I am analysisng resting state fMRI images. After denoising level in CONN toolbox I am not getting QA plots. On QA plots it is written "no QA project available". Kindly help me out with this.
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Difficulty in getting QA plots
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RE: Pediatric Template
Dear Alfonso and colleagues,
Sorry to post in such an old topic, but I have an additional question regarding pediatric templates so I figured I might as well ask it here. It may help someone in the future too.
So, we're also analyzing data from children (7-9 years), and we want to combine VBM and rsfMRI. To do this, we would like to make sure structural and functional data are all in the same space, more specifically, normalized to DARTEL template that we have created using age-appropriate TPM's from the template-o-matic toolbox. In your first response to this topic, you mentioned that a DARTEL template would be a good approach for normalization in infants, so I'm trying to implement it in conn toolbox.
From your previous responses to John, I get that SPM8 requires a T1 template, and SPM12 a TPM. How can we go about doing indirect normalization to a DARTEL template?
(hope this is not a trivial question, I'm not much of a SPM user).
Best regards
Paulo
Sorry to post in such an old topic, but I have an additional question regarding pediatric templates so I figured I might as well ask it here. It may help someone in the future too.
So, we're also analyzing data from children (7-9 years), and we want to combine VBM and rsfMRI. To do this, we would like to make sure structural and functional data are all in the same space, more specifically, normalized to DARTEL template that we have created using age-appropriate TPM's from the template-o-matic toolbox. In your first response to this topic, you mentioned that a DARTEL template would be a good approach for normalization in infants, so I'm trying to implement it in conn toolbox.
From your previous responses to John, I get that SPM8 requires a T1 template, and SPM12 a TPM. How can we go about doing indirect normalization to a DARTEL template?
(hope this is not a trivial question, I'm not much of a SPM user).
Best regards
Paulo
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compute effect size from F test 2nd level analysis
Dear expert,
we have used CONN for our resting state fMRI and anxiety relationship paper, and got the reviews back asking to clarify the 2nd level analysis and also to compute effect size for reported F stats.
It's a 2 seeds (left, right amygdala) FC maps per subjects enter into the 2nd level model, with motion gender as covariate of not interests, and with anxiety as covariate of interest. And we did an "OR" contrast, so eyes(2) for seed/source, and [0 0 1] for between subjects variable with anxiety as 1.
Can we say what's truly happening in 2nd level is a GLM as following?
[u]Both left and right amygdala were entered into one combined GLM model in CONN. It's an F-test using an 'eye(2)' contrast which tests an OR conjunction of the left [1 0 ] and right [0 1] amygdala contrasts, to identify areas where the connectivity with any of the seed regions (left or right) is correlated with anxiety.[/u]
Also they asks to report the Effect Size from the F test, we obtained F(2,150)=14.5 from the CONN 2nd level GUI, is there a way to do offline analysis to obtain the ROI's effect size towards anxiety ?
I tried to extract ROI value from both left and right amygdala separately, and then do a FC~seed +anxiety + motion + gender using mixed linear model, but the F value here is totally different and with totally different df. so I assume CONN computed the F stats very differently?
Can you explain how it's computed in CONN the F stats?
Thank you!!
Xiaozhen You
we have used CONN for our resting state fMRI and anxiety relationship paper, and got the reviews back asking to clarify the 2nd level analysis and also to compute effect size for reported F stats.
It's a 2 seeds (left, right amygdala) FC maps per subjects enter into the 2nd level model, with motion gender as covariate of not interests, and with anxiety as covariate of interest. And we did an "OR" contrast, so eyes(2) for seed/source, and [0 0 1] for between subjects variable with anxiety as 1.
Can we say what's truly happening in 2nd level is a GLM as following?
[u]Both left and right amygdala were entered into one combined GLM model in CONN. It's an F-test using an 'eye(2)' contrast which tests an OR conjunction of the left [1 0 ] and right [0 1] amygdala contrasts, to identify areas where the connectivity with any of the seed regions (left or right) is correlated with anxiety.[/u]
Also they asks to report the Effect Size from the F test, we obtained F(2,150)=14.5 from the CONN 2nd level GUI, is there a way to do offline analysis to obtain the ROI's effect size towards anxiety ?
I tried to extract ROI value from both left and right amygdala separately, and then do a FC~seed +anxiety + motion + gender using mixed linear model, but the F value here is totally different and with totally different df. so I assume CONN computed the F stats very differently?
Can you explain how it's computed in CONN the F stats?
Thank you!!
Xiaozhen You
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Minimum cluster size for FDR cluster-level correction
Hello!
Foremost, I apologize if this is a repeat question, but I was wondering whether there was a straightforward way to determine the minimum cluster size necessary to generate a p<.001 height threshold and p<.05 FDR cluster-level-corrected brain map. Would greatly appreciate any guidance!
Many thanks!
Ted
Foremost, I apologize if this is a repeat question, but I was wondering whether there was a straightforward way to determine the minimum cluster size necessary to generate a p<.001 height threshold and p<.05 FDR cluster-level-corrected brain map. Would greatly appreciate any guidance!
Many thanks!
Ted
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Repetition of file prepending
I have been running some fMRI data in the Conn toolbox. After realizing that I'd made a mistake the first time around, I re-ran my entire analysis from pre-processing to first-level analysis. I've noticed that the project is taking up a TON of space on my hard drive. When I looked down into the folders, I have files that don't look quite right. For instance, I have files that are prepended "swauswauswaurest". It seems that these files have been re-analyzed too many times. Is this correct? What is the appropriate prepending of the files that are ultimately used in the analysis (i.e., "swaurest")? Which files are used by Conn in the my current analyses? Can I delete any of the previous files to make space on my hard drive? Please let me know. Thanks!
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Using both time and frequency decomposition?
Hello,
I've been using the time decomposition (for sliding window dFC) and frequency decomposition (for applying various bandpass filters) in CONN, and I was simply wondering if there was a way to use both at the same time, e.g. to perform sliding window dFC at two different frequency bands? I am running CONN using the batch scripting functionality. It wouldn't be a huge problem to just run the processing twice, once with each bandpass filter, but it would be nice to save some processing time by doing it all together.
Thanks,
Kevin
I've been using the time decomposition (for sliding window dFC) and frequency decomposition (for applying various bandpass filters) in CONN, and I was simply wondering if there was a way to use both at the same time, e.g. to perform sliding window dFC at two different frequency bands? I am running CONN using the batch scripting functionality. It wouldn't be a huge problem to just run the processing twice, once with each bandpass filter, but it would be nice to save some processing time by doing it all together.
Thanks,
Kevin
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covariates (of interest and control) set-up
Hello,
Please can you advise whether I have set up covariates correctly for a GLM 2nd level analysis.
Covariates of interest:
AllSubjects [1,1,1,1,1....1,1,1]
Patients [1,1,1,1.......0,0,0]
Controls [0,0,0,0.......1,1,1]
Test_1 [-6.75, 0.18, -4.25.....]
Test_2 [-0.63, 0.92, -1.46,.....]
Control covariates:
Age (demeaned) [3.16, 10.16, -9.56.....]
Education (demeaned) [-0.33, 4.66, -2.33,....]
Gender [-0.5, -0.5, 0.5, 0.5,....]
All covariates also have a sub-group version e.g. Test_1_Patients, Gender_Controls.
Question 1:
The test scores, for each test, are normalised based on a population sample matched for education, gender & age (i.e., the score for person 1 and person 2 may have been normalised based on different populations. Formula score - population mean / population SD). In this case zero is meaningful. Do these need to be further normalised at a whole group level?
Question 2:
Are the control convariates set up correctly? I have read conflicting items on how to set up gender.
Question 3:
I have selected semi-partial correlations for ROI-to-ROI investigation.
One analysis is set up as:
Test_1_Controls > Test_1_Patients; one-sided positive
[0,0, -1, 1, 0, 0, 0] referring to [Patients, Controls, Test_1_Patients, Test_1_Controls, Gender, Age, Education]
Is it correct to say that this set up is testing whether in relation to Test_1 controls show higher ROI-to-ROI functional connectivity compared to patients while controlling for gender, age and education?
Thank you in advance for any assistance.
Therese
Please can you advise whether I have set up covariates correctly for a GLM 2nd level analysis.
Covariates of interest:
AllSubjects [1,1,1,1,1....1,1,1]
Patients [1,1,1,1.......0,0,0]
Controls [0,0,0,0.......1,1,1]
Test_1 [-6.75, 0.18, -4.25.....]
Test_2 [-0.63, 0.92, -1.46,.....]
Control covariates:
Age (demeaned) [3.16, 10.16, -9.56.....]
Education (demeaned) [-0.33, 4.66, -2.33,....]
Gender [-0.5, -0.5, 0.5, 0.5,....]
All covariates also have a sub-group version e.g. Test_1_Patients, Gender_Controls.
Question 1:
The test scores, for each test, are normalised based on a population sample matched for education, gender & age (i.e., the score for person 1 and person 2 may have been normalised based on different populations. Formula score - population mean / population SD). In this case zero is meaningful. Do these need to be further normalised at a whole group level?
Question 2:
Are the control convariates set up correctly? I have read conflicting items on how to set up gender.
Question 3:
I have selected semi-partial correlations for ROI-to-ROI investigation.
One analysis is set up as:
Test_1_Controls > Test_1_Patients; one-sided positive
[0,0, -1, 1, 0, 0, 0] referring to [Patients, Controls, Test_1_Patients, Test_1_Controls, Gender, Age, Education]
Is it correct to say that this set up is testing whether in relation to Test_1 controls show higher ROI-to-ROI functional connectivity compared to patients while controlling for gender, age and education?
Thank you in advance for any assistance.
Therese
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Non-parametric MVPA. Clarification
Dear Alfonso,
Following your suggestions in previous threads and impressed by recent debates regarding parametric vs non-parametric inferences (Eklund et al), I re-run my MVPA (5 components, 21 subjects, testing for condition A vs condition B) using non-parametric approach.
I have a couple of questions regarding the non-parametric approach that could, possibly, be also interested for other CONN users:
1. Does the permutation test in CONN estimate the null distribution for one side? I am a bit confused as the option 'two-sided' appears as default (please, see the screenshot attached). Please, correct me if I am wrong. The permutation approach will flip my labels (2Λ21 in my case), calculate a range of t-tests and then using max stats estimate the 5% threshold (this threshold we will apply then to our original map of t-tests). If this is what CONN does, what the 'two-sided' option means?
2. On the top of the screen, CONN displays F-stats for non-parametric. What are these degree of freedom? I am not sure how to interpret the F-value (please, see the screenshot).
3. Whether CONN uses smoothing for the variance of t-tests?
Thank you
alla
Following your suggestions in previous threads and impressed by recent debates regarding parametric vs non-parametric inferences (Eklund et al), I re-run my MVPA (5 components, 21 subjects, testing for condition A vs condition B) using non-parametric approach.
I have a couple of questions regarding the non-parametric approach that could, possibly, be also interested for other CONN users:
1. Does the permutation test in CONN estimate the null distribution for one side? I am a bit confused as the option 'two-sided' appears as default (please, see the screenshot attached). Please, correct me if I am wrong. The permutation approach will flip my labels (2Λ21 in my case), calculate a range of t-tests and then using max stats estimate the 5% threshold (this threshold we will apply then to our original map of t-tests). If this is what CONN does, what the 'two-sided' option means?
2. On the top of the screen, CONN displays F-stats for non-parametric. What are these degree of freedom? I am not sure how to interpret the F-value (please, see the screenshot).
3. Whether CONN uses smoothing for the variance of t-tests?
Thank you
alla
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Atrophy correction
Hi,
I am conducting seed-based analyses with between-group comparisons.
Given the fact that I work with neurodegenerative patients, one of the reviewer has required gray matter atrophy correction. I have a few questions and any advice could help:
1) is it possible on CONN and has anyone ever tried it?
2) what are the best approaches? a voxel-wise correction using Biological Parametric Mapping? using total GM volume or GM volume in my seed ROI as a covariate?
If anyone has references to suggest me, that would be great!
Thanks!
I am conducting seed-based analyses with between-group comparisons.
Given the fact that I work with neurodegenerative patients, one of the reviewer has required gray matter atrophy correction. I have a few questions and any advice could help:
1) is it possible on CONN and has anyone ever tried it?
2) what are the best approaches? a voxel-wise correction using Biological Parametric Mapping? using total GM volume or GM volume in my seed ROI as a covariate?
If anyone has references to suggest me, that would be great!
Thanks!
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Atlas visualization
Hi,
Is there a way to display selected ROIs from the default CONN atlas (HOA/AAL) on a surface for visualization purposes?
I noticed something similar in jpegs of the atlas in the CONN ROI folder.
Cheers
Emmanuel
Is there a way to display selected ROIs from the default CONN atlas (HOA/AAL) on a surface for visualization purposes?
I noticed something similar in jpegs of the atlas in the CONN ROI folder.
Cheers
Emmanuel
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RE: Questions about Harvard-Oxford Subcortical parcellation used for Conn toolbox
I am also curious about the atlas built-in CONN toolbox.
Could somebody give me a label or index of the atlas in COON?
Because I'd like to select specific brain regions to be as a new ROI
Thank you very much
Could somebody give me a label or index of the atlas in COON?
Because I'd like to select specific brain regions to be as a new ROI
Thank you very much
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ERROR in checking ROI data consistency across subjects: Undefined function or variable 'ROInamesall'
Hi,
While checking ROI data consistency across subjects (SETUP; step 6/7) I get the following error:
Undefined function or variable 'ROInamesall'.
Error in conn_process (line 901)
if ~anyissue, anyissue=~isequal(ROInamesall,names); end
Error in conn_process (line 16)
case 'setup', disp(['CONN: RUNNING SETUP STEP']); conn_process([0:4,4.5,5]);
Error in conn (line 4447)
else conn_process('setup'); ispending=false;
Error in conn_menumanager (line 120)
I have no idea what it means. I am completely new to CONN. I would really appreciate your help.
Thank you,
Joanna
While checking ROI data consistency across subjects (SETUP; step 6/7) I get the following error:
Undefined function or variable 'ROInamesall'.
Error in conn_process (line 901)
if ~anyissue, anyissue=~isequal(ROInamesall,names); end
Error in conn_process (line 16)
case 'setup', disp(['CONN: RUNNING SETUP STEP']); conn_process([0:4,4.5,5]);
Error in conn (line 4447)
else conn_process('setup'); ispending=false;
Error in conn_menumanager (line 120)
I have no idea what it means. I am completely new to CONN. I would really appreciate your help.
Thank you,
Joanna
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registration issue: ROI outside functional image
Hello,
I am doing a seed-based analysis based on ROIs previously defined (in MNI space) for specific regions of S1. For several subjects, these ROIs fall outside, or only partially inside, the brain following direct normalization. No fieldmaps or topups for distortion correction are available, but I tried a few different variations of using flirt and fnirt to use the anatomical images for each subject to register the functional images indirectly to MNI space. However this did not yield much better results, perhaps because I was using the wc0* images? (As far as I can tell CONN does not create skull stripped images in the native anatomical space). If anyone has any suggestions please let me know. I've attached a screenshot to give an example of the seed falling partially outside of the brain.
Best,
- Harris
I am doing a seed-based analysis based on ROIs previously defined (in MNI space) for specific regions of S1. For several subjects, these ROIs fall outside, or only partially inside, the brain following direct normalization. No fieldmaps or topups for distortion correction are available, but I tried a few different variations of using flirt and fnirt to use the anatomical images for each subject to register the functional images indirectly to MNI space. However this did not yield much better results, perhaps because I was using the wc0* images? (As far as I can tell CONN does not create skull stripped images in the native anatomical space). If anyone has any suggestions please let me know. I've attached a screenshot to give an example of the seed falling partially outside of the brain.
Best,
- Harris
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RE: denoising
Dear expert:
i have meet the same errors in the step of denosing(1st-level). the interface shows my conn is version of 18.a,and spm is 8. there are my errors which i have met: ERROR DESCRIPTION:
Undefined function 'eq' for input arguments of type 'struct'.
Error in conn_menumanager>@(x)any(x==varargin{1}) (line 327)
idx=find(cellfun(@(x)any(x==varargin{1}),CONN_MM.onregionhandle));
Error in conn_menumanager (line 327)
idx=find(cellfun(@(x)any(x==varargin{1}),CONN_MM.onregionhandle));
Error in conn_menu (line 535)
conn_menumanager('onregionremove',position.h5);
Error in conn (line 4872)
conn_menu('update',CONN_h.menus.m_preproc_00{3},[]);
Error in conn (line 4451)
if ~conn_projectmanager('ispending')&&~ispending, conn gui_preproc;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.17.a
SPM8 + Beamforming DEM FieldMap MEEGtools vbm8
Matlab v.2014a
storage: 17.7Gb available
spm @ E:\Toolbox\Toolbox\spm8\spm8
conn @ E:\Toolbox\conn
i have meet the same errors in the step of denosing(1st-level). the interface shows my conn is version of 18.a,and spm is 8. there are my errors which i have met: ERROR DESCRIPTION:
Undefined function 'eq' for input arguments of type 'struct'.
Error in conn_menumanager>@(x)any(x==varargin{1}) (line 327)
idx=find(cellfun(@(x)any(x==varargin{1}),CONN_MM.onregionhandle));
Error in conn_menumanager (line 327)
idx=find(cellfun(@(x)any(x==varargin{1}),CONN_MM.onregionhandle));
Error in conn_menu (line 535)
conn_menumanager('onregionremove',position.h5);
Error in conn (line 4872)
conn_menu('update',CONN_h.menus.m_preproc_00{3},[]);
Error in conn (line 4451)
if ~conn_projectmanager('ispending')&&~ispending, conn gui_preproc;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.17.a
SPM8 + Beamforming DEM FieldMap MEEGtools vbm8
Matlab v.2014a
storage: 17.7Gb available
spm @ E:\Toolbox\Toolbox\spm8\spm8
conn @ E:\Toolbox\conn
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Examining carryover/order effects in a cross-over design
Dear Alfonso and CONN community,
I'm analyzing the resting-state data from my study, in which each participant underwent 2 scans X 2 conditions.
This means that I my conditions are: Pre_Real, Pre_Sham, Post_Real, and Post_Sham.
Accordingly, I defined my repeated-measures ANOVA: AllSubjects [1], and Pre_Real, Pre_Sham, Post_Real, Post_Sham [-1 1 1 -1] (as specified in the CONN manual, p.26).
However, I have a reason to suspect that there might be a carryover effect. Therefore, I decided to perform a paired t-test, comparing only the Pre_Real and Pre_Sham, so I selected only the 2 of them and defined the contrast as [-1 1]. Here, I got some significant results (which is a cause for concern)
Additionally, I have a reason to believe that controlling for the order in which the participants received their treatments - would neutralize the order effect.
To this end, I defined the order effect using 2 second-level dichotomous covariates - Real_first and Sham_first, which are the opposite of each other. I'm not sure that this is the way to do it, though.
Given the experimental design's within-subject nature, I'd like to ask the following questions:
1. Did I define the carryover effect test correctly? or should I instead use the contrast Pre_Real, Pre_Sham, Post_Real, Post_Sham [-1 1 0 0]?
2. How should I define the order effect in order to check for its influence and possible association with the carryover effect?
Sorry for the long post and thanks in advance,
Subtly,
Yuval.
I'm analyzing the resting-state data from my study, in which each participant underwent 2 scans X 2 conditions.
This means that I my conditions are: Pre_Real, Pre_Sham, Post_Real, and Post_Sham.
Accordingly, I defined my repeated-measures ANOVA: AllSubjects [1], and Pre_Real, Pre_Sham, Post_Real, Post_Sham [-1 1 1 -1] (as specified in the CONN manual, p.26).
However, I have a reason to suspect that there might be a carryover effect. Therefore, I decided to perform a paired t-test, comparing only the Pre_Real and Pre_Sham, so I selected only the 2 of them and defined the contrast as [-1 1]. Here, I got some significant results (which is a cause for concern)
Additionally, I have a reason to believe that controlling for the order in which the participants received their treatments - would neutralize the order effect.
To this end, I defined the order effect using 2 second-level dichotomous covariates - Real_first and Sham_first, which are the opposite of each other. I'm not sure that this is the way to do it, though.
Given the experimental design's within-subject nature, I'd like to ask the following questions:
1. Did I define the carryover effect test correctly? or should I instead use the contrast Pre_Real, Pre_Sham, Post_Real, Post_Sham [-1 1 0 0]?
2. How should I define the order effect in order to check for its influence and possible association with the carryover effect?
Sorry for the long post and thanks in advance,
Subtly,
Yuval.
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RE: covariates (of interest and control) set-up
[i]Originally posted by therese1:[/i][quote]Hello Alfonso,
[/quote][quote]I'd love to get your opinion on the questions below. I'd greatly appreciate any help you can offer.[/quote][quote]Many thanks,[/quote][quote]Therese
[/quote][quote]Hello,
Please can you advise whether I have set up covariates correctly for a GLM 2nd level analysis.
Covariates of interest:
AllSubjects [1,1,1,1,1....1,1,1]
Patients [1,1,1,1.......0,0,0]
Controls [0,0,0,0.......1,1,1]
Test_1 [-6.75, 0.18, -4.25.....]
Test_2 [-0.63, 0.92, -1.46,.....]
Control covariates:
Age (demeaned) [3.16, 10.16, -9.56.....]
Education (demeaned) [-0.33, 4.66, -2.33,....]
Gender [-0.5, -0.5, 0.5, 0.5,....]
All covariates also have a sub-group version e.g. Test_1_Patients, Gender_Controls.
Question 1:
The test scores, for each test, are normalised based on a population sample matched for education, gender & age (i.e., the score for person 1 and person 2 may have been normalised based on different populations. Formula score - population mean / population SD). In this case zero is meaningful. Do these need to be further normalised at a whole group level?
Question 2:
Are the control convariates set up correctly? I have read conflicting items on how to set up gender.
Question 3:
I have selected semi-partial correlations for ROI-to-ROI investigation.
One analysis is set up as:
Test_1_Controls > Test_1_Patients; one-sided positive
[0,0, -1, 1, 0, 0, 0] referring to [Patients, Controls, Test_1_Patients, Test_1_Controls, Gender, Age, Education]
Is it correct to say that this set up is testing whether in relation to Test_1 controls show higher ROI-to-ROI functional connectivity compared to patients while controlling for gender, age and education?
Thank you in advance for any assistance.
Therese[/quote]
[/quote][quote]I'd love to get your opinion on the questions below. I'd greatly appreciate any help you can offer.[/quote][quote]Many thanks,[/quote][quote]Therese
[/quote][quote]Hello,
Please can you advise whether I have set up covariates correctly for a GLM 2nd level analysis.
Covariates of interest:
AllSubjects [1,1,1,1,1....1,1,1]
Patients [1,1,1,1.......0,0,0]
Controls [0,0,0,0.......1,1,1]
Test_1 [-6.75, 0.18, -4.25.....]
Test_2 [-0.63, 0.92, -1.46,.....]
Control covariates:
Age (demeaned) [3.16, 10.16, -9.56.....]
Education (demeaned) [-0.33, 4.66, -2.33,....]
Gender [-0.5, -0.5, 0.5, 0.5,....]
All covariates also have a sub-group version e.g. Test_1_Patients, Gender_Controls.
Question 1:
The test scores, for each test, are normalised based on a population sample matched for education, gender & age (i.e., the score for person 1 and person 2 may have been normalised based on different populations. Formula score - population mean / population SD). In this case zero is meaningful. Do these need to be further normalised at a whole group level?
Question 2:
Are the control convariates set up correctly? I have read conflicting items on how to set up gender.
Question 3:
I have selected semi-partial correlations for ROI-to-ROI investigation.
One analysis is set up as:
Test_1_Controls > Test_1_Patients; one-sided positive
[0,0, -1, 1, 0, 0, 0] referring to [Patients, Controls, Test_1_Patients, Test_1_Controls, Gender, Age, Education]
Is it correct to say that this set up is testing whether in relation to Test_1 controls show higher ROI-to-ROI functional connectivity compared to patients while controlling for gender, age and education?
Thank you in advance for any assistance.
Therese[/quote]
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ICA network analysis
Hi,
I am trying to anlayse the resting state in the patient group and healthy control using ICA network analysis...
Using the summary template, it is identifying two DMN networks (eg. ICA_1, ICA_4 seems equally related to DMN)
When I want to explore DMN networks between two groups, should I analyse separate ICA_1 and ICA_4? or can I multi-select two networks for anlaysis?
Also, is it possible to generate lists of regions that each ICA is selecting?
I'd really appreciate of any help!!
I am trying to anlayse the resting state in the patient group and healthy control using ICA network analysis...
Using the summary template, it is identifying two DMN networks (eg. ICA_1, ICA_4 seems equally related to DMN)
When I want to explore DMN networks between two groups, should I analyse separate ICA_1 and ICA_4? or can I multi-select two networks for anlaysis?
Also, is it possible to generate lists of regions that each ICA is selecting?
I'd really appreciate of any help!!
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↧
Threshold masks for aCompCor
Hello,
can I somewhere define the theshold for the WM/CSF masks that are used for signal denoising in CompCor?
If not, would it have a similar effect to choose only one dimesnion of the PCA instead of 5 (or more)?
Thanks in advance!
Nina
can I somewhere define the theshold for the WM/CSF masks that are used for signal denoising in CompCor?
If not, would it have a similar effect to choose only one dimesnion of the PCA instead of 5 (or more)?
Thanks in advance!
Nina
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Reporting a 2*2 RM-Anova using CONN
Hi,
I have 3 groups of participants, and I recorded a resting state 2 times in each participant.
I would like to report an ROI-to-ROI analyses, and I would like to know where to find the values for the F stat of the main group and main condition effects for each ROI.
I read the CONN manual, saying that I can run a 2*2 ANOVA, but I do not know how to report the results.
I would like to report something like
For blabla region as a seed, we realized a two-way RM-ANOVA with "Time" and "Group" as factors (interaction Group*Time: F(2,xx) = xxx, p = xxx,Group: F(2,xx) = xxx, p =xxx, Time: F(1,xx) = xx, p = xx).
Then the post-hoc test with the specific effect
Does anyone know where I could find the appropriate stats values?
I have 3 groups of participants, and I recorded a resting state 2 times in each participant.
I would like to report an ROI-to-ROI analyses, and I would like to know where to find the values for the F stat of the main group and main condition effects for each ROI.
I read the CONN manual, saying that I can run a 2*2 ANOVA, but I do not know how to report the results.
I would like to report something like
For blabla region as a seed, we realized a two-way RM-ANOVA with "Time" and "Group" as factors (interaction Group*Time: F(2,xx) = xxx, p = xxx,Group: F(2,xx) = xxx, p =xxx, Time: F(1,xx) = xx, p = xx).
Then the post-hoc test with the specific effect
Does anyone know where I could find the appropriate stats values?
↧
Error analysis(1st-level)
dear expert:
i have meet error in analysis(1st-level), and the error show that:
Error using set
Color value contains NaN, or element out of range 0.0 <= value <= 1.0
Error in conn_timedwaitbar (line 60)
set(findobj(b,'tag','patch'),'facecolor',(1-a)*[.2 .2 .8]+a*[.8 .8 .2]); %(1-a)*[5/6,2/6,1.5/6]+a*[1.5/6,5/6,2/6]);
Error in conn_process>conn_waitbar (line 4884)
else h=conn_timedwaitbar(varargin{:}); end
Error in conn_process (line 3790)
conn_waitbar(n/N,h,sprintf('Subject %d Condition %d',nsub,ncondition));
Error in conn_process (line 42)
case 'analyses_gui_seedandroi',disp(['CONN: RUNNING ANALYSIS STEP (ROI-to-ROI or seed-to-voxel analyses)']); conn_process([10,11,15],varargin{:});
Error in conn (line 6559)
else conn_process('analyses_gui_seedandroi',CONN_x.Analysis); ispending=false;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.18.a
SPM8 + Beamforming DEM FieldMap MEEGtools vbm8
Matlab v.2014a
storage: 190.6Gb available
spm @ E:\Toolbox\Toolbox\spm8\spm8
conn @ E:\Toolbox\conn
i don't know how to resolve it. i will be grateful if you can give me instructions. i am looking forward to receiving your replay. thank you very much.
best wishes
jiwen
i have meet error in analysis(1st-level), and the error show that:
Error using set
Color value contains NaN, or element out of range 0.0 <= value <= 1.0
Error in conn_timedwaitbar (line 60)
set(findobj(b,'tag','patch'),'facecolor',(1-a)*[.2 .2 .8]+a*[.8 .8 .2]); %(1-a)*[5/6,2/6,1.5/6]+a*[1.5/6,5/6,2/6]);
Error in conn_process>conn_waitbar (line 4884)
else h=conn_timedwaitbar(varargin{:}); end
Error in conn_process (line 3790)
conn_waitbar(n/N,h,sprintf('Subject %d Condition %d',nsub,ncondition));
Error in conn_process (line 42)
case 'analyses_gui_seedandroi',disp(['CONN: RUNNING ANALYSIS STEP (ROI-to-ROI or seed-to-voxel analyses)']); conn_process([10,11,15],varargin{:});
Error in conn (line 6559)
else conn_process('analyses_gui_seedandroi',CONN_x.Analysis); ispending=false;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.18.a
SPM8 + Beamforming DEM FieldMap MEEGtools vbm8
Matlab v.2014a
storage: 190.6Gb available
spm @ E:\Toolbox\Toolbox\spm8\spm8
conn @ E:\Toolbox\conn
i don't know how to resolve it. i will be grateful if you can give me instructions. i am looking forward to receiving your replay. thank you very much.
best wishes
jiwen
↧