<div dir="ltr"><div class="gmail_extra"><div>Dear Barbara,</div><div><br></div><div>I think you are right, the clustering output should report total number of variables=2 (and the total # of measurements = 185 trials, number of independent variables=1, and number of unit variables=1).</div><div><br></div><div>I think your design matrix should have two rows, rather than 1. For example, if you had 5 trials total (2 of 1 trial type, 3 of the other trial type), you'd specify the design matrix:</div><div><br></div><div> 1 2 3 1 2</div><div> 1 1 1 2 2</div><div><br></div><div>Where cfg.uvar=1 and cfg.ivar=2. Row two is what you are specifying for design currently. Row 1 counts the observations of each trials (1:numTrialType1 1:numTrialType2). Does that help?</div><div><br></div><div>Respectfully,</div><div>Clara</div>
<br><div class="gmail_quote">On Wed, Oct 8, 2014 at 7:31 AM, <span dir="ltr"><<a href="mailto:barbara.schorr@uni-ulm.de" target="_blank">barbara.schorr@uni-ulm.de</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">Dear Clara,<br>
<br>
thank you for your comments.<br>
<br>
I ran it as an independent samples Test (it is true, that this is the correct way).<br>
I also changed the design matrix to<br>
cfg.design = [ones(1,size(targetclean_tlt.<u></u>trial,1)) 2*ones(1,size(standardclean_<u></u>tlt.trial,1))]<br>
<br>
It works and there are no more error messages. However, when it displays the progress of the calculation there is the field: total number of observations, total number of variables and number of independent variables. It recognizes correctly that there are 185 trials in total (both conditions together). But it only counts 1 variable and 1 independent variable. Shouldn't it recognize 2 variables as I have 2 conditions?<br>
<br>
Best regards,<br>
Barbara<br>
<br>
<br>
Zitat von <a href="mailto:fieldtrip-request@science.ru.nl" target="_blank">fieldtrip-request@science.ru.<u></u>nl</a>:<br>
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
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Today's Topics:<br>
<br>
1. Problem with ft_timelockstatistics, within subject comparison<br>
of two conditions (<a href="mailto:barbara.schorr@uni-ulm.de" target="_blank">barbara.schorr@uni-ulm.de</a>)<br>
2. Re: Problem with ft_timelockstatistics, within subject<br>
comparison of two conditions (Clara A. Scholl)<br>
3. Re: help for statistics on ERD/ERS (Tzvetan Popov)<br>
4. Re: help for statistics on ERD/ERS (Giuly)<br>
<br>
<br>
------------------------------<u></u>------------------------------<u></u>----------<br>
<br>
Message: 1<br>
Date: Tue, 07 Oct 2014 15:42:53 +0200<br>
From: <a href="mailto:barbara.schorr@uni-ulm.de" target="_blank">barbara.schorr@uni-ulm.de</a><br>
To: <a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a><br>
Subject: [FieldTrip] Problem with ft_timelockstatistics, within<br>
subject comparison of two conditions<br>
Message-ID: <<a href="mailto:20141007154253.1acx2qfvso4k4so4@imap.uni-ulm.de" target="_blank">20141007154253.<u></u>1acx2qfvso4k4so4@imap.uni-ulm.<u></u>de</a>><br>
Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes";<br>
format="flowed"<br>
<br>
Dear fieldtripers,<br>
<br>
I would like to compare to conditions of an auditory oddball paradigm<br>
(target tones and standard tones).<br>
For the identification of the electrodes which show the biggest P300,<br>
I would like to use cluster based permutation test, i.e. I want to use<br>
ft_timelockstatistics, to identify the clusters with a significant<br>
difference between the target and the standardtones.<br>
Important: I don't want to do a group statistic, but I want to compare<br>
these two conditions within each subject, to identify interesting<br>
clusters for each subject separately.<br>
<br>
<br>
I wrote the script following the tutorials on the fieldtrip homepage.<br>
<br>
I already wrote a code but it does not work:<br>
%%<br>
<br>
for i = 3:10 % subject number<br>
mypfad = 'G:\BackUp07.07.14_DatenPrepr\<u></u>Daten1\P300'<br>
cd(mypfad)<br>
cd Kontrollen;<br>
List = dir<br>
cd (List(i).name);<br>
for j = 1:4 %session number<br>
cd (mypfad);<br>
cd Kontrollen;<br>
List = dir<br>
cd (List(i).name);<br>
eval(['cd M' num2str(j)]);<br>
load cleandata_tlt; %preprocessed timelocked data<br>
standardclean_tlt and targetclean_tlt<br>
<br>
cfg = []<br>
cfg.neighbourdist = .09;<br>
cfg.layout= ulmegilay;<br>
cfg.method = 'distance';<br>
<br>
Neighbours = ft_prepare_neighbours(cfg, standardclean_tlt)<br>
<br>
cfg = []<br>
cfg.method = 'montecarlo' ; %significance probability<br>
cfg.statistic = 'ft_statfun_depsamplesT'<br>
cfg.correctm = 'cluster'<br>
cfg.clusteralpha = 0.05 %alpha level of the sample specific<br>
test statistic that will<br>
% be used for thresholding<br>
cfg.clusterstatistic = 'maxsum'<br>
cfg.minnbchan = 4<br>
cfg.latency = [0.25 0.8]<br>
cfg.neighbours = Neighbours<br>
cfg.tail = 0<br>
cfg.clustertail = 0<br>
cfg.alpha = 0.025<br>
cfg.numrandomization = 1000<br>
<br>
design = [ones(size(targetclean_tlt.<u></u>trial,1),1);<br>
2*ones(size(standardclean_tlt.<u></u>trial,1),1)]';<br>
design([1:size(targetclean_<u></u>tlt.trial)<br>
1:size(standardclean_tlt.<u></u>trial,1)])<br>
<br>
<br>
cfg.design = design<br>
cfg.ivar = [ones(size(targetclean_tlt.<u></u>trial,1),1);<br>
2*ones(size(standardclean_tlt.<u></u>trial,1),1)]'<br>
cfg.uvar = [1:size(targetclean_tlt.trial)<br>
1:size(standardclean_tlt.<u></u>trial,1)]<br>
<br>
tlt_statsnew = ft_timelockstatistics(cfg, targetclean_tlt,<br>
standardclean_tlt )<br>
<br>
cd 'G:\BackUp07.07.14_DatenPrepr\<u></u>Daten1\P300';<br>
cd Kontrollen;<br>
List2 = dir<br>
cd (List2(i).name);<br>
eval(['cd M' num2str(j)]);<br>
save statnew tlt_statsnew<br>
<br>
end<br>
end<br>
<br>
<br>
This is what gets displayed while running the script:<br>
<br>
selected 245 channels<br>
selected 139 time bins<br>
selected 1 frequency bins<br>
using "ft_statistics_montecarlo" for the statistical testing<br>
using "ft_statfun_depsamplesT" for the single-sample statistics<br>
constructing randomized design<br>
total number of measurements = 189<br>
total number of variables = 1<br>
number of independent variables = 189<br>
number of unit variables = 189<br>
number of within-cell variables = 0<br>
number of control variables = 0<br>
using a permutation resampling approach<br>
<br>
Then, this error occurs:<br>
<br>
Error using resampledesign (line 168)<br>
A within-units shuffling requires a at least one unit variable and at least<br>
one independent variable<br>
<br>
Error in ft_statistics_montecarlo (line 241)<br>
resample = resampledesign(cfg, design);<br>
<br>
Error in statistics_wrapper (line 310)<br>
[stat, cfg] = statmethod(cfg, dat, design);<br>
<br>
Error in ft_timelockstatistics (line 113)<br>
[stat, cfg] = statistics_wrapper(cfg, varargin{:});<br>
<br>
I have no clue where I made a mistake. I have unit variables and<br>
independent variables (189 if I understand it correctly).<br>
Is there anything I am missing? Any additional information or is the<br>
design matrix wrong?<br>
<br>
<br>
I really appreciate your help.<br>
<br>
Best regards,<br>
Barbara<br>
<br>
<br>
<br>
<br>
Barbara Schorr, MSc<br>
Clinical and Biological Psychology<br>
University of Ulm<br>
Albert-Einstein-Allee 47<br>
89069 Ulm<br>
<br>
<br>
<br>
<br>
<br>
------------------------------<br>
<br>
Message: 2<br>
Date: Tue, 7 Oct 2014 09:55:36 -0400<br>
From: "Clara A. Scholl" <<a href="mailto:clara.scholl@gmail.com" target="_blank">clara.scholl@gmail.com</a>><br>
To: FieldTrip discussion list <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>><br>
Subject: Re: [FieldTrip] Problem with ft_timelockstatistics, within<br>
subject comparison of two conditions<br>
Message-ID:<br>
<<u></u>CAAHOyr7MU6npw9U4Wqkoo7OXxthQm<u></u>sTrjBroWcxLe6qTeSkC=<a href="mailto:g@mail.gmail.com" target="_blank">g@mail.<u></u>gmail.com</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Dear Barbara,<br>
<br>
Just three thoughts:<br>
<br>
1) Should cfg.ivar and cfg.uvar both be single values, i.e. the dimension<br>
of the design matrix that contains the independent and unit variables?<br>
Then you'd have cfg.ivar=1 and cfg.uvar=2 (or vise versa, depending on the<br>
design matrix).<br>
<br>
2) I think the design matrix itself might be off, right now it just seems<br>
to have dimensions of 1 x (# targets+standards). It should have a second<br>
dimension which counts the # of trials, something like:<br>
<br>
design(1,:) = [ones(size(targetclean_tlt.<u></u>trial,1),1);<br>
2*ones(size(standardclean_tlt.<u></u>trial,1),1)]';<br>
design(2,:)= ([1:size(targetclean_tlt.<u></u>trial) 1:size(standardclean_tlt.trial<br>
,1)])<br>
<br>
3) Since this is a design where each trial is an observation, I think you<br>
should be using indepsamplesT for cfg.statistic (the trials aren't paired<br>
and there aren't necessarily identical #'s of trials for each condition.<br>
<br>
What do you think?<br>
Respectfully,<br>
Clara<br>
<br>
<br>
On Tue, Oct 7, 2014 at 9:42 AM, <<a href="mailto:barbara.schorr@uni-ulm.de" target="_blank">barbara.schorr@uni-ulm.de</a>> wrote:<br>
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
Dear fieldtripers,<br>
<br>
I would like to compare to conditions of an auditory oddball paradigm<br>
(target tones and standard tones).<br>
For the identification of the electrodes which show the biggest P300, I<br>
would like to use cluster based permutation test, i.e. I want to use<br>
ft_timelockstatistics, to identify the clusters with a significant<br>
difference between the target and the standardtones.<br>
Important: I don't want to do a group statistic, but I want to compare<br>
these two conditions within each subject, to identify interesting clusters<br>
for each subject separately.<br>
<br>
<br>
I wrote the script following the tutorials on the fieldtrip homepage.<br>
<br>
I already wrote a code but it does not work:<br>
%%<br>
<br>
for i = 3:10 % subject number<br>
mypfad = 'G:\BackUp07.07.14_DatenPrepr\<u></u>Daten1\P300'<br>
cd(mypfad)<br>
cd Kontrollen;<br>
List = dir<br>
cd (List(i).name);<br>
for j = 1:4 %session number<br>
cd (mypfad);<br>
cd Kontrollen;<br>
List = dir<br>
cd (List(i).name);<br>
eval(['cd M' num2str(j)]);<br>
load cleandata_tlt; %preprocessed timelocked data<br>
standardclean_tlt and targetclean_tlt<br>
<br>
cfg = []<br>
cfg.neighbourdist = .09;<br>
cfg.layout= ulmegilay;<br>
cfg.method = 'distance';<br>
<br>
Neighbours = ft_prepare_neighbours(cfg, standardclean_tlt)<br>
<br>
cfg = []<br>
cfg.method = 'montecarlo' ; %significance probability<br>
cfg.statistic = 'ft_statfun_depsamplesT'<br>
cfg.correctm = 'cluster'<br>
cfg.clusteralpha = 0.05 %alpha level of the sample specific test<br>
statistic that will<br>
% be used for thresholding<br>
cfg.clusterstatistic = 'maxsum'<br>
cfg.minnbchan = 4<br>
cfg.latency = [0.25 0.8]<br>
cfg.neighbours = Neighbours<br>
cfg.tail = 0<br>
cfg.clustertail = 0<br>
cfg.alpha = 0.025<br>
cfg.numrandomization = 1000<br>
<br>
design = [ones(size(targetclean_tlt.<u></u>trial,1),1);<br>
2*ones(size(standardclean_tlt.<u></u>trial,1),1)]';<br>
design([1:size(targetclean_<u></u>tlt.trial) 1:size(standardclean_tlt.<br>
trial,1)])<br>
<br>
<br>
cfg.design = design<br>
cfg.ivar = [ones(size(targetclean_tlt.<u></u>trial,1),1);<br>
2*ones(size(standardclean_tlt.<u></u>trial,1),1)]'<br>
cfg.uvar = [1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.<br>
trial,1)]<br>
<br>
tlt_statsnew = ft_timelockstatistics(cfg, targetclean_tlt,<br>
standardclean_tlt )<br>
<br>
cd 'G:\BackUp07.07.14_DatenPrepr\<u></u>Daten1\P300';<br>
cd Kontrollen;<br>
List2 = dir<br>
cd (List2(i).name);<br>
eval(['cd M' num2str(j)]);<br>
save statnew tlt_statsnew<br>
<br>
end<br>
end<br>
<br>
<br>
This is what gets displayed while running the script:<br>
<br>
selected 245 channels<br>
selected 139 time bins<br>
selected 1 frequency bins<br>
using "ft_statistics_montecarlo" for the statistical testing<br>
using "ft_statfun_depsamplesT" for the single-sample statistics<br>
constructing randomized design<br>
total number of measurements = 189<br>
total number of variables = 1<br>
number of independent variables = 189<br>
number of unit variables = 189<br>
number of within-cell variables = 0<br>
number of control variables = 0<br>
using a permutation resampling approach<br>
<br>
Then, this error occurs:<br>
<br>
Error using resampledesign (line 168)<br>
A within-units shuffling requires a at least one unit variable and at least<br>
one independent variable<br>
<br>
Error in ft_statistics_montecarlo (line 241)<br>
resample = resampledesign(cfg, design);<br>
<br>
Error in statistics_wrapper (line 310)<br>
[stat, cfg] = statmethod(cfg, dat, design);<br>
<br>
Error in ft_timelockstatistics (line 113)<br>
[stat, cfg] = statistics_wrapper(cfg, varargin{:});<br>
<br>
I have no clue where I made a mistake. I have unit variables and<br>
independent variables (189 if I understand it correctly).<br>
Is there anything I am missing? Any additional information or is the<br>
design matrix wrong?<br>
<br>
<br>
I really appreciate your help.<br>
<br>
Best regards,<br>
Barbara<br>
<br>
<br>
<br>
<br>
Barbara Schorr, MSc<br>
Clinical and Biological Psychology<br>
University of Ulm<br>
Albert-Einstein-Allee 47<br>
89069 Ulm<br>
<br>
<br>
<br>
______________________________<u></u>_________________<br>
fieldtrip mailing list<br>
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<br>
</blockquote>
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<br>
------------------------------<br>
<br>
Message: 3<br>
Date: Tue, 7 Oct 2014 21:07:37 +0200<br>
From: Tzvetan Popov <<a href="mailto:tzvetan.popov@uni-konstanz.de" target="_blank">tzvetan.popov@uni-konstanz.de</a><u></u>><br>
To: FieldTrip discussion list <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>><br>
Subject: Re: [FieldTrip] help for statistics on ERD/ERS<br>
Message-ID: <<a href="mailto:D25CE622-A81C-493D-8905-8536BB51023C@uni-konstanz.de" target="_blank">D25CE622-A81C-493D-8905-<u></u>8536BB51023C@uni-konstanz.de</a>><br>
Content-Type: text/plain; charset=windows-1252<br>
<br>
Hi Giulia,<br>
<br>
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
Dear Fieldtrippers<br>
I'm writing to ask you some help on data in a single subject study.<br>
I did a time frequency decomposition and I would like to do a statistic to state whether the average TFR has significant ERD/ERS or not.<br>
I'm not sure how to proceed<br>
</blockquote>
What you are referring to is a ?between trial experiment? which is described in this tutorial:<br>
<a href="http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq" target="_blank">http://fieldtrip.fcdonders.nl/<u></u>tutorial/cluster_permutation_<u></u>freq</a><br>
One possible way to go is to compute the TFR?s with cfg.keeptrials = ?yes?. Next you?d treat the baseline and the task interval as two conditions by separating them using ft_selectdata. After this you can compute the statistical comparison in a similar fashion as described in the tutorial.<br>
Keep in mind that you have to cut the data into equal lengths. Please have a look at this post :<br>
<a href="http://mailman.science.ru.nl/pipermail/fieldtrip/2007-July/001303.html" target="_blank">http://mailman.science.ru.nl/<u></u>pipermail/fieldtrip/2007-July/<u></u>001303.html</a><br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
, as a first step I compared the single trial baseline with the respective event, with a t-test for each condition and band of interest but I'm not really sure if this is enough and anyway if it is the correct way.<br>
</blockquote>
Also please type ?actvsblT? in the search bar and then click on ?Search the FieldTrip mailing list?. There you?ll find some info about this.<br>
<br>
best<br>
tzvetan<br>
<br>
<br>
<br>
<br>
------------------------------<br>
<br>
Message: 4<br>
Date: Wed, 08 Oct 2014 10:45:23 +0200<br>
From: Giuly <<a href="mailto:giulia.rizza@tiscali.it" target="_blank">giulia.rizza@tiscali.it</a>><br>
To: FieldTrip discussion list <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>><br>
Subject: Re: [FieldTrip] help for statistics on ERD/ERS<br>
Message-ID: <<a href="mailto:eeebb8a2bf90ed8099aea3a3e21a7a38@tiscali.it" target="_blank">eeebb8a2bf90ed8099aea3a3e21a7<u></u>a38@tiscali.it</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Hi Tzvetan<br>
Thank you so much for your reply<br>
I will try these<br>
functions keeping in mind your explanation<br>
Best regards<br>
Giulia<br>
<br>
Il<br>
07.10.2014 21:07 Tzvetan Popov ha scritto:<br>
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
Hi Giulia,<br>
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
Dear<br>
</blockquote></blockquote>
Fieldtrippers I'm writing to ask you some help on data in a single<br>
subject study. I did a time frequency decomposition and I would like to<br>
do a statistic to state whether the average TFR has significant ERD/ERS<br>
or not. I'm not sure how to proceed<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
What you are referring to is a<br>
</blockquote>
"between trial experiment" which is described in this tutorial:<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
</blockquote>
<a href="http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq" target="_blank">http://fieldtrip.fcdonders.nl/<u></u>tutorial/cluster_permutation_<u></u>freq</a> [1]<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
</blockquote>
One possible way to go is to compute the TFR's with cfg.keeptrials =<br>
'yes'. Next you'd treat the baseline and the task interval as two<br>
conditions by separating them using ft_selectdata. After this you can<br>
compute the statistical comparison in a similar fashion as described in<br>
the tutorial.<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
Keep in mind that you have to cut the data into equal<br>
</blockquote>
lengths. Please have a look at this post :<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
</blockquote>
<a href="http://mailman.science.ru.nl/pipermail/fieldtrip/2007-July/001303.html" target="_blank">http://mailman.science.ru.nl/<u></u>pipermail/fieldtrip/2007-July/<u></u>001303.html</a><br>
[2]<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
, as a first step I compared the single trial baseline with<br>
</blockquote></blockquote>
the respective event, with a t-test for each condition and band of<br>
interest but I'm not really sure if this is enough and anyway if it is<br>
the correct way.<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
Also please type "actvsblT" in the search bar and<br>
</blockquote>
then click on "Search the FieldTrip mailing list". There you'll find<br>
some info about this.<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<br>
best<br>
tzvetan<br>
<br>
<br>
</blockquote>
______________________________<u></u>_________________<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
fieldtrip mailing<br>
</blockquote>
list<br>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex">
<a href="mailto:fieldtrip@donders.ru.nl" target="_blank">fieldtrip@donders.ru.nl</a> [3]<br>
<br>
</blockquote>
<a href="http://mailman.science.ru.nl/mailman/listinfo/fieldtrip" target="_blank">http://mailman.science.ru.nl/<u></u>mailman/listinfo/fieldtrip</a> [4]<br>
<br>
<br>
<br>
<br>
Scopri istella, il nuovo motore per il web italiano.<br>
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<br>
End of fieldtrip Digest, Vol 47, Issue 6<br>
******************************<u></u>**********<br>
<br>
</blockquote>
<br>
<br>
<br>
Barbara Schorr, MSc<br>
Clinical and Biological Psychology<br>
University of Ulm<br>
Albert-Einstein-Allee 47<br>
89069 Ulm<br>
<br>
<br>
<br>
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