[FieldTrip] Cluster based statistics on channel-channel-freq connectivity
tibor.auer at gmail.com
tibor.auer at gmail.com
Mon Sep 11 11:23:39 CEST 2023
Hi all,
In our recent paper
(https://urldefense.com/v3/__https://www.biorxiv.org/content/10.1101/2023.08.26.554888v2__;!!HJOPV4FYYWzcc1jazlU!94pz4Qiijp2VeSRYpmOrauMINch96GBkT2eYdC33QTyudtuTj54NOwu8XGJgqGYHBuz0TDbkzaBNfbW-BipRmwIU$ ), we used a
graph-based approach to define neighbourhood for connectivity. The code is
implemented in Automatic Analysis (https://urldefense.com/v3/__https://automaticanalysis.github.io__;!!HJOPV4FYYWzcc1jazlU!94pz4Qiijp2VeSRYpmOrauMINch96GBkT2eYdC33QTyudtuTj54NOwu8XGJgqGYHBuz0TDbkzaBNfbW-BjD6JY4c$ ).
Kind regards,
Tibor
Dr Tibor Auer, MD, PhD, FHEA
<mailto:tibor.auer at gmail.com> tibor.auer at gmail.com
+44-7906-863837
<https://urldefense.com/v3/__http://www.linkedin.com/in/tibor-auer__;!!HJOPV4FYYWzcc1jazlU!94pz4Qiijp2VeSRYpmOrauMINch96GBkT2eYdC33QTyudtuTj54NOwu8XGJgqGYHBuz0TDbkzaBNfbW-BrrYl017$ > LinkedIn: tibor-auer
From: fieldtrip <fieldtrip-bounces at science.ru.nl> On Behalf Of Michael
Glassen via fieldtrip
Sent: Thursday, August 31, 2023 10:11 PM
To: FieldTrip discussion list <fieldtrip at science.ru.nl>
Cc: Michael Glassen <mglassen at shp.rutgers.edu>
Subject: Re: [FieldTrip] Cluster based statistics on channel-channel-freq
connectivity
Just wanted to add some further information, I ran cluster statistics on my
connectivity data(32 subjects, 2 timepoints each, conn matrices were
246Channel_246Channel_4Freq(alphaband)). I ran this without a neighbors
file, and got 3 clusters with p<.05, with num randomization at 100 for
exploratory purposes. These clusters were all similar in that the first
channel dimension was the same across the cluster, the second channel
dimension were different channels but sequential, and the frequencys were
variable. I pasted the results below:
stat.posclusters(1)
ans =
struct with fields:
prob: 0.0099
clusterstat: 136.6784
stddev: 0.0099
cirange: 0.0194
[x y z] = findND(stat.posclusterslabelmat == 1); %findND works the same as
matlab builtin find, but works on matrices and returns the indices for each
dimension
x =
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
129
y
y =
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
28
42
44
46
50
53
54
z
z =
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
Best,
Michael Glassen
_____
From: fieldtrip <fieldtrip-bounces at science.ru.nl
<mailto:fieldtrip-bounces at science.ru.nl> > on behalf of Michael Glassen via
fieldtrip <fieldtrip at science.ru.nl <mailto:fieldtrip at science.ru.nl> >
Sent: Thursday, August 31, 2023 3:16 PM
To: fieldtrip at science.ru.nl <mailto:fieldtrip at science.ru.nl>
<fieldtrip at science.ru.nl <mailto:fieldtrip at science.ru.nl> >
Cc: Michael Glassen <mglassen at shp.rutgers.edu
<mailto:mglassen at shp.rutgers.edu> >
Subject: [FieldTrip] Cluster based statistics on channel-channel-freq
connectivity
Hi all,
I wanted to know if it was valid to run cluster based statistics on
connectomes created using ft_connectivity analysis on source data generated
from ft_virtualchannel. This gives me a connectome with
channel_channel_frequency dimensions. If this is valid, I was wondering how
neighbors would work. I created a neighbor file for the atlas I'm using that
works on power cluster statistics, but I'm unsure how this translates to
connectome now that there are channel pairs. I was thinking of editing the
connectome to be channelpair_frequency, and creating a neighbor file at the
channel pair level. If neither of these neighbor approaches work, would it
be valid to run stats without a neighbor file(clustering only based on
frequency)? Any input would be appreciated!
Best,
Michael Glassen
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