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A package for the automatic detection of evoked responses in SPES/CCEP data

Project description

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
  1. 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:

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

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