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<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'>Hi Peter,<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
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<p class=MsoNormal><font size=2 face=Arial><span lang=EN style='font-size:10.0pt;
font-family:Arial'>I’m trying to do clusterrandanalysis on TFR data with
the cfg. statistic=’actvsblT’ option. The tutorial ‘Cluster-level
randomization tests’ gives an example in which separate TFRs are
calculated for activation and baseline data. The clusterrandanalysis.m
documentation also states that two datasets must be passed. </span></font><span
lang=EN><o:p></o:p></span></p>
<p class=MsoNormal><font size=3 face="Times New Roman"><span lang=EN
style='font-size:12.0pt'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=2 face=Arial><span lang=EN style='font-size:10.0pt;
font-family:Arial'>However, I’d like to make the activation vs baseline
comparison work for baseline and activation TF windows identified in single
TFRs that include a prestimulus and a poststimulus period. To do so, I used
cfg. latency, cfg. frequency and cfg. keepindividual with freqgrandaverage to
create separate datastructures for the baseline and activation timefrequency
windows of interest. </span></font><span lang=EN><o:p></o:p></span></p>
<p class=MsoNormal><font size=3 color=blue face="Times New Roman"><span
lang=EN style='font-size:12.0pt;color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'>This
I don’t understand. In my terminology, “baseline” and “prestimulus”
are synonymous, as are “activation” and “poststimulus”.
The activation-versus-baseline statistic identifies samples (i.e., (sensor,frequency,time)-elements)
in the activation/poststimulus period that are different from the time-average
of the corresponding samples in the baseline/prestimulus period. If you use
freqgrandaverage to create an activation and a baseline datastructure of the
same size (with a positive time-axis for the activation period, and a negative time-axis
for the baseline period), then clusterrandanalysis should do the job.<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'>Greetings,<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'>Eric
Maris<o:p></o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
<p class=MsoNormal><font size=3 color=blue face="Bookman Old Style"><span
lang=EN style='font-size:12.0pt;font-family:"Bookman Old Style";color:blue'><o:p> </o:p></span></font></p>
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