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Lookup NU author(s): Professor Michael SchmidORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 The AuthorsBackground: The use of Rhesus macaques in vision research is crucial due to their visual system's similarity to humans. While invasive techniques have been the norm, there has been a shift towards non-invasive methods, such as facemasks and head molds, to enhance animal welfare and address ethical concerns. New Method: We present a non-invasive, 3D-printed chinrest with infrared sensors, adapted from canine research, allowing for accurate eye movement measurements and voluntary animal participation in experiments. Results: The chinrest method showed a 16% and 28% increase in average trial numbers for Monkey 1 and Monkey 2, respectively, compared to the traditional headpost method. The engagement was high, with monkeys performing over 500 trials per session and initiating a new trial after an average intertrial interval of approximately 1 second. The hit rate improved by about 10% for Monkey 1 in the chinrest condition, and the fixation precision, measured by the standard deviation of gaze positions, was significantly better in the chinrest condition, with Monkey 1 showing a reduction in fixation imprecision from 0.26° to 0.17° in the X-axis. Comparison with Existing Methods: The chinrest approach showed significant improvements in trial engagement and reduction in aborted trials due to fixation breaks, indicating less stress and potentially improved data quality compared to previous non-invasive methods. Conclusions: The chinrest method offers a significant advancement in primate cognitive testing by allowing for precise data collection while addressing animal welfare concerns, possibly leading to better scientific outcomes and a paradigm shift in primate research methodologies.
Author(s): Rima S, Greilsamer J, Haag M, Cadena-Valencia J, Sansonnens M, Francovich A, Lanz F, Zbinden A, Bergadano A, Schmid MC
Publication type: Article
Publication status: Published
Journal: Journal of Neuroscience Methods
Year: 2024
Volume: 408
Print publication date: 01/08/2024
Online publication date: 21/05/2024
Acceptance date: 18/05/2024
Date deposited: 03/06/2024
ISSN (print): 0165-0270
ISSN (electronic): 1872-678X
Publisher: Elsevier B.V.
URL: https://doi.org/10.1016/j.jneumeth.2024.110173
DOI: 10.1016/j.jneumeth.2024.110173
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