Hey Donna,
when I load a metric-file onto my surface, that according to
TMap*SignificantClusters* has NO clusters passing the corrected signifance
threshold and do the procedure you described below ("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."), I can see remaining clusters in
some cases. What does that mean? What happens exactly when I press "remove
islands" here?
Thanks for your help!
Julia
> 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
>
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
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