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At least 91 records · Page 5Linked to original sources
PubMed2000

Cognitive neuropharmacology: new perspectives for the pharmacology of cognition.

Taking its roots both in neuropharmacology and in cognitive science, cognitive neuropharmacology is an emerging approach in the field of psychopharmacology. It attempts to use theoretical knowledge to understand the biochemical bases of cognition and the mode of action of the commonly used drugs and to find new brain-targeted therapeutics. The aim of the present article is to throw up the main characteristics of this way of research. It is defined in comparison with its neighbouring approaches and by presenting its own rationale. Its particular methods mainly concern the animal modelling of the highest human cognitive functions and the original means of intra-cerebral drug administration. Finally, we present an illustrative example of a study in cognitive neuropharmacology and propose further perspectives.

Animals↗
PubMed2005

A user-centered framework for redesigning health care interfaces.

Numerous health care systems are designed without consideration of user-centered design guidelines. Consequently, systems are created ad hoc, users are dissatisfied and often systems are abandoned. This is not only a waste of human resources, but economic resources as well. In order to salvage such systems, we have combined different methods from the area of computer science, cognitive science, psychology, and human-computer interaction to formulate a framework for guiding the redesign process. The paper provides a review of the different methods involved in this process and presents a life cycle of our redesign approach. Following the description of the methods, we present a case study, which shows a successfully applied example of the use of this framework. A comparison between the original and redesigned interfaces showed improvements in system usefulness, information quality, and interface quality.

Artificial Intelligence↗
PubMed1993

The conceptual validity of a taxonomy of nursing interventions.

The purpose of this paper is to report validity evidence for the nursing intervention taxonomy developed as part of the Nursing Intervention Lexicon and Taxonomy (NILT) Study. Using eclectic classification methods of library science, cognitive science, nursing science and computational linguistics, a taxonomy of nursing interventions consisting of seven categories was developed. These categories which incorporate care as a central concept are described and defined, and prototypical examples of each category are presented. Brinberg & McGrath's validity schema provides the framework within which evidence for validity as value, validity as correspondence and validity as generalizability were examined. Comparison of the NILT categories with previously published categorizations of nursing functions and interventions provides strong support for the validity of this classification. Additionally, comparison of the NILT categories with two internationally derived categorizations of nursing functions supports the robustness or generalizability of the NILT classification.

Job Description↗
PubMed2007

How to make an autonomous robot as a partner with humans: design approach versus emergent approach.

In this paper, we discuss what factors are important to realize an autonomous robot as a partner with humans. We believe that it is important to interact with people without boring them, using verbal and non-verbal communication channels. We have already developed autonomous robots such as AIBO and QRIO, whose behaviours are manually programmed and designed. We realized, however, that this design approach has limitations; therefore we propose a new approach, intelligence dynamics, where interacting in a real-world environment using embodiment is considered very important. There are pioneering works related to this approach from brain science, cognitive science, robotics and artificial intelligence. We assert that it is important to study the emergence of entire sets of autonomous behaviours and present our approach towards this goal.

Artificial Intelligence↗
PubMed2001

A cognitive-perceptual analysis of projective tests used with children.

There are both general and specific problems with projective tests--the production, comprehension, and interpretation of two-dimensional visual representations. At the general level, there is a need to integrate findings from the neuro- and cognitive sciences, cognitive, perceptual, and affective development, and the understanding and interpretation of pictorial material based on the accumulated research base in the arts. At the specific level, much of the research base on projective tests is poor or outdated; evidence for clinical utility is mixed or negative; and the tests possess poor reliability and validity while the putative underlying psychological process of projection" has not been subject to rigorous empirical examination--the term remains vague and elusive. While earlier critiques and reviews have focused on problems in validity and reliability, their has been a lack of attention to the development of children's pictorial abilities as pertain to projective techniques. Although many of the principles delineated here also apply to adolescents and adults, an important challenge for clinicians is to develop and employ better methods in the "projective" assessment of children.

Adolescent↗
PubMed2003

Dental informatics: an emerging biomedical informatics discipline.

Biomedical informatics is a maturing discipline. During the last forty years, it has developed into a research discipline of significant scale and scope. One of its subdisciplines, dental informatics, is beginning to emerge as its own entity. While there is a growing cadre of trained dental informaticians, dental faculty and administrators in general are not very familiar with dental informatics as an area of scientific inquiry. Many confuse informatics with information technology (IT), are unaware of its scientific methods and principles, and cannot relate dental informatics to biomedical informatics as a whole. This article delineates informatics from information technology and explains the types of scientific questions that dental and other informaticians typically explore. Scientific investigation in informatics centers primarily on model formulation, system development, system implementation, and the study of effects. Informatics draws its scientific methods mainly from information science, computer science, cognitive science, and telecommunications. Dental informatics shares many types of research questions and methods with its parent discipline, biomedical informatics. However, there are indications that certain research questions in dental informatics require novel solutions that have not yet been developed in other informatics fields.

Dental Research↗
PubMed1983

Utilization of cognitive style in the clinical laboratory sciences.

Cognitive style addresses the individual's unique preference for learning. Cognitive style differs from ability, achievement, performance, and productivity in that it is not measured quantitatively; it is value-free. Non one cognitive style is better than another. It is established in early childhood and remains stable. Cognitive style information has immediate use for those in an academic setting and those in any setting requiring effective communication. Cognitive style information has been widely used in medical settings, schools, hospitals, post graduate training and patient instruction. A practical model used in community colleges and in medical education is the Modified Hill Model. In that model 28 elements are assessed and the resultant "map" presents a graphic picture of learning preference. Research indicates that knowledge of cognitive style is effective in improving academic achievement and person-to-person communication. In medical technology, cognitive style can be effectively used in teaching (students, staff or patient), in work group communication, and in informing the many publics of the vital role played by medical technology.

Chemistry, Clinical↗
PubMed2003

Artificial life: organization, adaptation and complexity from the bottom up.

Artificial life attempts to understand the essential general properties of living systems by synthesizing life-like behavior in software, hardware and biochemicals. As many of the essential abstract properties of living systems (e.g. autonomous adaptive and intelligent behavior) are also studied by cognitive science, artificial life and cognitive science have an essential overlap. This review highlights the state of the art in artificial life with respect to dynamical hierarchies, molecular self-organization, evolutionary robotics, the evolution of complexity and language, and other practical applications. It also speculates about future connections between artificial life and cognitive science.

Journal Article↗
PubMed2003

Behavioural studies of strategic thinking in games.

Game theory is a mathematical language for describing strategic interactions, in which each player's choice affects the payoff of other players (where players can be genes, people, companies, nation-states, etc.). The impact of game theory in psychology has been limited by the lack of cognitive mechanisms underlying game-theoretic predictions. 'Behavioural game theory' is a recent approach linking game theory to cognitive science by adding cognitive details about 'social utility functions', theories of limits on iterated thinking, and statistical theories of how players learn and influence others. New directions include the effects of game descriptions on choice ('framing'), strategic heuristics, and mental representation. These ideas will help root game theory more deeply in cognitive science and extend the scope of both enterprises.

Journal Article↗
PubMed1996

Some prerequisites for a study of the evolution of cognition in the animal kingdom.

A distinction is made between two definitions of animal cognition: the one most frequently employed in cognitive sciences considers cognition as extracting and processing information; a more phenomenologically inspired model considers it as attributing to a form of the outside world a significance, linked to the state of the animal. The respective fields of validity of these two models are discussed along with the limitations they entail, and the questions they pose to evolutionary biologists are emphasized. This is followed by a presentation of a general overview of what might be the study of the evolution of knowledge in animals.

Animals↗