| Name | erdetect JSON |
| Version |
2.6.2
JSON |
| download |
| home_page | None |
| Summary | A package for the automatic detection of evoked responses in SPES/CCEP data |
| upload_time | 2025-01-09 22:56:51 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | GPLv3 |
| keywords |
evoked response
detection
ieeg
n1
spes
ccep
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 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](https://github.com/MultimodalNeuroimagingLab/erdetect/wiki/).
The tool can be configured by three means:
- Graphical User Interface (GUI)
- Command-line, arguments and options can be found [here](https://github.com/MultimodalNeuroimagingLab/erdetect/wiki/Configuration#command-line-arguments)
- JSON input configuration file, usage documentation can be found [here](https://github.com/MultimodalNeuroimagingLab/erdetect/wiki/Configuration#json-input-configuration-file)
## 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](http://www.mathworks.com/matlabcentral/fileexchange/25500).
- 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
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