[FieldTrip] preprocessing procedures for ECoG/iEEG data

Teresa Madsen braingirl at gmail.com
Wed Feb 15 17:27:42 CET 2017

I would say it depends on your data:  is your DC offset fairly consistent
(in which case demeaning once would probably be fine), or do your signals
have slow drift over time (in which case detrending trials might be
better)?  You might also want to consider removing large artifacts first,
as extreme values can skew your mean or trends.  Have a look at your raw
data using ft_databrowser to decide.


On Wed, Feb 8, 2017 at 2:47 PM, Tim Meehan <timeehan at gmail.com> wrote:

> Hi Vitoria,
> 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
> individual trials?
> Thanks,
> Tim
> On Thu, Feb 2, 2017 at 4:45 AM, Vitória Piai <v.piai.research at gmail.com>
> wrote:
>> 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, 882–913.
>> 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,
>> Vitoria
>> 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.
>> Thanks!
>> Tim
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Teresa E. Madsen, PhD
Research Technical Specialist:  *in vivo *electrophysiology & data analysis
Division of Behavioral Neuroscience and Psychiatric Disorders
Yerkes National Primate Research Center
Emory University
Rainnie Lab, NSB 5233
954 Gatewood Rd. NE
Atlanta, GA 30329
(770) 296-9119
braingirl at gmail.com
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