I would recommend going through the DCM tutorial in the SPM manual on the SPM website, its about page 300.
Quick explanations:
> when I extract VOI's, I am asked for 'Adjust data','Which session' and
> 'Expression' in GUI and Batch.
> 1) What does it mean by adjust data? Is it trying to adjust data across
> all the four sessions (my experiment has four sessions).
This lets you mean correct the timeseries, excluding movement and other nuisance regressors from the extacted ROI.
To use this you create an F-contrast, called the 'effects of interest' contrast, which gives the effects of all your experimental conditions. When creating it, set its matrix to be the identity matrix, with 1's in the columns which are of interest to your results (i.e. not the movement parameters and any other nuisance regressors).
> 2) Rather than 'Which session', Can I do it over all the sessions.
> Because i am looking for effect of a condition which is basically based
> on activation from sum of all four sessions. My activation list is from
> t-contrast.
No. You either extract separate ROIs for each session, and therefore create separate models per session, or prior to making your design matrix, you concatenate all your sessions together into one big session, with extra regressors to handle inter-session differences (search the mailing list for how to do this). If you have enough trials per session, I'd strongly recommend separate models per session.
> 3) Why does it asks for 'Expression'?
This lets you combine ROIs. For example, if you wants activations from your SPM and that also fall within an 8mm sphere, you specify these in the batch and put i1 && i2.
Best,
Peter
>
> I figured this VOI issue which i was mentioning DCM.U.dt file as they
> are based of SPM.Sess. Please let me know
>
>
>
> Thanks
>
> ----- Original Message -----
> From: "Peter Zeidman" <[log in to unmask]>
> To: "Kushal Kapse" <[log in to unmask]>
> Cc: [log in to unmask]
> Sent: Thursday, July 25, 2013 10:48:14 AM
> Subject: RE: DCM.U.dt = SPM.Sess.U(1).dt;
>
> Regarding your question about the meaning of the fields in DCM.U...
>
> DCM.U.dt - In your experiment you may only get a volume every 2 or 3
> seconds, but in DCM we want to model a finer time resolution than this.
> So the software splits each of your volumes into a number of time bins
> (giving us 'microtime'). So for example, if you want 16 time bins per
> volume, then dt = 1/16 = 0.0625 .
>
> DCM.U.u - Your input regressor(s), e.g. timecourse of a stimulus
> switching on and off, in microtime, i.e. using the above dt.
>
>
> OK, so the key part of the error is:
>
> > DCM.U.dt = SPM.Sess.U(1).dt;
> >
> > ??? Reference to non-existent field 'U'.
>
> This tells you that either DCM.U or SPM.Sess.U does not exist, when it
> is expected to. The latter is the more likely cause. So, here's what to
> investigate...
>
> If you look at the SPM structure loaded into the workspace, has it got
> a structure within that called Sess, and a structure within that called
> U? If not, then SPM is not an estimated model created with SPM version
> 8 or above. Did you script the creation of the SPM structure too or use
> the GUI?
>
> Best,
> P.
>
> > -----Original Message-----
> > From: Kushal Kapse [mailto:[log in to unmask]]
> > Sent: 25 July 2013 15:15
> > To: Zeidman, Peter
> > Cc: [log in to unmask]
> > Subject: Re: DCM.U.dt = SPM.Sess.U(1).dt;
> >
> > Hi Peter,
> >
> > Thanks for your reply. I am using the same dcm__spm8_batch script to
> > run my DCM experiment. I did make one model in GUI and went into
> > workspace to understand how DCM.U is defined. Following is what my
> > error states and below that is what my model (which i made in GUI and
> > then looked into workspace) looks like. I am not able to understand
> > what the workspace structure of DCM.U means. Please take a look below
> > and let me know where am I wrong.
> >
> > ERROR----------------------------------------------------------------
> -
> > -
> > -----------------------------------------------------------------
> >
> >
> > ??? Field reference for multiple structure elements that is followed
> > by more reference blocks is an error.
> >
> > Error in ==> script at 80
> > DCM.U.dt = SPM.Sess.U(1).dt;
> >
> > ??? Reference to non-existent field 'U'.
> >
> > DCM.U structure--------------------------% this is when i did one
> > model in GUI and checked it in workspace
> >
> >
> > DCM.U <1x1 struct>
> > dt 0.1563 % i didnt understand where this number comes
> from
> > name <1x1 cell> %this is my condition called pictures
> > u <1808x1 double> % i didnt understand this at all
> > (124,1) 1
> > .
> > .
> > .
> > .
> > (1747x1) 1
> >
> > ---------------------------------------------------------------------
> -
> > -
> > ---------------------------------------------------------------------
> -
> >
> > my doubts:
> >
> > 1- i theoretically understand that dt is time bin (sec), but how is
> it
> > calculated? How can i calculate that specifically for my experiment
> > 2- DCM.U.u is stimulus function matrix. But where does those matrix
> > numbers come from
> >
> > I am changing the dcm_spm8_batch.m script starting from extracting
> > VOI's. Following is the script where i have made the changes so far.
> >
> > -------------------------------Changes made to dcm__spm8_batch.m for
> > replicating my
> > experiment----------------------------------------------
> > ---
> >
> >
> >
> > % Directory containing the attention data
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > data_path='Z:\datapath\';
> >
> > % Initialise SPM
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > spm('Defaults','fMRI');
> > spm_jobman('initcfg');
> > spm_get_defaults('cmdline',1);
> >
> >
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> > %
> > %%%%
> > % VOLUMES OF INTEREST
> >
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> > %
> > %%%%
> >
> > % EXTRACTING TIME SERIES: A
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > clear matlabbatch
> > matlabbatch{1}.spm.util.voi.spmmat =
> > cellstr(fullfile(data_path,'SPM.mat'));
> > matlabbatch{1}.spm.util.voi.adjust = 0; % "effects of ...."
> > F-contrast matlabbatch{1}.spm.util.voi.session = 1; % session 1
> > matlabbatch{1}.spm.util.voi.name = 'A';
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.spmmat = {''}; % using SPM.mat
> > above matlabbatch{1}.spm.util.voi.roi{1}.spm.contrast = 3; % "pic
> > minus scrambled" T-contrast
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.threshdesc = 'none';
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.thresh = 0.001;
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.extent = 0;
> > matlabbatch{1}.spm.util.voi.roi{2}.sphere.centre = [-63 -27 21] %
> > arbitrary matlabbatch{1}.spm.util.voi.roi{2}.sphere.radius = 5;
> > %matlabbatch{1}.spm.util.voi.roi{2}.sphere.move.global.spm = 1; %
> > global max
> %matlabbatch{1}.spm.util.voi.roi{2}.sphere.move.global.mask
> > = ''; % none matlabbatch{1}.spm.util.voi.expression = 'i1 & i2';
> > spm_jobman('run',matlabbatch);
> >
> > % EXTRACTING TIME SERIES: B
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > clear matlabbatch
> > matlabbatch{1}.spm.util.voi.spmmat =
> > cellstr(fullfile(data_path,'SPM.mat'));
> > matlabbatch{1}.spm.util.voi.adjust = 0; % "effects of ...."
> > F-contrast matlabbatch{1}.spm.util.voi.session = 2; % session 1
> > matlabbatch{1}.spm.util.voi.name = 'B';
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.spmmat = {''}; % using SPM.mat
> > above matlabbatch{1}.spm.util.voi.roi{1}.spm.contrast = 3; % "pic
> > minus scrambled" T-contrast
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.thresh = 0.001;
> > matlabbatch{1}.spm.util.voi.roi{1}.spm.extent = 0;
> > matlabbatch{1}.spm.util.voi.roi{2}.sphere.centre = [21 -6 42] %
> > arbitrary matlabbatch{1}.spm.util.voi.roi{2}.sphere.radius = 5;
> > %matlabbatch{1}.spm.util.voi.roi{2}.sphere.move.global.spm = 1; %
> > global max
> %matlabbatch{1}.spm.util.voi.roi{2}.sphere.move.global.mask
> > = ''; % none matlabbatch{1}.spm.util.voi.expression = 'i1 & i2';
> > spm_jobman('run',matlabbatch);
> >
> >
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> > %
> > %%%%
> > % DYNAMIC CAUSAL MODELLING
> >
> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> > %
> > %%%%
> >
> > clear DCM
> >
> > % SPECIFICATION DCM "A to B"
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > load(fullfile(data_path,'SPM.mat'));
> >
> > load(fullfile(data_path,'VOI_A_1.mat'),'xY');
> > DCM.xY(1) = xY;
> > load(fullfile(data_path,'VOI_B_1.mat'),'xY');
> > DCM.xY(2) = xY;
> >
> > DCM.n = length(DCM.xY); % number of regions
> > DCM.v = length(DCM.xY(1).u); % number of time points
> > matlabbatch{1}.spm.stats.fmri_spec.timing.RT = 2.5;
> > DCM.Y.dt = SPM.xY.RT;
> > DCM.Y.X0 = DCM.xY(1).X0;
> > for i = 1:DCM.n
> > DCM.Y.y(:,i) = DCM.xY(i).u;
> > DCM.Y.name{i} = DCM.xY(i).name;
> > end
> >
> > DCM.Y.Q = spm_Ce(ones(1,DCM.n)*DCM.v);
> >
> >
> > DCM.U.dt = SPM.Sess.U(1).dt;
> > DCM.U.name = [SPM.Sess.U.name(1)];
> > DCM.U.u = [SPM.Sess.U(1).u(33:end,1)];
> >
> > DCM.delays = repmat(SPM.xY.RT,2,1);
> > DCM.TE = 0.04;
> >
> > DCM.options.nonlinear = 0;
> > DCM.options.two_state = 0;
> > DCM.options.stochastic = 0;
> > DCM.options.nograph = 1;
> >
> > DCM.a = [1 1; 1 1];
> > DCM.b = zeros(2,2); DCM.b(1,1) = 1; DCM.b(1,1) = 0; DCM.c = [0
> > 0;1,0]; DCM.d = zeros(2,2);
> >
> > save(fullfile(data_path,'model-1.mat'),'DCM');
> >
> >
> > % SPECIFICATION DCM "B to A"
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > DCM.b = zeros(2,2); DCM.b(1,1) = 0; DCM.b(1,1) = 1; DCM.c = [1
> > 0;0,0] save(fullfile(data_path,'model-2.mat'),'DCM');
> >
> > % ESTIMATION
> > %--------------------------------------------------------------------
> -
> > -
> > ----
> > DCM_model1 = spm_dcm_estimate(fullfile(data_path,'model-1.mat'));
> > DCM_model2 = spm_dcm_estimate(fullfile(data_path,'model-2.mat'));
> >
> >
> >
> > Please advice me on how to understand DCM.U structure and where am i
> > misleading so that i can make those changes.
> >
> >
> > Thanks a lot
> >
> >
> >
> > ----- Original Message -----
> > From: "Peter Zeidman" <[log in to unmask]>
> > To: "Kushal Kapse" <[log in to unmask]>
> > Cc: [log in to unmask]
> > Sent: Thursday, July 25, 2013 5:29:25 AM
> > Subject: RE: DCM.U.dt = SPM.Sess.U(1).dt;
> >
> > Dear Kushal,
> > Sorry, I don't fully understand the problem you're facing.
> >
> > It seems you're trying to create a DCM by writing a script. I suggest
> > you look at the example script at:
> >
> > http://www.fil.ion.ucl.ac.uk/spm/data/attention/dcm_spm8_batch.m
> >
> > Alternatively, if you're unsure of the format to use DCM.U, I suggest
> > generating a DCM model using the GUI, then loading it into the Matlab
> > workspace and having a look at what's inside it.
> >
> > Feel free to ask again if you're still stuck.
> >
> > Best,
> > Peter.
> >
> > > -----Original Message-----
> > > From: Kushal Kapse [mailto:[log in to unmask]]
> > > Sent: 24 July 2013 22:38
> > > To: Zeidman, Peter
> > > Cc: [log in to unmask]
> > > Subject: DCM.U.dt = SPM.Sess.U(1).dt;
> > >
> > > Hi peter and other SPM users,
> > >
> > > I am going through same issue for DCM. But my experiment is
> > different.
> > > I am not able to understand how would i change code(see below), for
> > my
> > > experiment. I went through spm_get_ons.m and spm_dcm_estimate.m to
> > > figure this out. but wasnt successful.
> > >
> > > DCM.U.dt = SPM.Sess.U(1).dt;
> > > DCM.U.name = [SPM.Sess.U.name(1)];
> > > DCM.U.u = [SPM.Sess.U(1).u(33:end,1)];
> > >
> > > I saw one more post on this which stated
> > > https://www.jiscmail.ac.uk/cgi-
> > >
> >
> bin/webadmin?A2=ind1004&L=SPM&F=&S=&X=61A0FC0F022B49A505&Y=analysisthr
> > > e
> > > ad%40gmail.com&P=580450
> > >
> > > "The DCM.U.u field contains the inputs (i.e., input vectors and
> > > modulatory vectors resampled into microtime). Microtime is the
> > > number of bins each TR is split into, and is specified by
> > > defaults.stats.fmri.fmri_t. The offset is specified in spm_get_ons.
> > > See around line 238. Therefore, if you you are using a design that
> > has
> > > been setup by SPM, you should index it exactly as shown in the code
> > > you listed below: SPM.Sess.U(k).u(33:end,1) and so on, where k =
> > > condition you are indexing."
> > >
> > >
> > > BUT, I am still not able to figure out how i change those three
> > > lines for my experiment.
> > > I am changing the SPM-DCM code for first time for my experiment and
> > > hence if anyone of you guys can give me feedback on this, it would
> > > be helpful.
> > >
> > >
> > > Thanks in advance
> > > Kushal
> > >
> > >
> > > ----- Original Message -----
> > > From: "Peter Zeidman" <[log in to unmask]>
> > > To: [log in to unmask]
> > > Sent: Monday, April 15, 2013 10:17:00 AM
> > > Subject: Re: [SPM] DCM - batch
> > >
> > > Hi Carmen,
> > > (I'm CC'ing the mailing list in case anyone else is following this
> > > question.)
> > >
> > > Your models are different because the one produced using the batch
> > > editor has mean-centring switched on, and the one using the GUI
> does
> > > not. Not only will this change your DCM.U.u (changing the mean to
> > > zero), but it also alters the interpretation of your DCM results.
> > > See the previous message I have pasted below from Karl.
> > >
> > > (I can't guarantee there are no other differences in your models,
> > > but that's the most obvious one!)
> > >
> > > All the best,
> > > Peter.
> > >
> > > ...
> > > If you centre the input, it will have a mean of zero. This means
> > > that the modulating input will increase and decrease the extrinsic
> > > connectivity (A parameter); as opposed to just increasing it, if
> the
> > > input is always positive. The interpretation of the B parameter
> > > therefore changes in a subtle way, and becomes closer to a
> classical
> > > interaction.
> > >
> > > I hope that this helps.
> > > With very best wishes,
> > > Karl
> > >
> > > > -----Original Message-----
> > > > From: SPM (Statistical Parametric Mapping)
> > > [mailto:[log in to unmask]]
> > > > On Behalf Of carmen
> > > > Sent: 15 April 2013 09:29
> > > > To: [log in to unmask]
> > > > Subject: [SPM] DCM - batch
> > > >
> > > > Dear SPM-list,
> > > > I still don’t understand what exactly DCM.U.u is and why the
> > > > values differ between a DCM-model created by GUI and the same
> > > > model
> > created
> > > > by the batch code. Probably resulting from the differences here,
> > the
> > > > values for DCM.Ep.A, DCM.Ep.B and DCM.Ep.C differ as well.
> > > > This is the code I use (model with 4 VOIs and two conditions as
> > > input):
> > > >
> > > >
> > >
> >
> load(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3
> > > > \GLM','SPM.mat'));
> > > >
> > > >
> > >
> >
> load(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3
> > > > \GLM','VOI_Thalamus_R_1.mat'),'xY');
> > > > DCM.xY(1) = xY;
> > > >
> > >
> >
> load(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3
> > > > \GLM','VOI_S2_R_1.mat'),'xY');
> > > > DCM.xY(2) = xY;
> > > >
> > >
> >
> load(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3
> > > > \GLM','VOI_Amygdala_L_1.mat'),'xY');
> > > > DCM.xY(3) = xY;
> > > >
> > >
> >
> load(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3 \GLM','VOI_Hippocampus_R_1.mat'),'xY');
> > > > DCM.xY(4) = xY;
> > > >
> > > > DCM.n = length(DCM.xY);
> > > > DCM.v = length(DCM.xY(1).u);
> > > >
> > > > DCM.Y.dt = SPM.xY.RT;
> > > > DCM.Y.X0 = DCM.xY(1).X0;
> > > > for i = 1:DCM.n
> > > > DCM.Y.y(:,i) = DCM.xY(i).u;
> > > > DCM.Y.name{i} = DCM.xY(i).name; end
> > > >
> > > > DCM.Y.Q = spm_Ce(ones(1,DCM.n)*DCM.v);
> > > >
> > > > DCM.U.dt = SPM.Sess.U(1).dt;
> > > > DCM.U.name = cellstr([SPM.Sess.U(1).name, SPM.Sess.U(2).name]);
> > > > DCM.U.u = [SPM.Sess.U(1).u(33:end,1) ...
> > > > SPM.Sess.U(2).u(33:end,1)];
> > > >
> > > > DCM.delays = repmat(SPM.xY.RT,DCM.n,1);
> > > > DCM.TE = 0.04;
> > > >
> > > > DCM.options.nonlinear = 0;
> > > > DCM.options.two_state = 0;
> > > > DCM.options.stochastic = 0;
> > > > DCM.options.nograph = 1;
> > > >
> > > > DCM.a = [1 0 0 0 ; 1 1 0 0 ; 1 1 1 0 ; 0 0 1 1 ]; DCM.b =
> > > > zeros(4,4,2); DCM.b(3,1,2) = 1; DCM.c = [1 0 ; 0 0; 0 0; 0
> 0DCM.d
> > =
> > > > zeros(4,4,0);
> > > >
> > > >
> > >
> >
> save(fullfile('D:\fMRI\Cannabis\Auswertung_Cannabis\Drona_R30\DCM\DCM_
> > > > 3
> > > > \GLM','DCM_Model1_batch.mat'),'DCM');
> > > >
> > > >
> > > > Thanks a lot!!
> > >
> >
>
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