An information theoretic approach to classify cognitive states using fMRI

Itir Onal, Mete Ozay, Orhan Firat, Ilke Öztekin, Fatos T.Yarman Vural

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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. The samples are generated during an fMRI experiment employing item recognition (IR) and judgment of recency (JOR) tasks. For each sample, estimated arc weights of the local mesh with optimal size are used to classify whether it belongs to IR or JOR tasks. Results indicate that the suggested connectivity model with optimal mesh size for each sample represent the information distribution in the brain better than the state-of-the art methods.

本文言語English
ホスト出版物のタイトル13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
DOI
出版ステータスPublished - 2013 12 1
イベント13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013 - Chania, Greece
継続期間: 2013 11 102013 11 13

出版物シリーズ

名前13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013

Other

Other13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
CountryGreece
CityChania
Period13/11/1013/11/13

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

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