|
Size: 6334
Comment:
|
Size: 7765
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 3: | Line 3: |
| = 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 [[Download|downloadable package]]. |
= Welcome! = Brainstorm is a collaborative, open-source application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data analysis ('''visualization, processing and advanced source modeling'''). |
| Line 6: | Line 6: |
| 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 that have been using Brainstorm. | {{attachment:brainstorm_banner.gif}} |
| Line 8: | Line 8: |
| Last but not least, Brainstorm is thoroughly documented in [[http://neuroimage.usc.edu/brainstorm3_register/download.php|these pages]] and support is provided through an [[http://neuroimage.usc.edu/forums|online forum]]. | 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[[http://neuroimage.usc.edu/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. |
| Line 18: | Line 24: |
| * MEG / EEG recordings: * Reading data from the most popular file formats ([[#line-78|list here]]) * Interactive access to the original files, or copy in the database * Reviewing and editing of event markers in continuous files * Detecting automatically repetitive artifacts (eye blinks, heartbeats...) * Removing artifacts using Signal Space Projections (SSP) |
* '''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) |
| Line 25: | Line 33: |
| * Pre-processing: | * '''Pre-processing: ''' |
| Line 31: | Line 39: |
| * Averaging * Noise covariance estimation |
* Multiple options for epoch averaging * Estimation of noise statistics for improved source modeling |
| Line 34: | Line 42: |
| * Recordings visualization: * Various time series displays * Data mapping on 2D or 3D surfaces * Generate slides and animations * Channel selection, and manipulation of clusters of electrodes |
* '''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.) |
| Line 40: | Line 48: |
| * MRI visualization and coregistration: * Analysis on individual anatomy or MNI / Colin27 brain * Import MRI and meshes from most of the existing file formats ([[#line-78|list here]]) * Co-registration with the MEG/EEG coordinate system * Volume rendering (several display modes) * Deformation of the MNI template to fit an set of digitized head points |
* '''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) |
| Line 47: | Line 55: |
| * 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 * Graphical batching tools (apply the same process to many files in a few clicks) |
* '''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) |
| Line 53: | Line 61: |
| * Forward modeling: | * '''Head modeling: ''' |
| Line 55: | Line 63: |
| * EEG: Berg's three-layer sphere * Interactive interface to define the best fitting sphere |
* EEG: Berg's three-layer sphere, Boundary Element Models (with OpenMEEG) * Interactive interface to define the best-fitting sphere |
| Line 58: | Line 66: |
| * Inverse modeling: | * '''Source modeling: ''' |
| Line 62: | Line 70: |
| * All methods can be cortically constrained or not, and with constrained orientations or not | * All models can be cortically-constrained or not, and with/without constrained orientations |
| Line 64: | Line 72: |
| * Source display and analysis: * Surface and volume rendering of the estimated sources * Re-projection of the sources in the MRI volume * Definition of cortical regions of interest (scouts) * Re-projection of estimated sources on a surface with a higher or lower definition * Spatial smoothing before group analysis * Easy screen captures, creation of movies and contact sheets * Import and display of xfit dipoles * Time-frequency analysis: * Time-frequency decomposition of recordings and sources time series using Morlet wavelets * Time and frequency scales: linear or bands * Many display modes available |
* '''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 |
| Line 77: | Line 85: |
| * Group analysis: * Registration of individual brains on the MNI "Colin27" brain |
* '''Group analysis: ''' * Registration of individual brains to a brain template (MNI/Colin27) |
| Line 81: | Line 89: |
| * Documentation and support: | * '''Documentation and support: ''' |
| Line 83: | Line 91: |
| * Detailed step by step tutorials for most of the common features | * Detailed step-by-step [[Tutorials|tutorials]] for most common features |
| Line 86: | Line 94: |
| == What you cannot do with Brainstorm == | == What you cannot do with Brainstorm (yet) == |
| Line 99: | Line 107: |
| * Any type of ASCII arrays | * Any type of ASCII (text) files |
| Line 102: | Line 110: |
| * CTF (.ds directory) | * CTF (.ds folders) |
| Line 127: | Line 135: |
| === Meshes: === | === Surface tessellations/meshes: === |
| Line 134: | Line 142: |
| === Noise covariance matrix: === | === Noise statistics (sensor covariance arrays): === |
| Line 138: | Line 146: |
| === Dipoles: === | === Dipole models: === |
Welcome!
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 throughour 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 (text) files
MEG:
- CTF (.ds folders)
- 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)
Surface tessellations/meshes:
- BrainVISA (.mesh)
BrainSuite (.dsgl, .dfs)
FreeSurfer
- ASCII (.tri)
- Neuromag (.fif)
Noise statistics (sensor covariance arrays):
- Neuromag / MNE (.fif)
- ASCII arrays
Dipole models:
- Elekta Neuromag XFit (.bdip)