An Information Theoretic Approach to Classify Cognitive States Using fMRI


Onal I., Ozay M., Firat O., GİLLAM İ., YARMAN VURAL F. T.

IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE), Chania, Greece, 10 - 13 November 2013 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Chania
  • Country: Greece

Abstract

In this study, an information theoretic approach is proposed to model brain connectivity during a cognitive processing task, measured by functional Magnetic Resonance Imaging (fMRI). For this purpose, a local mesh of varying size is formed around each voxel. The arc weights of each mesh are estimated using a linear regression model by minimizing the squared error. Then, the optimal mesh size for each sample, that represents the information distribution in the brain, is estimated by minimizing various information criteria which employ the mean square error of linear regression model. The estimated mesh size shows the degree of locality or degree of connectivity of the voxels for the underlying cognitive process.