World Wide Series Seminar PiVR is a system that allows experimenters to immerse small animals into virtual realities. The system tracks the position of the animal and presents light stimulation according to predefined rules, thus creating a virtual landscape in which the animal can behave.
Several excellent computational frameworks exist that enable high-throughput and consistent tracking of freely moving unmarked animals. SimBA introduce and distribute a plug-and play pipeline that enables users to use these pose-estimation approaches in combination with behavioral annotation for the generation of supervised machine-learning behavioral predictive classifiers.
Stytra, a flexible, open-source software package, written in Python and designed to cover all the general requirements involved in larval zebrafish behavioral experiments.
It provides timed stimulus presentation, interfacing with external devices and simultaneous real-time tracking of behavioral parameters such as position, orientation, tail and eye motion in both freely-swimming and head-restrained preparations.
DeepLabCut™ is an efficient method for 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames).
Bonsai is a high-performance, easy to use, and flexible visual programming language for designing closed-loop neuroscience experiments combining physiology and behaviour data.
Bonsai has allowed scientists with no previous programming experience to quickly develop their own experimental rigs and is also being increasingly used as a platform to integrate new open-source hardware and software from the experimental neuroscience community.
Ethoscopes are machines for high-throughput analysis of behavior in Drosophila and other animals.
Ethoscopes provide a software and hardware solution that is reproducible and easily scalable.
They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source.
BonVision is an open-source closed-loop visual environment generator developed by the Saleem Lab and Solomon Lab at the UCL Institute of Behavioural Neuroscience in collaboration with NeuroGEARS.
BonVision’s key features include:
DeepLabStream is a python based multi-purpose tool that enables the realtime tracking of animals and manipulation of experiments. Our toolbox is adapted from the previously published DeepLabCut (Mathis et al., 2018) and expands on its core capabilities.
We describe the “FishCam”, a low-cost (500 USD) autonomous camera package to record videos and images underwater. The system is composed of easily accessible components and can be programmed to turn ON and OFF on customizable schedules.
Two-photon calcium imaging is now widely used to infer neuronal dynamics from changes in fluorescence of an indicator. However, state of the art computational tools are not optimized for the reliable detection of fluorescence transients from highly synchronous neurons located in densely packed regions such as the CA1 pyramidal layer of the hippocampus during early postnatal stages of development.