An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments

In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one‐to‐one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks even when the search space of possible choice tasks is very large. As proof‐of‐concept, we used this novel approach to generate respondent‐specific choice tasks with either low or high context‐based complexity that we operationalize by the similarity of alternatives and the conflict between alternatives. We find in an experiment that an increase in the similarity of the alternatives and an increase in the number of conflicts within the choice task lead to an increased use of non‐compensatory strategies and a decreased use of compensatory decision strategies. In contrast, the size of the choice tasks, measured by the number of attributes and alternatives, only weakly influences the strategy selection. Copyright © 2014 John Wiley & Sons, Ltd.     

Human Germline CRISPR-Cas Modification: Toward a Regulatory Framework

CRISPR germline editing therapies (CGETs) hold unprecedented potential to eradicate hereditary disorders. However, the prospect of altering the human germline has sparked a debate over the safety, efficacy, and morality of CGETs, triggering a funding moratorium by the NIH. There is an urgent need for practical paths for the evaluation of these capabilities. We propose a model regulatory framework for CGET research, clinical development, and distribution. Our model takes advantage of existing legal and regulatory institutions but adds elevated scrutiny at each stage of CGET development to accommodate the unique technical and ethical challenges posed by germline editing.     

人际互动中社会学习的计算神经机制

人类在社会互动中通过他人的行为对他人特质、意图及特定情境下的社会规范进行学习, 是优化决策、维护积极社会互动的重要条件。近年来, 越来越多的研究通过结合计算模型与神经影像技术对社会学习的认知计算机制及其神经基础进行了深入考察。已有研究发现, 人类的社会学习过程能够较好地被强化学习模型与贝叶斯模型刻画, 主要涉及的认知计算过程包括主观期望、预期误差和不确定性的表征以及信息整合的过程。大脑对这些计算过程的执行主要涉及奖惩加工相关脑区(如腹侧纹状体与腹内侧前额叶)、社会认知加工相关脑区(如背内侧前额叶和颞顶联合区)及认知控制相关脑区(如背外侧前额叶)。需要指出的是, 计算过程与大脑区域之间并不是一一映射的关系, 提示未来研究可借助多变量分析与脑网络分析等技术从系统神经科学的角度来考察大尺度脑网络如何执行不同计算过程。此外, 将来研究应注重生态效度, 利用超扫描技术考察真实互动下的社会学习过程, 并更多地关注内隐社会学习的计算与神经机制。     

Two types of debunking arguments

Debunking arguments are arguments that seek to undermine a belief or doctrine by exposing its causal origins. Two prominent proponents of such arguments are the utilitarians Joshua Greene and Peter Singer. They draw on evidence from moral psychology, neuroscience, and evolutionary theory in an effort to show that there is something wrong with how deontological judgments are typically formed and with where our deontological intuitions come from. They offer debunking explanations of our emotion-driven deontological intuitions and dismiss complex deontological theories as products of confabulatory post hoc rationalization. Through my discussion of Greene and Singer’s empirically informed debunking of deontology, I introduce the distinction between two different types of debunking arguments. The first type of debunking argument operates through regular undercutting defeat, whereas the second type relies on higher-order evidence. I argue that the latter type of debunking argument, of which the argument from confabulation is an example, is objectionably sloppy and therefore inadmissible in academic discussion.     

Psycho-logic: some thoughts and after-thoughts

The main features of the system of psycho-logic and its historical origins, especially in the writings of Heider and Piaget, are briefly reviewed. An updated version of the axioms of psycho-logic, and a list of the semantic primitives of Wierzbicka are presented. Some foundational questions are discussed, including the genetically determined limitations of human knowledge, the constructive, moral, and political nature of the approach, the role of fortuitous events, the ultimate limitations of psychological knowledge (the "balloon" to be inflated from the inside), the role of the subjective unconscious, and the implications of the approach for practice.     

Of BOLD Claims and Excessive Fears: A Call for Caution and Patience Regarding Political Neuroscience

Published and informal assessments of the prospects for neuroimaging in political science have tended to range from overexuberant to reflexively dismissive. We seek to present a cautious but fair middle ground in considering this new methodology, primarily from an epistemological perspective. Our examination centers on the relationship between two levels of analysis, focusing on the potential for connection between behavior‐based theories of political psychology and cognition and the neural processes and systems involved in generating behaviors and states of mind. We explore the place of each level of analysis on its own, as well as the potential for the fruitful interaction of the two. This analysis brings together opinions and ideas presented by others in various forums and across multiple disciplines, offers a discussion of the the promises and perils of neuroimaging in its application to social science, as well as some practical thoughts regarding its early‐stage incorporation into political psychology. We argue in favor of proceeding with more substantial incorporation of neuroimaging into political psychology's methodological arsenal, but note that this will initially require both (1) greater acceptance of work more focused on presenting empirical results than on providing dispositive evidence in broader theoretical debates and (2) a commitment on the part of those conducting this research to refrain from overstating the definitiveness of its theoretical implications.     

Mechanism of Stimulation: An Alternative Explanation for Genetic Variation in the Evolutionary Theory

A new evolutionary concept is presented, based on the principle of biological diversity by organismal adaptation, more specifically the origin of the first variations and the process leading to speciation. The article suggests the mechanism of stimulation as the major promoter of genetic variation, making an overall assessment and accurate to the natural phenomenon responsible for this evolutionary step. Constantly, environmental forces interact with the organism, favoring changes to the organs toward adaptation. Stimulation focuses on this action–reaction between organism and environment, trying to decipher the causes/consequences resulting. The article also addresses possible relationships and constraints with neo-Darwinism.     

数学认知能力的遗传证据研究综述

数学认知能力是人类最重要的高级认知功能之一,许多研究者对其遗传性给出了相关的证据。本文从数感具有跨种系的特点、婴儿具有数量辨别能力、数学遗传的双生子研究以及遗传综合症病人的研究等间接和直接证据层面对数学认知能力的遗传性研究进行了简要的总结分析,指出对数学认知能力的遗传基因研究还需要从正常人的角度做进一步的研究探索,以便真正找到数学能力的遗传基因。