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| * <<HTML(<FONT color="#DDDDDD">)>> [[http:///VisualSingleOrig|MEG visual: single subject (Elekta/Orig)]]<<HTML(</FONT>)>> * <<HTML(<FONT color="#DDDDDD">)>> [[http:///VisualGroupOrig|MEG visual: group study (Elekta/Orig)]]<<HTML(</FONT>)>> |
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<<HTML(</TD></TR></TABLE>)>> == Basic Electrophysiology tutorial == <<HTML(<TABLE class="tuto-table"><TR><TD width=350>)>> '''Starting a new study''' * [[https://neuroimage.usc.edu/brainstorm/e-phys/Introduction|Importing RAW e-phys data]] '''Spike Sorting''' * [[https://neuroimage.usc.edu/brainstorm/e-phys/SpikeSorting|Unsupervised spike-sorting]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/SpikeSorting#Supervised_Spike_Sorting|Supervised spike-sorting]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/SpikeSorting#Spike_sorting_outside_of_Brainstorm|Spike sorting outside of Brainstorm]] '''Converting Raw data to LFP''' * [[https://neuroimage.usc.edu/brainstorm/e-phys/RawToLFP|Without Bayesian Spike Removal]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/RawToLFP#Conversion_to_LFP_with_Bayesian_Spike_Removal|With Bayesian Spike Removal]] <<HTML(</TD><TD>)>> ''' e-Phys functions''' * [[https://neuroimage.usc.edu/brainstorm/e-phys/functions|Tuning Curves]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/functions#Noise_Correlation|Noise Correlation]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/functions#Spike_Field_Coherence|Spike Field Coherence]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/functions#Raster_Plots|Raster Plots]] * [[https://neuroimage.usc.edu/brainstorm/e-phys/functions#Spike_triggered_Average|Spike Triggered Average]] ''' Converting to Brainstorm events''' * [[https://neuroimage.usc.edu/brainstorm/e-phys/ConvertToBrainstormEvents|Importing events from external spike-sorters]] |
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'''Deprecated documentation''' * [[Tutorials/VisualSingleOrig|MEG visual: single subject (Elekta/Orig)]] * [[Tutorials/VisualGroupOrig|MEG visual: group study (Elekta/Orig)]] |
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| These tutorial pages suppose you are comfortable with the basic concepts of MEG and EEG source imaging. If you're not, we engage you to read some background information, which will quickly help you getting up to speed with this field: * [[http://www.canada-meg-consortium.org/EN/MegIntro|Canada MEG consortium: Basics of MEG]]<<BR>>A non-technical overview of MEG and EEG, with an emphasis on source modeling. |
These tutorial pages suppose you are comfortable with the basic concepts of MEG and EEG source imaging. If you're not, we encourage you to read some background information, which will quickly help you getting up to speed with this field: * [[http://rdcu.be/pydB|Nature Neuroscience review paper on MEG for Human Electrophysiology and Imaging]] (Baillet S, 2017) * [[https://www.mcw.edu/Magnetoencephalography-Program-MEG/About-MEG.htm|Introduction to MEG (Medical College of Wisconsin)]] <<BR>>A non-technical overview of MEG and EEG, with an emphasis on source modeling. |
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| * Slides from a selection of educational courses: [[http://megcommunity.org/index.php?option=com_content&view=article&id=27&Itemid=13|megcommunity.org]] | * Slides from a selection of educational courses: [[http://megcommunity.org/education/teaching-slides|megcommunity.org]] |
Tutorials
These tutorial pages suppose you are comfortable with the basic concepts of MEG/EEG analysis and source imaging. If you're not, we encourage you to read some background literature.
To get a quick overview of the software interface, you can watch this introduction video.
If you are looking for the old tutorials, they are still available ?here.
Get started
The easiest way to get started with Brainstorm is to read and follow carefully these introduction tutorials. The number between brackets represents the number of printed pages for each tutorial. All in one page.
Some sections are still being edited or under review: Editing process.
| Starting a new study 1. Create a new protocol [9] 2. Import the subject anatomy [8] 3. Explore the anatomy [13] Reviewing 4. Channel file / MRI registration [11] 5. Continuous recordings [9] 6. Multiple windows [5] 7. Event markers [10] Pre-processing 8. Stimulation delays [9] 9. Select files / Run processes [11] 10. Power spectrum / Frequency filters [15] 11. Bad channels [6] 12. Artifact detection [8] 13. Artifact cleaning with SSP [16] 14. Additional bad segments [7] | Epoching and averaging 15. Import epochs [9] 16. Average response [7] 17. Visual exploration [10] 18. Colormaps [5] 19. Clusters of sensors [4] Source modeling 20. Head model [9] 21. Noise/data covariance [7] 22. Source estimation [28] [TODO] 23. Scouts [17] Advanced processing 24. Time-frequency [33] 25. Difference [13] 26. Statistics [30] 27. Workflows [10] 28. Scripting [31] |
Other analysis scenarios
Basic Electrophysiology tutorial
| Starting a new study Spike Sorting Converting Raw data to LFP | e-Phys functions Converting to Brainstorm events |
Advanced tutorials
| Anatomy and registration Recordings Software Deprecated documentation | Source modeling Advanced processing |
Background readings
These tutorial pages suppose you are comfortable with the basic concepts of MEG and EEG source imaging. If you're not, we encourage you to read some background information, which will quickly help you getting up to speed with this field:
Nature Neuroscience review paper on MEG for Human Electrophysiology and Imaging (Baillet S, 2017)
Introduction to MEG (Medical College of Wisconsin)
A non-technical overview of MEG and EEG, with an emphasis on source modeling.MEG: An Introduction to Methods
Editors: P Hansen, M Kringelbach, R Salmelin, Oxford University Press, 2010, 448 pages.The Oxford Handbook of Social Neuroscience
Editors: J Decety, JT Cacioppo, Oxford University Press, 2011, 1128 pages
A draft version of the MEG chapter by Sylvain Baillet can be found here.Good practice for conducting and reporting MEG research, Gross et al, Neuroimage, 2013.
Slides from a selection of educational courses: megcommunity.org
We can also come and organize a training session at your institution, or visit us at the MNI.
Now you are well equipped to go through the software tutorial, Enjoy!