# permutation clustering test using TFCE
**URL:** https://mne.discourse.group/t/permutation-clustering-test-using-tfce/769
**Category:** Mailing List Archive (read-only)
**Tags:** list-archive
**Created:** [July 31, 2014, 8:03am UTC](https://mne.discourse.group/t/permutation-clustering-test-using-tfce/769 "2014-07-31T08:03:37Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@system](https://mne.discourse.group/u/system)
#### Post date: [July 31, 2014, 8:03am UTC](https://mne.discourse.group/t/permutation-clustering-test-using-tfce/769/1 "2014-07-31T08:03:37Z")
Hi Denis,
I tried the spatio-temporal clustering with TFCE
(spatio\_temporal\_cluster\_1samp\_test) on alpha power data (size of epoch :
2s; decimation = 4 (so 501 time points)) with n\_jobs = 6 and the default
TFCE parameter (dict(start = 0, step = 0.2)).
According to script output, 48 thresholds were used from 0 to 9.4.
After 5h (!!), 10262484 clusters were found and finally after some others
hours the script crashed before the end ("cannot allocate memory")...
I tried on shorter data (1s so 250 time points) but it was also too long
and too memory-demanding. Then I tried to change the step parameter to
decrease the number of thresholds to test. I took step =0.5. 17 thresholds
were used from 0 to 8. 5121000 clusters were found and my script also ended
up crashing. So... what do you suggest to get acceptable computation time?
By the way, with p\_threshold =0.001, I got no cluster; with p\_threshold
=0.01, I got one occipito-parietal cluster (pvalue = 0.026) lasting around
500ms, after something about 10min of computation.
Hoping that it is useful for you,
Best,
Laetitia G.
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### Author:  [@system](https://mne.discourse.group/u/system)
#### Post date: [July 31, 2014, 1:14pm UTC](https://mne.discourse.group/t/permutation-clustering-test-using-tfce/769/2 "2014-07-31T13:14:01Z")
Thanks Latitia,
> Hi Denis,
>
> I tried the spatio-temporal clustering with TFCE
(spatio\_temporal\_cluster\_1samp\_test) on alpha power data (size of epoch :
2s; decimation = 4 (so 501 time points)) with n\_jobs = 6 and the default
TFCE parameter (dict(start = 0, step = 0.2)).
I think we need to improve the documentation on TFCE a bit. A good default
range is probably
dict(start=2, step=0.2)
> According to script output, 48 thresholds were used from 0 to 9.4.
> After 5h (!!), 10262484 clusters were found and finally after some others
hours the script crashed before the end ("cannot allocate memory")...
>
For TFCE N clusters equals N features. Howver if you do not scan the enitre
range of the test statistic you wont have to wait thast long.
> I tried on shorter data (1s so 250 time points) but it was also too long
and too memory-demanding. Then I tried to change the step parameter to
decrease the number of thresholds to test. I took step =0.5. 17 thresholds
were used from 0 to 8. 5121000 clusters were found and my script also ended
up crashing. So... what do you suggest to get acceptable computation time?
>
See above. Btw for roughtly 10.000 clusters with 15-20 thresholds I'm
waiting for roughly 15-20 minutes per iteration (multiple iterations with
step\_down=0.05).
> By the way, with p\_threshold =0.001, I got no cluster; with p\_threshold
=0.01, I got one occipito-parietal cluster (pvalue = 0.026) lasting around
500ms, after something about 10min of computation.
>
I'm not sure what you refer to by `p_threshold`. Either you pass a dict or
a float. The latter will be a classical cluster permuation analysis, the
former TFCE.
You can howver use the p\_threhold as start value for TFCE.
> Hoping that it is useful for you,
> Best,
> Laetitia G.
Yes, thanks!
Best,
Denis
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