Machine learning methods for environmental-enrichment-related variations in behavioral responses of laboratory rats

• Autores: Miren Karmele Lopez de Ipiña Peña , Hodei Cepeda, Catalina Requejo Rodríguez, Elsa Fernández Le Mouël, Pilar María Calvo Salomon, José Vicente Lafuente Sánchez
• Localización: Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I / José Manuel Ferrández Vicente (dir. congr.) , José Ramón Álvarez Sánchez (dir. congr.) , Félix de la Paz López (dir. congr.) , Francisco Javier Toledo Moreo (dir. congr.), Hojjat Adeli (dir. congr.), 2019, ISBN 978-3-030-19591-5, págs. 420-427
• Idioma: inglés
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• Resumen

  • Environmental enrichment (EE) paradigms are designed toenhance laboratory animals surroundings to encourage natural behaviors. Some enrichment paradigms also include a social component, based on the social interactions typical of the genus and species. Novel automatic methodologies based on image are becoming useful tools to improve laboratory works. This paper present a first approach to the automatic image analysis of laboratory rats in EE: behaviour, drug effects and pathology. The new methodology is based on image and Machine Learning paradigms and will become a useful tool for Neuroscience issues