Assessing the effects of 5-HT 2A and 5-HT 5A receptor antagonists on DOI-induced head-twitch response in male rats using marker-less deep learning algorithms.
Autor: | Cyrano E; Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, Kraków, 31-343, Poland., Popik P; Behavioral Neuroscience and Drug Development, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, Kraków, 31-343, Poland. nfpopik@cyf-kr.edu.pl. |
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Jazyk: | angličtina |
Zdroj: | Pharmacological reports : PR [Pharmacol Rep] 2024 Nov 27. Date of Electronic Publication: 2024 Nov 27. |
DOI: | 10.1007/s43440-024-00679-1 |
Abstrakt: | Background: Serotonergic psychedelics, which display a high affinity and specificity for 5-HT Methods: This study aimed to assess the feasibility of a marker-less workflow for detecting head-twitch responses using deep learning algorithms. High-speed videos were analyzed using the DeepLabCut neural network to track head movements, and the Simple Behavioral Analysis (SimBA) toolkit was employed to build models identifying specific head-twitch responses. Results: In studying DOI (0.3125-2.5 mg/kg) effects, the deep learning algorithm workflow demonstrated a significant correlation with human observations. As expected, the preferential 5-HT Conclusions: Previous drug discrimination studies demonstrated that the 5-HT Competing Interests: Declarations. Competing interests: The authors declare no competing interests. (© 2024. The Author(s).) |
Databáze: | MEDLINE |
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