Yesterday I started the source localization on the spm dataset.
Today, I was able to complete the process for the entire brain
volume. The code I used was a hybrid of the two examples I listed
yesterday (raw to dSPM on SPM dataset and
compute dSPM on volume source space).
The results are displayed below ...
import matplotlib.pyplot as plt
%matplotlib inline
im = plt.imread('/Users/Alan/Desktop/Screen Shot 2014-05-20 at 3.10.07 PM.png')
plt.imshow(im)
These are graphs of the difference between the evoked data
for faces and the evoked data for scrambled images. Note
that this is not a formal comparison, it simply shows
the difference between the means. The region marked by the
crosshairs is the right amygdala, which is a good sign
going forward. Since the amygdala is a subcortical structure,
its good that we find activation at the whole brain level
that we can test once we're able to isolate subcortical
structures.
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