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Setup

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Alfonso,

I am hoping that you (or someone ) can help me. I have struggled using CONN on one of my data sets. I originally processed data sets individually and was able to go through first level analysis with no problems. However, when I tried to merge them I encountered multiple errors saying that the projects were not the same. Since I did not use conn_batch to run this data this is certainly possible.  After several attempts to figure out what was wrong.

I decided to start over.  I gathered the pre-processed data from the individual subjects and entered that through CONN batch script into setup. I am only doing 5 subjects.  I was able to enter them into CONN and see the results through the GUI.  However, when I ran Setup on the data via the GUI I am giving the following messages as Setup is running

warning: set-1 data for subject 1 session 1 not found
warning: set-1 data for subject 1 session 2 not found
warning: set-1 data for subject 2 session 1 not found
warning: set-1 data for subject 2 session 2 not found
warning: set-1 data for subject 3 session 1 not found
warning: set-1 data for subject 3 session 2 not found
...

The importing seems to be functioning. It takes about 2 minutes per subject.  However, when it finishes it briefly moves to Denoising stage and then tells me that I need to "Run first the Setup step by pressing "Done" in the Setup Tab".  At this point, I am out of ideas.  The setup looks good to me but obviously I am doing something wrong.  

Please help.

Bob


Here is my conn batch script.

function batch = me2ConnSetup

topDir = '/PACS-PI0/PACS-PI0/lindquist/me2/data/bkraft/'
me2Index = [35, 37, 38, 39, 40];
nSubjects = length(me2Index);
nSessions = 2;
nConditions = 2;
%
% Define the name of the conn.mat file.
%
outputDir = fullfile(topDir, 'group');
batch.filename = fullfile(outputDir, 'conn_me2.mat');
%
% Preprocessing Data sets
%
batch.Setup.nsubjects = nSubjects; % Number of Subjects
batch.Setup.RT = 2; % Repitition Time
% Functional and structural data for Sessions 1 and 2
%
batch.Setup.conditions.names{1} = 'restec';
batch.Setup.conditions.names{2} = 'neutral';
for iiSubject=1:nSubjects
for iiConditions=1:nConditions
for iiSessions=1:nSessions
batch.Setup.conditions.onsets{iiConditions}{iiSubject}{iiSessions} = []; % Condition{nCondition}{nSubject}{nSessions}
batch.Setup.conditions.durations{iiConditions}{iiSubject}{iiSessions} = [];
end
end
end
% For resting state fMRI onset is 0 and duration is inf
for ii=1:nSessions
for iiSubject=1:nSubjects
batch.Setup.conditions.onsets{ii}{iiSubject}{ii} = 0; % Condition{nCondition}{nSubject}{nSessions}
batch.Setup.conditions.durations{ii}{iiSubject}{ii} = inf;
end
end
%
%
batch.Setup.subjects.effect_names{1} = 'subjectID';
batch.Setup.covariates.names{1} = 'motion';

% batch.Setup.covariates.names{2} = 'scrubbing';

for iiSubject=1:length(me2Index)
iiSubject

subjectDir = fullfile(topDir, sprintf('me%03d', me2Index(iiSubject)))
batch.Setup.structurals{iiSubject}{1} = fullfile(subjectDir, 'wcrT1w.nii');
batch.Setup.masks.Grey{iiSubject} = fullfile(subjectDir, 'wc1crT1w.nii');
batch.Setup.masks.White{iiSubject} = fullfile(subjectDir, 'wc2crT1w.nii');
batch.Setup.masks.CSF{iiSubject} = fullfile(subjectDir, 'wc3crT1w.nii');
batch.Setup.functionals{iiSubject}{1} = fullfile(subjectDir, 'swaurestec.nii');
batch.Setup.functionals{iiSubject}{2} = fullfile(subjectDir, 'swauneutral.nii');

batch.Setup.covariates.files{1}{iiSubject}{1} = fullfile(subjectDir, 'rp_restec.txt');
% batch.Setup.covariates.files{2}{iiSubject}{1} = fullfile(subjectDir, 'art_regression_outliers_waurestec.mat');

batch.Setup.covariates.files{1}{iiSubject}{2} = fullfile(subjectDir, 'rp_neutral.txt');
% batch.Setup.covariates.files{2}{iiSubject}{2} = fullfile(subjectDir, 'art_regression_outliers_wauneutral.mat');

batch.Setup.subjects.effects{1}(iiSubject) = me2Index(ii);
end

conn_batch(batch)

Aquiring VDM* file for phase map correction

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Hi,

I was hoping include the phase maps we collected in the realignment and unwarping step for preprocessing in CONN. We are using a GE 3T scanner and while I can see both the magnitude and phase images in dicom format as part of the 62 slice time series, the converted version to a single .nii file has produced only phase map images for both echo times and not the magnitude images. Both the phase maps and the magnitude images are required for creating a vdm* file using the Fieldmap Toolbox and so I am at a bit of a loss as to how to get to the vdm* stage with what I have. Does anyone have any ideas as to how I could either get a magnitude image to use in the fieldmap toolbox or if I am able to just use the two phase maps to create a vdm* file? 

Thanks!

Isabella

Preprocessing failure, problem writing header

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Hi there,

I tested out my preprocessing and first-level analysis using one machine (Mac iMac, El Capitan, conn 16a, spm12, and art-2015-10) and it ran smoothly, albeit it took a long time.

So I'm trying to navigate my analysis to a faster windows machine (Dell Precision T1700, Windows 7, conn 16a, spm12, and art-2015-10).  However, for some reason the same preprocessing pipeline shuts down during the first stage (realignment and normalization) on this CPU.

------------------------------------------------------------------------
Running job #1
------------------------------------------------------------------------
Running 'Realign & Unwarp'

SPM12: spm_realign (v6070) 09:31:56 - 12/05/2016
========================================================================
Error: Permission denied
There was a problem writing to the header of
"C:\Users\cnl1796\Documents\Jeremy\tDCS_Patient_Study\Data\mri\Data\tDCS_TBI_01_01_A\SCANS\3\nii\cmrr_mb4_restingstateTE28.nii"
Failed 'Realign & Unwarp'
Error using nifti/create (line 26)
Unable to write header for "C:\Users\cnl1796\Documents\Jeremy\tDCS_Patient_Study\Data\mri\Data\tDCS_TBI_01_01_A\SCANS\3\nii\cmrr_mb4_restingstateTE28.nii".
In file "C:\Users\cnl1796\Documents\MATLAB\spm12\@nifti\create.m" (v5451), function "create" at line 26.
In file "C:\Users\cnl1796\Documents\MATLAB\spm12\spm_get_space.m" (v6379), function "spm_get_space" at line 51.
In file "C:\Users\cnl1796\Documents\MATLAB\spm12\spm_realign.m" (v6070), function "spm_realign" at line 167.
In file "C:\Users\cnl1796\Documents\MATLAB\spm12\config\spm_run_realignunwarp.m" (v6554), function "spm_run_realignunwarp" at line 78.
The following modules did not run:
Failed: Realign & Unwarp


Any recommendations on how to resolve this issue would be very much appreciated!

All the best,

Jeremy

RE: Matlab warnings & queue job issues

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Thank you for looking into this further. Below is the result of that test:
The atlas file looks fine in fslview, too.

>> conn
Warning: MATLAB has disabled some advanced graphics rendering features by switching to software OpenGL. For more information, click here.
Warning: Cannot recognise format. Trying Analyze.
> In read_hdr_raw (line 50)
In read_hdr (line 30)
In nifti (line 26)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
In conn_getinfo (line 18)
In conn (line 606)
In conn (line 105)
Warning: QFORM0 representation has been rounded.
> In encode_qform0 (line 27)
In mayo2nifti1 (line 63)
In nifti (line 30)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
In conn_getinfo (line 18)
In conn (line 606)
In conn (line 105)
>> try,
a=spm_vol(fullfile(fileparts(which('conn')),'rois','atlas.nii'));
disp('loading atlas.nii file ok');
catch
disp('error when loading atlas.nii');
end
loading atlas.nii file ok
>> try,
a=spm_vol(fullfile(fileparts(which('spm')),'canonical','avg152T1.nii'));
disp('loading avg152T1.nii file ok');
catch
disp('error when loading avg152T1.nii');
end
loading avg152T1.nii file ok

RE: Discrepancy between GUI and Batch processing

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[color=#000000]Hi Vikram,[/color]

[color=#000000]Yes, both gui and batch processing use the exact same functions so you should be getting the same results. Could you please send me both of your conn_*.mat files so I can take a quick look to see if I can identify any potential differences between those projects?[/color]

[color=#000000]Thanks[/color]
[color=#000000]Alfonso[/color]
[i]Originally posted by Vikram Rao:[/i][quote]Hi Conn Users,

I have been wanting to batch the gui setup using conn_batch. I m using conn 13 with spm8 and both gui and batch run without any errors, however, the results dont match. The only two things i m changing from defaults in both gui and batch is the following: Changing units from percent signal change to 'raw' and  i am doing only roi-roi analysis. I am not sure why the final correlation matrices are different. I am looking within the first level folder. Please advise. 


 Following is my code:

%% CONN batch using CONN_13

clc
clear all
close all
[dirlist]=textread('/Volumes/analysis/CONN/CONN_auto/data/file_list.txt','%s');% text file that contains the path to each subject's folders
addpath(genpath('/scripts/matlab_shared_toolboxes/conn/')) % CONN_13
spm8
%% CONN setup
batch.filename='CONN_auto.mat';
batch.Setup.isnew=1;
batch.Setup.overwrite='Yes';
batch.Setup.acquisitiontype=1;
batch.Setup.voxelmask=1;
batch.Setup.voxelresolution=1;
batch.Setup.nsubjects=9;
batch.Setup.RT=2;
batch.Setup.analyses=[1]; %Only ROI-to-ROI pipelines (changed from the default)
batch.Setup.analysisunits=2; % raw unit (changed from default: percent signal change)
batch.Setup.voxelresolution=1;
batch.Setup.roiextract=2;
batch.Setup.overwrite='Yes';
for isub=1:length(dirlist) %9
<span style="white-space: pre;"> </span>rootdir=dirlist{isub};
<span style="white-space: pre;"> </span>batch.Setup.functionals{isub}{1}= spm_select('ExtFPList',fullfile(rootdir,'Resting'),'^rest_dn_w.*s\.nii$',1:216);
<span style="white-space: pre;"> </span>batch.Setup.structurals{isub}=spm_select('ExtFPList',fullfile(rootdir,'anat'),'^wFSP.*R\.nii$');
<span style="white-space: pre;"> </span>batch.Setup.covariates.files{1}{isub}{1}=spm_select('FPList',fullfile(rootdir,'Resting'),'^art_regression_outliers_and_movement.*\.mat$');
<span style="white-space: pre;"> </span>batch.Setup.covariates.names={'motionart'};
<span style="white-space: pre;"> </span>batch.Setup.conditions.names={'rest'};
<span style="white-space: pre;"> </span>batch.Setup.conditions.onsets{1}{isub}{1}=0; batch.Setup.conditions.durations{1}{isub}{1}=inf; % rest condition (all sessions)
end
batch.Setup.done=1;
%% CONN preprocessing (all defaults)
batch.Preprocessing.filter=[0.0080, 0.0900];
batch.Preprocessing.detrending=1;
batch.Preprocessing.despiking=1;
batch.Preprocessing.overwrite='Yes';
batch.Preprocessing.done=1;
%% CONN Analysis (all defaults)
batch.Analysis.done=1;
batch.Analysis.overwrite='Yes';
%% Run the batch
conn_batch(batch)[/quote]

RE: scrubbing but not shinier...

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[color=#000000]Hi Chaleece,[/color]

[color=#000000]Yes, that definitely looks like residual noise in the seed-to-voxel correlation maps. Just to clarify, could you please comment on whether the variance/size of the voxel-to-voxel histogram for that subject (displayed in the figures that you attached) looks similar or larger than that expected from other subjects in your experiment (e.g. use the 'show all' button to compare these histograms across all subjects)? (the reason I ask is because to my eye this denoised histogram looks "wider" than what I would expect, this may reflect simply relatively short scanning time -e.g. if that looks similar across all subjects- or it may reflect an issue with this particuar subject -e.g. if that looks narrower for other subjects-). In general, potential things to try to make the Denoising step more conservative would be to increase the number of dimensions in the 'WhiteMatter' and 'CSF' confounding effects, and/or using more conservative ART thresholds. Another venue in this case would be to try to identify why this particular subject may show higher residual noise than expected (e.g. perhaps this reflects an issue during preprocessing? was this subject moving significantly more than others? was this movement constrained to one particular session?) and try to address those issues directly if possible. Last keep in mind that if the degrees of freedom in your dataset are relatively low across the board then making the Denoising step more conservative will push those degrees of freedom even lower, negatively affecting the quality of the data for other subjects, so it may be more effective to simply disregard this subject (or some subset of runs/sessions for this subject) from the analyses.[/color]

[color=#000000]Hope this helps[/color]
[color=#000000]Alfonso[/color]

[i]Originally posted by Chaleece Sandberg:[/i][quote]Hello good people!
I am analyzing resting state data and using the default pipeline.
I have one subject for which there are outliers from art, but the scrubbing does not show any % BOLD explained. In the first level results, it looks as if there are "motion-contaminated" results. I am attaching a screenshot.
1. Why might scrubbing not help with this subject?
2. What can I do to improve the denoising for this individual?
I have been perusing the forum, but can't seem to find an answer that fits. 
Any advice is greatly appreciated![/quote]

RE: A couple if issues: confounds, ART, MVPA stat

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Dear Alfonso

Thank you again!!!
I followed your advice and the non-parametric statistics with MVPA components with height threshold p<0.001 uncorrected, cluster threshold: cluster size p<0.05 uncorrected, for the contrast of main interest (subject effects: drug>placebo, conditions: rest post>rest pre) gave me 4 clusters: 25, 16, 14, 10 voxels (by going down with the second threshold to p<0.01, only the first one will survive). FDR, FWE result in an "empty brain". Just to be sure: do you find the effects and small number of voxels (and the applied statistical thresholds for identifying the seed) valid/publishable and worth pursuing with post hoc test analysis? (for all or at least for the first cluster?)

Best,
Lucas

serial correlation

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Hello,
I would like to know if the Conn toolbox has implemented any correction for serial correlation as AR before running the connectivity analysis.
Thanks in advance for any help.
regards, Katia Andrade

RE: Matlab warnings & queue job issues

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Good morning Alfonso,
Below is the result of that test:

>> conn
Warning: MATLAB has disabled some advanced graphics rendering features by switching to software OpenGL. For more information, click here.
Warning: Cannot recognise format. Trying Analyze.
> In read_hdr_raw (line 50)
In read_hdr (line 30)
In nifti (line 26)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
In conn_getinfo (line 18)
In conn (line 606)
In conn (line 105)
Warning: QFORM0 representation has been rounded.
> In encode_qform0 (line 27)
In mayo2nifti1 (line 63)
In nifti (line 30)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
In conn_getinfo (line 18)
In conn (line 606)
In conn (line 105)
MEvent. CASE!
MEvent. CASE!
MEvent. CASE!
MEvent. CASE!
>> ls('-al',fullfile(fileparts(which('conn')),'rois'))

path=fullfile(fileparts(which('conn')),'rois');
names=cat(1,dir(fullfile(path,'*.nii')),dir(fullfile(path,'*.img')));
for n=1:numel(names)
disp(names(n).name);
try
a=spm_vol(fullfile(path,names(n).name));
disp(a);
end
end
total 14068
drwxr-x--- 2 dlamb woods 4096 May 9 10:45 .
drwxr-x--- 5 dlamb woods 20480 May 9 10:56 ..
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._atlas.info
-rwxr-x--- 1 dlamb woods 2735 May 9 10:45 atlas.info
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._atlas.nii
-rwxr-x--- 1 dlamb woods 7221384 May 9 10:45 atlas.nii
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._atlas.txt
-rwxr-x--- 1 dlamb woods 4876 May 9 10:45 atlas.txt
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._dmn.info
-rwxr-x--- 1 dlamb woods 356 May 9 10:45 dmn.info
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._dmn.nii
-rwxr-x--- 1 dlamb woods 7109489 May 9 10:45 dmn.nii
-rwxr-x--- 1 dlamb woods 4096 May 9 10:45 ._dmn.txt
-rwxr-x--- 1 dlamb woods 17 May 9 10:45 dmn.txt

._atlas.nii
Warning: Cannot recognise format. Trying Analyze.
> In read_hdr_raw (line 50)
In read_hdr (line 30)
In nifti (line 26)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
Warning: QFORM0 representation has been rounded.
> In encode_qform0 (line 27)
In mayo2nifti1 (line 63)
In nifti (line 30)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
._dmn.nii
Warning: Cannot recognise format. Trying Analyze.
> In read_hdr_raw (line 50)
In read_hdr (line 30)
In nifti (line 26)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
Warning: QFORM0 representation has been rounded.
> In encode_qform0 (line 27)
In mayo2nifti1 (line 63)
In nifti (line 30)
In spm_vol_nifti (line 19)
In spm_vol>spm_vol_hdr (line 128)
In spm_vol (line 61)
atlas.nii
fname: '/home/dlamb/cam/software/conn/conn_2_dlamb/rois/atlas.nii'
dim: [182 218 182]
dt: [2 0]
pinfo: [3x1 double]
mat: [4x4 double]
n: [1 1]
descrip: 'FSL3.3'
private: [1x1 nifti]

dmn.nii
fname: '/home/dlamb/cam/software/conn/conn_2_dlamb/rois/dmn.nii'
dim: [181 217 181]
dt: [2 0]
pinfo: [3x1 double]
mat: [4x4 double]
n: [1 1]
descrip: ''
private: [1x1 nifti]

RE: ??between-source group comparisons??

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[color=#000000]Hi again Alfonso,
just a quick question. Statistically speaking, how should I report in the manuscript the between-subject comparison for laterality (the one you describe in your reply below?)[/color]

[color=#000000]Thank youu in advance[/color]
[color=#000000]Francesco[/color]


[color=#000000] 
[/color][i]Originally posted by Alfonso Nieto-Castanon:[/i][quote][color=#000000]Hi Fran,[/color]

[color=#000000]Yes, that makes perfect sense, if you select 'patients' and 'controls' (with between-subjects contrast [-1 1]), and two sources (with between-sources contrast [-1 1]), these analyses will show you those areas where laterality effects (differences in connectivity between the two sources) are different in controls vs. patients. [/color]

[color=#000000]Best[/color]
[color=#000000]Alfonso[/color]
[i]Originally posted by Fran :[/i][quote]Hello everyone,
I have run a number of between-source comparisons to assess laterality (or lateralization) for a number of seeds. Now I have results for "all subjects", "controls" and "patients" separately.
What I'd like to know really is if there is a difference between controls and patients for these between-source comparisons.
I wonder if it makes sense to run these comparisons in CONN (e.g., selecting the contrast "patients > controls" for a given between-source comparison)...

Alfonso, this would actually complete the analysis you recommended to run in a previous thread.

Thank you
Francesco[/quote][/quote]

serial correlation

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Hello,
I would like to know if the Conn toolbox has implemented any correction for serial correlation as AR before running the connectivity analysis.
Thanks in advance for any help.
regards, Katia Andrade

RE: Analysing resting-state fMRI data

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[color=#000000]Dear Natasha[/color]
 
I'm also facing a similar problem with you.
I'm also comparing CONN with DPARSFA regarding 1st-level ROI-to-ROI analysis, but their results are quite different.

I would think, this difference might be caused by difference in preprocessing procedures of them. CONN performs nuisance regression after slice-timing, realignment, (coregistration), normalization and smoothing, while DPARSFA does them in this order: slice-timing, realignment, (coregistration), nuisance regression, normalization and smoothing.

I have no idea about which is correct (or better), but it seems that the BOLD time course derived by DPARSFA is more noisy than that of CONN. I suppose that normalization and smoothing before nuisance regression may reduce noise in CONN.

How do you think about?

I would be grateful if someone who knew about two toolboxes could help me.

Best,
Satoru Hiwa
[i]Originally posted by Natasha Faria:[/i][quote]I am relatively new to working with fMRI data and have a basic question regarding usage of connectivity toolboxes.
I have 2 groups of sample data: Patient and Control; both processed using the same steps; and to analyse the resultant data I have decided to compare the output from two different toolboxes.
I am comparing resultant analysis data from two toolboxes; one of which is CONN and the other being DPARSF.
I have used the 1st level bivariate correlation ROI-to-ROI analysis in CONN folllowed by 2nd level FDR corrected two sided p value computation to compare functional connectivity patterns between control and group.
In DPARSF, I have used only the Functional connectivity option to obtain the correlation coefficients for each subject. Following which I have used Matlab to compute Mean, Standard deviation for the two groups and subsequent two sided T test to compute the p value.

According to my knowledge, both the analysis methods appear to be similar, but the results from both are largely different; with DPARSF showing mainly only left ROI to right corresponding ROI higher functional connectivity.
Any clarification and assistance in the following matter would be greatly appreciated in order to understand this better.[/quote]

Leave one out

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Has anyone figured out how to run leave one out analysis in conn?

ART error message using load

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Hi Alfonso,

Could you help at all with identifying what I failed to do that would lead to getting this error message? It came up when trying to run ART in 14p. I don't know if it could be related, but as part of the pre-processing pipeline, we had chosen only to segment and normalize the structural files previous to ART as we already had the realigned and other files.

ERROR DESCRIPTION:

Error using load
Argument must contain a string.
Error in art>read_art_sess_file (line 1624)
case 0, for n=1:numel(M),M{n}=load(M{n}); end
Error in art>art_OpeningFcn (line 227)
[num_sess,global_type_flag,drop_flag,motionFileType,motion_threshold,global_threshold,use_diff_motion,use_diff_global,use_norms,SPMfile,mask_file,output_dir,P,M] = ...
Error in gui_mainfcn (line 221)
feval(gui_State.gui_OpeningFcn, gui_hFigure, [], guidata(gui_hFigure), varargin{:});
Error in art (line 129)
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
Error in conn_art (line 8)
[varargout{1:nargout}]=art(varargin{:});
Error in conn_setup_preproc (line 864)
h=conn_art('sess_file',matlabbatch{n}.art);
Error in conn (line 593)
ok=conn_setup_preproc('',varargin{2:end});
Error in conn_menumanager (line 109)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.14.p
SPM8 + Anatomy Beamforming DEM FieldMap MEEGtools aal conn marsbar
Matlab v.2011b
storage: 448.7Gb available

Thanks very much!
Mary

Error in dynamic FC

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Dear Alfonso,

(1) we found the following error when performing dynamic FC. We use rsfMRI runs (300 scans each) from 13 patients, 20 controls. All were preprocessed in conn 15h without problems. We use a small network of 6 ROIs. The error message is below - Thanks for any help!

Eugenio

ERROR DESCRIPTION:

Error using eig
Input to EIG must not contain NaN or Inf.
Error in conn_ica (line 47)
[Q,D]=eig(X*X'/(Ns-1));
Error in conn_invPPI (line 164)
[S,W]=conn_ica(reshape(B1,[Nr*Nr Nk1])',[],'dodisp',DOPLOT,'rndseed',RNDSEED);
Error in conn_process (line 2871)
[H,B,H0,B0]=conn_invPPI(Y,Ncomponents,X,Xfilter,1);
Error in conn_process (line 40)
case 'analyses_gui_dyn',disp(['CONN: RUNNING DYNAMIC CONNECTIVITY STEP']); conn_process([13.5],varargin{:});
Error in conn (line 4469)
conn_process('analyses_gui_dyn');
Error in conn_menumanager (line 119)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.15.h
SPM8 + Anatomy Beamforming DEM FieldMap LI MEEGtools Masking TFCE marsbar psc rwls vbm8 xjview
Matlab v.2014a
storage: 599.4Gb available

RE: Denoised Data Output Option Problem

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Dear Jeff and Alfonso

I am trying to do the same: to use the denoised and split data from CONN and run the ICA on GIFT. The files are quite big in size (700Mb for a 7 min long RS) and while running MDL analysis for estimating the number of components, I got a "dimensionality estimation error" (requested array exceeds maximum array size preference). Have you encounterd the same issue?

Best,
Lucas

duplications in ROI_Subject#_Condition#.mat

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Dear Alfonso,

I am trying to extract time series from 90 ROIs using CONN. I have three sessions in a block design, where each session includes a different music-listening task. I have assigned a different condition to each session. Each session has 150 scans for a total of 450 scans across the entire experiment. In my ROI_Subject#_Condition.mat files, I see that the time series included in each file is the same (i.e., instead of having three condition files per subject with time series for only 150 scans, I have three identical condition files with 450 scans each---all duplicated data). Am I mis-specifying something in the setup? Or is it safe to assume that these files include the denoised data for all three conditions in the order in which I included them in the Setup>Conditions tab?

Any insights would be greatly appreciated.

Kind regards,
Cameron

Issue with set-up

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Hi CONN team and community,

I am new to the toolbox and am setting up my first project. My data is already preprocessed so I am using the toolbox solely to derive network metrics. I have run into the following error at the first stage of the project:

ERROR DESCRIPTION:

Error using class
Cannot change the number of fields of class 'cfg_item' without first typing 'clear classes'.
Error in cfg_item (line 108)
item = class(struct(fnd{:}), 'cfg_item');
Error in cfg_repeat (line 95)
gitem = cfg_item;
Error in cfg_mlbatch_root (line 16)
c0 = cfg_repeat;
Error in cfg_util>local_initcfg (line 1318)
c0 = cfg_mlbatch_root;
Error in cfg_util (line 618)
[c0 jobs cjob] = local_initcfg;
Error in spm_jobman (line 160)
cfg_util('initcfg'); % This must be the first call to cfg_util
Error in conn_setup_preproc (line 936)
spm_jobman('initcfg');
Error in conn_process (line 209)
conn_setup_preproc('run_structural_segment','subjects',nsub);
Error in conn_process (line 12)
case 'setup', disp(['CONN: RUNNING SETUP STEP']); conn_process([0:5]);
Error in conn (line 2437)
conn_process('setup');
Error in conn_menumanager (line 119)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN v.15.d
SPM8 + Beamforming DEM FieldMap MEEGtools vbm8
Matlab v.2014a
storage: 70.5Gb available

Any help and/or advice would be greatly appreciated!

Best,

Christina

Error in preprocessing (realign)

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Hello,

I have tried to preprocess my data in the toolbox and this message appears:

ERROR DESCRIPTION:

Error using MATLABbatch system
Job execution failed. The full log of this run can be found in MATLAB command window, starting with the lines (look for the line showing the exact #job as displayed in this error message)
------------------
Running job #1
------------------
CONN v.15.h
SPM12 + DEM FieldMap MEEGtools
Matlab v.2015b
storage: 106.5Gb available


========================================================================
Computing mask... : ...done
Reslicing images... : ...done
Writing mean image... : ...done
Completed : 09:41:04 - 21/05/2016
Done 'Realign & Unwarp'
The following modules did not run:
Failed: Realign & Unwarp

http://www.nitrc.org/forum/forum.php?forum_id=1144



Any idea?

Thank you in advance,
Best regards,

Olaia

Removing task-effects

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Dear CONN Experts,

I have a question regarding task-effects regression in task-based functional connectivity analysis. Is there a way to check how well task effects were regressed out from functional time-series and what percent of variance remained unaccounted for by the model?

Best,
Karolina
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