A chinrest-based approach to measure eye movements and experimental task engagement in macaques with minimal restraint.
J Neurosci Methods
; 408: 110173, 2024 Aug.
Article
em En
| MEDLINE
| ID: mdl-38782125
ABSTRACT
BACKGROUND:
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. NEWMETHOD:
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 1â¯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 EXISTINGMETHODS:
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.Palavras-chave
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Macaca mulatta
Limite:
Animals
Idioma:
En
Revista:
J Neurosci Methods
Ano de publicação:
2024
Tipo de documento:
Article