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‎code/plugins/update_plugins.sh

Whitespace-only changes.

‎plugins/ARfitStudio/index.md

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title: ARfitStudio
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long_title: ARfitStudio
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parent: Plugins
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nav_order: 7
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/ARfitStudio).
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What is ARfitStudio
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-------------------
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‎plugins/EEG-BIDS/index.md

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title: EEG-BIDS
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long_title: EEG-BIDS
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parent: Plugins
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nav_order: 9
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/EEG-BIDS).
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![EEG-BIDS](https://github.com/sccn/EEG-BIDS/assets/1872705/47675a55-6573-47d7-abec-48e364d5ad8a)
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# EEG-BIDS

‎plugins/ICLabel/index.md

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title: ICLabel
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long_title: ICLabel
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parent: Plugins
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nav_order: 13
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/ICLabel).
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# ICLabel
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An automatic EEG independent component classifer plugin for EEGLAB.
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For more information, see [the ICLabel website tutorial](https://labeling.ucsd.edu/tutorial/about).

‎plugins/NFT/index.md

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parent: Plugins
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categories: plugins
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has_children: true
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nav_order: 3
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/NFT).
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### Open Source Matlab Toolbox for Neuroelectromagnetic Forward Head Modeling
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![right](NFTsmall.jpg "wikilink")

‎plugins/NIMA/index.md

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title: NIMA
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long_title: NIMA
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parent: Plugins
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nav_order: 26
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/NIMA).
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NIMA stands for Nima's Images from Measure-projection Analysis. Measure
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Projection Toolbox (MPT) is a published method (Bigdely-Shamlo et al.,
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2013), and for his wiki page see [this

‎plugins/PACT/index.md

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parent: Plugins
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categories: plugins
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has_children: true
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nav_order: 4
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/PACT).
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What is PACT?
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-------------
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‎plugins/PACTools/index.md

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title: PACTools
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long_title: PACTools
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parent: Plugins
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nav_order: 17
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/PACTools).
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[![GitHub stars](https://img.shields.io/github/stars/sccn/PACTools?color=%235eeb34&logo=GithUb&logoColor=%23fafafa)](https://github.com/sccn/PACTools/stargazers)
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[![GitHub forks](https://img.shields.io/github/forks/sccn/PACTools?color=%23b3d9f5&logo=GitHub)](https://github.com/sccn/PACTools/network)
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[![GitHub issues](https://img.shields.io/github/issues/sccn/PACTools?color=%23fa251e&logo=GitHub)](https://github.com/sccn/PACTools/issues)

‎plugins/PowPowCAT/index.md

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title: PowPowCAT
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long_title: PowPowCAT
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parent: Plugins
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nav_order: 16
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/PowPowCAT).
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Presentation slides (Click the cat to download)
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=================================================
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<a href="images/PowPowCAT_31stEEGLABWorkshop.pdf" class="image fit"><img src="images/PowPowCAT_logo.png" alt=""></a>

‎plugins/SIFT/Chapter-7.-Statistics-in-SIFT.md

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Another current method to compute statistics is to export the connectivity matrices stored in the CAT substructure of the EEG dataset. On the MATLAB command line type:
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```matlab
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```
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>> EEG(1).CAT.Conn
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ans =

‎plugins/SIFT/index.md

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parent: Plugins
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categories: plugins
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has_children: true
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nav_order: 1
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/SIFT).
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![700px\|link=](https://github.com/sccn/SIFT/assets/1872705/1abc1d2d-36bb-4cfb-9328-b57a96044f55)
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‎plugins/amica/index.md

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title: amica
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long_title: amica
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parent: Plugins
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nav_order: 19
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/amica).
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# Amica
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Code for AMICA: Adaptive Mixture ICA with shared component
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‎plugins/clean_rawdata/index.md

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parent: Plugins
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categories: plugins
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has_children: true
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nav_order: 6
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/clean_rawdata).
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Historical Background (01/07/2020 updated)
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------------------------------------------
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‎plugins/dipfit/index.md

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title: dipfit
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long_title: dipfit
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parent: Plugins
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nav_order: 14
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/dipfit).
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Description
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=====
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DIPFIT is an [EEGLAB](http://eeglab.org) plugin to perform inverse source localization.

‎plugins/eegstats/index.md

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title: eegstats
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long_title: eegstats
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parent: Plugins
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nav_order: 15
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/eegstats).
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# EEGSTATS plugin for EEGLAB
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This plugin computes frequency band power, alpha peak frequency, and alpha asymmetry. It uses the [restingIAF](https://github.com/corcorana/restingIAF) MATLAB code for some computation.

‎plugins/fMRIb/index.md

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title: fMRIb
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long_title: fMRIb
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parent: Plugins
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nav_order: 20
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/fMRIb).
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THIS REPOSITORY IS LOOKING FOR A MAINTAINER. IF YOU USE THIS TOOL, CONSIDER MAINTAINING IT.
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# Introduction

‎plugins/firfilt/index.md

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title: firfilt
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long_title: firfilt
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parent: Plugins
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nav_order: 27
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/firfilt).
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Documentation
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-------------
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See [this page](https://eeglab.org/others/Firfilt_FAQ.html) or the [paper](https://home.uni-leipzig.de/biocog/eprints/widmann_a2015jneuroscimeth250_34.pdf) for documentation.

‎plugins/get_chanlocs/index.md

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parent: Plugins
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categories: plugins
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has_children: true
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/get_chanlocs).
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<h3>
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<b>*get_chanlocs*: Compute 3-D electrode positions from a 3-D head image

‎plugins/groupSIFT/index.md

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title: groupSIFT
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long_title: groupSIFT
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parent: Plugins
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nav_order: 11
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/groupSIFT).
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[![IMAGE ALT TEXT HERE](http://img.youtube.com/vi/jHngHEIsg7Q/0.jpg)](http://www.youtube.com/watch?v=jHngHEIsg7Q)
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Click to play the movie on Youtube. This movie shows the first application of *groupSIFT* in Loo et al. (2019) *NeuroImage: Clinical*

‎plugins/imat/index.md

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title: imat
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long_title: imat
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parent: Plugins
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nav_order: 23
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---
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To view the plugin source code, please visit the plugin's [GitHub repository](https://github.com/sccn/imat).
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# IMAT
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Independent Modulator Analysis Toolbox
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‎plugins/nsgportal/Creating-and-managing-a-job-from-pop_nsg-GUI.md

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<!-- EEGLAB GUI to launch pop_nsg-->
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<center>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/eeglab_nsgtools_menus.jpg" alt="drawing" width="400"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/eeglab_nsgtools_menus.jpg?raw=true" alt="drawing" width="400"/>
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</center>
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The GUI depicted below will pop up. The GUI can also be invoked from the MATLAB command windows by typing *pop_nsg*.
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<center>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsgguineu.jpg" alt="drawing" width="600"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsgguineu.jpg?raw=true" alt="drawing" width="600"/>
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</center>
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## Submitting a job to NSG
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<!-- Defining JOB ID -->
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<center>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsg_job2send.jpg" alt="drawing" width="600"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsg_job2send.jpg?raw=true" alt="drawing" width="600"/>
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</center>
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After this, you may click the button **Run job on NSG** to submit the job to NSG. But don't do this yet! You may want to test your job submission before that, right?
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<!-- Job submited -->
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsg_jobsubmitted.jpg" alt="drawing" width="600"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/pop_nsg_jobsubmitted.jpg?raw=true" alt="drawing" width="600"/>
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## Checking job status periodically
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<!-- Job submited -->
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/result_explorer1.jpg" alt="drawing" width="700"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/result_explorer1.jpg?raw=true" alt="drawing" width="700"/>
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</center>
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From this file explorer, navigate (by clicking into) to the folder *TestingEEGLABNSG* to acces the result files.
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Then, select e.g. the file *IC_scalp_maps.jpg* and then click the button **Load/plot**. The figure below will pop up. This figure was actually generated as part of our NSG job results (see script *run_ica_nsg.m*).
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<!-- topos -->
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/results_topos.jpg" alt="drawing" width="400"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/results_topos.jpg?raw=true" alt="drawing" width="400"/>
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</center>
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In a similar way, a *.set* file can be selected and loaded from this interface.

‎plugins/nsgportal/Registering-at-NSG.md

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The first step to using the Open EEGLAB Portal is to create an NSG account [HERE](https://www.nsgportal.org/gest/reg.php) (or by clicking on "Register account" on the NSG home page).
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG11.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG11.png?raw=true" alt="drawing" width="500"/>
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After your account is approved by the NSG team (typically within 2 days), the second step is to enter your NSG user credentials [HERE](https://nsgdev.sdsc.edu:8443/portal2/login!input.action) (else select, "Access NSG portal" on the [NSG home page](http://www.nsgportal.org/)).
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG2.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG2.png?raw=true" alt="drawing" width="500"/>
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</center>

‎plugins/nsgportal/Scheme-of-plug-in-functions-call.md

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The figure below shows a scheme of function calls in _nsgportal_. In the plug-in there are two main sets, or layers, of functions designated by the prefix _pop__ and _nsg__. The _pop__ functions open a parameter entry window when called with fewer than the required arguments, else run directly without opening a window. The second class of nsgportal functions with prefix _nsg__ can be called directly from MATLAB command line or from other MATLAB scripts or functions. These functions perform lower-level processing than the pop_ functions. A plug-in function (_eegplugin_nsgportal_) manages the inclusion and appearance of an nsgportal item in the main EEGLAB window menu.
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<center>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/nsgportal_scheme_call.png" alt="drawing" width="1000"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/nsgportal_scheme_call.png?raw=true" alt="drawing" width="1000"/>
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</center>

‎plugins/nsgportal/Setting-up-the-plug-in.md

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Use menu item **Tools > NSG Tools > NSG portal credentials and settings**. Simply enter your NSG user name and user password (see description above on this page). Inputs **NSG key** and **NSG Url** do not need to be modified. The entry **Output folder** is the folder where NSG data will be downloaded.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-Nsgcredentials.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-Nsgcredentials.png?raw=true" alt="drawing" width="500"/>
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‎plugins/nsgportal/Using-pop_nsg-command-line-tools-in-your-EEGLAB-plug-in.md

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The second function will be the focus of this tutorial. The aim of the plug-in is to perform ICA decomposition via NSG using one of two implemented decomposition approaches, 'runica' or 'jader', that performs Infomax or JADE ICA decomposition, respectively. If called from the EEGLAB menu by manually selecting the EEGLAB GUI menu item specified in the *eegplugin_icansg* function (see figure below), the plug-in will use the current EEG dataset structure loaded into EEGLAB, and will pop up an option entry window asking which ICA method to use. The figure below shows the *eegplugin_icansg* menu item selected and the *pop_icansg* window popped up as a result.
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<center>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/plugin_runicansg.jpg" alt="drawing" width="600"/>
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<img src="https://github.com/sccn/nsgportal/blob/master/docs/img/plugin_runicansg.jpg?raw=true" alt="drawing" width="600"/>
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The plug-in pop-function (*pop_icansp*)can also be called from the MATLAB command line; in this case, you may pass as input the EEG dataset structure you want to decompose as well as the decomposition method to apply to the data. The sample code below specifies both the EEG dataset structure to operate on and the ICA decomposition type to apply; it thus will perform ICA decomposition via NSG on the currently loaded (EEG structure) dataset (using *'runica'*) *without* popping up a parameter input window:

‎plugins/nsgportal/Using-the-Open-EEGLAB-Portal.md

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Start by login into the NSG portal. Once logged in, you may upload a **zipped file** containing 1) an EEGLAB script calling 2) one or more data files by name (they should be in or under the same folder as the script). Then click on the "Data" tab and select "Upload data", then upload a file containing your script and data.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG3.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG3.png?raw=true" alt="drawing" width="500"/>
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</center>
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You may download a 3.5-MB sample zip file (containing EEG data and a sample script [HERE](https://sccn.ucsd.edu/mediawiki/images/7/7c/Testingeeglabonnsg.zip). Below is its list of contents:
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/200px-NSG32.png" alt="drawing" width="200"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/200px-NSG32.png?raw=true" alt="drawing" width="200"/>
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</center>
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The EEGLAB script (test.m) in this upload file is shown below ( try minor alterations for testing purposes)
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG33.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG33.png?raw=true" alt="drawing" width="500"/>
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</center>
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Now create a new NSG task. To do this, click on the "Task" tab and select, "Create new task." Click on, "Select input data" and select the zip file you have uploaded above. Click on "Select tool" and select "EEGLAB".
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG4.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG4.png?raw=true" alt="drawing" width="500"/>
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</center>
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Then click on "Select parameters". Enter the name of your script. This script must be at the root (top) folder of your zip archive. You may also (optionally) change other NSG settings on this page.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG5.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG5.png?raw=true" alt="drawing" width="500"/>
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Finally, press "Save parameters". This will bring you back to the previous screen. You may now press, "Save and Run Task" which will enter the task into the Comet queue. A warning is shown as in the image below. Simply click OK.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/300px-NSG6_add.png" alt="drawing" width="350"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/300px-NSG6_add.png?raw=true" alt="drawing" width="350"/>
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Once the task has been run, you will receive an email from NSG (see email for the test job below).
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG6_3.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG6_3.png?raw=true" alt="drawing" width="500"/>
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</center>
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Upon receiving this message, go back to the NSG interface and select the task you ran from the list of tasks, as shown below.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG6.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG6.png?raw=true" alt="drawing" width="500"/>
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</center>
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Select "View" following the heading "Output" (see above): this will bring the output below.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG7.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG7.png?raw=true" alt="drawing" width="500"/>
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</center>
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You may now download the task output, a zip file containing the results of your task. Output files (see listing below) include the Matlab log and error log for your task. If your script saved data files, they will be there. For example, if you use the zip file and script provided above, below (left) is what the unzipped output archive will contain. The figure below (right) is the .jpg image created by the test.m script. Saving output images in Matlab .fig format (instead of .jpg) will allow you to read them into Matlab (for further editing, etc.). Note: The numeric data plotted in a figure can be read from the .fig file structure as well. Alternatively, saving figures in Postscript (e.g., as .epsc) will allow you to edit them in Illustrator.
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Note: To save needless transfer time and effort, the uploaded data file itself will not be returned with the output unless your script explicitly saves it under a new name. In future this will also allow you to temporarily store and reuse the uploaded data.
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<center>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG8.png" alt="drawing" width="500"/>
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<img src="https://github.com/nucleuscub/pop_nsg_wiki/blob/master/docs/img/500px-NSG8.png?raw=true" alt="drawing" width="500"/>
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</center>
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### Interact with NSG through command line interface NSG-R and the creation of NSG EEGLAB Plugin

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