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Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis
Recently, scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) multimodal fusion has been pursued in an effort to study human brain function and dysfunction to obtain more comprehensive information on brain activity in which the spatial and temporal resolutions are bot...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117508/ https://www.ncbi.nlm.nih.gov/pubmed/30197593 http://dx.doi.org/10.3389/fninf.2018.00056 |
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author | Dong, Li Luo, Cheng Liu, Xiaobo Jiang, Sisi Li, Fali Feng, Hongshuo Li, Jianfu Gong, Diankun Yao, Dezhong |
author_facet | Dong, Li Luo, Cheng Liu, Xiaobo Jiang, Sisi Li, Fali Feng, Hongshuo Li, Jianfu Gong, Diankun Yao, Dezhong |
author_sort | Dong, Li |
collection | PubMed |
description | Recently, scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) multimodal fusion has been pursued in an effort to study human brain function and dysfunction to obtain more comprehensive information on brain activity in which the spatial and temporal resolutions are both satisfactory. However, a more flexible and easy-to-use toolbox for EEG–fMRI multimodal fusion is still lacking. In this study, we therefore developed a freely available and open-source MATLAB graphical user interface toolbox, known as the Neuroscience Information Toolbox (NIT), for EEG–fMRI multimodal fusion analysis. The NIT consists of three modules: (1) the fMRI module, which has batch fMRI preprocessing, nuisance signal removal, bandpass filtering, and calculation of resting-state measures; (2) the EEG module, which includes artifact removal, extracting EEG features (event onset, power, and amplitude), and marking interesting events; and (3) the fusion module, in which fMRI-informed EEG analysis and EEG-informed fMRI analysis are included. The NIT was designed to provide a convenient and easy-to-use toolbox for researchers, especially for novice users. The NIT can be downloaded for free at http://www.neuro.uestc.edu.cn/NIT.html, and detailed information, including the introduction of NIT, user’s manual and example data sets, can also be observed on this website. We hope that the NIT is a promising toolbox for exploring brain information in various EEG and fMRI studies. |
format | Online Article Text |
id | pubmed-6117508 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61175082018-09-07 Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis Dong, Li Luo, Cheng Liu, Xiaobo Jiang, Sisi Li, Fali Feng, Hongshuo Li, Jianfu Gong, Diankun Yao, Dezhong Front Neuroinform Neuroscience Recently, scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) multimodal fusion has been pursued in an effort to study human brain function and dysfunction to obtain more comprehensive information on brain activity in which the spatial and temporal resolutions are both satisfactory. However, a more flexible and easy-to-use toolbox for EEG–fMRI multimodal fusion is still lacking. In this study, we therefore developed a freely available and open-source MATLAB graphical user interface toolbox, known as the Neuroscience Information Toolbox (NIT), for EEG–fMRI multimodal fusion analysis. The NIT consists of three modules: (1) the fMRI module, which has batch fMRI preprocessing, nuisance signal removal, bandpass filtering, and calculation of resting-state measures; (2) the EEG module, which includes artifact removal, extracting EEG features (event onset, power, and amplitude), and marking interesting events; and (3) the fusion module, in which fMRI-informed EEG analysis and EEG-informed fMRI analysis are included. The NIT was designed to provide a convenient and easy-to-use toolbox for researchers, especially for novice users. The NIT can be downloaded for free at http://www.neuro.uestc.edu.cn/NIT.html, and detailed information, including the introduction of NIT, user’s manual and example data sets, can also be observed on this website. We hope that the NIT is a promising toolbox for exploring brain information in various EEG and fMRI studies. Frontiers Media S.A. 2018-08-24 /pmc/articles/PMC6117508/ /pubmed/30197593 http://dx.doi.org/10.3389/fninf.2018.00056 Text en Copyright © 2018 Dong, Luo, Liu, Jiang, Li, Feng, Li, Gong and Yao. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Dong, Li Luo, Cheng Liu, Xiaobo Jiang, Sisi Li, Fali Feng, Hongshuo Li, Jianfu Gong, Diankun Yao, Dezhong Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title | Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title_full | Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title_fullStr | Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title_full_unstemmed | Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title_short | Neuroscience Information Toolbox: An Open Source Toolbox for EEG–fMRI Multimodal Fusion Analysis |
title_sort | neuroscience information toolbox: an open source toolbox for eeg–fmri multimodal fusion analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6117508/ https://www.ncbi.nlm.nih.gov/pubmed/30197593 http://dx.doi.org/10.3389/fninf.2018.00056 |
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