Brain Decoding Of Fmri Connectivity Graphs Using Decision Tree Ensembles

Functional connectivity analysis of fMRI data can reveal synchronized activity between anatomically distinct brain regions. Here, we exploit the characteristic connectivity graphs of task and resting epochs to perform classification between these conditions. Our approach is based on ensembles of decision trees, which combine powerful discriminative ability with interpretability of results. This makes it possible to extract discriminative graphs that represent a subset of the connections that distinguish best between the experimental conditions. Our experimental results also show that the method can be applied for group-level brain decoding.


Published in:
2010 7Th Ieee International Symposium On Biomedical Imaging: From Nano To Macro, 1137-1140
Presented at:
7th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, NETHERLANDS, Apr 14-17, 2010
Year:
2010
Publisher:
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa
ISBN:
978-1-4244-4126-6
Keywords:
Laboratories:




 Record created 2011-12-16, last modified 2018-03-18


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