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* | * ''"Very well organized and useful" '' * ''"Very clear and useful lectures" '' * ''"Thanks a lot! Very nice workshop!" '' * ''"Very clear: written tutorial is perfect" '' * ''"This software is user-friendly and very nicely designed: congrats!" '' * ''"The online tutorials were really my first introduction to EEG and I found it essential for understanding the course. The workshop is not necessarily for beginners but I am very glad I came as I learnt a lot!"'' |
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Number of participants: 30<<BR>>Number of returned documents: 22 (73%)<<BR>>[[http://neuroimage.usc.edu/brainstorm/WorkshopLosAngeles2015Survey?action=AttachFile&do=get&target=workshop_survey.pdf|Link to the pdf document|&do=get]]. | Number of participants: 30<<BR>>Number of returned documents: 22 (73%)<<BR>>[[http://neuroimage.usc.edu/brainstorm/WorkshopLosAngeles2015Survey?action=AttachFile&do=get&target=workshop_survey.pdf|Link to the pdf document]]. |
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* Never used: % * Some simulation work: % * Some experimental work: % |
* Never used: 55% * Some simulation work: 22% * Some experimental work: 22% |
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* 3: % * 4: % * '''5: %''' |
* 3: 5% * '''4: 45% ''' * '''5: 55%''' |
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* Yes: % * No: % |
* Yes: 36% * No: 64% |
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* EEG: * MEG: * MEG+EEG: * NIRS: * sEEG/ECoG: * Scripting: * Pre-processing: * Visualization of recordings: * Source analysis: * Time-frequency: * Functional connectivity: * Statistics: * Research: * Clinical applications: * Epilepsy: * Baby / child studies: |
* EEG: 86% * MEG: 18% * MEG+EEG: 9% * NIRS: 5% * sEEG/ECoG: 18% * Scripting: 32% * Pre-processing: 36% * Visualization of recordings: 59% * Source analysis: 73% * Time-frequency: 77% * Functional connectivity: 64% * Statistics: 45% * Research: 36% * Clinical applications: 27% * Epilepsy: 18% * Baby / infant studies: 18% |
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* '''Good clarity: ''' * '''Good pace: ''' * A bit slow: * Uneven pace: * Need more short breaks: * Too much time on personal questions: * Some advertised topics were not covered: * Need more time / two days: |
* '''Good clarity: 12''' * '''Good pace: 11''' * Practice too fast: 2 * Practice too slow: 1 * Lectures too slow: 1 * More time on practice on personal data: 3 * Too much information: 2 * Need more time / three days: 1 * Lecture on source modeling earlier in the day: 1 |
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* Connectivity: * EEG examples (digitizer, ECoG positions): * EEG/SEEG examples (recordings): * Interface with command line Matlab: * More on frequency analysis: |
* '''Statistics: 8''' * Resting state: 1 * Steady state evoked potentials: 1 * Bad channel interpolation: 1 * More connectivity: 2 * More phase-amplitude coupling: 1 * Diagram representation of the processing pipeline: 1 * More scripting: 1 * EEG examples (digitizer, ECoG positions): * EEG/SEEG examples (recordings): * Interface with command line Matlab: * More on frequency analysis: |
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* Integration with fMRI: * Realtime processing and display: |
* Advanced ERP analysis: 1 * Tutorial on dipole fitting: 1 * Easier way to batch: 1 * ERP segmentation: 1 * More statistics: 1 * Support for Nicolet ".e" EEG format: 1 * Integration with fMRI: * Realtime processing and display: == Notes for future workshops == * The statistical analysis was completely skipped. It didn't have a clear time slot in the program because the EEG/epilepsy dataset was not adapted to illustrate it, then it got skipped because we were running out of time. We need to make sure we introduce the stat features and the thresholding interface even with this dataset. |
Brainstorm workshop survey: Geneva 2015
Selected comments from attendees
"Very well organized and useful"
"Very clear and useful lectures"
"Thanks a lot! Very nice workshop!"
"Very clear: written tutorial is perfect"
"This software is user-friendly and very nicely designed: congrats!"
"The online tutorials were really my first introduction to EEG and I found it essential for understanding the course. The workshop is not necessarily for beginners but I am very glad I came as I learnt a lot!"
Survey results
Number of participants: 30
Number of returned documents: 22 (73%)
Link to the pdf document.
Summary
- Before today's class, how would you describe your use of Brainstorm:
- Never used: 55%
- Some simulation work: 22%
- Some experimental work: 22%
- Experienced user: 0%
- How helpful was the class in learning Brainstorm: 1(worst) to 5(best)
- 1: 0%
- 2: 0%
- 3: 5%
4: 45%
5: 55%
- Did you try the online tutorial before coming to class:
- Yes: 36%
- No: 64%
- Interested in using Brainstorm for:
- EEG: 86%
- MEG: 18%
- MEG+EEG: 9%
- NIRS: 5%
- sEEG/ECoG: 18%
- Scripting: 32%
- Pre-processing: 36%
- Visualization of recordings: 59%
- Source analysis: 73%
- Time-frequency: 77%
- Functional connectivity: 64%
- Statistics: 45%
- Research: 36%
- Clinical applications: 27%
- Epilepsy: 18%
- Baby / infant studies: 18%
Comments and suggestions
The number indicates the number of participants who made similar comments.
Comments about the workshop
Good clarity: 12
Good pace: 11
- Practice too fast: 2
- Practice too slow: 1
- Lectures too slow: 1
- More time on practice on personal data: 3
- Too much information: 2
- Need more time / three days: 1
- Lecture on source modeling earlier in the day: 1
Missing topics and requests
Statistics: 8
- Resting state: 1
- Steady state evoked potentials: 1
- Bad channel interpolation: 1
- More connectivity: 2
- More phase-amplitude coupling: 1
- Diagram representation of the processing pipeline: 1
- More scripting: 1
- EEG examples (digitizer, ECoG positions):
- EEG/SEEG examples (recordings):
- Interface with command line Matlab:
- More on frequency analysis:
Missing tools in Brainstorm
- Advanced ERP analysis: 1
- Tutorial on dipole fitting: 1
- Easier way to batch: 1
- ERP segmentation: 1
- More statistics: 1
- Support for Nicolet ".e" EEG format: 1
- Integration with fMRI:
- Realtime processing and display:
Notes for future workshops
- The statistical analysis was completely skipped. It didn't have a clear time slot in the program because the EEG/epilepsy dataset was not adapted to illustrate it, then it got skipped because we were running out of time. We need to make sure we introduce the stat features and the thresholding interface even with this dataset.