Publications by authors named "Shreya Tirumala Kumara"
Behavioral neuroscience requires precise and unbiased methods for animal behavior assessment to elucidate complex brain-behavior interactions. Traditional manual scoring methods are often labor-intensive and can be prone to error, necessitating advances in automated techniques. Recent innovations in computer vision have led to both marker- and markerless-based tracking systems.
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- In behavioral neuroscience, traditional methods for scoring animal behavior are labor-intensive and biased, prompting a shift towards automated tracking systems using computational methods and image-processing algorithms.
- This study highlights the effectiveness of using ArUco markers in a marker-based tracking approach to assess rat behavior during a nose-poking task, achieving a high classification accuracy of 98% compared to manual video analysis.
- Additionally, a two-state engagement model based on the tracking data allows researchers to identify critical transitions in engagement, providing insights into optimal session durations and enhancing the efficiency of behavioral data collection.