Evoked Response Detection

A python package and docker application for the automatic detection of evoked responses in SPES/CCEP data

Python Usage

1. First install ERdetect, in the command-line run:

pip install erdetect

2. To run:

• a) With a graphical user interface:

python -m erdetect ~/bids_data ~/output/ --gui

• b) From the commandline:

python -m erdetect ~/bids_data ~/output/ [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]

• c) To process a subset directly in a python script:

import erdetect
erdetect.process_subset('/bids_data_root/subj-01/ieeg/sub-01_run-06.edf', '/output_path/')

Docker Usage

To launch an instance of the container and analyse data in BIDS format, in the command-line interface/terminal:

docker run multimodalneuro/erdetect <bids_dir>:/data <output_dir>:/output [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]

For example, to run an analysis, type:

docker run -ti --rm \
-v /local_bids_data_root/:/data \
-v /local_output_path/:/output \
multimodalneuro/erdetect /data /output --participant_label 01

Configuration & Documentation

General documentation can be found here.

The tool can be configured by three means:

• Graphical User Interface (GUI)
• Command-line, arguments and options can be found here
• JSON input configuration file, usage documentation can be found here

Acknowledgements

• Written by Max van den Boom (Multimodal Neuroimaging Lab, Mayo Clinic, Rochester MN)

• Deviation from baseline method by Dorien van Blooijs & Dora Hermes (2018), with optimized parameters by Jaap van der Aar

• Adapted the peak-finder algorithm by Nathanael Yoder, see Matlab version.

• Dependencies:

  • IeegPrep (https://github.com/MultimodalNeuroimagingLab/ieegprep)
  • BIDS-validator (https://github.com/bids-standard/bids-validator)
  • NumPy
  • SciPy
  • Matplotlib

• This project was funded by the National Institute Of Mental Health of the National Institutes of Health Award Number R01MH122258 to Dora Hermes