DBscorer: An Open-Source Software for Automated Accurate Analysis of Rodent Behavior in Forced Swim Test and Tail Suspension Test

Abstract

Authors would like to thank Mr M. Manjunath and the staff at the central animal facility at IISc for technical help.

Effect of aqueous extract of barley and wheat grass in stress induced depression in Swiss mice

“…Reduction in duration of immobility showed the antidepressant-like effect. The duration of immobility was calculated on 0, 2, and 4th, days of the experiment [ 35 , 36 ].…”

Open-source software for automated rodent behavioral analysis

“…Another defining feature of a user-friendly 10.3389/fnins.2023.1149027 software is its compatibility with different operating systems. While certain programs like DBscorer (Nandi et al, 2021) Automated analysis software have certain prerequisites for reliable use of their key-point (Table 1) tracking system in pose estimation. Programs like BehaviorDEPOT (Gabriel et al, 2022), are less effected by environmental changes compared to machine learning-based software, and therefore provide a better key-point tracking performance.…”

“…This decreases the generalizability of outputs to novel experimental data. DBscorer ( Nandi et al, 2021 ), for instance, only offers mobility and immobility statistics by using image processing and heuristics. Although these heuristics can be extended and optimized over time by experts, as offered by BehaviorDEPOT ( Gabriel et al, 2022 ), covering more experimental settings and behaviors is a time-consuming endeavor.…”

“…ToxTrac ( Rodriquez et al, 2017 ) shows outstanding performance in processing speed while having on par accuracy scores with other tracking tools. DBscorer ( Nandi et al, 2021 ) and BehaviorDEPOT ( Gabriel et al, 2022 ), however, are not ideal for real-time analysis, as they require tracking and pose data from DeepLabCut ( Mathis et al, 2018 ), a deep learning-based tracking tool. These properties make heuristics-based tools suitable for researchers who work with relatively stable experimental conditions and lack sufficient annotated data or computational power required for machine learning or and deep learning models.…”

Simulation of Rat Behavior in a Light-Dark Box via Neuroevolution

“…Here, calculating the mean number of hidden neurons of the top 30 virtual rats on the light-dark box, we have only 1.67; however, the mean number of sensors is slightly higher: 2.9. Many software systems have been developed to accurately track the trajectory of rodents in different experimental apparatus, even aquatic [Krynitsky et al 2020, Drai and Golani 2001, Nandi et al 2021. A recent software was developed for quantifying not only rodent exploration, but also their sensory (whisker) and motor behaviours [Gillespie et al 2019].…”