![]() There are also several methods for in-depth visualizations of behavioral patterns. 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. SimBA takes users through a step-by-step process and we provide detailed installation instructions and tutorials for different use case scenarios online. 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 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. SimBA does not require any specialized equipment or computational expertise. 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. The manual scoring of rodent social behaviors is time-consuming and subjective, impractical for large datasets, and can be incredibly repetitive and boring. 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. Link to the Github repository Get to PsychoPy website Automated monitor calibration (for supported photometers).Input from keyboard, mouse, microphone or button boxes.Coder interface for those that like to program.Flexible stimulus units (degrees, cm, or pixels).Platform independent - run the same script on Win, macOS or Linux.Linear gratings, bitmaps constantly updating Huge variety of stimuli (see screenshots) generated in real-time:.For it to get better it needs as much input from everyone as possible. PsychoPy has been written and provided to you absolutely for free. And if you make changes that others might use then please consider giving them back to the community via the mailing list. It is used by many labs worldwide for psychophysics, cognitive neuroscience and experimental psychology.īecause it’s open source, you can download it and modify the package if you don’t like it. PsychoPy combines the graphical strengths of OpenGL with the easy Python syntax to give scientists a free and simple stimulus presentation and control package. PsychoPy is an open-source package for running experiments in Python (a real and free alternative to Matlab). Link to the GitHub repository Get to Wavesurfer site A similar tool for Python is provided by the companion PyWaveSurfer project.Ĭan integrate with Vidrio Technologies ScanImage for laser-scanning microscopy Provides a tool for reading WaveSurfer data files in Matlab. Saves data in HDF5 format, an open standard for scientific data User can extend with custom Matlab scripts for online analysis, visualizationĬustom Matlab code can be run at start/end of trials, or periodically during acquisition Works with National Instruments X-series DAQ boardsįlexible and fast multi-electrode test pulse generation Tight integration with Heka and Axon patch-clamp amplifiers Works with any model of patch-clamp amplifier ShuTu was written by Dezhe Jin (Penn State University) and Ting Zhao (Janelia) in collaboration with Nelson Spruston (Janelia).Ī more detailed description of ShuTu can be found here (Frontiers in Neuroinformatics).įor more resources, including software downloads, go here (Dezhe Jin's ShuTu site).WaveSurfer is an application for acquiring neurophysiology data in Matlab developed by Dr Adam Taylor at Janelia Farm Research CampusĪcquisition can be either trial-based or continuousĪcquisition and stimulation can be triggered by external TTL inputsįlexible stimulus generation: pulses, trains, sinusoids, etc Thus, ShuTu was developed to facilitate a two-step process: sophisticated algorithms perform the automated reconstruction, which is then superimposed on the images, along with a convenient user interface to facilitate efficient completion of the reconstruction via manual annotation. ![]() It can also handle fluorescence images from confocal stacks, however, by first inverting the images.Įven when there is only a single neuron in the imaged volume, automated reconstruction is tricky, because of background. It is designed for neurons stained following patch-clamp recording and biocytin filling/staining. ShuTu (Chinese for “dendrite”) is a software platform for semi-automated reconstruction of neuronal morphology.
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