# Creating Paired Differences

If you analyze 2-time point longitudinal data, you will eventually observe that it is easier to create and analyze difference data (e.g. data from time 2 minus data from time 1). However, if you’re not a scripting guru this might be an annoying task.

This `PairDiff.m` script will take an even number of images and produce a set of paired difference images, even minus odd.

```function PairDiff(Imgs,BaseNm)
% PairDiff(Imgs,BaseNm)
% Imgs   - Matrix of (even-number of) filenames
% BaseNm - Basename for difference images
%
% Create pairwise difference for a set of images (img2-img1, img4-img3, etc),
% named according to BaseNm (BaseNm_0001, BaseNm_0002, BaseNm_0003, etc).
%______________________________________________________________________
% \$Id: PairDiff.m,v 1.2 2012/02/16 21:36:41 nichols Exp \$

if nargin<1 | isempty(Imgs)
Imgs = spm_select(Inf,'image','Select n*2 images');
end
if nargin<2 | isempty(BaseNm)
BaseNm = spm_input('Enter difference basename','+1','s','Diff');
end
V = spm_vol(Imgs);
n = length(V);
if rem(n,2)~=0
error('Must specify an even number of images')
end

V1 = V(1);
V1  = rmfield(V1,{'fname','descrip','n','private'});
V1.dt = [spm_type('float32') spm_platform('bigend')];

for i=1:n/2
V1.fname = sprintf('%s_%04d.img',BaseNm,i);
V1.descrip = sprintf('Difference %d',i);
Vo(i) = spm_create_vol(V1);
end

%
% Do the differencing
%

fprintf('Creating differenced data ')

for i=1:2:n

img = img2-img1;

spm_write_vol(Vo((i+1)/2),img);

end
```

After I created this I realized that Ged Ridgway also has a similar script, make_diffs.m , that takes two lists of images (baseline, followup) and does the same thing, though with perhaps more intuitive filenames.

# SPM8 Gem 1: Zero NaN’s with the zeronan.m script

Follow-up to SPM99 Gem 3: NaNing zero values from the NISOx blog (formerly Neuroimaging Statistics Tips & Tools)

This was the topic of SPM99 Gem 3, converting NaN’s to zeros. For SPM8, see the following script `zeronan.m` that will zero NaN’s for you.

-Tom

```function ofNm = zeronan(ifNm,val)
% FORMAT ofNm = zeronan(ifNm,val)
% ifNm  - Input filename(s)
% val   - Value to set NaN's to (defaults to zero)
%
% Output:
% ofNm  - Cell array of output filenames.
%
%
% Images have NaN's replaced with zeros, and new images, prefixed with a
% 'z', are created.
%
%________________________________________________________________________
% Based on zeronan.m,v 1.3 2005/10/26 21:58:55 nichols Exp
% Thomas Nichols, 1 April 2011

if nargin<2, val = 0; end
if nargin0'); end

if ~iscell(ifNm)
ifNm = cellstr(ifNm)';
else
ifNm = ifNm(:)';
end

OtfNm = {};

for fNm = ifNm

fNm = fNm{:};

OfNm = ['z' fNm];
[pth,nm,xt,vol] = spm_fileparts(fNm);
OfNm = fullfile(pth,['z' nm xt]);

% Code snippet from John Ashburner...
VI       = spm_vol(fNm);
VO       = VI;
VO.fname = OfNm;
VO       = spm_create_vol(VO);
for i=1:VI.dim(3),
img      = spm_slice_vol(VI,spm_matrix([0 0 i]),VI.dim(1:2),0);
tmp      = find(isnan(img));
img(tmp) = val;
VO       = spm_write_plane(VO,img,i);
end;

OtfNm = {OtfNm{:} OfNm};

end

if nargout>0
ofNm = OtfNm;
end
```

# SPM5 Gem 6: Corrected cluster size threshold

This is SPM5 version of SPM2 Gem 13.

This is a script that will tell you the corrected cluster size threshold for given cluster-defining threshold: CorrClusTh.m

The usage is pretty self explanatory:

``` Find the corrected cluster size threshold for a given alpha
function [k,Pc] =CorrClusTh(SPM,u,alpha,guess)
SPM   - SPM data structure
u     - Cluster defining threshold
If less than zero, u is taken to be uncorrected P-value
alpha - FWE-corrected level (defaults to 0.05)
guess - Set to NaN to use a Newton-Rhapson search (default)
Or provide a explicit list (e.g. 1:1000) of cluster sizes to
search over.
If guess is a (non-NaN) scalar nothing happens, except the the
corrected P-value of guess is printed.

Finds the corrected cluster size (spatial extent) threshold for a given
cluster defining threshold u and FWE-corrected level alpha.
```

To find the 0.05 (default alpha) corrected cluster size threshold for a 0.01 cluster-defining threshold:

```>> load SPM
>> CorrClusTh(SPM,0.01)
For a cluster-defining threshold of 2.4671 the level 0.05 corrected
cluster size threshold is 7860 and has size (corrected P-value) 0.0499926
```

Notice that, due to the discreteness of cluster sizes you cannot get an exact 0.05 threshold.

The function uses an automated search which may sometimes fail. If you specify a 4th argument you can manually specify the cluster sizes to search over:

```>> CorrClusTh(SPM,0.01,0.05,6000:7000)

WARNING: Within the range of cluster sizes searched (6000...7000)
a corrected P-value <= alpha was not found (smallest P: 0.0819589)

Try increasing the range or an automatic search.
```

Lastly, you can use it as a look up for a specific cluster size threshold. For example, how much over the 0.05 level would a cluster size of 7859 be?

```>> CorrClusTh(SPM,0.01,0.05,7859)
For a cluster-defining threshold of 2.4671 a cluster size threshold of
7859 has corrected P-value 0.050021
```

Just a pinch!

# SPM5 Gem 5: Unnormalizing a point

This script of Johns will find the corresponding co-ordinate in the un-normalized image: get_orig_coord2.m (same script as for SPM2).

# SPM5 Gem 4: Switching between SPM versions

This function will allow you to switch between different SPM versions. WARNING! As SPM depends on various global (and sometimes, local workspace) variables, this function clears all variables as part of the switch.

The function will need to be put in a directory in your Matlab path that does not contain SPM. spmsel.m

# SPM5 Gem 3: Resizing images

A generalized version of John’s reorient script (see Gem2) by Ged Ridgeway, which allows specification of arbitrary voxel dimensions: resize_img.m (this was current as of April 2007; see Ged’s script directory for updates.)

# SPM5 Gem 2: Reslicing images

To reslice an image at 1mm cubic voxels, axial orientation, use this reorient.m script (from an email from John dated Mon, 5 Jun 2006 13:02:05 +0100; see also Gem3 and SPM99 Gem7).