence or absence of developmental relationships distinguishes effective and ineffective interventions for diverse populations across developmental settings. The conclusion is that developmental relationships are the foundational metric with which to judge the quality and forecast the impact of interventions for at-risk children and youth. It is both critical and possible to give foremost considerations to whether program, practice, and policy decisions promote or hinder developmental relationships among those who are served and those who serve. T raditionally rooted in medical and pharmaceutical science, the term active ingredient refers to the critical component of an intervention that is responsible for producing desired change in outcomes (e.g., sodium fluoride in toothpaste). What if everything we do to promote children’s positive development hinges upon a similarly essential element? What if the efficacy of every policy, program, or intervention is determined by whether such effort ultimately promoted or hindered the active mechanisms associated with such an ingredient—the developmental active ingredient? In this article, we advance the working hypothesis that there is such a universally applicable active ingredient underlying effective interventions. We propose that developmental relationships, characterized by attachment, reciprocity, progressive complexity, and balance of power, consistently promote positive development for children and youth across diverse developmental settings. Furthermore, we argue that the effectiveness of child-serving programs, practices, and policies is determined first and foremost by whether they strengthen or weaken developmental relationships. We will first define developmental relationships with sufficient theoretical and operational specificity. Then, using case examples drawn from empirical studies, this working hypothesis is applied to explain what distinguishes effective or ineffective interventions or programs for diverse at-risk populations. We conclude with the practical implications of our hypothesis on program design, professional practice, and policymaking. Competing Hypotheses of Active Ingredients