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spm_correlation_demo.m

 

      		
    

    

      
        

          
        

        
Copyright 2013 Allen Institute for Brain Science
Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License at



http://www.apache.org/licenses/LICENSE-2.0



Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

      		
      
        

      		
    

    

      
        

          
        

        
This script first does a differential search to identify the top and
bottom probes ranked by their differential expression between contrast
and target brain regions.  Expression values for these probes are then
correlated to the values sampled from an activity map computed by the
Statistical Parametric Mapping
library at human brain microarray sample locations (after mapping the 
coordinates to MNI).  The data set used in this demonstration code
were computed by following the SPM manual’s walkthrough of the visual
attention example data
set.  Specifically, follow the dynamic causal modeling walkthrough.

      		
      
        

      		
    

    

      
        

          
        

        
The selected SPM activity map shows strong activation in the visual
cortex, so the differential search is between structures in the visual
cortex (cuneus and lingual gyrus) and the rest of the cortex.

      		
      
        
target_ids = [4008];
contrast_ids = [4184,4191];
activation_file =  '../attention/GLM/spmT_0002.hdr';
mask_file = '../attention/GLM/mask.hdr';
n = 25;
specimen_name = 'H0351.2001';

      		
    

    

      
        

          
        

        
% Do the computation.

      		
      
        
specimen = download_specimen(specimen_name);
[top_corrs,samples] = expression_spm_correlation(target_ids,contrast_ids,activation_file,mask_file,n,specimen);
bottom_corrs = expression_spm_correlation(contrast_ids,target_ids,activation_file,mask_file,n,specimen);

      		
    

    

      
        

          
        

        
% Plot the results.
This is some data shuffling to get the legend to display properly.  I’m
displaying the first n correlations (which come from the contrast vs
target set of probes) in red, then the second n correlations (target vs
contrast) in blue.  I pad with zeros so that they display side-by-side.


      		
      
        
figure;
hold on;
bar([top_corrs zeros(1,n)],'FaceColor','red');
bar([zeros(1,n) bottom_corrs],'FaceColor','blue');
xlabel('probe');
ylabel('correlation to SPM activation');
legend('high fold change','low fold change');
axis([0 2*n -.2 .2]);