open-discussion
open-discussion > Error
May 10, 2016 04:05 PM | Caron Clark - University of Arizona
Error
Thanks for creating this toolbox. I was thrilled to find it.
I am not very good with Matlab and am new to this form of analysis so apologies if this is a stupid question.
I am running the first level analysis on a bunch of participants and have just adapted your anadef script to do this. However, for many of the subjects, I am finding that I get the following error:
Retrieving data from ROI 17 using summary function mean ...
Summarizing data with summary function: mean
Initialising parameters : ...done
Covariance estimate : ...voxelwise
Model : estimation
Temporal non-sphericity (over voxels) : ...estimation
ReML Block - 1
ReML Iteration : 1 ...1.134073e+01
ReML Iteration : 2 ...2.286396e+04
ReML Iteration : 3 ...5.594243e+00
ReML Iteration : 4 ...6.116961e+03
ReML Iteration : 5 ...3.742198e+00
ReML Iteration : 6 ...8.546006e+00
ReML Iteration : 7 ...6.250731e-01
ReML Iteration : 8 ...4.084047e-01
ReML Iteration : 9 ...8.420834e-02
ReML Iteration : 10 ...3.495538e-02
ReML Iteration : 11 ...9.900201e-03
Initialising parameters : ...computingIndex exceeds matrix dimensions.
Error in spdiags (line 102)
a((len(k)+1):len(k+1),:) = [i i+d(k) B(i+(m>=n)*d(k),k)];
Error in pr_estimate (line 128)
s = spdiags(1./sqrt(diag(s)),0,nScan,nScan);
Error in pr_estimate (line 345)
SPM = pr_estimate(SPM,marsY);
Error in mardo_5/estimate (line 72)
SPM = pr_estimate(SPM, marsY);
Error in BASCO>pushbuttonmodelspecest_Callback (line 424)
E = estimate(D,Y); % estimate model based on ROI summary
Error in gui_mainfcn (line 95)
feval(varargin{:});
Error in BASCO (line 20)
gui_mainfcn(gui_State, varargin{:});
Error in
matlab.graphics.internal.figfile.FigFile/read>@(hObject,eventdata)BASCO('pushbuttonmodelspecest_Callback',hObject,eventdata,guidata(hObject))
Error while evaluating UIControl Callback
It is difficult to trouble shoot without being able to see what SPM is doing and I wondered if you have any ideas? I have different trial numbers for each condition in each case as it is a correct vs. incorrect trial analysis. It also seems to be related to different ROIs in each case .
Thanks in advance
I am not very good with Matlab and am new to this form of analysis so apologies if this is a stupid question.
I am running the first level analysis on a bunch of participants and have just adapted your anadef script to do this. However, for many of the subjects, I am finding that I get the following error:
Retrieving data from ROI 17 using summary function mean ...
Summarizing data with summary function: mean
Initialising parameters : ...done
Covariance estimate : ...voxelwise
Model : estimation
Temporal non-sphericity (over voxels) : ...estimation
ReML Block - 1
ReML Iteration : 1 ...1.134073e+01
ReML Iteration : 2 ...2.286396e+04
ReML Iteration : 3 ...5.594243e+00
ReML Iteration : 4 ...6.116961e+03
ReML Iteration : 5 ...3.742198e+00
ReML Iteration : 6 ...8.546006e+00
ReML Iteration : 7 ...6.250731e-01
ReML Iteration : 8 ...4.084047e-01
ReML Iteration : 9 ...8.420834e-02
ReML Iteration : 10 ...3.495538e-02
ReML Iteration : 11 ...9.900201e-03
Initialising parameters : ...computingIndex exceeds matrix dimensions.
Error in spdiags (line 102)
a((len(k)+1):len(k+1),:) = [i i+d(k) B(i+(m>=n)*d(k),k)];
Error in pr_estimate (line 128)
s = spdiags(1./sqrt(diag(s)),0,nScan,nScan);
Error in pr_estimate (line 345)
SPM = pr_estimate(SPM,marsY);
Error in mardo_5/estimate (line 72)
SPM = pr_estimate(SPM, marsY);
Error in BASCO>pushbuttonmodelspecest_Callback (line 424)
E = estimate(D,Y); % estimate model based on ROI summary
Error in gui_mainfcn (line 95)
feval(varargin{:});
Error in BASCO (line 20)
gui_mainfcn(gui_State, varargin{:});
Error in
matlab.graphics.internal.figfile.FigFile/read>@(hObject,eventdata)BASCO('pushbuttonmodelspecest_Callback',hObject,eventdata,guidata(hObject))
Error while evaluating UIControl Callback
It is difficult to trouble shoot without being able to see what SPM is doing and I wondered if you have any ideas? I have different trial numbers for each condition in each case as it is a correct vs. incorrect trial analysis. It also seems to be related to different ROIs in each case .
Thanks in advance
Threaded View
Title | Author | Date |
---|---|---|
Caron Clark | May 10, 2016 | |
Ralf Veit | Jul 21, 2016 | |
Lisanne Jenkins | Nov 28, 2016 | |
Jerry Zhu | Aug 11, 2016 | |
jean valjean | Jul 18, 2016 | |