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#!/bin/bash | ||
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DIRECTORY="/path/to/directory" | ||
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if [ -d "$DIRECTORY" ]; then | ||
# Directory exists, pull changes | ||
cd "$DIRECTORY" | ||
git pull | ||
else | ||
# Directory doesn't exist, clone from GitHub | ||
git clone https://github.com/username/repository.git "$DIRECTORY" | ||
fi |
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title: NFT | ||
long_title: NFT | ||
parent: Plugins | ||
categories: plugins | ||
has_children: true | ||
nav_order: 3 | ||
--- | ||
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 | ||
Pre-compiled binaries for the following 3rd party programs are distributed | ||
within the NFT toolbox for convinience of the users. The binaries are compiled | ||
for 32 and 64 bit Linux distributions. | ||
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![right](NFTsmall.jpg "wikilink") | ||
All of these programs have opensource licenses and provide full source-code. | ||
Please visit home-pages of individual programs for more information on usage, | ||
source-code and license information. | ||
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### What is NFT? | ||
ASC: Adaptive skeleton climbing | ||
homepage: http://www.cse.cuhk.edu.hk/~ttwong/papers/asc/asc.html | ||
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Neuroelectromagnetic Forward Modeling Toolbox (NFT) is a MATLAB toolbox | ||
for generating realistic head models from available data (MRI and/or | ||
electrode locations) and for computing numerical solutions for solving | ||
the forward problem of electromagnetic source imaging (Zeynep Akalin | ||
Acar & S. Makeig, 2010). NFT includes tools for segmenting scalp, skull, | ||
cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic | ||
resonance (MR) images. The Boundary Element Method (BEM) is used for the | ||
numerical solution of the forward problem. After extracting the | ||
segmented tissue volumes, surface BEM meshes may be generated. When a | ||
subject MR image is not available, a template head model may be warped | ||
to 3-D measured electrode locations to obtain an individualized BEM head | ||
model. Toolbox functions can be called from either a graphic user | ||
interface (gui) compatible with EEGLAB (sccn.ucsd.edu/eeglab), or from | ||
the MATLAB command line. Function help messages and a user tutorial are | ||
included. The toolbox is freely available for noncommercial use and open | ||
source development under the GNU Public License. | ||
QSLIM: Quadric-based surface simplification | ||
homepage: http://mgarland.org/software/qslim.html | ||
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### Why NFT? | ||
BEM_MATRIX: The METU-FP Toolkit | ||
homepage: http://www.eee.metu.edu.tr/metu-fp/ | ||
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The NFT is released under an open source license, allowing researchers | ||
to contribute and improve on the work for the benefit of the | ||
neuroscience community. By bringing together advanced head modeling and | ||
forward problem solution methods and implementations within an easy to | ||
use toolbox, the NFT complements EEGLAB, an open source toolkit under | ||
active development. Combined, NFT and EEGLAB form a freely available EEG | ||
(and in future, MEG) source imaging solution. | ||
PROCMESH: Mesh correction and processing. No web page yet. Please contact NFT developers for source code. | ||
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The toolbox implements the major aspects of realistic head modeling and | ||
forward problem solution from available subject information: | ||
MATITK: Matlab and ITK | ||
homepage: http://www.sfu.ca/~vwchu/matitk.html | ||
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1. Segmentation of T1-weighted MR images: The preferred method of | ||
generating a realistic head model is to use a 3-D whole-head | ||
structural MR image of the subject's head. The toolbox can generate | ||
a segmentation of scalp, skull, CSF and brain tissues from a | ||
T1-weighted image. | ||
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2. High-quality BEM meshes: The accuracy of the BEM solution depends on | ||
the quality of the underlying mesh that models tissue | ||
conductance-change boundaries. To avoid numerical instabilities, the | ||
mesh must be topologically correct with no self-intersections. It | ||
should represent the surface using high-quality elements while | ||
keeping the number of elements as small as possible. The NFT can | ||
create high-quality linear surface BEM meshes from the head | ||
segmentation. | ||
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3. Warping a template head model: When a whole-head structural MR image | ||
of the subject is not available, a semi-realistic head model can be | ||
generated by warping a standard template BEM mesh to the digitized | ||
electrode coordinates (instead of vice versa). | ||
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4. Registration of electrode positions with the BEM mesh: The digitized | ||
electrode locations and the BEM mesh must be aligned to compute | ||
accurate forward problem solutions and lead field matrices. | ||
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5. Accurate high-performance forward problem solution: The NFT uses a | ||
high-performance BEM implementation from the open source METU-FP | ||
Toolkit for bioelectromagnetic field computations. | ||
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### Required Resources | ||
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Matlab 7.0 or later running under any operating system (Linux, Windows). | ||
A large amount of RAM is useful - at least 2 GB (4-8 GB recommended for | ||
forward problem solution of realistic head models). The Matlab Image | ||
Processing toolbox is also recommended. | ||
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### NFT Reference Paper | ||
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Zeynep Akalin Acar & Scott Makeig, [Neuroelectromagnetic Forward Head | ||
Modeling | ||
Toolbox](http://sccn.ucsd.edu/%7Escott/pdf/Zeynep_NFT_Toolbox10.pdf). | ||
<em>Journal of Neuroscience Methods</em>, 2010 | ||
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Download | ||
-------- | ||
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To download the NFT, go to the [NFT download | ||
page](http://sccn.ucsd.edu/nft/). | ||
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NFT User's Manual | ||
----------------- | ||
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- [Chapter 01: Getting Started with NFT](Chapter_01_Getting_Started_with_NFT "wikilink") | ||
- [Chapter 02: Head Modeling from MR Images](Chapter_02_Head_Modeling_from_MR_Images "wikilink") | ||
- [Chapter 03: Forward Model Generation](Chapter_03_Forward_Model_Generation "wikilink") | ||
- [Chapter 04: NFT Examples](Chapter_04_NFT_Examples "wikilink") | ||
- [Chapter 05: NFT Commands and Functions](Chapter_05_NFT_Commands_and_Functions "wikilink") | ||
- [Appendix A: BEM Mesh Format](NFT_Appendix_A) | ||
- [Appendix B: Function Reference](NFT_Appendix_B) | ||
- [Appendix C: Effect of brain-to-skull conductivity ratio estimate](NFT_Appendix_C) | ||
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- [Click here to download the NFT User Manual as a PDF book](NFT_Tutorial.pdf) | ||
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<div align=right> | ||
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Creation and documentation by: | ||
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Zeynep Akalin Acar | ||
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Project Scientist | ||
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[email protected] | ||
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</div> | ||
Note: The MATITK shared libraries are installed in the 'mfiles' directory. |
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