Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice
Year: 2024
Type: article
Abstract: Machine learning and pose estimation using a convolutional neural network accurately detected and objectively scored buprenorphine-induced changes in locomotor behaviors of mice on an elevated zero maze (EZM). Confirmatory factor analysis supports the interpretation that the anxiety-like construct accounted for the buprenorphine-induced changes in motor behavior. The results have noteworthy implications for the relationship between Darwin's story model of mammalian emotions and computational models of anxiety-like behavior in mice.
Source: Journal of Neurophysiology
Authors: Ohm Sharma, Michael Mykins, Rebecca E. Bergee, Joshua M. Price, Michael A. O'Neil, Nicole Mickels, Megan Von Hagen, James O’Connor, Helen A. Baghdoyan, Ralph Lydic
Institution: University of Tennessee at Knoxville
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Funder: University of Tennessee
OpenAlex ID: W4405952691