nelson-lab-to-nwb

NWB conversion scripts for the Nelson lab data to the Neurodata Without Borders data format.

Installation

The package can be installed from this GitHub repo, which has the advantage that the source code can be modifed if you need to amend some of the code we originally provided to adapt to future experimental differences. To install the conversion from GitHub you will need to use git (installation instructions). The package also requires Python > 3.9. We also recommend the installation of conda (installation instructions) as it contains all the required machinery in a single and simple install.

From a terminal (note that conda should install one in your system) you can do the following:

For Windows users the conda create command should be run with Administrator privileges.

git clone https://github.com/catalystneuro/nelson-lab-to-nwb
cd nelson-lab-to-nwb
conda env create --file make_env.yml
conda activate env_nelson
python -m ipykernel install --user --name env_nelson

This creates a conda environment which isolates the conversion code from your system libraries. We recommend that you run all your conversion related tasks and analysis from the created environment in order to minimize issues related to package dependencies.

Alternatively, if you have Python > 3.9 on your machine and you want to avoid conda altogether (for example if you use another virtual environment tool), you can install the repository with the following commands using only pip:

git clone https://github.com/catalystneuro/nelson-lab-to-nwb
cd nelson-lab-to-nwb
pip install -e .

Note: both of the methods above install the repository in editable mode.

Conversion

At each experiment's folder you will find:

• The conversion scripts convert_session.py.
• The converter code <experiment>_converter.py.
• Example metadata files metadata_example.yaml.
• Jupyter notebooks example_conversion.ipynb demonstrating the usage of the conversion scripts and basic exploratory data analysis.
• A README.md file with a basic description of the data.

With Jupyter notebooks

To run the example notebooks, just navigate to the experiment's folder and run from the terminal:

conda activate env_nelson
jupyter notebook

This will open a new tab in your browser with the Jupyter interface. From there you can open the example_conversion.ipynb notebook and follow along.

With your own Python scripts

To convert the data with your own Python scripts, you can import the session_to_nwb function from convert_session.py. For example:

from nelson_lab_to_nwb.tdt_sessions_converter import session_to_nwb

nwbfile_path = session_to_nwb(
    output_folder_path="output_tdt",
    tdt_folder_path="/path_to/folder/",
    noldus_file_path="/path_to/file.xlsx",
    aim_score_file_path="/path_to/file.xlsx",
    behavioral_video_file_path="/path_to/file.avi",
    user_metadata_file_path="/path_to/metadata.yaml",
    noldus_variables_columns_names=["Elongation", "Velocity", "Distance moved", "Rotation"],
    noldus_epoc_name="Cam2",
    aim_epoc_name="TTL1",
    overwrite=True,
    verbose=True,
)

Upload to DANDI archive

Detailed instructions on how to upload the data to the DANDI archive can be found here.