FEB 08, 2018 12:00 PM PST

Data Collection as Environmental Enrichment: Automated Behavioral Measurement in Voluntary Home Cage Operant Tasks

Speaker
  • Postdoctoral Researcher, Department of Comparative Medicine, Stanford University
    Biography
      Dr. Jamie Ahloy Dallaire received his B.Sc. in Biology from McGill University (2004-2007), in Montréal, Québec, then went on to study fundamental and applied ethology with Dr. Georgia Mason at the University of Guelph, in Ontario. There, his M.Sc. work (2008-2011) pertained to abnormal repetitive behaviors, environmental enrichment, and animal welfare in American mink and in Asiatic black bears. In his doctoral research (2011-2015), Dr. Ahloy Dallaire studied the developmental effects and evolutionary functions of play in mink and in lambs. Since 2015, he has been working on automated behavioral assessment of pain in laboratory mice, with Dr. Joseph Garner in the Department of Comparative Medicine at Stanford University. Since 2017, he has additionally been working on barbering and ulcerative dermatitis in laboratory mice as models of trichotillomania and skin-picking disorder, and planning a first-in-human clinical trial of a therapeutic candidate in collaboration with UCLA clinician researchers. He also frequently collaborates with animal researchers and clinical scientists on aspects of experimental design and statistical analysis, to help them conduct powerful and informative experiments.

      In terms of fundamental ethology, Dr. Ahloy Dallaire's research interests include animal play as well as using behavior to assess emotions, motivation, and welfare in animals. In terms of applied ethology, Dr. Ahloy Dallaire's current work aims to decrease the negative impacts of biomedical research on laboratory animal welfare, and to deliver better outcomes for human patients through improved research. He believes that good welfare makes for good science, and that these two goals can be achieved in conjunction through a focus on the 3Rs (hhttp://nc3rs.org.uk/the-3rs).

    Abstract

    Biomedical research suffers from a translation gap, where most treatments that seem effective when tested on animals turn out not to work in human patients. This is likely due in large part to differences in how animal and human experiments are performed, and a key step in overcoming this problem is to treat animals like we treat human patients. This means making their well-being a top priority and giving them control over stressors in their housing and testing environments.

    Cognitive tests of learning and memory are typically performed in an operant chamber outside of the home cage. Many of the aversive features of these hand-run tests – handling by experimenters, temporary separation from social companions, and being placed in unfamiliar environments – can be eliminated by testing animals on a voluntary basis, inside their home cages. Automated home cage operant tests further help ensure that animals volunteer to be tested only when appropriately motivated. Properly designed tests that tap into animals’ intrinsic motivations and match the level of cognitive challenge to their level of skill can even be a valuable form of environmental enrichment.

    Aversive features and low or fluctuating motivation associated with conventional hand-run operant tests can negatively impact cognitive performance. Automated home cage operant tests may then more accurately assess learning and memory. Large-scale replication studies further suggest that results of these tests are more consistent across different laboratories. By yielding control to experimental animals and allowing them to be tested voluntarily rather than through coercion, automated home cage operant tests may additionally pave the way towards improved translation from animal to human patients. If so, this would serve as a prime example of how good animal welfare can lead to good science, with improved quality of life for experimental animals and accelerated development of treatments for human patients.


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    FEB 08, 2018 12:00 PM PST

    Data Collection as Environmental Enrichment: Automated Behavioral Measurement in Voluntary Home Cage Operant Tasks


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