[Eeglablist] tftopo() after newtimef()

[Arnaud Delorme]

Dear Michele,

timef and newtimef should be backward compatible.
The erspboot matrix returned by newtimef may depend on the type of statistics that is being used.

I have just checked and the default (when you call newtimef from the EEGLAB graphic interface using menu item "Plot > Time-frequency transform > Channel time-frequency" is (nfreqs,2). It simply needs to be transposed for tftopo.

If you are using other types of statistics ('boottype' option), then in some case you cannot use tftopo to mask the data. However, if the erspboot matrix is of size [nfreq , times], you may simply mask the ersp matrix (ersp .* erspboot).

Hope this helps,

Best,

Arno

On Aug 31, 2012, at 2:24 AM, Michele Barsotti wrote:

> Dear experts,
> 
> I would like to plot a tftopo image using the data extracted from the newtimef() function.
> 
> In the wiki-eeglab, I found  the script for plotting the same graph, but using the output of the function timef() instead of the function newtimef(). 
> (http://sccn.ucsd.edu/wiki/Chapter_02:_Writing_EEGLAB_Scripts)
> 
> Then, the problem concerns the erspboot:
> - while the function timef() provides the erspboot Matrix (2,nfreqs) of [lower;upper] ERSP significance diffs,  
> the function newtimef() returns the erspboot as a mask for the ersp values that is a matrix of dimension [nfreq , times] even if the help of this function says that "erspboot  = (nfreqs,2) matrix of [lower upper] ERSP significance." , like the help of timef() do.
> 
> I would like to know if there is a way to obtain the min and max boot values from the mask or a built-in function that transforms the output of newtimef() with that of timef().
> 
>  I report here the output obtained with  the parameters "... 'timesout'    [895]  'nfreq'  [19] ..." 
>         ersp: [19x895 single]
>          itc: [19x895 single]
>      powbase: [1x19 single]
>        times: [1x895 double]
>        freqs: [1x19 double]
>     erspboot: [19x895 logical]
>      itcboot: [19x1 double]
>       tfdata: [19x895x17 single]
> 
> 17 are the trials of my dataset.
> 
> Thanks in advance 
> 
> 
> -- 
>         -Michele-
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