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| * '''Latest software updates''' :<<BR>>[[News|http://neuroimage.usc.edu/brainstorm/News]] * '''Join the Brainstorm community now''' :<<BR>> [[http://www.facebook.com/BrainstormSoftware|facebook.com/BrainstormSoftware]] * '''New training opportunities ''': Halifax, Seattle, Florence<<BR>>[[Training|Register to those workshops]] * '''Important update on the Brainstorm-generated scripts''':<<BR>>[[Note2013Jan22|You may have to modify your scripts, read more...]] |
<<HTML(<div id="fb-root"></div> <script>(function(d, s, id) {var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "//connect.facebook.net/en_US/all.js#xfbml=1"; fjs.parentNode.insertBefore(js, fjs);}(document, 'script', 'facebook-jssdk'));</script>)>> * '''Latest software updates''':<<BR>>[[News|http://neuroimage.usc.edu/brainstorm/News]] * '''New training opportunities''': [[Training|Register now!]]<<BR>> Osaka (May 31) * '''Stay in touch with the Brainstorm community with'''''' [[http://www.facebook.com/BrainstormSoftware|Facebook]]'''<<BR>><<HTML(<div class="fb-like" data-href="http://www.facebook.com/BrainstormSoftware" data-send="true" data-width="450" data-show-faces="true"></div>)>> * <<HTML(<FORM METHOD="get" ACTION="http://neuroimage.usc.edu/bst/search_users.php" name="form" onSubmit="return validateForm(this);"><B>Find users by location</B>: <INPUT type='text' name='u' size=30><input type="submit" style="visibility: hidden;" /></FORM>)>> |
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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). '' '' | Brainstorm is a collaborative, open-source application dedicated to MEG/EEG/sEEG/ECoG data analysis (visualization, processing and advanced source modeling). |
| Line 16: | Line 18: |
| 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. '' '' | 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. |
| Line 18: | Line 20: |
| Since the project started by the end of the 1990's, our server has registered more than 8,000 accounts and about 500 users are actively updating the software. See our''' '''[[Pub|reference page]]''' '''for a list of published studies featuring Brainstorm at work! '' '' | Since the project started by the end of the 1990's, our server has registered more than 8,000 accounts and about 500 users are actively updating the software. See our [[Pub|reference page]] for a list of published studies featuring Brainstorm at work! |
| Line 20: | Line 22: |
| 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 [[Tutorials|online tutorials]] and support through our forum but there is nothing better than a course to make your learning curve steeper. Consult our''' '''[[Training|training pages]]''' '''for upcoming opportunities to learn better and faster! '' '' | 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 [[Tutorials|online tutorials]] and support through our forum but there is nothing better than a course to make your learning curve steeper. Consult our [[Training|training pages]] for upcoming opportunities to learn better and faster! |
| Line 22: | Line 24: |
| Finally, have a look regularly at our''' '''[[News|What's new]]''' '''page for staying on top of Brainstorm news and updates and <<HTML(<A href="www.facebook.com/brainstormsoftware">)>> ''' {{attachment:facebook_like.png|http://www.facebook.com/brainstormsoftware}} '''Like us on Facebook<<HTML(</A>)>> to stay in touch.''' '''We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community! '' '' | Finally, have a look regularly at our [[News|What's new]] page for staying on top of Brainstorm news and updates and <<HTML(<A href="www.facebook.com/brainstormsoftware">)>> ''' {{attachment:facebook_like.png|http://www.facebook.com/brainstormsoftware}} '''Like us on Facebook<<HTML(</A>)>> to stay in touch. We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community! |
| Line 27: | Line 29: |
| This software was generated primarily with support from the National Institutes of Health under grants R01-EB002010, R01-EB009048, and R01-EB000473. '' '' | This software was generated primarily with support from the National Institutes of Health under grants R01-EB002010, R01-EB009048, and R01-EB000473. |
| Line 29: | Line 31: |
| Primary support was provided by the Centre National de la Recherche Scientifique (CNRS, France) for the Cognitive Neuroscience & Brain Imaging Laboratory (La Salpetriere Hospital and Pierre & Marie Curie University, Paris, France), and by the Montreal Neurological Institute to the MEG Program at''' !McGill '''University'''. ''''' '' | Primary support was provided by the Centre National de la Recherche Scientifique (CNRS, France) for the Cognitive Neuroscience & Brain Imaging Laboratory (La Salpetriere Hospital and Pierre & Marie Curie University, Paris, France), and by the Montreal Neurological Institute to the MEG Program at''' !McGill '''University. |
| Line 31: | Line 33: |
| Additional support was also from two grants from the French National Research Agency (ANR) to the Cognitive Neuroscience Unit (PI: Ghislaine Dehaene; Inserm/CEA, Neurospin, France) and to the ViMAGINE project (PI: Sylvain Baillet; ANR-08-BLAN-0250), and by the Epilepsy Center in the Cleveland Clinic Neurological Institute. '' '' | Additional support was also from two grants from the French National Research Agency (ANR) to the Cognitive Neuroscience Unit (PI: Ghislaine Dehaene; Inserm/CEA, Neurospin, France) and to the ViMAGINE project (PI: Sylvain Baillet; ANR-08-BLAN-0250), and by the Epilepsy Center in the Cleveland Clinic Neurological Institute. |
| Line 34: | Line 36: |
| 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. '' '' | 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. |
| Line 36: | Line 38: |
| 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]] ] ''''' ''''' | 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]] ] |
| Line 39: | Line 41: |
| * '''MEG/EEG recordings:''' ''''' ''''' * Digitize the position of the EEG electrodes and the subject's head shape using a Polhemus device ''''' ''''' * Read data from the most popular file formats ([[#line-78|listed here]]) ''''' ''''' |
* '''MEG/EEG recordings:''' * Digitize the position of the EEG electrodes and the subject's head shape using a Polhemus device * Read data from the most popular file formats ([[#line-78|listed here]]) |
| Line 43: | Line 45: |
| * 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) ''''' ''''' |
* 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 50: | Line 52: |
| * '''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 ''''' ''''' |
* '''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 |
| Line 59: | Line 61: |
| * '''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.) ''''' ''''' |
* '''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 65: | Line 67: |
| * '''MRI visualization and coregistration: ''' ''''' ''''' | * '''MRI visualization and coregistration: ''' |
| Line 67: | Line 69: |
| * 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]]) ''''' ''''' |
* 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]]) |
| Line 71: | Line 73: |
| * Automatic or interactive co-registration with the MEG/EEG coordinate system ''''' ''''' * Volume rendering (multiple display modes) ''''' ''''' |
* Automatic or interactive co-registration with the MEG/EEG coordinate system * Volume rendering (multiple display modes) |
| Line 74: | Line 76: |
| * '''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) ''''' ''''' |
* '''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 80: | Line 82: |
| * '''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 ''''' ''''' |
* '''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 |
| Line 85: | Line 87: |
| * '''Source modeling: ''' ''''' ''''' * L2 Minimum-norm current estimates ''''' ''''' * dSPM ''''' ''''' * sLORETA ''''' ''''' * All models can be cortically-constrained or not, and with/without constrained orientations ''''' ''''' |
* '''Source modeling: ''' * L2 Minimum-norm current estimates * dSPM * sLORETA * All models can be cortically-constrained or not, and with/without constrained orientations |
| Line 91: | Line 93: |
| * '''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 ''''' ''''' |
* '''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 |
| Line 100: | Line 102: |
| * '''Time-frequency decompositions: ''' ''''' ''''' * Time-frequency analyses of sensor data and sources time series using Morlet wavelet, Fast Fourier Transfor, and Hilbert transform ''''' ''''' * Define time and frequency scales of interest ''''' ''''' * Multiple display modes available ''''' ''''' |
* '''Time-frequency decompositions: ''' * Time-frequency analyses of sensor data and sources time series using Morlet wavelet, Fast Fourier Transfor, and Hilbert transform * Define time and frequency scales of interest * Multiple display modes available |
| Line 109: | Line 111: |
| * '''Group analysis: ''' ''''' ''''' * Registration of individual brains to a brain template (MNI/Colin27) ''''' ''''' * Statistical analysis (t-tests) ''''' ''''' |
* '''Group analysis: ''' * Registration of individual brains to a brain template (MNI/Colin27) * Statistical analysis (t-tests) |
| Line 113: | Line 115: |
| * '''Documentation and support: ''' ''''' ''''' * Easy and automatic updates of the software ''''' ''''' * Detailed step-by-step [[Tutorials|tutorials]] for most common features ''''' ''''' * Active user forum ''''' ''''' |
* '''Documentation and support: ''' * Easy and automatic updates of the software * Detailed step-by-step [[Tutorials|tutorials]] for most common features * Active user forum |
| Line 121: | Line 122: |
| * ANT EEProbe continuous (.cnt) ''''' ''''' * BDF / BDF+ (Biosemi 24bit binary) ''''' ''''' * BESA exports (.avr, .mul) ''''' ''''' * !BrainVision !BrainAmp (.eeg) ''''' ''''' * !BrainVision Analyzer (.txt) ''''' ''''' * Cartool binary files (.ep, .eph) ''''' ''''' * EDF / EDF+ (European Data Format) ''''' ''''' * EEGLab sets (.set) ''''' ''''' * EGI !NetStation epoch-marked file (.raw/.epoc) ''''' ''''' * MANSCAN Microamp (.mbi/.mb2) ''''' ''''' * Neuroscan (.cnt, .eeg, .avg, .dat) ''''' ''''' * Any type of ASCII (text) files ''''' ''''' |
* ANT EEProbe continuous (.cnt) * BDF / BDF+ (Biosemi 24bit binary) * BESA exports (.avr, .mul) * !BrainVision !BrainAmp (.eeg) * !BrainVision Analyzer (.txt) * Cartool binary files (.ep, .eph) * EDF / EDF+ (European Data Format) * EEGLab sets (.set) * EGI !NetStation epoch-marked file (.raw/.epoc) * MANSCAN Microamp (.mbi/.mb2) * Neuroscan (.cnt, .eeg, .avg, .dat) * Any type of ASCII (text) files |
| Line 135: | Line 136: |
| * CTF (.ds folders) ''''' ''''' * Neuromag FIFF (.fif) ''''' ''''' * BTi / 4D Neuroimaging ''''' ''''' * LENA format ''''' ''''' |
* CTF (.ds folders) * Elekta Neuromag FIFF (.fif) * BTi / 4D Neuroimaging * Yokogawa / KIT * LENA format |
| Line 141: | Line 143: |
| * 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, .asc) ''''' ''''' * ASCII arrays ''''' ''''' |
* ANT Xensor (.elc) * BESA (.sfp, .elp, .eps/.ela) * Cartool (.xyz, .els) * Curry (.res, .rs3) * EEGLab (.ced, .xyz, .set) * EETrak (.elc) * EGI (.sfp) * EMSE (.elp) * Neuroscan (.dat, .tri, .asc) * Polhemus (.pos .pol .elp .txt) * ASCII arrays |
| Line 153: | Line 156: |
| * Nifti-1 (.nii, .nii.gz) ''''' ''''' * Analyze (.img/.hdr) ''''' ''''' * BrainVISA GIS (.ima/.dim) ''''' ''''' * CTF (.mri) ''''' ''''' * MGH (.mgh, .mgz) ''''' ''''' * Neuromag (.fif) ''''' ''''' |
* Analyze (.img/.hdr) * BrainVISA GIS (.ima/.dim) * CTF (.mri) * MINC (.mnc) * MGH (.mgh, .mgz) * Neuromag (.fif) * Nifti-1 (.nii, .nii.gz) |
| Line 161: | Line 165: |
| * BrainVISA (.mesh) ''''' ''''' * !BrainSuite (.dsgl, .dfs) ''''' ''''' |
* BrainVISA (.mesh) * !BrainSuite (.dsgl, .dfs) |
| Line 164: | Line 168: |
| * !FreeSurfer (lh.*, rh.*)''''' ''''' * FSL: VTK (.vtk) ''''' ''''' * FSL: Geomview (.off) ''''' ''''' * ASCII (.tri) ''''' ''''' * Neuromag (.fif) ''''' ''''' |
* !FreeSurfer (lh.*, rh.*) * FSL: VTK (.vtk) * FSL: Geomview (.off) * MNI obj (.obj) * ASCII (.tri) * Neuromag (.fif) |
| Line 172: | Line 177: |
| * !BrainSuite (.dfs) | |
| Line 175: | Line 181: |
| === Noise statistics (sensor covariance arrays): === * Neuromag / MNE (.fif) ''''' ''''' * ASCII arrays ''''' ''''' |
|
| Line 180: | Line 182: |
| * Elekta Neuromag XFit (.bdip) ''''' ''''' | * Elekta Neuromag XFit (.bdip) |
News
Latest software updates:
http://neuroimage.usc.edu/brainstorm/NewsNew training opportunities: Register now!
Osaka (May 31)Stay in touch with the Brainstorm community with Facebook
Introduction
Brainstorm is a collaborative, open-source application dedicated to MEG/EEG/sEEG/ECoG 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 8,000 accounts 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 tutorials 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 page for staying on top of Brainstorm news and updates and 
Like us on Facebook to stay in touch. We hope you enjoy using Brainstorm as much as we enjoy developing and sharing these tools with the community!
Support
This software was generated primarily with support from the National Institutes of Health under grants R01-EB002010, R01-EB009048, and R01-EB000473.
Primary support was provided by the Centre National de la Recherche Scientifique (CNRS, France) for the Cognitive Neuroscience & Brain Imaging Laboratory (La Salpetriere Hospital and Pierre & Marie Curie University, Paris, France), and by the Montreal Neurological Institute to the MEG Program at McGill University.
Additional support was also from two grants from the French National Research Agency (ANR) to the Cognitive Neuroscience Unit (PI: Ghislaine Dehaene; Inserm/CEA, Neurospin, France) and to the ViMAGINE project (PI: Sylvain Baillet; ANR-08-BLAN-0250), and by the Epilepsy Center in the Cleveland Clinic Neurological Institute.
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:
- Digitize the position of the EEG electrodes and the subject's head shape using a Polhemus device
Read data from the most popular file formats (listed here)
- 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:
- Generate surfaces from MRI volume: head, inner skull and outer skull
- 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 (multiple 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 wavelet, Fast Fourier Transfor, and Hilbert transform
- Define time and frequency scales of interest
- Multiple display modes available
Functional connectivity:
- Correlation, coherence, Granger causality, phase-locking value
- Both at sensor and source levels
- Dynamic circle plots for representing dense and high-dimensional connectivity graphs
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
Supported file formats
EEG:
- ANT EEProbe continuous (.cnt)
- BDF / BDF+ (Biosemi 24bit binary)
- BESA exports (.avr, .mul)
BrainVision BrainAmp (.eeg)
BrainVision Analyzer (.txt)
- Cartool binary files (.ep, .eph)
- EDF / EDF+ (European Data Format)
- EEGLab sets (.set)
EGI NetStation epoch-marked file (.raw/.epoc)
- MANSCAN Microamp (.mbi/.mb2)
- Neuroscan (.cnt, .eeg, .avg, .dat)
- Any type of ASCII (text) files
MEG:
- CTF (.ds folders)
- Elekta Neuromag FIFF (.fif)
- BTi / 4D Neuroimaging
- Yokogawa / KIT
- LENA format
Sensors locations:
- ANT Xensor (.elc)
- BESA (.sfp, .elp, .eps/.ela)
- Cartool (.xyz, .els)
- Curry (.res, .rs3)
- EEGLab (.ced, .xyz, .set)
- EETrak (.elc)
- EGI (.sfp)
- EMSE (.elp)
- Neuroscan (.dat, .tri, .asc)
- Polhemus (.pos .pol .elp .txt)
- ASCII arrays
MRI volumes:
- Analyze (.img/.hdr)
- BrainVISA GIS (.ima/.dim)
- CTF (.mri)
- MINC (.mnc)
- MGH (.mgh, .mgz)
- Neuromag (.fif)
- Nifti-1 (.nii, .nii.gz)
Surface meshes:
- BrainVISA (.mesh)
BrainSuite (.dsgl, .dfs)
- Curry BEM surfaces (.db*, .s0*)
FreeSurfer (lh.*, rh.*)
- FSL: VTK (.vtk)
- FSL: Geomview (.off)
- MNI obj (.obj)
- ASCII (.tri)
- Neuromag (.fif)
- 3D masks or atlases from MRI files (tesselation is created automatically)
Surface atlases:
BrainSuite (.dfs)
FreeSurfer (.annot, .label)
- Gifti texture (.gii)
Dipole models:
- Elekta Neuromag XFit (.bdip)