3Rs-based optimization of mice behavioral testing: The habituation/dishabituation olfactory test.
J Neurosci Methods
; 332: 108550, 2020 02 15.
Article
en En
| MEDLINE
| ID: mdl-31838181
BACKGROUND: There is clear evidence that most of the paradigms that are used in the field of behavioral neuroscience suffer from a lack of reliability mainly because of oversimplification of both testing procedures and interpretations. In the present study we show how an already existing behavioral test, the olfactory habituation / dishabituation task, can be optimized in such a way that animal number and animal distress could be minimized, number/confidence of behavioral outcomes and number of explored behavioral dimensions could be increased. NEW METHOD: We used ethologically relevant technical and procedural changes associated with videotracking-based automated quantification of sniffing behavior to validate our new setup. Mainly internal and construct validity were challenged through the implementation of a series of simple experiments. RESULTS: We show that the new version of the test: 1) has very good within and inter laboratory replicability, 2) is sensitive to some environmental / experimental factors while insensitive to others, 3) allows investigating hedonism, both state and trait anxiety, efficacy of anxiolytic molecules, acute stress, mental retardation-related social impairments and learning and memory. 4) We also show that interest for both nonsocial and social odors is stable over time which makes repetitive testing possible. CONCLUSIONS: This work paves the way for future studies showing how behavioral tests / procedures may be improved by using ethologically relevant changes, in order to question laboratory animals more adequately. Refining behavioral tests may considerably increase predictivity of preclinical tests and, ultimately, help reinforcing translational research.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Olfato
/
Odorantes
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Año:
2020
Tipo del documento:
Article