实验性恶心与呕吐——大脑皮层与内脏相关研究的新途径

大脑皮层与内脏关系的脑机制是揭示心身疾病和心理疾病的重要依据。本文综述了经典条件学习与期待性恶心与呕吐的关系以及实验性恶心与呕吐的研究方法。作者认为,实验性恶心与呕吐结合脑成像技术是研究大脑皮层与内脏关系神经机制的重要途径。     

Research in person‐centred,experiential and humanistic counselling and psychotherapy: Meeting new challenges

As a result of the programme of research into client‐centred therapy led by Carl Rogers, the humanistic therapies could claim, in the 1950s, to possess a comprehensive evidence base. Over the following decades, however, there was a marked decline in the productivity and influence of research into person‐centred and humanistic therapies. The present paper celebrates the publication of three books that mark a resurgence in research into these approaches, and comments on emerging themes and trends.     

时间洞察力的概念及研究方法

对时间洞察力的概念和研究方法进行了总结、辨析和阐述,认为时间洞察力是一种相对稳定的个体差异变量,是个体在对时间的认知、体验和行动(或行动倾向)上所表现出的人格特质。并对时间洞察力的概念界定和方法学方面存在的问题进行了反思。     

The error statistical philosopher as normative naturalist

We argue for a naturalistic account for appraising scientific methods that carries non-trivial normative force. We develop our approach by comparison with Laudan’s (American Philosophical Quarterly 24:19–31, 1987, Philosophy of Science 57:20–33, 1990) “normative naturalism” based on correlating means (various scientific methods) with ends (e.g., reliability). We argue that such a meta-methodology based on means–ends correlations is unreliable and cannot achieve its normative goals. We suggest another approach for meta-methodology based on a conglomeration of tools and strategies (from statistical modeling, experimental design, and related fields) that affords forward looking procedures for learning from error and for controlling error. The resulting “error statistical” appraisal is empirical—methods are appraised by examining their capacities to control error. At the same time, this account is normative, in that the strategies that pass muster are claims about how actually to proceed in given contexts to reach reliable inferences from limited data.     

Parameters, Predictions, and Evidence in Computational Modeling: A Statistical View Informed by ACT-R

Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive theories, encouraging a "model fixed, data variable" paradigm that makes it difficult to interpret model predictions and to account for individual differences. This article proposes a likelihood-based, "data fixed, model variable" paradigm in which models are treated as stochastic processes in experiments with participant-to-participant variation that can be applied to a broad range of mechanistic cognitive architectures. This article discusses the implementation and implications of this view in model validation, with a concrete focus on a simple class of ACT-R models of cognition. This article is not intended as a recipe for broad application of these preliminary, proof-of-concept methods, but as a framework for communication between statisticians searching for interesting problems in the cognitive modeling sphere, and cognitive modelers interested in generalizing from deterministic to stochastic model validation, in the face of random variation in human experimental data.     

Using Cases with Contrary Facts to Illustrate and Facilitate Ethical Analysis

There has been increasing interest in developing practical, non-theoretical tools for analyzing ethical problems in public health, biomedicine, and other scientific disciplines so that professionals can make and justify ethical decisions in their own research or practice. Tools for ethical decisionmaking, together with case studies on ethics, are often used in graduate education programs and in continuing professional education. Students can benefit from opportunities to further develop their analytical skills, to recognize ethical issues, and to develop their moral sensitivity. One practical approach for illustrating and facilitating ethical analysis uses cases with contrary facts and circumstances, an approach which complements rather than replaces theoretical approaches to moral reasoning. Cases with contrary facts and circumstances are presented in two or more alternative ways so that the facts, circumstances, or framing of one version runs counter to that of the other version (s). Cases with contrary facts, together with practical steps for identifying and analyzing ethical issues, are likely to be useful tools for illustrating and facilitating ethics analysis and stimulating the moral imagination. The findings and conclusions in this article are those of the author and do not necessarily represent the views of the Centers for Disease Control and Prevention.     

Challenges of Evaluating Multilevel Interventions

This article uses the Comprehensive Mixed-Methods Participatory Evaluation (CMMPE; Nastasi and Hitchcock Transforming school mental health services: Population-based approaches to promoting the competency and wellness of children, Thousand Oaks, CA: Corwin Press with National Association of School Psychologists 2008; Nastasi et al. School-based mental health services: creating comprehensive and culturally specific programs. Washington, DC: American Psychological Association 2004) model as a framework for addressing the multiplicity of evaluation decisions and complex nature of questions related to program success in multilevel interventions. CMMPE defines program success in terms of acceptability, integrity, social or cultural validity, outcomes (impact), sustainability and institutionalization, thus broadening the traditional notions of program outcomes. The authors use CMMPE and an example of a community-based multilevel sexual risk prevention program with multiple outcomes to discuss challenges of evaluating multilevel interventions. The sexual risk program exemplifies what Schensul and Tricket (this issue) characterize as multilevel intervention–multilevel evaluation (M–M), with both intervention and evaluation at community, health practitioner, and patient levels. The illustration provides the context for considering several challenges related to M–M designs: feasibility of randomized controlled trials within community-based multilevel intervention; acceptability and social or cultural validity of evaluation procedures; implementer, recipient, and contextual variations in program success; interactions among levels of the intervention; unanticipated changes or conditions; multiple indicators of program success; engaging multiple stakeholders in a participatory process; and evaluating sustainability and institutionalization. The complexity of multilevel intervention and evaluation designs challenges traditional notions of evaluation research and experimental designs. Overcoming these challenges is critical to effective translation of research to practice in psychology and related disciplines.     

Top-down predictions in the cognitive brain

The human brain is not a passive organ simply waiting to be activated by external stimuli. Instead, we propose that the brain continuously employs memory of past experiences to interpret sensory information and predict the immediately relevant future. The basic elements of this proposal include analogical mapping, associative representations and the generation of predictions. This review concentrates on visual recognition as the model system for developing and testing ideas about the role and mechanisms of top-down predictions in the brain. We cover relevant behavioral, computational and neural aspects, explore links to emotion and action preparation, and consider clinical implications for schizophrenia and dyslexia. We then discuss the extension of the general principles of this proposal to other cognitive domains.