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A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
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Interdisciplinary perspectives on the development, integration, and application of cognitive ontologies
Janna Hastings1, Gwen A Frishkoff2, Barry Smith3
1European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, UK ; Department of Philosophy and Swiss Center for Affective Sciences, University of Geneva Switzerland ; Evolutionary Bioinformatics, Swiss Institute for Bioinformatics Lausanne, Switzerland.
Frontiers in Neuroinformatics
|July 8, 2014
Summary
Developing standardized cognitive ontologies is crucial for neuroscience and psychology. Key challenges include defining cognitive processes, harmonizing representations, and testing utility for data annotation and knowledge discovery.
Area of Science:
- Cognitive Science
- Neuroscience
- Biomedical Informatics
Background:
- Cognitive ontologies are essential for organizing and interpreting complex data in cognitive and neuroscientific research.
- Current development faces challenges in standardization, harmonization, and practical application.
Purpose of the Study:
- To review progress in cognitive ontology development.
- To identify and address key challenges hindering their coordinated use.
- To propose solutions for advancing cognitive ontology resources.
Main Methods:
- Analysis of current cognitive ontology development.
- Discussion of three primary challenges: definition standardization, representational harmonization, and utility testing.
- Recommendation of a standardized definition for cognitive processes.
Main Results:
- Identified the need for standardized definitions of cognitive processes, recommending a specific approach.
- Highlighted the necessity of harmonizing ontological representations to enable multi-modal data integration.
- Emphasized the importance of testing ontologies for large-scale data annotation, search, and knowledge discovery.
Conclusions:
- Standardized definitions and harmonization are critical for effective cognitive ontologies.
- Community-wide adoption is essential to validate the utility of these resources for psychological and neuroscientific data inference.
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