[FieldTrip] preprocessing procedures for ECoG/iEEG data
timeehan at gmail.com
Wed Feb 8 20:47:06 CET 2017
Thanks for your input.
Maybe you (or anyone else) could clarify one thing for me. When demeaning
and/or detrending, is it better to do on a long continuous block or within
On Thu, Feb 2, 2017 at 4:45 AM, Vitória Piai <v.piai.research at gmail.com>
> Hi Tim,
> The answers to your questions will depend a lot on what you're planning on
> doing later.
> For 1), again it depends. If you're mainly interested in high gamma, it
> doesn't really matter that much since you'll do spectral decomposition
> later on. You could demean the data and not use any filters (or maybe a
> low-pass if you want to get some help with artifact rejection).
> For 2) here some more recent references that may help. The bottom line is,
> as David said, all methods have prons and cons. Choose wisely depending on
> what you want to be able to claim about your data!
> Mercier, M. R., Bickel, S., Megevand, P., Groppe, D. M., Schroeder, C. E.,
> Mehta, A. D., & Lado, F. A. (2017). Evaluation of cortical local field
> potential diffusion in stereotactic electro-encephalography recordings: a
> glimpse on white matter signal. NeuroImage, 147, 219–232.
> Arnulfo, G., Hirvonen, J., Nobili, L., Palva, S., & Palva, J. M. (2015).
> Phase and amplitude correlations in resting-state activity in human
> stereotactical EEG recordings. NeuroImage, 112, 114–127.
> Shirhatti, V., Borthakur, A., & Ray, S. (2016). Effect of reference scheme
> on power and phase of the local field potential. Neural Computation, 28,
> Trongnetrpunya, A., Nandi, B., Kang, D., Kocsis, B., Schroeder, C. E., &
> Ding, M. (2016). Assessing granger causality in electrophysiological data:
> removing the adverse effects of Common Signals via Bipolar Derivations.
> Frontiers in Systems Neuroscience, 9: 189.
> Since you're mentioning high gamma, I'm assuming you have stimuli being
> presented and you want to look at changes in high gamma as a function of
> those. In that case, I guess you have a good idea what your time windows
> will be like. So for 3) your suggestion would be a good way to go. What I
> usually do is to segment longer chunks of data than my narrow time windows
> of interest, mark the artifacts but do not reject any trials yet. I then
> save the artifacts and once I finally settle on what my time windows will
> be, I exclude trials with artifacts within that time window.
> - ft_databrowser will allow you to mark and save artifacts,
> ft_rejectartifact will allow you to remove trials containing the artifacts.
> Good luck,
> On 1/30/2017 11:10 PM, Tim Meehan wrote:
> Hello all,
> I am a new user of fieldtrip and new to analyzing electrophysiological
> data. I have familiarized myself with some basics of preprocessing of EEG
> data, but I would like to know if there are special considerations for
> dealing with ECoG/iEEG data -- our dataset has recordings from both
> subdural surface electrodes and depth electrodes, sampled at 2kHz. We are
> initially most interested in extracting the high-gamma band (70-150 Hz)
> envelope as a measure of local activity.
> First a general question: is there anyone who could point me to or provide
> me with a preprocessing procedure in fieldtrip that is tailored for
> ECoG/iEEG? I've perused the ECoG section in the wiki but there is no
> information on preprocessing there.
> If this is too vague, some specific questions I have are:
> 1) What cutoffs do people tend to use for low and high-pass filters?
> 2) What is your choice for re-referencing, if any? Our initial
> reference/ground are the left and right mastoids. I have seen papers that
> re-reference to the nearest neighbor. I think I need to use
> ft_apply_montage to do this, but beyond that I could use some guidance.
> 3) At what point do you epoch into trials? My guess is after high/low-pass
> filtering and re-referencing but before artifact detection and removal?
> Any feedback on these would be very much appreciated. If you need more
> details please let me know.
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