schneider-lab-to-nwb

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

Installation from Github

We recommend installing the package directly from Github. This option 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). We also recommend the installation of conda (installation instructions) as it contains all the required machinery in a single and simple instal

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

git clone https://github.com/catalystneuro/schneider-lab-to-nwb
cd schneider-lab-to-nwb
conda env create --file make_env.yml
conda activate schneider_lab_to_nwb_env

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 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/schneider-lab-to-nwb
cd schneider-lab-to-nwb
pip install -e .

Note: both of the methods above install the repository in editable mode. The dependencies for this environment are stored in the dependencies section of the pyproject.toml file.

Helpful Definitions

This conversion project is comprised primarily by DataInterfaces, NWBConverters, and conversion scripts.

In neuroconv, a DataInterface is a class that specifies the procedure to convert a single data modality to NWB. This is usually accomplished with a single read operation from a distinct set of files. For example, in this conversion, the Zempolich2024BehaviorInterface contains the code that converts all of the behavioral data to NWB from a raw .mat file.

In neuroconv, a NWBConverter is a class that combines many data interfaces and specifies the relationships between them, such as temporal alignment. This allows users to combine multiple modalites into a single NWB file in an efficient and modular way.

In this conversion project, the conversion scripts determine which sessions to convert, instantiate the appropriate NWBConverter object, and convert all of the specified sessions, saving them to an output directory of .nwb files.

Repository structure

Each conversion is organized in a directory of its own in the src directory:

schneider-lab-to-nwb/
├── LICENSE
├── MANIFEST.in
├── README.md
├── make_env.yml
├── pyproject.toml
└── src
    └── schneider_lab_to_nwb
        ├── __init__.py
        ├── another_conversion
        └── zempolich_2024
            ├── __init__.py
            ├── zempolich_2024_behaviorinterface.py
            ├── zempolich_2024_convert_all_sessions.py
            ├── zempolich_2024_convert_session.py
            ├── zempolich_2024_intrinsic_signal_imaging_interface.py
            ├── zempolich_2024_metadata.yaml
            ├── zempolich_2024_notes.md
            ├── zempolich_2024_nwbconverter.py
            ├── zempolich_2024_open_ephys_recording_interface.py
            └── zempolich_2024_optogeneticinterface.py

For the conversion zempolich_2024 you can find a directory located in src/schneider-lab-to-nwb/zempolich_2024. Inside that conversion directory you can find the following files:

• __init__.py : This init file imports all the datainterfaces and NWBConverters so that they can be accessed directly from schneider_lab_to_nwb.zempolich_2024.

• zempolich_2024_convert_session.py : This conversion script defines the session_to_nwb() function, which converts a single session of data to NWB. When run as a script, this file converts 4 example sessions to NWB, representing all the various edge cases in the dataset.

• zempolich_2024_convert_dataset.py : This conversion script defines the dataset_to_nwb() function, which converts the entire Zempolich 2024 dataset to NWB. When run as a script, this file calls dataset_to_nwb() with the appropriate arguments.

• zempolich_2024_nwbconverter.py : This module defines the primary conversion class, Zempolich2024NWBConverter, which aggregates all of the various datainterfaces relevant for this conversion.

• zempolich_2024_behaviorinterface.py : This module defines Zempolich2024BehaviorInterface, which is the data interface for behavioral .mat files.

• zempolich_2024_optogeneticinterface.py : This module defines Zempolich2024OptogeneticInterface, which is the data interface for optogenetic stimulation from .mat files.

• zempolich_2024_intrinsic_signal_imaging_interface.py : This module defines Zempolich2024IntrinsicSignalOpticalImagingInterface, which is the data interface for intrinsic signal images (.tiff and .jpg).

• zempolich_2024_open_ephys_recording_interface.py : This module defines Zempolich2024OpenEphysRecordingInterface, which is a lightweight wrapper around neuroconv's OpenEphysLegacyRecordingInterface that is responsible for converting the OpenEphys recording data. This interface adds some extra conversion-specific metadata like relative channel positions, brain area, etc.

• zempolich_2024metadata.yaml : This metadata .yaml file provides high-level metadata for the nwb files directly as well as useful dictionaries for some of the data interfaces. For example,

  • Subject/species is "Mus musculus", which is directly included in the NWB file.
  • Ecephys/folder_name_to_start_datetime gives a mapping from 2-part folder names (ex. m53/Day1_A1) to session start times, which is used in cases where the session start time recorded by OpenEphys is ambiguous.

• zempolich_2024_notes.md : This markdown file contains my notes from the conversion for each of the data interfaces. It specifically highlights various edge cases as well as questions I had for the Schneider Lab (active and resolved).

Future conversions for this repo should follow the example of zempolich_2024 and create another folder of conversion scripts and datainterfaces. As a placeholder, here we have src/schneider-lab-to-nwb/another_conversion.

Running a Conversion

To convert the 4 example sessions, simply run

python src/schneider_lab_to_nwb/zempolich_2024/zempolich_2024_convert_session.py

To convert the whole dataset, simply run

python src/schneider_lab_to_nwb/zempolich_2024/zempolich_2024_convert_dataset.py

Note that the dataset conversion uses multiprocessing, currently set to 4 workers. To use more or fewer workers, simply change the max_workers argument to dataset_to_nwb().