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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