DataJoint Elements is a growing compilation of community-curated, open-source software modules for building automated data pipelines and analysis workflows for neuroscience experiments.
DataJoint Elements enables:
Secure tracking of animal subjects, equipment, and procedures Automatic data ingestion Customized research workflows Faster deployment Improved reproducibility Greater continuity across projects Secure tracking.
DataJoint Core is an open-source toolkit for defining and operating computational data pipelines (i.e., sequences of steps for data acquisition, processing, and transformation).
Pipelines built in DataJoint Core offer:
Efficient design with intuitive queries Automated, reproducible computation with full referential integrity Coordination of multiple human and computer workers Flexibility to adapt and change DataJoint Core includes libraries for Python and MATLAB, a REST API, and GUI tools for data entry and visualizations.
SqueakR is an open-source R package, available on CRAN, which streamlines bioacoustics research through automated data processing and visualizations for rodent vocalizations exported from DeepSqueak.
These functions are harnessed through the ‘SqueakR’ Shiny Dashboard, available as a function within the package, which can be used to visualize experimental results and analyses, as well as conduct statistical significance test between call features across groups.
Climbing fiber inputs to Purkinje cells provide instructive signals critical for cerebellum-dependent associative learning. Studying these signals in head-fixed mice facilitates the use of imaging, electrophysiological, and optogenetic methods. Here, a low cost behavioral platform (~$1000) was developed that allows tracking of associative learning in head-fixed mice that locomote freely on a running wheel.
BrainJ enables high-throughput analysis of serial tissue sections imaged using confocal or widefield techniques. Developed in Fiji, our approach leverages freely available tools for machine learning pixel classification for cell detection and mesoscale mapping of axons and dendrites.
FastSurfer is a fast and extensively validated deep-learning pipeline for the fully automated processing of structural human brain MRIs. As such, it provides FreeSurfer conform outputs, enables efficient big-data analysis for large cohort studies, and time-critical clinical applications such as structure localization during image acquisition or rapid extraction of quantitative measures for precision medicine.
Mesmerize is a platform for the annotation and analysis of neuronal calcium imaging data. Mesmerize encompasses the entire process of calcium imaging analysis from raw data to interactive visualizations. Mesmerize allows you to create FAIR-functionally linked datasets that are easy to share.
Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months.
CASCADE translates calcium imaging ΔF/F traces into spiking probabilities or discrete spikes. CASCADE is based on deep networks and runs on Python (Linux/Windows/Mac); it can be used either as a web application (Colaboratory notebook), or locally on a CPU or GPU.