Katsiaryna V. Gris's research while affiliated with Université de Sherbrooke and other places
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Publications (11)
Using automated supervised behavioral assessment software, we recorded and analyzed 24 h non-interrupted recordings of mice for a duration of 11 days. With the assistance of free R programming, we used correlation matrix-based hierarchical clustering and factor analysis to separate the 33 activities into meaningful clusters and groups without losin...
Technological advances in computer vision led to the development of various algorithms that are designed to analyze human and animal behavior. We have used an algorithm based on hidden Markov model to monitor the behavior of two different knock-out mice and a healthy control. The goal of this study was to detect behavioral changes in mice with sing...
Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) associated with inappropriate activation of lymphocytes, hyperinflammatory responses, demyelination, and neuronal damage. In the past decade, a number of biological immunomodulators have been developed that suppress the peripheral immune responses and slow down the...
Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, d...
Citations
... Power analysis and advanced statistics can potentially help to reduce the number of replicates (Guo et al., 2013) and to analyze complex multiple parameters simultaneously. Using R programming, Yamamoto et al. (2018) demonstrate how multiparametric cluster and factor analysis can be used to analyze and to categorize 33 different behaviors of mice recorded noninterrupted for 11 days. Their data analysis enabled them to interpret behavioral changes that are associated with the effect of social isolation, intermittent socialization, and re-introduction to a familiar home cage. ...
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... The emergence of computational neuroethology tools allows for fast, reliable, and systematic detection of recorded movement over time to extract multiple metrics in different contexts. This extraction is critical for identifying unique sub-populations and assessing the therapeutic value of manipulations for pre-clinical animal studies for psychiatric disorders (Luxem et al., 2023;Popovitz et al., 2021;Shemesh & Chen, 2023;Tanas et al., 2022;Yamamoto et al., 2018). Thus, to capture the complexity of individual variations in a mosaic Mecp2-heterozygous population over multiple days of pup retrieval behavior, we used DeepLabCut, a marker-less pose estimation software, to derive animal trajectories, and performed multidimensional analysis of trajectory kinematics in adolescent and adult female WT and Het (Mathis et al., 2018;Nath et al., 2019). ...
... It has been shown to have high concordance with human scoring and advantageously allows for behavioral measurements over long periods of time (Melo-Carrillo and Lopez-Avila, 2013;Roughan et al., 2009;Yamamoto et al., 2018;Zhang et al., 2021). Previous literature has shown that HCS can detect behavioral differences in post-operative pain, neuropathic injury models, lipopolysaccharide (LPS) sepsis models, and inflammatory models of pain (Lehmann et al., 2013;Roughan et al., 2009;V Gris et al., 2018;Wright-Williams et al., 2013;Zhang et al., 2021). However, analysis of the large dataset obtained is non-trivial and can make interpretation of the results difficult (e.g., what does it mean to have an animal that "turns" less). ...
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... NLRX1 has been reported to be associated with several diseases [20,[57][58][59][60]. Decreased NLRX1 expression was observed in human intracranial aneurysms and in hypoxic cardiomyocytes, kidney, brain and intestine [27,[61][62][63][64]. Decreased NLRX1 expression in chronic obstructive pulmonary disease patients is linked to pulmonary disease severity and poor prognosis [65]. ...
... Using patterns in animal pose over sliding temporal windows, supervised algorithms are trained to find predefined behaviors of interest. These automated behavioral assessments often exceed human performance 13 , increase throughput and https://doi.org/10.1038/s41593-024-01649-9 ...
