Depending on what you're doing, several of us have little auxiliary
packages that might help. For e.g. extracting single-trial mean voltage
within a given time window, I have a utility function in my philistine
package:
https://philistine.readthedocs.io/en/latest/api/philistine.mne.retrieve.html#philistine.mne.retrieve
Phillip
???External Email - Use Caution???
Hi Bianca,
To expand on Denis's answer a little:
Many MNE-Python objects (Raw, Epochs, Evoked, SourceEstimate) have a
to_data_frame() method that will create a Pandas DataFrame in memory,
which you can then save to many formats including CSV.? From what you've
told us, that might be an easier way than using FIF as an intermediate
format. Looping over subjects in Python, you could write a separate CSV
for each subject and the combine them in R, or you can combine the
pandas DataFrames within Python before writing one big CSV. Or (as Denis
says) you can write the loop within R and use MNE-R to do whatever
preprocessing steps you need, and then in theory you don't even need to
write intermediate files (though you might want to anyway).
-- dan
Daniel McCloy
http://dan.mccloy.info/
Research Engineer
Institute for Learning and Brain Sciences
University of Washington
? ? ? ? External Email - Use Caution? ? ? ?
Hi Bianca,
Hi Bianca,
Did you have a look at? MNE-R? https://mne.tools/mne-r/index.html
It is a small library that facilitates calling MNE-Python through R
and making data frames from fif-compatible data structures.
For what concerns your question, the fif file is not meant to handle
data from multiple subjects.
You would use other formats for that.
In Python we usually? do things in memory, making big matrices from
multiple subjects.
For getting data for all subjects, you would need to write separate
files and combine them in R or make a big data frame.
I? hope that helps.
Denis
>
>? ? ? ? ?External Email - Use Caution? ? ? ?
>
>
> MNE Analysis Team,
>?
> Let me first begin by stating what our lab is primarily interested
in, and currently doing. We do psychophys studies directly related
to startle-blink response and postauricular response.? We also work
with skin conductance, corrugator, zygomatic (EMG), EOG, ECG, and
EEG.? Currently, we run Neuroscan, and use the resulting CNT files
to do statistical analysis on all study subjects with SPSS and R.?
We have been in works this summer to complete a script through
Jupyter notebooks that will process our raw CNT files into processed
FIF files, and this is where the questions begin.
>?
> How large can a FIF file be?? If a FIF file has a limitation on
its size, how do we run statistical analysis on multiple files for
the same participant?? Furthermore, how do we run analysis on
multiple subjects and multiple files? Will a FIF file be compatible
with statistical analysis?? The real issue that our lab sees is how
will be able to create component scores that can be output to other
programs for statistical analysis, primarily R.? There's a hint
about how to do this at the start of the scripts on this page after
the from import statements:
>
https://martinos.org/mne/stable/auto_examples/connectivity/plot_mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-connectivity-plot-mne-inverse-envelope-correlation-py
>?
> However, maybe we require further explanation as we are not
interested necessarily in one subject at a time rather ALL subjects
at a time.
>?
> Thank you in advance for any insight that you may be able to
provide on these matters and of course your time.
>?
> Best,
> UNLV PEPLab
> Bianca Islas
> Research Assistant
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