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 T-Map*TMapClusters.metric 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
