Software Solutions
CatalystNeuro develops software solutions across the data pipeline aimed to help neuroscientists focus on the science and accelerate their discovery process immediately. We release and support packages for data homogenization, visualization, analysis, and lab-wide records. These libraries are developed by a team that focuses specifically on neural data and good software practices. Our projects are packaged, documented, and tested for robustness and ease of use. Everything we build is released as it is developed under a permissive license.
We commonly work with labs to customize these software solutions to the specific needs of the lab, interfacing our platforms with their data formats and analysis packages.
Analysis and Visualization Software
Our core projects allow us to develop software over the long term that meets needs that reoccur in the neurophysiology community.
ecogVlS
A GUI for electrophysiology data visualization, annotation, and preprocessing. ecogVlS was originally designed for the Chang Lab at UCSF to streamline preprocessing pipeline with the NWB data standard. The GUI is pure python which makes it hackable and easy to customize for specific applications. Graphing is performed by PyQtGraph, which is very performant.
NWBWidgets
A library of widgets for visualization of NWB data in a Jupyter notebook (or lab). The widgets allow you to navigate through the hierarchical structure of the NWB file and visualize specific data elements. It is designed to work out-of-the-box with NWB files and to be easy to extend. This work is in collaboration with Kitware and has been funded in part by Kitware and the Allen Institute SBIR project.
ROI ExtractorsPython-based module for extracting converting, and handling recorded optical imaging data from between different file formats. Inspired by the SpikeInterface project.
lazy_opsLazy transposing and slicing for h5py Datasets. Slice and transpose h5py Datasets lazily so that you can efficiently read only the data you need.
NWB Extensions
Neurodata Extensions (NDX) allow labs to standardize, share, and publish data outside of the core scope of NWB inside NWB files. We regularly build extensions to support unique data types and use-cases within cellular neurophysiology.
Simulation Output
This extension defines two NWB neuorodata_types, CompartmentSeries and Compartments. CompartmentSeries stores continuous data (e.g. membrane potential, calcium concentration) from many compartments of many cells, and scales to hundreds of thousands of compartments. Compartments stores the meta-data associated with those compartments, and is stored in SimulationMetaData. Compatibility with SONATA. Collaboration with Stanford University and the Allen Institute. Funded by the Ripple U19.
Bipolar Scheme
Structure for storing the bipolar schema of a recording in NWB file. Allows for storage of bipolar recordings, stimulation configurations, or offline bipolar re-referencing. Also allows for multiple electrodes to be combined into a single anode or cathode. Collaboration with the Chang Lab, UC San Francisco.
Point Cloud Table
Stores point cloud data in NWB. This can be used to track the shape of an animal over time. PointCloudTable inherits from DynamicTable, and can store an entire session of point cloud data in 4 datasets. Collaboration with Kitware Inc and the Soltesz Lab, Stanford University. Funded by the Ripple U19.
FRET
NWB extension for storing Fluorescence Resonance Energy Transfer (FRET) experimental data. A collaboration with Jaeger Lab, Emory University and The Kavli Foundation.
Lab-specific Repositories
Building lab-specific repositories allow us to customize our general tools for each lab’s specific use-case, and to showcase how that lab can use those tools to interface with their existing data and analysis.
Tollas and Brens
Tols-lc-to-nwb: Convert patch-master mat intracellular electrophyslology to NWB. Developed in collaboration with the Tolias and Berens lobs under the DANDI project
Dieter Jaeger, Emory Universityjaeger-lab-data-to-nwb: Convert FRET optical imaging, extracellular electrophysiology, nad behavior. Funded by Kavil Foundation
Gyorgy Buzsaki, NYUbuzsoki-lob-to-nwb: Convert extracellulor electrophyslology and behavior, Funded by Stanford University, NIH as part of the Ripple U19.
Richard Axel, Columbia Universityaxe-Lab-to-nwb: NWB conversion scripts and tutorials for SCAPE microscopy data. Funded by Simons Foundation
Lisa Giocomo, Stanford Universitygiocomo-lab-to-nwt: Scripts and tutorials for converting SpikeGLX neuropixel extrocellular electrophyslology data to NWB. Wicludes demonstration of applying Spikelnteiface for spike-sorting.Funded by Simons Foxidation
Beth Buffalo, University of Washingtonbuffalo-lab-to-nwb: Scripts which convert Buffalo lab data to NWB format. Currently we only support conversion for processed data Funded by the Simons Foundation.
Contributions:
We are major contribution to the following repositories: