Hierarchical Event Descriptors (HED) is an open standard and supporting ecosystem for describing experimental events, conditions, and experiment organization in a format that is both human- and machine-readable to enable analysis, re-analysis, and meta/mega analysis.

SWC files (file extension of .swc) are text-based (ASCII text) files that describe three-dimensional neuronal or glial morphology. These digital reconstructions represent morphology as a vectorized tree structure, made of a series of connected nodes. An SWC file contains a series of text-based rows where each neuron node is described by a single row of only seven space-separated values. The format is simple and intuitive; a parser of or writer to the format could be implemented by anyone with knowledge of any programming language.

NetPyNE is an open-source Python package designed for the development, simulation, and analysis of biological neuronal networks. Built on top of the widely used NEURON simulator, NetPyNE is a high-level interface for creating, managing, and simulating complex neural network models using declarative network specification.

Publication:

NetPyNE, a tool for data-driven multiscale modeling of brain circuits, eLife 2019;8:e44494. https://doi.org/10.7554/eLife.44494/

The SPARC data structure is a consistent file structure and naming convention, based on the Brain Imaging Data Structure (BIDS) to ensure that the diverse types of data in SPARC is organized in a similar manner.

Neo is an object model for handling electrophysiology data in multiple formats. It is suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. Neo has been implemented as a Python package for working with electrophysiology data, together with support for reading a wide range of neurophysiology file formats (including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro), and support for writing to a subset of these formats plus non-proprietary formats including Kwik and HDF5.

The neuromorphological file format balances structure with flexibility by storing each modeled object as a unique data element and providing mechanisms for grouping any number and type of data elements. File-level metadata is retained to provide detail on the origin of the sample, ensuring that the provenance of derivative data is tracked and that important source information is not separated from the corresponding data.

The Five Recommendations for FAIR Software aim to encourage the greater adoption of FAIR principles by providing a set of starting recommendations that researchers can use to improve the quality, reach, and reproducibility of their software.The FAIR principles are a concept which originated in data management. The acronym stands for Findable, Accessible, Interoperable and Reusable. They have served as a flagship for promoting good data management practices, but until recently they were not directly applicable to software. FAIR principles aim to have a positive effect in research software development.

Neuroscience information exchange format (NIX) data model allows storing fully annotated scientific datasets, i.e. the data together with rich metadata and their relations in a consistent, comprehensive format. Its aim is to achieve standardization by providing a common data structure and APIs for a multitude of data types and use cases, focused on but not limited to neuroscience.

Neurodata Without Borders (NWB) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build analysis tools for neurophysiology data. NWB is designed to store a variety of neurophysiology data, including data from intracellular and extracellular electrophysiology experiments, data from optical physiology experiments, and tracking and stimulus data.

The Brain Imaging Data Structure (BIDS) is a standard prescribing a formal way to name and organize MRI data and metadata in a file system that simplifies communication and collaboration between users and enables easier data validation and software development through using consistent paths and naming for data files.