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Machine Learning Methods for Environmental-Enrichment-Related Variations in Behavioral Responses of Laboratory Rats

  • Karmele López-de-IpiñaEmail author
  • Hodei Cepeda
  • Catalina Requejo
  • Elsa Fernandez
  • Pilar Maria Calvo
  • Jose Vicente Lafuente
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11486)

Abstract

Environmental enrichment (EE) paradigms are designed to enhance 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.

Keywords

Entropy Nonlinear analysis Image analysis Clustering Optical flow Pattern recognition Intelligent methods Environmental monitoring 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Karmele López-de-Ipiña
    • 1
    Email author
  • Hodei Cepeda
    • 2
  • Catalina Requejo
    • 2
  • Elsa Fernandez
    • 1
  • Pilar Maria Calvo
    • 1
  • Jose Vicente Lafuente
    • 2
  1. 1.EleKin Research Group, Department of Systems Engineering and AutomaticsUniversity of the Basque Country (UPV/EHU)DonostiaSpain
  2. 2.Neuroscience DepartmentUniversity of the Basque Country (UPV/EHU)LeioaSpain

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