[FieldTrip] [ext] Re: Load already preprocessed data to fieldtrip functions

[daniel.strahnen at uni-ulm.de]

Hi all,

sorry for bothering you again, but importing already preprocessed LFP data to fieldtrip is still giving me trouble.
I now try to create the following data structure:

data.label		 = 	{'CH1'; 'CH2'; 'CH3'; 'CH4'; 'CH5'; 'CH6'; 'CH7'};
data.time{1} 		 = 	1:1800; % time is 30 minutes, so 1800 seconds
data.trial{1}		= 	Output_data'; % Output_data' is a matrix: Channels x timepoints
                             			            % timepoints = 1800000 (1800 seconds  x 1000
                              			            % samples per second
data.fsample 		= 	1000; % Sampling rate of 1kHz

The error I get: Error using ft_datatype_raw (line 83)
inconsistent number of samples in trial 1
As I can see this is because I use 1800 for time, but the amount of samples are 1800000 (multiplied with the sampling rate), but when I change the time to 1800000 other errors occur within the analysis functions.
I only have one long trial with 7 channels  of 30 minutes that I want to analyse using ft_freqanalysis and the connectivity functions.

Thank you very much in advance and best regards

Daniel

-----Ursprüngliche Nachricht-----
Von: Mathis Kaiser <mathis.kaiser at charite.de> 
Gesendet: Dienstag, 4. Juni 2019 18:26
An: daniel.strahnen at uni-ulm.de
Betreff: Re: [ext] Re: [FieldTrip] Load already preprocessed data to fieldtrip functions

Hi Daniel,

also see
http://www.fieldtriptoolbox.org/faq/how_are_the_various_data_structures_defined/
and e.g. http://www.fieldtriptoolbox.org/reference/ft_datatype_timelock/
for info on required fields of your data structure.

Here's a Matlab code snippet that creates a minimal working timelock
structure:

%%%

prePost = [-1 1]; % time around stimulus onset sampleFreq = 500; timeVec = prePost(1):1/sampleFreq:prePost(2);

nChan = 32;
nSamples = length(timeVec);

data.avg = randn(nChan,nSamples); % just some random data data.dimord = 'chan_time'; data.label = compose('e%02i', 1:nChan); data.time = timeVec;

figure;
ft_singleplotER([],data)

%%%

Best,
Mathis


On 04.06.19 17:00, daniel.strahnen at uni-ulm.de wrote:
> Thanks for the advice! Would it be possible for you to send me just 
> the structure the you mentioned since I don’t have any data here that 
> is compatible to the Fieldtrip pipeline?
> 
>  
> 
> *Von:* fieldtrip <fieldtrip-bounces at science.ru.nl> *Im Auftrag von 
> *Stephen Politzer-Ahles
> *Gesendet:* Montag, 3. Juni 2019 17:40
> *An:* fieldtrip at science.ru.nl
> *Betreff:* Re: [FieldTrip] Load already preprocessed data to fieldtrip 
> functions
> 
>  
> 
> An easy way to hack it is to preprocess some other data using the 
> Fieldtrip pipeline, grab the structure that's created, and then 
> manually replace the appropriate fields (like .trial, .average, .time, 
> etc.) with the fields from your own data. You may also have to replace 
> some other fields, like .dimord, if they don't match yours; but this 
> is pretty straightforward to do once you get familiar with the 
> Fieldtrip data structure. This is what I've done in the past when I 
> have data I processed in some other software or toolbox but then I 
> want to use Fieldtrip's functions for cluster-based permutation tests or whatnot.
> There may be more proper or more efficient ways to do it, but this 
> hack has worked fine for me so far.
> 
>  
> 
> ---
> 
> Stephen Politzer-Ahles
> The Hong Kong Polytechnic University
> Department of Chinese and Bilingual Studies 
> http://www.mypolyuweb.hk/~sjpolit/
> 
>  
> 
>  
> 
>  
> 
>     Message: 1
>     Date: Sun, 2 Jun 2019 16:28:08 +0200
>     From: <daniel.strahnen at uni-ulm.de <mailto:daniel.strahnen at uni-ulm.de>>
>     To: <fieldtrip at science.ru.nl <mailto:fieldtrip at science.ru.nl>>
>     Subject: [FieldTrip] Load already preprocessed data to fieldtrip
>             functions
>     Message-ID: <000401d5194f$66ece690$34c6b3b0$@uni-ulm.de
>     <http://uni-ulm.de>>
>     Content-Type: text/plain; charset="utf-8"
> 
>     Is it possible to use the fieldtrip functions for already
>     preprocessed data
>     that is organized in a .mat file.
> 
>     The data is stored in a matrix organized as follows: Channels x 
> samples
> 
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