[FieldTrip] Circular Correlation coefficient
David Syloni
david.syloni at gmail.com
Wed Feb 3 17:25:21 CET 2016
Dear Julian,
To calculate Hilbert transform I created 0.5 sec "trials" from the data.
and used
hibert_t1 = ft_preproc_hilbert( cell2mat(data_no_artifacts.trial(1)),
'angle')
Is it right?
Thanks,
David
On Tue, Feb 2, 2016 at 6:04 PM, David Syloni <david.syloni at gmail.com> wrote:
> Dear Julian,
>
> Thank you for the answer. I will try to apply it as you described.
> However, it's important to note, that my data doesn't contain real trials,
> this is a EEG during one continuous stimulus (110 sec).
> Can your approach work also for this case?
>
>
> Thanks,
>
>
> David
>
> On Tue, Feb 2, 2016 at 1:51 PM, Julian Keil <julian.keil at gmail.com> wrote:
>
>> Dear David,
>>
>> I won't discuss whether this is a sensible comment by the reviewer, but
>> here are some basic steps that you could take.
>>
>> To compute the circular correlation between two signals, you obviously
>> need to obtain the phase angles first.
>> One option to do this is to use a Hilbert transform on band-pass filtered
>> data (on a single-trial level)
>> As soon as you have your single trial phase angles, you can compute the
>> correlation between two signals within each subject.
>> Once you have done this, you could see whether there is a consistent
>> pattern over subjects.
>>
>> You can find similar approaches in the following papers:
>>
>> van Elswijk, G., Maij, F., Schoffelen, J.-M., Overeem, S., Stegeman, D.
>> F., & Fries, P. (2010). Corticospinal Beta-Band Synchronization Entails
>> Rhythmic Gain Modulation. Journal of Neuroscience, 30(12), 4481–4488.
>> http://doi.org/10.1523/JNEUROSCI.2794-09.2010
>>
>> Keil, J., Timm, J., SanMiguel, I., Schulz, H., Obleser, J., &
>> Schonwiesner, M. (2014). Cortical brain states and corticospinal
>> synchronization influence TMS-evoked motor potentials. Journal of
>> Neurophysiology, 111(3), 513–519. http://doi.org/10.1152/jn.00387.2013
>>
>> Good luck,
>>
>> Julian
>>
>> Am 02.02.2016 um 09:14 schrieb David Syloni:
>>
>> Dear Julian,
>>
>> Thank you for the answer. I was asked by reviewers to calculate circular
>> correlation instead of PLV. Sorry for too general description.
>> Actually, I found the toolbox , but I don't understand how to compute
>> " sample of angles in radians" (the input for the circ_corrcc function
>> ).
>> I would very appreciate a help to transform my fieldtrip data to the
>> input format , required by circ_corrcc.
>>
>> Thanks!
>>
>>
>> David
>>
>> On Tue, Feb 2, 2016 at 9:57 AM, Julian Keil <julian.keil at gmail.com>
>> wrote:
>>
>>> Hi David,
>>>
>>> to compute circular statistics (e.g. phase correlations) you need to
>>> leave fieldtrip a bit.
>>> Here's the toolbox I usually use:
>>> http://www.mathworks.com/matlabcentral/fileexchange/10676-circular-statistics-toolbox--directional-statistics-
>>>
>>> As you don't describe why you need circular statistics, it's a bit hard
>>> to give a more helpful answer.
>>>
>>> Good luck,
>>>
>>> Julian
>>>
>>> Am 01.02.2016 um 13:40 schrieb David Syloni:
>>>
>>> > Dear Fieldtripers,
>>> >
>>> > I'm trying to apply connectivity analysis with continuous EEG data.
>>> >
>>> > I'm using:
>>> >
>>> >
>>> >
>>> > cfg = [];
>>> > cfg.method = 'mtmfft';
>>> > cfg.taper = 'dpss';
>>> > cfg.output = 'fourier';
>>> > cfg.tapsmofrq = 4;
>>> > cfg.width=2;
>>> > cfg.foilim = [0 250];
>>> > cfg.keeptrials = 'yes';
>>> > freq = ft_freqanalysis(cfg, data_no_artifacts);
>>> >
>>> >
>>> >
>>> >
>>> > cfg = [];
>>> > cfg.method = 'plv';
>>> > 'mtmfft'
>>> > cfg.foilim = [8 12];
>>> > cfg.bandwidth=5;
>>> > cfg.tapsmofrq = 4;
>>> > cfg.keeptrials = 'yes';
>>> > cfg.output = 'powandcsd';
>>> > cfg.channelcmb = c;
>>> > coh = ft_connectivityanalysis(cfg, freq);
>>> >
>>> > Right now I should calculate Circular Correlation and I'm stuck with
>>> it.
>>> >
>>> > I would very appreciate your help!
>>> >
>>> > Thanks in advance,
>>> >
>>> > David
>>> > _______________________________________________
>>> > fieldtrip mailing list
>>> > fieldtrip at donders.ru.nl
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>>>
>>>
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>>
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