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SimBA

JANUARY 23, 2020

Simon Nilsson from Sam Golden’s lab at the University of Washington recently shared their project SimBA (Simple Behavioral Analysis), an open source pipeline for the analysis of complex social behaviors:


“The manual scoring of rodent social behaviors is time-consuming and subjective, impractical for large datasets, and can be incredibly repetitive and boring. If you spend significant time manually annotating videos of social or solitary behaviors, SimBA is an open-source GUI that can automate the scoring for you. SimBA does not require any specialized equipment or computational expertise.

SimBA uses data from popular open-source tracking tools in combination with a small amount of behavioral annotations to create supervised machine learning classifiers that can then rapidly and accurately score behaviors across different background settings and lighting conditions. Although SimBA is developed and validated for complex social behaviors such as aggression and mating, it has the flexibility to generate classifiers in different environments and for different behavioral modalities. SimBA takes users through a step-by-step process and we provide detailed installation instructions and tutorials for different use case scenarios online. SimBA has a range of in-built tools for video pre-processing, accessing third-party tracking models, and evaluating the performance of machine learning classifiers. There are also several methods for in-depth visualizations of behavioral patterns. Because of constraints in animal tracking tools, the initial release of SimBA is limited to processing social interactions of differently coat colored animals, recorded from a top down view, and future releases will advance past these limitations. SimBA is very much in active development and a manuscript is in preparation. Meanwhile, we are very keen to hear from users about potential new features that would advance SimBA and help in making automated behavioral scoring accessible to more researchers in behavioral neuroscience.”


For more information on SimBA, you can check out the project’s Github page here.

For those looking to contribute or try out SimBA and are looking for feedback, you can interact on the project’s Gitter page.

Plus, take a look at their recent twitter thread detailing the project.

If you would like to be added to the project’s listserv for updates, fill out this form here.