[FieldTrip] Scaling issues with EEG time frequency analysis

[Tzvetan Popov]

Dear Arti,
the units on the tutorial are in Tesla^2. In your case they might end up being in V^2 if you first convert them to volts instead of bits, i.e. the reason why you end up with those high values.
So, to your question, your are not doing anything wrong.
best 
tzvetan

> Thanks Peter. Perhaps I wasn't clear in the previous email. The time frequency values that I got are too high. I had to changes the Z axis limits to -500 to 500 instead of the [-3e-27 3e-27] values on the tutorial. Is there anything I am doing wrong?
> Thanks
> Arti
> 
> On Mon, Oct 13, 2014 at 8:41 PM, Peter Goodin <pgoodin at swin.edu.au> wrote:
> Hi Arti, 
> 
> Try lowering the cfg.zlim values (%% Plot TFR). 
> 
> Peter
> 
> __________________________
> Peter Goodin, 
> BSc (Hons), Ph.D Candidate.
> 
> Brain and Psychological Sciences Research Centre (BPsych)
> Swinburne University, 
> Hawthorn, Vic, 3122
> http://www.swinburne.edu.au/swinburneresearchers/index.php?fuseaction=profile&pid=4149
> 
> Monash Alfred Psychiatry Research Centre (MAPrc)
> Level 4, 607 St Kilda Road, 
> Melbourne 3004
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Arti Abhishek [mailtome.2113 at gmail.com]
> Sent: Monday, 13 October 2014 5:49 PM
> To: fieldtrip at science.ru.nl
> Subject: [FieldTrip] Scaling issues with EEG time frequency analysis
> 
> Dear fieldtrip users,
> 
> I am a new fieldtrip user and I am having some problems with frequency analysis. My EEG data is recorded from Neuroscan NuAmps system (22 bit). I have used the following script (I wrote the script from the examples on the fieldtrip website), but I get the time frequency plots with huge values. Could anyone please suggest me what I am doing wrong?
> 
> Thanks
> Arti
> cfg =[];
> 
> cfg.dataset = 's01.cnt';
> 
> cfg.channel = {'all'};
> 
> cfg.layout = 'NuAmps.lay';
> 
> lay = ft_prepare_layout(cfg);
> 
> % Event identification
> 
> cfg.trialdef.eventtype = 'trigger';
> 
> cfg.trialdef.eventvalue = 101;
> 
> cfg.trialdef.prestim = 1;
> 
> cfg.trialdef.poststim = 2;
> 
> cfg.reref = 'yes';
> 
> cfg.implicitref = 'A1';
> 
> cfg.refchannel = {'A1' 'A2'};
> 
> cfg = ft_definetrial(cfg);
> 
> % % Filtering
> 
> % cfg.hpfilter = 'yes';
> 
> % cfg.hpfreq = 0.1;
> 
> % cfg.hpfilttype = 'fir';
> 
> dataFIC = ft_preprocessing(cfg);
> 
> %% Summary detection of bad trials
> 
> cfg = [];
> 
> cfg.method = 'summary';
> 
> cfg.layout = lay; % this allows for plotting
> 
> cfg.channels = [1:34];   
> 
> data_clean = ft_rejectvisual(cfg, dataFIC);
> 
> % Calculate TFR for condition1
> 
> cfg = [];
> 
> cfg.trials = find(data_clean.trialinfo==101);
> 
> cfg.channel = 'EEG';
> 
> cfg.method = 'wavelet';               
> 
> cfg.width = 7; 
> cfg.output = 'pow'; 
> 
> cfg.foi = 2:2:48;                 
> 
> cfg.toi = -0.5:0.05:1;                  
> 
> s01_TFRwave4ch = ft_freqanalysis(cfg, data_clean);
> 
> %% Plot TFR
> 
> cfg = [];
> 
> cfg.baseline = [-0.5 -0.1];
> 
> cfg.baselinetype = 'absolute';         
> 
> cfg.zlim = [-500 500];
> cfg.showlabels = 'yes';        
> 
> cfg.layout = lay;
> 
> figure
> 
> ft_multiplotTFR(cfg, s01_TFRwave4ch)
> 
> 
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