No, that is not what I meant. I meant that based on the filename, I would have expected only clusters that DID survive multiple comparisons testing (based on the supra-threshold cluster test described in Nichols & Holmes 2002, adapted to the surface) would be non-zero in your *Clusters*metric; however, your observation that more than one cluster was non-zero in that file is inconsistent with that expectation. The significant report (.txt file) listed only one significant cluster.
So I would not trust the *Clusters*metric to contain corrected clusters unless: * Your significance report was in error (e.g., it was from a different test). * You had some other metric column showing as an underlay, thereby erroneously leading you to believe *Clusters*metric had more than one non-zero cluster. If your goal is to display only the significant cluster, this can be done manually by loading the unthresholded tmap (i.e., metric w/o clusters in the name) and using Surface: ROI to select the nodes below -2.66; disconnect islands; invert the selection; and set metric to zero. > Hi Donna, > > Thanks for your quick reply. so that means that the clusters I see when I > load T-Map*TMapClusters.metric are all clusters in the real T-Map file > that exceed my T-threshold, which means that their significance is not > corrected for mulitple comparisons, right? > > Thanks again, > > Julia > >> Hi Julia, >> >> Again, it has been years since I have used the cluster-based test, >> having switched to TFCE. I'd probably have to dig around to find an old >> dataset like that. >> >> But from what I remember, there was a tmap*metric that had a column with >> the unthresholded t-map, but then there was also a tmap*Clusters*metric >> that zeroed out everything that wasn't in a significant cluster. Based >> on your filename, I'd guess that was the >> latter type, so should have everything NOT in a significant cluster >> zeroed out. If not, I'd wonder whether you have some underlay or >> secondary overlay that is set to a different column/metric. >> >> At any rate, worst case, you can use Surface: ROI to threshold the >> metric at -2.66 and select only nodes connected to the currently >> selected node (where you ID a node inside the significant cluster). >> >> Donna >> >> On 12/01/2010 01:07 PM, Julia Bender wrote: >>> Hi Donna, >>> >>> thanks for updating the code. I've rerun my stats with different >>> thresholds (T=2.66, p.05). My *_SignificantClusters.txt file tells me >>> that >>> there is only one significant cluster: >>> >>> TMap >>> ---- >>> Column Thresh Num-Nodes Area Area-Corrected COG-X >>> COG-Y COG-Z P-Value >>> 1 -2.660 4203 2775.767090 2827.737549 40.409 >>> -12.974 -27.389 0.002000 >>> >>> but when I load the T-Map*TMapClusters.metric file onto my surface I >>> can >>> see several clusters. Are those the uncorrected significant clusters? >>> TMap >>> ---- >>> Column Thresh Num-Nodes Area Area-Corrected COG-X >>> COG-Y COG-Z P-Value >>> 1 -2.660 4203 2775.767090 2827.737549 40.409 >>> -12.974 -27.389 0.002000 >>> 1 2.660 435 219.168182 220.613358 28.160 >>> -52.169 56.452 0.258000 >>> 1 2.660 184 153.448578 158.166473 44.849 >>> -24.530 49.967 0.365000 >>> 1 2.660 229 153.459183 149.640244 35.705 >>> -20.871 50.301 0.394000 >>> 1 2.660 153 106.938622 107.896500 45.769 >>> -0.412 39.610 0.541000 >>> 1 2.660 142 90.582855 88.234703 27.666 >>> -23.322 -13.406 0.641000 >>> 1 2.660 143 81.723625 80.440567 49.349 >>> -24.353 -2.452 0.683000 >>> 1 2.660 181 67.850945 68.252045 19.675 >>> -10.697 58.506 0.755000 >>> 1 2.660 151 70.042465 67.372482 38.421 >>> -37.124 46.450 0.757000 >>> 1 -2.660 48 58.272926 59.562595 7.732 >>> 17.195 -16.283 0.804000 >>> 1 2.660 59 57.713173 56.583248 38.887 >>> 13.286 33.244 0.821000 >>> 1 -2.660 43 40.167896 41.627560 29.441 >>> -80.470 -15.188 0.898000 >>> 1 2.660 70 31.806927 31.897322 21.620 >>> -64.665 49.982 0.937000 >>> 1 2.660 57 29.297220 30.987967 5.613 >>> -8.313 65.568 0.941000 >>> 1 2.660 43 27.218239 26.574488 16.105 >>> 30.667 49.513 0.960000 >>> 1 2.660 31 14.005635 13.789747 37.211 >>> -5.401 -5.390 0.993000 >>> 1 2.660 21 12.719942 12.593773 50.215 >>> -25.851 41.114 0.994000 >>> 1 2.660 13 10.736663 10.448134 23.142 >>> 39.879 31.981 0.997000 >>> 1 2.660 9 5.134305 5.243526 17.070 >>> -60.562 62.295 0.999000 >>> 1 2.660 2 1.532340 1.510908 23.168 >>> -34.540 -5.696 0.998000 >>> >>> It looks like it. >>> >>> Is there a way to display only the corrected significant clusters? >>> >>> Thanks a lot for your help, >>> >>> Julia >>> >>> >>>> All of the statistical tests have been corrected so they should now >>>> produce the correct P-Value. >>>> >>>> An updated caret distribution, v5.616, is now available for download >>>> from >>>> http://brainvis.wustl.edu/wiki/index.php/Caret:Download >>>> (username=Rabbit >>>> password=Carrot). >>>> >>>> The effect is generally very minimal (2/iterations -- .0004 using our >>>> typical 5k). >>>> >>>> On 11/08/2010 09:18 AM, Donna Dierker wrote: >>>> >>>>> Julia, >>>>> >>>>> I see what you mean. Based on the report you uploaded, the p-values >>>>> listed here seem off by .002: >>>>> >>>>> 1 2.500 1712 1229.060425 1242.687012 -27.858 >>>>> -75.308 -13.617 0.036000 >>>>> 1 2.500 1960 1059.480713 1062.812378 -21.474 >>>>> -62.266 50.506 0.044000 >>>>> >>>>> I'll ask John about it. >>>>> >>>>> Donna >>>>> >>>>> On 11/08/2010 04:07 AM, Julia Bender wrote: >>>>> >>>>>> Hi Donna, >>>>>> >>>>>> thanks for your answers. I've uploaded >>>>>> "T-Map_LH_cCue_EndoLeft.metric_TMap_Significant_Clusters.txt" which >>>>>> is the >>>>>> example file we've been talking about. As far as I see it the >>>>>> cluster >>>>>> >>>>>> TMap >>>>>> ---- >>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>> COG-X COG-Y COG-Z P-Value >>>>>> 1 2.500 1712 1229.060425 1242.687012 -27.858 >>>>>> -75.308 -13.617 0.036000 >>>>>> >>>>>> fits in between rank 37 (area corrected 1273.066772) and 38 >>>>>> (area-corrected 1240.362915). >>>>>> >>>>>> Thanks for your help, >>>>>> >>>>>> Julia >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>>> On 11/04/2010 09:57 AM, Julia Bender wrote: >>>>>>> >>>>>>> >>>>>>>> Hi Donna, >>>>>>>> >>>>>>>> thank you so much for your detailed reply. It helped a great deal. >>>>>>>> Three things remain somewhat unclear to me: >>>>>>>> >>>>>>>> 1. I think I figured out why the list of permuted clusters in >>>>>>>> xx.metric_TMap_Significant_Clusters.txt only has 696 instead of >>>>>>>> 1000 >>>>>>>> (=number of iterations) columns in the example contrast. My input >>>>>>>> columns >>>>>>>> were n=13, which would allow up to 2^13=8192 iterations. But only >>>>>>>> 696 of >>>>>>>> the 1000 iterations produce clusters with a T-Value above my >>>>>>>> defined >>>>>>>> threshold. Theses are the ones listed in the output file. Is that >>>>>>>> possible? >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>> Sure, it certainly is possible for the data to not survive >>>>>>> threshold, >>>>>>> but I'm not used to it. >>>>>>> >>>>>>> >>>>>>>> 2. The significant cluster in the example has an area-corrected >>>>>>>> value of >>>>>>>> 1242.687012 and is assigned a p-value of 0.036. This means that it >>>>>>>> resides >>>>>>>> on rank 36 out of my 1000 iterations, right? When I looked up the >>>>>>>> 100 >>>>>>>> largest clusters list (my predefined P-threshold was .1) in my >>>>>>>> output >>>>>>>> file >>>>>>>> the significant cluster would actually take rank 38. what am I >>>>>>>> getting >>>>>>>> wrong here? >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>> Keep in mind that the p-values are based on the distribution built >>>>>>> by >>>>>>> the random tmaps, but the area of clusters on the real tmap is >>>>>>> typically >>>>>>> in between two areas on the randomized list. >>>>>>> >>>>>>> If your real tmap cluster is bigger than the 38th biggest random >>>>>>> cluster, but smaller than the 37th, then I'd expect it to have a >>>>>>> p-value >>>>>>> of 38/iterations. >>>>>>> >>>>>>> If this is not happening, I don't know why. Upload your >>>>>>> significance >>>>>>> report, and I'll have a look: >>>>>>> >>>>>>> http://pulvinar.wustl.edu/cgi-bin/upload.cgi >>>>>>> >>>>>>> >>>>>>>> 3.The correction for multiple comparisons is done by thresholding >>>>>>>> all >>>>>>>> real >>>>>>>> T-map clusters above the predefined T-Value with the smallest >>>>>>>> iterations*alpha cluster of the permutation distribution according >>>>>>>> to >>>>>>>> area-corrected? The corrected P-value for real T-map clusters that >>>>>>>> survive >>>>>>>> this threshold is derived from the rank the clusters hold in the >>>>>>>> total >>>>>>>> iterations list according to area-corrected? >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>> I would put it differently. Any clusters in the real tmap >>>>>>> surviving >>>>>>> the >>>>>>> threshold that exceed the minimum significance cut-off in corrected >>>>>>> area >>>>>>> are significant. >>>>>>> >>>>>>> >>>>>>>> Again, thanks a lot for your answers!! >>>>>>>> >>>>>>>> Julia >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>>> Hi Julia, >>>>>>>>> >>>>>>>>> Bear with me, because it's been years since I used the >>>>>>>>> caret_command >>>>>>>>> tests, which are mostly cluster tests. We switched from cluster >>>>>>>>> to >>>>>>>>> TFCE >>>>>>>>> a year or so ago: >>>>>>>>> >>>>>>>>> http://brainvis.wustl.edu/wiki/index.php/Caret:Documentation:Statistics#Threshold-Free_Cluster_Enhancement_.28TFCE.29 >>>>>>>>> >>>>>>>>> >>>>>>>>> But those tests are in caret_stats, which is a separate >>>>>>>>> tool/package >>>>>>>>> based on java. Let me know if you want to know more about that. >>>>>>>>> >>>>>>>>> My inline replies below reflect my best recollection of the >>>>>>>>> cluster >>>>>>>>> tests. >>>>>>>>> >>>>>>>>> Donna >>>>>>>>> >>>>>>>>> On 10/08/2010 08:16 AM, Julia Bender wrote: >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> Hi Donna, >>>>>>>>>> >>>>>>>>>> I've looked more into the "caret_command >>>>>>>>>> -metric-statistics-one-sample-t-test" output files. I'm having >>>>>>>>>> trouble >>>>>>>>>> understanding what all the information means. Maybe you can >>>>>>>>>> correct >>>>>>>>>> me: >>>>>>>>>> >>>>>>>>>> 1. xx.metric_TMap.metric: >>>>>>>>>> Map of T-Values for the wholebrain (?) for the contrast defined >>>>>>>>>> in the >>>>>>>>>> xx.metric input files. Those are T-Values exceeding the T-Value >>>>>>>>>> thresholds >>>>>>>>>> and alpha level I specified in >>>>>>>>>> "caret_command-metric-statistics-one-sample-t-test" (eg -300000 >>>>>>>>>> 2.5 >>>>>>>>>> 0.1 >>>>>>>>>> in >>>>>>>>>> my case). >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> They are not thresholded. The 2.5 and 0.1 affect the cluster >>>>>>>>> size, >>>>>>>>> which affects downstream outputs. But this TMap is >>>>>>>>> unthresholded. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> They are not corrected for multiple comparisons(?). >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> No, definitely not. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> This is the one I should load onto my surface. When I load >>>>>>>>>> that TMap, why can I still see T-Values below my defined >>>>>>>>>> threshold? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> Right. I like to use the unthresholded t/f-map for my figures, >>>>>>>>> but >>>>>>>>> generate a border around the clusters that were significant, and >>>>>>>>> show >>>>>>>>> the border overlaid on the unthresholded t-map. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> 2.xx.metric_ShuffledTMap.metric: >>>>>>>>>> Distribution of T-Values derived from permuting + and - on each >>>>>>>>>> element >>>>>>>>>> in >>>>>>>>>> xx in N iterations (in my case 1000) >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> Right, and less than 1000, depending on how many columns there >>>>>>>>> are >>>>>>>>> in >>>>>>>>> your input composite metric. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> 3.xx.metric_TMap_Significant_Clusters.txt: >>>>>>>>>> This is what the help page says: >>>>>>>>>> "1. Find the biggest cluster in each column of the permutation >>>>>>>>>> T-Map >>>>>>>>>> metric/shape file and sort them by cluster size." >>>>>>>>>> I see two lists of clusters in the output file. I assume the one >>>>>>>>>> that >>>>>>>>>> is >>>>>>>>>> the result of this sorting is the lower one. It has about 700 >>>>>>>>>> rows >>>>>>>>>> depending on xx, why does it not have 1000 rows, one for each >>>>>>>>>> permutation? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> See Sample Report: Two Sample T-Test here: >>>>>>>>> >>>>>>>>> http://brainvis.wustl.edu/OLD/courses/stats_neurosci/2008_BMEcourse/BME_dld_talk.htm >>>>>>>>> >>>>>>>>> >>>>>>>>> Yours is a one-sample t-test, but I think the cluster lists will >>>>>>>>> be the >>>>>>>>> same. >>>>>>>>> >>>>>>>>> If your last list of clusters has less than 1000 rows, then you >>>>>>>>> had >>>>>>>>> fewer than 10 columns in your input composite metric. If n is >>>>>>>>> the >>>>>>>>> number of columns, and 2 raised to the n is less than your input >>>>>>>>> iterations, then Caret will stop at 2^n. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> Are the clusters sorted by Num-Nodes, Area or Area corrected? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> Descending area-corrected. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> In my files >>>>>>>>>> they seem kind of sorted by both... How is a cluster defined? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> By your input thresholds. The permuted t-maps are thresholded at >>>>>>>>> the >>>>>>>>> level specified, and then clusters of contiguous supra-threshold >>>>>>>>> nodes >>>>>>>>> are found. Only the largest in each iteration is saved. Then >>>>>>>>> they are >>>>>>>>> listed in descending order of area-corrected size. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> "2. Find the largest (alpha)(iterations) clusters in the >>>>>>>>>> Permutation >>>>>>>>>> T-Map >>>>>>>>>> and use its cluster size as the Significant Cluster Cutoff." >>>>>>>>>> I assume this is the list of T-Values right below the above list >>>>>>>>>> of >>>>>>>>>> clusters, why does it contain clusters with a P-Value that is >>>>>>>>>> above my >>>>>>>>>> defined alpha? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> The last table lists all the largest clusters for each iteration, >>>>>>>>> regardless of its p. The second table is what you want. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> "3. Find clusters in the Real T-Map file." This must be the >>>>>>>>>> upper >>>>>>>>>> list >>>>>>>>>> of >>>>>>>>>> clusters (containing much less rows than the lower one) >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> Correct. That link above shows this the best. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> "4. Report all clusters in Real T-Map file that are larger than >>>>>>>>>> Significant Cluster Cutoff." This is the list of T-Values below >>>>>>>>>> this >>>>>>>>>> list, >>>>>>>>>> containing only clusters that are bigger than the cluster with >>>>>>>>>> the >>>>>>>>>> highest >>>>>>>>>> P-Value found in 2. that pass the alpha and T-Value thresholds I >>>>>>>>>> specified >>>>>>>>>> in "caret_command-metric-statistics-one-sample-t-test". >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> Again, here is the relevant excerpt from the link above: >>>>>>>>> >>>>>>>>> Significant Area: 306.226 <--- area of smallest cluster listed >>>>>>>>> in >>>>>>>>> next >>>>>>>>> section >>>>>>>>> >>>>>>>>> Shuffled TMap <--- Top alpha*iterations biggest clusters are >>>>>>>>> listed >>>>>>>>> below, >>>>>>>>> in descending area-corrected sequence. >>>>>>>>> (i.e., the smallest of which determines the signifiance area >>>>>>>>> cut-off) >>>>>>>>> ------------- >>>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>>> COG-X >>>>>>>>> COG-Y COG-Z P-Value >>>>>>>>> 821 2.660 2300 1439.637207 1559.143188 >>>>>>>>> -37.249 >>>>>>>>> 0.007 -3.456 >>>>>>>>> 150 2.660 792 598.519104 858.216492 >>>>>>>>> -49.142 >>>>>>>>> -32.369 11.918 >>>>>>>>> 548 2.660 1380 641.563843 643.790466 >>>>>>>>> -35.004 >>>>>>>>> 2.519 -14.981 >>>>>>>>> ... (middle biggest alpha*iterations entries omitted) >>>>>>>>> 681 -2.660 279 249.739059 312.872681 >>>>>>>>> -48.189 >>>>>>>>> -9.576 10.352 >>>>>>>>> 649 2.660 237 198.468857 311.602844 >>>>>>>>> -16.170 >>>>>>>>> -79.223 30.149 >>>>>>>>> 633 -2.660 217 119.337837 306.226257 >>>>>>>>> -42.479 >>>>>>>>> -48.846 41.505 >>>>>>>>> >>>>>>>>> >>>>>>>>> TMap <--- Significant real tmap clusters (i.e., >= significant >>>>>>>>> area) >>>>>>>>> are >>>>>>>>> listed here; no entries here means no clusters were significant. >>>>>>>>> ---- >>>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>>> COG-X >>>>>>>>> COG-Y COG-Z P-Value >>>>>>>>> 3 2.660 344 229.353973 362.322113 >>>>>>>>> -45.677 >>>>>>>>> -27.442 18.039 0.029000 >>>>>>>>> >>>>>>>>> Shuffled TMap <--- All iterations max clusters are listed below, >>>>>>>>> in >>>>>>>>> descending area-corrected sequence. >>>>>>>>> ------------- >>>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>>> COG-X >>>>>>>>> COG-Y COG-Z P-Value >>>>>>>>> 821 2.660 2300 1439.637207 1559.143188 >>>>>>>>> -37.249 >>>>>>>>> 0.007 -3.456 >>>>>>>>> 150 2.660 792 598.519104 858.216492 >>>>>>>>> -49.142 >>>>>>>>> -32.369 11.918 >>>>>>>>> 548 2.660 1380 641.563843 643.790466 >>>>>>>>> -35.004 >>>>>>>>> 2.519 -14.981 >>>>>>>>> ... (middle biggest alpha*iterations entries omitted) >>>>>>>>> 3 2.660 1 0.475079 0.472114 >>>>>>>>> -18.520 >>>>>>>>> -24.418 -21.858 0.999000 >>>>>>>>> 3 -2.660 1 0.474738 0.456814 >>>>>>>>> -21.478 >>>>>>>>> -36.579 -17.077 0.999000 >>>>>>>>> 3 2.660 1 0.000000 0.000000 >>>>>>>>> -6.822 >>>>>>>>> -46.751 8.581 0.999000 >>>>>>>>> >>>>>>>>> ------------------------------------------------------------------------ >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> 4. T-Map_LH_cCue_EndoL_vs_Cue_ExoL.metric_TMapClusters.metric >>>>>>>>>> Is this the map of clusters defined above? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>> This is what I believe you thought xx.metric_TMap.metric was, but >>>>>>>>> it is >>>>>>>>> unthresholded. >>>>>>>>> >>>>>>>>> This TMapClusters one zeroes out all nodes that are NOT within a >>>>>>>>> significant cluster. >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>>> I'm sorry, I know these are a many questions. Thanks a lot for >>>>>>>>>> your >>>>>>>>>> help! >>>>>>>>>> >>>>>>>>>> Julia >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> Julia, >>>>>>>>>>> I looked at your report and your t-map, which is consistent >>>>>>>>>>> with >>>>>>>>>>> the >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> caret_command -metric-information output you included below. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> Just making sure you understand this part of the report: >>>>>>>>>>> TMap >>>>>>>>>>> ---- >>>>>>>>>>> Column Thresh Num-Nodes Area Area-Corrected >>>>>>>>>>> COG-X >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> COG-Y COG-Z P- >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> Value >>>>>>>>>>> 1 2.500 3064 2223.228027 2245.943848 >>>>>>>>>>> -30.317 >>>>>>>>>>> -73.796 -12.228 0.0 >>>>>>>>>>> 12000 >>>>>>>>>>> 1 2.500 3372 1865.999878 1863.883423 >>>>>>>>>>> -21.516 >>>>>>>>>>> -62.842 46.382 0.0 >>>>>>>>>>> 17000 >>>>>>>>>>> 1 2.500 1557 681.308838 674.981384 >>>>>>>>>>> -32.967 >>>>>>>>>>> -5.873 48.701 0.0 >>>>>>>>>>> 59000 >>>>>>>>>>> These are the clusters in your real t-map that were significant >>>>>>>>>>> at >>>>>>>>>>> the >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> 0.1 >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> alpha you specified, using the 2.5 threshold. (Note that all >>>>>>>>>>> the >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> significant clusters were at the positive end.) >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> I believe the reason you saw different max/min in the Caret GUI >>>>>>>>>>> was >>>>>>>>>>> that >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> you had the permuted t-map loaded, instead of the real one. In >>>>>>>>>> your >>>>>>>>>> message below, you said, "Adjustment:Column: permuted >>>>>>>>>> T-Values,Threshold >>>>>>>>>> type". There is nothing about permuted in the file you >>>>>>>>>> uploaded. If >>>>>>>>>> you >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> were viewing the permuted/shuffled t-map, this would also >>>>>>>>>>> explain why >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> little would survive a low threshold. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> But we don't necessarily (or even usually) use the same values >>>>>>>>>>> we >>>>>>>>>>> used >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> for >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> cluster thresholds as the threshold for displaying t-maps, >>>>>>>>>>> e.g., >>>>>>>>>>> for >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> publication purposes. I think we like to see some color >>>>>>>>>> differentiation >>>>>>>>>> beyond the cluster threshold max. If they are the same, the >>>>>>>>>> color >>>>>>>>>> will >>>>>>>>>> saturate at the max. Sometimes we'll use a p-value derived from >>>>>>>>>> the >>>>>>>>>> degrees of freedom and get a corresponding t-value from that, >>>>>>>>>> and >>>>>>>>>> use >>>>>>>>>> that >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> for thresholding. Other times we might just use, say, +/-4.0 >>>>>>>>>>> or >>>>>>>>>>> higher, >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> depending on how big the values get in the data. Usually we'll >>>>>>>>>> use a >>>>>>>>>> symmetric scale (i.e., -x to +x -- rather than different >>>>>>>>>> min/max). >>>>>>>>>> Donna >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>> On 08/11/2010 09:12 AM, Julia Bender wrote: >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>>> Hi Donna, >>>>>>>>>>>> I've just uploaded the two files. >>>>>>>>>>>> Thanks for your help! >>>>>>>>>>>> Julia >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>>> Julia, >>>>>>>>>>>>> It will be easier for me to get my head around your question >>>>>>>>>>>>> if >>>>>>>>>>>>> I >>>>>>>>>>>>> can >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>> get two files: >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>> * T-Map_LH_cCue_Endo.metric_TMap.metric (whatever the final >>>>>>>>>>>>> output >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>> metric was, but NOT the permuted/shuffled tmap file). >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>> * The report named something like *Signicance*.txt >>>>>>>>>>>>> Could you upload those here: >>>>>>>>>>>>> http://pulvinar.wustl.edu/cgi-bin/upload.cgi >>>>>>>>>>>>> My brain would be ever so grateful. >>>>>>>>>>>>> Donna >>>>>>>>>>>>> On 08/11/2010 07:07 AM, Julia Bender wrote: >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>>> Hey everyone, >>>>>>>>>>>>>> I'm a bit confused about how to threshold my T-Maps in >>>>>>>>>>>>>> caret5. >>>>>>>>>>>>>> I >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> created >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> the maps with the following command: >>>>>>>>>>>>>> /usr/local/caret/bin_linux/caret_command >>>>>>>>>>>>>> -metric-statistics-one-sample-t-test $EACHMETRIC >>>>>>>>>>>>>> $FIDUCIAL_COORD >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> $OPEN_TOPO $SURFACE_SHAPE 3 T-Map_$EACHMETRIC -300000.0 2.5 0.10 >>>>>>>>>> 10 1 >>>>>>>>>> 1000 >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> 0 4 >>>>>>>>>>>>>> So I put the negative threshold to -300000 and the positive >>>>>>>>>>>>>> threshold >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> to >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> 2.5. When I look at the resulting Tmap.metric files it gives >>>>>>>>>>>>>> me >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> something >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> like this: >>>>>>>>>>>>>> Filename: T-Map_LH_cCue_Endo.metric_TMap.metric >>>>>>>>>>>>>> Number of Nodes: 73730 >>>>>>>>>>>>>> Number of Columns: 1 >>>>>>>>>>>>>> Column Minimum Maximum Mean Sample >>>>>>>>>>>>>> Dev >>>>>>>>>>>>>> % >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> Positive % Negative Column Name >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> 1 -9.785 6.076 -0.950 >>>>>>>>>>>>>> 2.639 >>>>>>>>>>>>>> 36.234 63.766 T-Values >>>>>>>>>>>>>> As far as I understand, this means the maximum negative T >>>>>>>>>>>>>> value in >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> this >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> metric is -9.785 and the maximum positive T value is 6.076. >>>>>>>>>>>>>> When I >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> open >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> the file in caret though (Color mapping: Auto Scale, Display >>>>>>>>>>>>>> mode: >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> Both, >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> Display Color Bar, Threshold Adjustment:Column: permuted >>>>>>>>>>>>>> T-Values,Threshold type: Column) the bar tells me that my >>>>>>>>>>>>>> maximum >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> negative >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> value is -3.7 and my maximum positive value is 2.6. This >>>>>>>>>>>>>> also >>>>>>>>>>>>>> holds >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> when >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> I >>>>>>>>>>>>>> adjust the thresholds in the fields below to -2 and 2, when >>>>>>>>>>>>>> almost >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>> all >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>>>>>> activation disappears. >>>>>>>>>>>>>> Which is the correct information? >>>>>>>>>>>>>> Thanks a lot for your help! >>>>>>>>>>>>>> Julia >>>>>>>>>>>>>> Dipl. Psych. Julia Bender >>>>>>>>>>>>>> Humboldt Universität zu Berlin >>>>>>>>>>>>>> Mathematisch - Naturwissenschaftliche Fakultät II >>>>>>>>>>>>>> Institut für Psychologie, Abt. Klinische Psychologie >>>>>>>>>>>>>> Unter den Linden 6 >>>>>>>>>>>>>> D-10099 Berlin >>>>>>>>>>>>>> >> >> _______________________________________________ >> caret-users mailing list >> [email protected] >> http://brainvis.wustl.edu/mailman/listinfo/caret-users >> > > > Dipl. Psych. Julia Bender > Humboldt Universit�t zu Berlin > Mathematisch - Naturwissenschaftliche Fakult�t II > Institut f�r Psychologie, Abt. Klinische Psychologie > Unter den Linden 6 > D-10099 Berlin > > _______________________________________________ > caret-users mailing list > [email protected] > http://brainvis.wustl.edu/mailman/listinfo/caret-users > _______________________________________________ caret-users mailing list [email protected] http://brainvis.wustl.edu/mailman/listinfo/caret-users
