trodes_to_nwb

Converts data from SpikeGadgets .rec files to the NWB 2.0+ Data Format.

It then validates the NWB file using the NWB Inspector for compatilibity for upload to the DANDI archive.

This replaces rec_to_nwb.

Installation

You can install trodes_to_nwb in two ways.

For most users, we recommend installing trodes_to_nwb in a virtual or conda environment via pip.

Developers should install from source.

1. Install from PyPI

   pip install trodes_to_nwb
   

2. Install from source

   Note: We currently reccomend using mamba as a package manager. If using conda, please replace mamba with conda in the command below.

   git clone https://github.com/LorenFrankLab/trodes_to_nwb.git
   
   cd trodes_to_nwb
   
   mamba env create -f environment.yml
   
   mamba activate trodes_to_nwb
   
   pip install -e .
   

Usage

1. Place your files in a folder. Subfolders are okay. The files with the following extensions should be in your directory:

   • .rec: binary file containing the ephys recording, accelerometer, gyroscope, magnetometer, DIO data, header
   • .videoPositionTracking: trodes tracked position (optional)
   • .h264: video file
   • .cameraHWSync: position timestamps
   • .stateScriptLog: state script controls the experimenter parameters

   These files need to be named in the following format {date}_{animal}_{epoch}_{tag}.{extension} where date is in the YYYYMMDD format, epoch is an integer with zero padding (e.g. 02 and not 2), and tag can be any handy short descriptor. For example, 20230622_randy_02_r1.rec is the recording file for animal randy, second epoch, run 1 (r1) for June 22, 2023.

   (Note: By default, Trodes saves video-related files (.h264, videoPositionTracking, cameraHWSync) slightly different from this format as {date}_{animal}_{epoch}_{tag}.{camera number}.{extension}. This is accepted by this conversion package, and used to match camera to position tracking in epochs with mulitple cameras)

2. Create a metadata yaml file for each recording session. See this example metadata yaml file. We recommend using the NWB YAML Creator to create the metadata yaml file in the correct format.

   The metadata yaml file should be named {date}_{animal}.metadata.yml where date is in the YYYYMMDD format and placed in the same directory as the .rec files.

   Here is an example valid directory structure:

   `-- beans
      |   |
      |   `-- raw
      |       |
      |       `-- 20190718
      |           |-- 20190718_beans_01_s1.1.h264
      |           |-- 20190718_beans_01_s1.1.trackgeometry
      |           |-- 20190718_beans_01_s1.1.videoPositionTracking
      |           |-- 20190718_beans_01_s1.1.videoTimeStamps
      |           |-- 20190718_beans_01_s1.1.videoTimeStamps.cameraHWSync
      |           |-- 20190718_beans_01_s1.rec
      |           |-- 20190718_beans_01_s1.stateScriptLog
      |           `-- 20190718_beans_metadata.yml
      |
      `-- README.md
   

3. Run the code in python. This will create a NWB file for each .rec file in the output directory.

   from trodes_to_nwb.convert import create_nwbs
   
   path = "/path/to/your/data" # from step 1
   output_dir = "/path/to/your/output/directory"
   
   create_nwbs(
       path,
       output_dir,
       header_reconfig_path=None,
       probe_metadata_paths=None,
       convert_video=False,
       n_workers=1,
       query_expression=None,
   )
   

   For the example directory structure above, the path would look like this:

   path = "/path/to/your/data/beans/raw"
   

   Note the following optional arguments:

   • header_reconfig_path: If you want to change the header information, you can provide a path to a yaml file with the new header information. See this example header reconfig yaml file. For example, this can be important for data recorded from non-tetrode devices.
   • probe_metadata_paths: By default, several common probe device types configurations are included in the package. If you are using a probe that is not included, you can provide a path to a yaml file with the probe metadata. See this example probe metadata yaml file for an example.
   • convert_video: Converts the .h264 video file to .mp4. This requires ffmpeg to be installed on your system.
   • n_workers: Number of workers to use for parallel processing. Defaults to 1.
   • query_expression: A query expression to select which files to convert. For example, if you have several animals in your folder, you could write "animal == 'sample'" to select only the sample animal. Defaults to None which converts all files in the directory.

   For complete example code of the conversion, see the tutorial notebook