Presentation at https://livemeeg2020.org
Using the right tools and methods is crucial to get the most out of your MEG and EEG data, and obtaining good results requires that you understand how to optimally use these analysis methods. However, disseminating or sharing your results involves more than just using these analysis methods and reporting on their outcomes in a paper. There is much more knowledge that you are acquiring during your study, for example what the best analysis strategy is, or the most optimal settings of that specific algorithm. I will present recent advancements in the FieldTrip toolbox that support you in managing and sharing your data using BIDS, and in sharing the details of your analysis pipeline. Both your primary findings (i.e. your publication), your data, and your insights on how to best analyze the data are crucial to bring the field forward and to create the biggest impact of your research!
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How FieldTrip can help you with good scientific practices
1. How FieldTrip can help you with
good scientific practices
Robert Oostenveld
Donders Institute, Radboud University, Nijmegen, NL
Karolinska Institutet, Stockholm, SE
Slides available at
bit.ly/2SysId7
oostenvr r.oostenveld@donders.ru.nl
2. Improving your scientific practices
Asking the right questions
Using the right machinery
Tools and methods
Using the machinery right
Training and education
Good
3. Improving your scientific practices
Asking the right questions
Using the right machinery
Tools and methods
Using the machinery right
Training and education
Preregistration
Code availability
Data availability
4. Improving your scientific practices
Asking the right questions
Using the right machinery
Tools and methods
Using the machinery right
Training and education
Preregistration
Code availability
Data availability
5. Sharing your code
Published results from neuroimaging data are often not
reproducible (e.g. Gilmore et al., 2017)
It is still not common that (e.g. FieldTrip, EEGLAB, SPM, BrainStorm, MNE-Python)
analysis pipelines and intermediate data are shared
Why is code not shared?
new research, hence idiosyncratic analysis scripts
written by neuroscientists, not by programmers
written by students that learn on-the-job
source code in scripts is often exploratory
unorganized and computationally inefficient
poorly documented
As academics we set high standards, also for ourselves, so
“I will improve and document the code later, prior to sharing it…
6. Sharing your code
Every FieldTrip function could already do
cfg.inputfile
cfg.outputfile
Now they can also do
cfg.reproducescript
This results in straightforward, clean and “standard”
MATLAB scripts - just like the FieldTrip tutorials.
https://www.fieldtriptoolbox.org/walkthrough
https://www.fieldtriptoolbox.org/tutorials
https://www.youtube.com/fieldtriptoolbox
Mats van Es
Eelke Spaak
Jan-Mathijs
Schoffelen
9. Sharing your code
Excuses for not sharing code
source code in scripts is often exploratory and messy
unorganized and computationally inefficient
poorly documented
“I will improve and document the code later, prior to
sharing it…”
I can share my code now, and it is not
any worse than the FieldTrip tutorials
10. Sharing your data
FieldTrip is mostly used for importing data and then analyzing it.
Now also for exporting/converting data and decorating with metadata
data2bids(cfg)
If BIDS metadata is available, like channels.tsv or events.tsv,
it will be read and used.
Fewer experiment and data-specific details have to be implemented in the
analysis scripts, more details are stored alongside the data.
11. Sharing your data
www.fieldtriptoolbox.org/example/bids/
ftp.fieldtriptoolbox.org/pub/fieldtrip/example/
Converting an example EEG dataset for sharing in BIDS
Converting an example behavioral dataset for sharing in BIDS
Converting the combined MEG/fMRI MOUS dataset for sharing in BIDS
Converting an example NIRS dataset for sharing in BIDS
Converting an example EMG dataset for sharing in BIDS
Converting an example motion tracking dataset for sharing in BIDS
Converting an example eyetracker dataset for sharing in BIDS
Converting an example audio dataset for sharing in BIDS
Converting an example video dataset for sharing in BIDS
Convert the EEG sedation dataset for sharing in BIDS
Combining simultaneous recordings in BIDS
https://bids.neuroimaging.io
12. Sharing your data (here as an example for MRI)
Shared code as BIDS apps or
as MATLAB/Python/Julia scripts
Shared data in BIDS
with metadata
Original raw data
from the device
14. Improving your research
Preregistration
Code availability
Data availability
Open Access
Open Source
Team Science
Incentives
Inclusivity
Ethical research
Slides available at
bit.ly/2SysId7
oostenvr
r.oostenveld@
donders.ru.nl