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help > RE: Graph-theory in conn
Jul 11, 2012 02:07 AM | Alfonso Nieto-Castanon - Boston University
RE: Graph-theory in conn
Hi Igor,
Regarding the question about second-level contrasts, you are exactly right, you would first create (in Setup->Covariates->Second-level) one 'Control' (set to [1 1 0 0]) and one 'Patient' (set to [0 0 1 1]) covariate. Then, when defining the contrasts of interest (in the Results tab) you would select both your 'Control' and 'Patient' effects in the 'Subject effects' list, and enter in 'between-subject contrast' [1,-1] (if you want to estimate the differences between control and patients). If you have a single condition (e.g. 'rest') you would simply select it from the 'conditions' list (and enter simply 1 in the 'between-conditions' contrast), and similarly if you have a single seed ROI (e.g. for seed-to-voxel analyses) you would select that and enter simply 1 in the corresponding contrast field.
Regarding the atlas files, there are two formats of the associated .txt files that can be entered to conn:
1) [ROI_label]: as you described, you simply enter in order all of the labels in the atlas (the one in the first row of the .txt file will correspond to the areas in the .nii file labeled as '1', the label in the second row will correspond to the areas labeled as '2', etc.)
2) [ROI_number ROI_label]: you can also enter pairs of numbers/labels (separated by a whitespace or a tab) and, for each pair, conn will associate the areas in the .nii file labeled as 'ROI_number' value with the associated 'ROI_label' string.
In addition you can also use (instead of a .txt file) a .csv file (comma-separated file) or .xls file (excel format) using the same convention as the case (2) above (two columns, the first with ROI numbers and the second with ROI labels).
In any way, if you are interested you can also find the AAL atlas (relabeled to this format) in the standard distribution of conn under the directory conn/utils/otherrois/ (the files named aal.nii and aal.txt)
Hope this helps
Alfonso
Originally posted by Igor M:
Regarding the question about second-level contrasts, you are exactly right, you would first create (in Setup->Covariates->Second-level) one 'Control' (set to [1 1 0 0]) and one 'Patient' (set to [0 0 1 1]) covariate. Then, when defining the contrasts of interest (in the Results tab) you would select both your 'Control' and 'Patient' effects in the 'Subject effects' list, and enter in 'between-subject contrast' [1,-1] (if you want to estimate the differences between control and patients). If you have a single condition (e.g. 'rest') you would simply select it from the 'conditions' list (and enter simply 1 in the 'between-conditions' contrast), and similarly if you have a single seed ROI (e.g. for seed-to-voxel analyses) you would select that and enter simply 1 in the corresponding contrast field.
Regarding the atlas files, there are two formats of the associated .txt files that can be entered to conn:
1) [ROI_label]: as you described, you simply enter in order all of the labels in the atlas (the one in the first row of the .txt file will correspond to the areas in the .nii file labeled as '1', the label in the second row will correspond to the areas labeled as '2', etc.)
2) [ROI_number ROI_label]: you can also enter pairs of numbers/labels (separated by a whitespace or a tab) and, for each pair, conn will associate the areas in the .nii file labeled as 'ROI_number' value with the associated 'ROI_label' string.
In addition you can also use (instead of a .txt file) a .csv file (comma-separated file) or .xls file (excel format) using the same convention as the case (2) above (two columns, the first with ROI numbers and the second with ROI labels).
In any way, if you are interested you can also find the AAL atlas (relabeled to this format) in the standard distribution of conn under the directory conn/utils/otherrois/ (the files named aal.nii and aal.txt)
Hope this helps
Alfonso
Originally posted by Igor M:
Thanks a lot, Alfonso!
I am not sure what I had the cost function set to last time, but I bumped it up to 0.4 and got a nice ".network" file with all the measures. Your help was very valuable.
One more question.
(1) If I do want to compare measures between groups, should I set the contrasts to the following:
Between-subjects: [1, -1]
Between-conditions: 1
Between-sources: 1
Additionally, I would also need second-level covariates called "Control" and "Patient" and these should be set to [1 1 0 0] and [0 0 1 1] for four participants who are [Control, Control, Patient, Patient].
Is this correct? I think it should be, but don't want to incorrectly assume anything.
- IM
EDIT:
One more question.
How can I use the AAL template provided here with conn? When using the "ROI_MNI_V4.nii" file there is an error message saying that "ROI_MNI_V4.txt" is not in the correct format.
How exactly should the label file be formatted?
I tried to figure out the correct formatting based on BA.txt but couldn't.
1 (L). Primary Somatosensory Cortex
1 (R). Primary Somatosensory Cortex
10 (L). Anterior Prefrontal Cortex
10 (R). Anterior Prefrontal Cortex
What do the numbers in the left column match up with? There are no voxels with those values in BA.img.
EDIT#2: I think I figured it out. Is the labeling based on line number within BA.txt (i.e. (L)Primary Somatosensory Cortex has a voxel intensity of 1, (R)Primary Somatosensory Cortex has a voxel intensity of 2, (L). Anterior Prefrontal Cortex is 3)?
Do you have a correctly labeled AAL template? It would save me a lot of time if I could avoid having to relabel all 90 regions.
Thanks!!
Originally posted by Alfonso Nieto-Castanon:
I am not sure what I had the cost function set to last time, but I bumped it up to 0.4 and got a nice ".network" file with all the measures. Your help was very valuable.
One more question.
(1) If I do want to compare measures between groups, should I set the contrasts to the following:
Between-subjects: [1, -1]
Between-conditions: 1
Between-sources: 1
Additionally, I would also need second-level covariates called "Control" and "Patient" and these should be set to [1 1 0 0] and [0 0 1 1] for four participants who are [Control, Control, Patient, Patient].
Is this correct? I think it should be, but don't want to incorrectly assume anything.
- IM
EDIT:
One more question.
How can I use the AAL template provided here with conn? When using the "ROI_MNI_V4.nii" file there is an error message saying that "ROI_MNI_V4.txt" is not in the correct format.
How exactly should the label file be formatted?
I tried to figure out the correct formatting based on BA.txt but couldn't.
1 (L). Primary Somatosensory Cortex
1 (R). Primary Somatosensory Cortex
10 (L). Anterior Prefrontal Cortex
10 (R). Anterior Prefrontal Cortex
What do the numbers in the left column match up with? There are no voxels with those values in BA.img.
EDIT#2: I think I figured it out. Is the labeling based on line number within BA.txt (i.e. (L)Primary Somatosensory Cortex has a voxel intensity of 1, (R)Primary Somatosensory Cortex has a voxel intensity of 2, (L). Anterior Prefrontal Cortex is 3)?
Do you have a correctly labeled AAL template? It would save me a lot of time if I could avoid having to relabel all 90 regions.
Thanks!!
Originally posted by Alfonso Nieto-Castanon:
Hi Igor,
You are right that the 'results' tab is for second-level analyses (to perform inferences about the population) so it requires multiple subjects. In any particular analysis, beta values represent effect sizes, T-values are the statistics, p-unc represent the false positive level of each individual test, and p-FDR represents the false discovery rate (a correction of the false positive level to account for multiple comparisons). All of these values depend on the actual contrasts that you choose for your second-level analyses. If you want to explore manually the graph-theory measures (e.g. global efficiency) for each subject 'export data' will create a .csv and a .network file with this information (the .network file can be loaded directly from matlab; the only reason I can think that would result in this files being 'empty' would be if you are using an overly conservative adjacency matrix threshold). If you want to explore the ROI-to-ROI connectivity matrix manually question 14 in the FAQ (http://www.alfnie.com/software/conn) should point you in the right direction.
Hope this helps
Alfonso
Originally posted by Igor M:
You are right that the 'results' tab is for second-level analyses (to perform inferences about the population) so it requires multiple subjects. In any particular analysis, beta values represent effect sizes, T-values are the statistics, p-unc represent the false positive level of each individual test, and p-FDR represents the false discovery rate (a correction of the false positive level to account for multiple comparisons). All of these values depend on the actual contrasts that you choose for your second-level analyses. If you want to explore manually the graph-theory measures (e.g. global efficiency) for each subject 'export data' will create a .csv and a .network file with this information (the .network file can be loaded directly from matlab; the only reason I can think that would result in this files being 'empty' would be if you are using an overly conservative adjacency matrix threshold). If you want to explore the ROI-to-ROI connectivity matrix manually question 14 in the FAQ (http://www.alfnie.com/software/conn) should point you in the right direction.
Hope this helps
Alfonso
Originally posted by Igor M:
It looks like I solved the above problem by
running an analysis with 2 participants instead of just 1.
Results are now showing up in the "Network theory" window.
My question now is how to interpret these.
What are the "beta, T, p-unc, and p-FDR" values related to?
Are these based on the contrast that was set up in the "second-level Results" window?
What if I just want to look at the Global efficiency of a network based on all nodes and don't want a group contrast?
How do you display the actual parameters (i.e. actual "global efficiency")?
How do you display the correlation matrix between ROIs?
"Export data" creates one .csv file and a .dl file per subject, but these files are all empty for some reason.
Any help would be greatly appreciated.
Results are now showing up in the "Network theory" window.
My question now is how to interpret these.
What are the "beta, T, p-unc, and p-FDR" values related to?
Are these based on the contrast that was set up in the "second-level Results" window?
What if I just want to look at the Global efficiency of a network based on all nodes and don't want a group contrast?
How do you display the actual parameters (i.e. actual "global efficiency")?
How do you display the correlation matrix between ROIs?
"Export data" creates one .csv file and a .dl file per subject, but these files are all empty for some reason.
Any help would be greatly appreciated.
Threaded View
| Title | Author | Date |
|---|---|---|
| Igor M | Jul 9, 2012 | |
| Igor M | Jul 9, 2012 | |
| Alfonso Nieto-Castanon | Jul 10, 2012 | |
| Igor M | Jul 10, 2012 | |
| Alfonso Nieto-Castanon | Jul 11, 2012 | |
| Saman Sarraf | Jan 21, 2014 | |
| Igor M | Jul 12, 2012 | |
| Alfonso Nieto-Castanon | Jul 13, 2012 | |
| Igor M | Jul 21, 2012 | |
| Alfonso Nieto-Castanon | Jul 21, 2012 | |