Thanks for the answer. Suppose we trust 100% the conjunction analysis. Why do you think MVPA ROI analysis result will require more analytic support? If I have an ROI within a network of regions, which decodes beyond chance, is it not an evidence that this region contains the relevant information?
On Mon, Sep 23, 2013 at 4:40 PM, Yaroslav Halchenko <[email protected]>wrote: > > On Mon, 23 Sep 2013, Vadim Axel wrote: > > > Hi, > > There are two commonly used approaches to analyze the data of the > > experiment below: > > Simple design with two conditions (A and B), which �both activate > large > > network of well established regions (e.g. conjunction analysis of A > > > baseline and B > baseline). The question is whether we can find neural > > correlates of difference between the two. > > the answer I guess is: yes -- we should be able to if "conditions are > right" (power, etc) > > > Direct group-level analysis > > comparison between A and B results in small activations (~5% of volume > > comparing to commonality of conjunction analysis) and these > activations > > are located mostly outside the main network, all over the brain. > > Remembering that statistics is there only to help us to support/reject > our hypotheses, not really to be treated as "the ground truth", you > might have set up your analysis to include only the "differential" > activations which are within the main network, since that is where you > believe activity or relevance is. > > > Given > > that the result is dependent on p-value threshold, it looks like a > > classical blobology. �Another approach is to select (independently) > the > > ROIs of the common network nodes and to run MVPA. > > or even run MVPA on full brain happen you data has enough power to cope > with such large initial feature space. > > > With this analysis I > > successfully discriminate between the two conditions. So, two people > > analyzing the same data can draw absolutely different conclusions: one > > would say, that small regions X, Y, Z are the regions, which > discriminate > > between conditions A and B; > > which given your results above would be sensible conclusion imho besides > that I would have clarified that this set of regions is not necessarily > exhaustive (thus "the regions" statement might be a bit too strong) > > > the other, in contrast, would say that since > > both A and B activate common network > > depending on what is implied by "activate common network" I might argue > because it would be hard (if not impossible) to prove null hypothesis > here that the network is the same for both A and B. > > > , the difference between the two lies > > within this network (different patterns of activity). � > > > What approach is more reliable in your opinion? > > as I stated above (if I got the question right), the 2nd approach would > require (much) more analysis to support itself. > > -- > Yaroslav O. Halchenko, Ph.D. > http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org > Senior Research Associate, Psychological and Brain Sciences Dept. > Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 > Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 > WWW: http://www.linkedin.com/in/yarik > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
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