Dear all,

 

I’m a beginner in using the longitudinal processing pipeline (as well as statistical analysis) and it would be great to get some insights or hints to analyze my data.

 

I have a dataset consisting of 11 subjects each acquired at 7 different time points with an isotropic resolution of 1 and 0.8 mm at 3T using a 64-channel head coil. Using that dataset I want to investigate short term differences in e.g. cortical thickness with the goal to assess the degree of biological variance during that time period.

 

I have plotted the mean cortical thickness of each time point of every subject (using lme_timePlot and lme_lowessPlot) showing a somewhat random distribution across time and from my perspective fairly high standard deviation. I wanted to have a look at the individual percent change by overlaying the symmetric percent change on fsaverage, but wasn’t quite sure of the scale. Is it in percent? So in case I set the scale bar between 1 and 5, the color relates to 1 to 5 percent?

 

What other ways would make sense to have a look at? I definitely cannot compare groups, as there is just one. The days and time of acquistion are rather randomly choosen, so I potentially cannot use either as a covariate.  

 

Best,

Falk

 

...............................................

 

University Clinic for Neurology

 

Otto-von-Guericke-university Magdeburg
Medical faculty
Leipziger Str. 44
39120 Magdeburg

 

Phone +49-391-6117-512

falk.luesebrink@med.ovgu.de
http://www.kneu.ovgu.de/kneu.html