Spike2 data conversion

Install NeuroConv with the additional dependencies necessary for reading Spike2 data by Cambridge Electronic Design (CED).

pip install "neuroconv[spike2]"

Warning

The sonpy library that reads Spike2 files only publishes wheels for Windows (Python 3.9 to 3.14) and, on Linux and macOS, for Python 3.14 and above. On any other combination the extra installs everything except sonpy and the interface throws an error naming the platform and the Python version.

Note

Reading is broken right now against sonpy>=1.9.12, which removed the sonpy.lib namespace that Neo uses. See NeuralEnsemble/python-neo#1890.

Convert Spike2 data to NWB using Spike2RecordingInterface.

from datetime import datetime
from zoneinfo import ZoneInfo
from pathlib import Path
from neuroconv.datainterfaces import Spike2RecordingInterface

# For this interface we need to pass the specific path to the files.
file_path = f"{ECEPHY_DATA_PATH}/spike2/m365_1sec.smrx"
# Change the file_path to the location in your system
interface = Spike2RecordingInterface(file_path=file_path, verbose=False)

# Extract what metadata we can from the source files
metadata = interface.get_metadata()
# For data provenance we add the time zone information to the conversion
session_start_time = datetime(2020, 1, 1, 12, 30, 0, tzinfo=ZoneInfo("US/Pacific"))
metadata["NWBFile"].update(session_start_time=session_start_time)
# Add subject information (required for DANDI upload)
metadata["Subject"] = dict(subject_id="subject1", species="Mus musculus", sex="M", age="P30D")

# Choose a path for saving the nwb file and run the conversion
nwbfile_path = f"{path_to_save_nwbfile}"
interface.run_conversion(nwbfile_path=nwbfile_path, metadata=metadata)