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Brainstorm is a free Matlab application dedicated to Magnetoencephalography(MEG) and Electroencephalography(EEG) data visualization, processing and cortical source estimation. <<BR>>Our intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.<<BR>>For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge. | ||<tablestyle="width: 700px; height: 662px;">Brainstorm is a collaborative, open-source application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data analysis ('''visualization, processing and advanced source modeling'''). Our objective is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique. For physicians and researchers, the main advantage of Brainstorm is its rich and intuitive graphic interface, which does not require any programming knowledge. We are also putting the emphasis on practical aspects of data analysis (e.g., with scripting for batch analysis and intuitive design of analysis pipelines) to promote reproducibility and productivity in MEG/EEG research. Finally, although Brainstorm is developed with Matlab (and Java), it does not require users to own a Matlab license: an executable, platform-independent (Windows, MacOS, Linux) version is made available in the [[Download|downloadable package]].|| || ||Since the project started by the end of the 1990's, our server has registered more than 6,000 software downloads and about 500 users are actively updating the sofware. See our [[Pub|reference page]] for a list of published studies featuring Brainstorm at work! The best way to learn how to use Brainstorm, like any other academic software, is to benefit from local experts. However, you may be the first one in your institution to consider using Brainstorm for your research. We are happy to provide comprehensive [[Introduction/Tutorials|online documentation]] and support through [[Introduction/../forums|our forum]] but there is nothing better than a [[Training|course]] to make your learning curve steeper. Consult our [[Training|training pages]] for upcoming opportunities to learn better and faster! Finally, have a look regularly at our [[News|What's New]] pages for staying on top of Brainstorm news and updates. We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community! || || Brainstorm is a collaborative, open-source application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data analysis ('''visualization, processing and advanced source modeling'''). Our objective is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique. For physicians and researchers, the main advantage of Brainstorm is its rich and intuitive graphic interface, which does not require any programming knowledge. We are also putting the emphasis on practical aspects of data analysis (e.g., with scripting for batch analysis and intuitive design of analysis pipelines) to promote reproducibility and productivity in MEG/EEG research. Finally, although Brainstorm is developed with Matlab (and Java), it does not require users to own a Matlab license: an executable, platform-independent (Windows, MacOS, Linux) version is made available in the [[Download|downloadable package]]. Since the project started by the end of the 1990's, our server has registered more than 6,000 software downloads and about 500 users are actively updating the software. See our [[Pub|reference page]] for a list of published studies featuring Brainstorm at work! The best way to learn how to use Brainstorm, like any other academic software, is to benefit from local experts. However, you may be the first one in your institution to consider using Brainstorm for your research. We are happy to provide comprehensive [[Introduction/Tutorials|online documentation]] and support through [[Introduction/../forums|our forum]] but there is nothing better than a [[Training|course]] to make your learning curve steeper. Consult our [[Training|training pages]] for upcoming opportunities to learn better and faster! Finally, have a look regularly at our [[News|What's New]] pages for staying on top of Brainstorm news and updates. We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community! == How to cite Brainstorm == Please cite the following reference in your publications if you have used our software for your data analyses: [[CiteBrainstorm|How to cite Brainstorm]]. It is also good offline reading to get an overview of the main features of the application. Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM (2011), ''Brainstorm: A User-Friendly Application for MEG/EEG Analysis'', '''Computational Intelligence and Neuroscience''', vol. 2011, Article ID 879716, 13 pages. doi:10.1155/2011/879716 [ [[http://www.hindawi.com/journals/cin/2011/879716/|html]], [[http://downloads.hindawi.com/journals/cin/2011/879716.pdf|pdf]] ] |
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* Import MEG / EEG recordings from the most popular file formats ([[FileFormats|list here]]) | * '''MEG/EEG recordings:''' * Read data from the most popular file formats ([[#line-78|listed here]]); can import form multiple ASCII files as well * Interactive access to data files in native formats * Import data in Matlab * Import and order data in a well-organized database (by studies, subjects, conditions) * Review, edit, import, export event markers in continuous, ongoing recordings * Automatic detection of well-defined artifacts (eye blinks, heartbeats...) * Artifact correction using Signal Space Projections (SSP) |
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* Data visualization: * Various time series displays * Data mapping on the head surface * Generate slides and animations * Channel selection |
* '''Pre-processing: ''' * Epoching * Detection of bad trials / bad channels * Baseline correction |
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* 3D surface rendering | * Resampling * Multiple options for epoch averaging * Estimation of noise statistics for improved source modeling |
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* MRI visualization and coregistration: * Import MRI scans, from most of the existing file formats ([[FileFormats|list here]]) * Co-registration with the MEG/EEG coordinate system * Volume rendering |
* '''Powerful and versatile visualization: ''' * Various time series displays (epoched, continuous raw, butterfly, columns, etc.) * Data mapping on 2D or 3D surfaces (disks, true geometry of sensor array, scalp surface, etc.) * Generate slides and animations (export as contact sheets, movies, jpegs, ...) * Channel selection and sensor clustering (save and organize your favorites, share with your collaborators, etc.) |
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* Database: * Classification of recordings with three levels of definition (protocol, subject, condition/event) * Quick access to all the data in a study * Quick comparison between subjects or conditions * Graphic batching tools (apply a same process to many files in a few clicks) |
* '''MRI visualization and coregistration: ''' * Use individual or template anatomy (MNI / Colin27 brain) * Template anatomy can be warped to individual head surface * Import MRI volumes and tessellated surface envelopes from most of the existing file formats ([[#line-78|listed here]]) * Automatic or interactive co-registration with the MEG/EEG coordinate system * Volume rendering (mulitple display modes) |
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* Forward modeling: * Single sphere method * Overlapping spheres method * Realistic head models using BEM and FEM * Inverse modeling: * Minimum-norm imaging of the cortical current density |
* '''Database: Keep your data organized''' * Ordering of data, source models, time-frequency maps, statistical maps, etc. by protocol, subject and condition/event * Quick access to all the data in a study for efficient, batch processing * Quick access to comparisons between subjects or conditions * Graphical batching tools (apply the same process to many files e.g., your entire study, in a few clicks) |
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* Group analysis: * Registration of individual brains on the MNI "Colin27" brain * Statistical analysis (t-tests, permutations) |
* '''Head modeling: ''' * MEG: Single sphere, overlapping spheres * EEG: Berg's three-layer sphere, Boundary Element Models (with OpenMEEG) * Interactive interface to define the best-fitting sphere |
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== What you cannot do with Brainstorm == * Intensive pre-processing of MEG/EEG recordings (noise, artifact correction/rejection, re-averaging, etc.):<<BR>> => use your constructor's software, or other software solutions (MNE, EEGLab, etc.). [[Links|See here]]. |
* '''Source modeling: ''' * L2 Minimum-norm current estimates * dSPM * sLORETA * All models can be cortically-constrained or not, and with/without constrained orientations |
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* MRI segmentation:<<BR>> => use !FreeSurfer, !BrainSuite or !BrainVisa. [[Links|See here]]. | * '''Source display and analysis: ''' * Multiple options for surface and volume rendering of the source maps * Re-projection of the sources in the MRI volume (from surface points to voxels) * Definition of regions of interest (scouts) * Re-projection of estimated sources on a surface with higher or lower resolution, on a group template * Surface or volume spatial smoothing (group analysis) * Share your results: screen captures, make movies and contact sheets! * Import and display of Xfit (MEG Elekta software) dipole models * '''Time-frequency decompositions: ''' * Time-frequency analyses of sensor data and sources time series using Morlet wavelets * Define time and frequency scales of interest * Multiple display modes available |
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== Requirements == Brainstorm is written in Matlab code only, thus it can run on any operating system supported by Matlab (including Windows, Linux, MacOS...). |
* '''Group analysis: ''' * Registration of individual brains to a brain template (MNI/Colin27) * Statistical analysis (t-tests) |
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If you have a Matlab licence: | * '''Documentation and support: ''' * Easy and automatic updates of the software * Detailed step-by-step [[Tutorials|tutorials]] for most common features * Active user forum |
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* You can download and run directly the Brainstorm source scripts, * Minimum Matlab version: 7.1 (= R14-SP3) * Minimum Java VM version: 1.5 (To check that: type "ver" at Matlab command prompt) |
== What you cannot do with Brainstorm (yet) == * MRI segmentation: Use !FreeSurfer, !BrainSuite or !BrainVisa. [[Links|See here]]. |
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If you do not have a Matlab licence: | * Advanced statistics: Use R, Statistica, SPSS, Matlab, Excel, etc. |
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* You can download the Brainstorm binaries corresponding to your operating system. * The executables are build using the Matlab Compiler (mcc) * They will install automatically the Matlab Component Runtime (MCR) on your computer, a freely redistributable library |
== Supported file formats == === EEG: === * EGI !NetStation epoch-marked file (.raw/.epoc) * Neuroscan (.cnt, .eeg, .avg, .dat) * !BrainAmp (.eeg) * EEGLab sets (.set) * Cartool simple binary files (.ep, .eph) * !ErpCenter (.erp/.hdr) * Any type of ASCII arrays === MEG: === * CTF (.ds directory) * Neuromag FIFF (.fif) * BTi / 4D Neuroimaging * LENA format === Sensors locations: === * Cartool (.xyz, .els) * BESA (.sfp, .elp, .eps/.ela) * Polhemus Isotrak (.pos, .elp) * Curry (.res, .rs3) * EEGLab (.ced, .xyz, .set) * EETrak (.elc) * EGI (.sfp) * EMSE (.elp) * Neuroscan (.dat, .tri) * ASCII arrays === MRI volumes: === * Analyze (.img/.hdr) * Nifti-1 (.nii) * CTF (.mri) * BrainVISA GIS (.ima/.dim) * Neuromag (.fif) * MGH (.mgh, .mgz) === Meshes: === * BrainVISA (.mesh) * !BrainSuite (.dsgl, .dfs) * !FreeSurfer * ASCII (.tri) * Neuromag (.fif) === Noise covariance matrix: === * Neuromag / MNE (.fif) * ASCII arrays === Dipoles: === * Elekta Neuromag XFit (.bdip) |
Introduction
Brainstorm is a collaborative, open-source application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data analysis (visualization, processing and advanced source modeling). Our objective is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique. For physicians and researchers, the main advantage of Brainstorm is its rich and intuitive graphic interface, which does not require any programming knowledge. We are also putting the emphasis on practical aspects of data analysis (e.g., with scripting for batch analysis and intuitive design of analysis pipelines) to promote reproducibility and productivity in MEG/EEG research. Finally, although Brainstorm is developed with Matlab (and Java), it does not require users to own a Matlab license: an executable, platform-independent (Windows, MacOS, Linux) version is made available in the downloadable package. |
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Since the project started by the end of the 1990's, our server has registered more than 6,000 software downloads and about 500 users are actively updating the sofware. See our reference page for a list of published studies featuring Brainstorm at work! The best way to learn how to use Brainstorm, like any other academic software, is to benefit from local experts. However, you may be the first one in your institution to consider using Brainstorm for your research. We are happy to provide comprehensive ?online documentation and support through ?our forum but there is nothing better than a course to make your learning curve steeper. Consult our training pages for upcoming opportunities to learn better and faster! Finally, have a look regularly at our What's New pages for staying on top of Brainstorm news and updates. We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community! |
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Brainstorm is a collaborative, open-source application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data analysis (visualization, processing and advanced source modeling). Our objective is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique. For physicians and researchers, the main advantage of Brainstorm is its rich and intuitive graphic interface, which does not require any programming knowledge. We are also putting the emphasis on practical aspects of data analysis (e.g., with scripting for batch analysis and intuitive design of analysis pipelines) to promote reproducibility and productivity in MEG/EEG research. Finally, although Brainstorm is developed with Matlab (and Java), it does not require users to own a Matlab license: an executable, platform-independent (Windows, MacOS, Linux) version is made available in the downloadable package.
Since the project started by the end of the 1990's, our server has registered more than 6,000 software downloads and about 500 users are actively updating the software. See our reference page for a list of published studies featuring Brainstorm at work!
The best way to learn how to use Brainstorm, like any other academic software, is to benefit from local experts. However, you may be the first one in your institution to consider using Brainstorm for your research. We are happy to provide comprehensive ?online documentation and support through ?our forum but there is nothing better than a course to make your learning curve steeper. Consult our training pages for upcoming opportunities to learn better and faster! Finally, have a look regularly at our What's New pages for staying on top of Brainstorm news and updates.
We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community!
How to cite Brainstorm
Please cite the following reference in your publications if you have used our software for your data analyses: How to cite Brainstorm. It is also good offline reading to get an overview of the main features of the application.
Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM (2011), Brainstorm: A User-Friendly Application for MEG/EEG Analysis, Computational Intelligence and Neuroscience, vol. 2011, Article ID 879716, 13 pages. doi:10.1155/2011/879716 [ html, pdf ]
What you can do with Brainstorm
MEG/EEG recordings:
Read data from the most popular file formats (listed here); can import form multiple ASCII files as well
- Interactive access to data files in native formats
- Import data in Matlab
- Import and order data in a well-organized database (by studies, subjects, conditions)
- Review, edit, import, export event markers in continuous, ongoing recordings
- Automatic detection of well-defined artifacts (eye blinks, heartbeats...)
- Artifact correction using Signal Space Projections (SSP)
Pre-processing:
- Epoching
- Detection of bad trials / bad channels
- Baseline correction
- Frequency filtering
- Resampling
- Multiple options for epoch averaging
- Estimation of noise statistics for improved source modeling
Powerful and versatile visualization:
- Various time series displays (epoched, continuous raw, butterfly, columns, etc.)
- Data mapping on 2D or 3D surfaces (disks, true geometry of sensor array, scalp surface, etc.)
- Generate slides and animations (export as contact sheets, movies, jpegs, ...)
- Channel selection and sensor clustering (save and organize your favorites, share with your collaborators, etc.)
MRI visualization and coregistration:
- Use individual or template anatomy (MNI / Colin27 brain)
- Template anatomy can be warped to individual head surface
Import MRI volumes and tessellated surface envelopes from most of the existing file formats (listed here)
- Automatic or interactive co-registration with the MEG/EEG coordinate system
- Volume rendering (mulitple display modes)
Database: Keep your data organized
- Ordering of data, source models, time-frequency maps, statistical maps, etc. by protocol, subject and condition/event
- Quick access to all the data in a study for efficient, batch processing
- Quick access to comparisons between subjects or conditions
- Graphical batching tools (apply the same process to many files e.g., your entire study, in a few clicks)
Head modeling:
- MEG: Single sphere, overlapping spheres
- EEG: Berg's three-layer sphere, Boundary Element Models (with OpenMEEG)
- Interactive interface to define the best-fitting sphere
Source modeling:
- L2 Minimum-norm current estimates
- dSPM
- sLORETA
- All models can be cortically-constrained or not, and with/without constrained orientations
Source display and analysis:
- Multiple options for surface and volume rendering of the source maps
- Re-projection of the sources in the MRI volume (from surface points to voxels)
- Definition of regions of interest (scouts)
- Re-projection of estimated sources on a surface with higher or lower resolution, on a group template
- Surface or volume spatial smoothing (group analysis)
- Share your results: screen captures, make movies and contact sheets!
- Import and display of Xfit (MEG Elekta software) dipole models
Time-frequency decompositions:
- Time-frequency analyses of sensor data and sources time series using Morlet wavelets
- Define time and frequency scales of interest
- Multiple display modes available
Group analysis:
- Registration of individual brains to a brain template (MNI/Colin27)
- Statistical analysis (t-tests)
Documentation and support:
- Easy and automatic updates of the software
Detailed step-by-step tutorials for most common features
- Active user forum
What you cannot do with Brainstorm (yet)
MRI segmentation: Use FreeSurfer, BrainSuite or BrainVisa. ?See here.
- Advanced statistics: Use R, Statistica, SPSS, Matlab, Excel, etc.
Supported file formats
EEG:
EGI NetStation epoch-marked file (.raw/.epoc)
- Neuroscan (.cnt, .eeg, .avg, .dat)
BrainAmp (.eeg)
- EEGLab sets (.set)
- Cartool simple binary files (.ep, .eph)
ErpCenter (.erp/.hdr)
- Any type of ASCII arrays
MEG:
- CTF (.ds directory)
- Neuromag FIFF (.fif)
- BTi / 4D Neuroimaging
- LENA format
Sensors locations:
- Cartool (.xyz, .els)
- BESA (.sfp, .elp, .eps/.ela)
- Polhemus Isotrak (.pos, .elp)
- Curry (.res, .rs3)
- EEGLab (.ced, .xyz, .set)
- EETrak (.elc)
- EGI (.sfp)
- EMSE (.elp)
- Neuroscan (.dat, .tri)
- ASCII arrays
MRI volumes:
- Analyze (.img/.hdr)
- Nifti-1 (.nii)
- CTF (.mri)
- BrainVISA GIS (.ima/.dim)
- Neuromag (.fif)
- MGH (.mgh, .mgz)
Meshes:
- BrainVISA (.mesh)
BrainSuite (.dsgl, .dfs)
FreeSurfer
- ASCII (.tri)
- Neuromag (.fif)
Noise covariance matrix:
- Neuromag / MNE (.fif)
- ASCII arrays
Dipoles:
- Elekta Neuromag XFit (.bdip)