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.
Video capture is increasingly necessary for neuroscience research where neural and behavioral data are synchronized to reveal correlative and causal relationships. This relies on a recording system that can capture quality videos without significant alterations to preexisting experimental conditions (e.
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.
While accurate behavioral state classification is critical for many research applications, it is often done manually, which can be both tedious and inaccurate. Here we present a novel artificial neural network that uses electrophysiological features to automatically classify behavioral state in rats with high accuracy, sensitivity, and specificity.
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.
Some forms of canine cognition research require a dispenser that can accurately dispense precise quantities of treats. When using off-the-shelf or retrofitted dispensers, there is no guarantee that a precise number of treats will be dispensed.