NeuroConv
=========
.. image:: img/neuroconv_logo.png
:width: 300
..
:scale: 100 %
:align: right
NeuroConv is a Python package for converting neurophysiology data in a variety
of proprietary formats to the Neurodata Without Borders (NWB) standard.
Features:
* Reads data from 50 popular neurophysiology data formats and writes to NWB using best practices.
* Extracts relevant metadata from each format.
* Handles large data volume by reading datasets piece-wise.
* Minimizes the size of the NWB files by automatically applying chunking and lossless compression.
* Supports ensembles of multiple data streams, and supports common methods for temporal alignment of streams.
Installation
------------
To install the latest stable release of **neuroconv** you can use `pip `_. To do this, run:
.. code-block:: bash
pip install neuroconv
Installation instructions for specific format dependencies can be found in the :ref:`Conversion Examples Gallery ` for each format.
For instructions on installing the latest development version or additional installation options, see the `GitHub README `_.
How to use the documentation
----------------------------
Our documentation is structured to cater to users ranging from beginners to advanced developers and contributors.
Below is an overview of the key sections to help you navigate our documentation effectively
* **Getting Started: Conversion Examples Gallery**
If you're new to NeuroConv or NWB, start with the :ref:`Conversion Examples Gallery `.
This section provides concise scripts for converting data from common formats (e.g., Blackrock, Plexon, Neuralynx) to NWB. It's designed to get you up and running quickly.
* **User Guide**
The :ref:`User Guide ` offers a comprehensive overview of NeuroConv's data model and functionalities.
It is recommended for users who wish to understand the underlying concepts and extend their scripts beyond basic conversions.
* **How To Guides**
The :ref:`How To Guides ` section contains practical guides for using NeuroConv effectively and solve
common problems.
* **Developer Guide**
For developers interested in contributing to NeuroConv, the :ref:`Developer Guide ` provides essential information such as
instructions for building your own classes, our coding style, instructions on how to build the documentation,
run the testing suite, etc.
* **API Reference**
Detailed documentation of the NeuroConv API can be found in the :ref:`API ` section.
Do you find that some information is missing or some section lacking or unclear? Reach out with an issue or pull request on our `GitHub repository `_.
We are happy to help and appreciate your feedback.
Citing NeuroConv
----------------
If you use NeuroConv in your research, please cite our paper:
Mayorquin, H., Baker, C., Adkisson-Floro, P., Weigl, S., Trapani, A., Tauffer, L., RĂ¼bel, O., & Dichter, B. (2025).
NeuroConv: Streamlining Neurophysiology Data Conversion to the NWB Standard.
*Proceedings of the 24th Python in Science Conference* (SciPy 2025). https://doi.org/10.25080/cehj4257
**BibTeX:**
.. code-block:: bibtex
@inproceedings{mayorquin2025neuroconv,
title={NeuroConv: Streamlining Neurophysiology Data Conversion to the NWB Standard},
author={Mayorquin, Heberto and Baker, Cody and Adkisson-Floro, Paul and Weigl, Szonja and Trapani, Alessandra and Tauffer, Luiz and R\"ubel, Oliver and Dichter, Benjamin},
booktitle={Proceedings of the 24th Python in Science Conference},
year={2025},
month={July},
doi={10.25080/cehj4257}
}
.. toctree::
:maxdepth: 2
:hidden:
user_guide/index
conversion_examples_gallery/index
how_to/index
developer_guide/index
api/index
Related links
-------------
For an overview of the NWB standard and ecosystem, please view:
- The `NWB Overview `_
For a no code solution to conversion to NWB, please view:
- The `NWB-Guide Project `_
For more information regarding the NWB Standard, please view
- The `NWB Format Specification `_
For examples of conversion pipelines that use NeuroConv, check out: https://catalystneuro.com/nwb-conversions/
.. seealso::
Watch a video introduction to NeuroConv `here `_
.. Indices and tables
.. ==================
..
.. * :ref:`genindex`
.. * :ref:`modindex`
.. * :ref:`search`