Classification of fMRI Data by Using Clustering

MOĞULTAY H., Alkan S., Yarman-Vural F. T.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16 - 19 May 2015, pp.2381-2383 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.2381-2383
  • Keywords: fMRI, Clustering, Multi Voxel Pattern Analysis (MVPA), VENTRAL TEMPORAL CORTEX, OBJECTS, REPRESENTATIONS, FACES
  • Middle East Technical University Affiliated: Yes


Recognition of the the cognitive states by using functional Magnetic Rezonans Imaging (fMRI) data is a challenging problem that has been a focus of scientific research for a long time. In this study the effectiveness of clustering and the ensemble learning techniques on fMRI dataset is investigated and different paramaters are compared. Moreover, the performance of these techniques are tested on both raw voxel intensity values and meshes formed by multiple voxels. Clusters are compared to the functional brain regions, however higher performances are obtained when the number of clusters is higher than the number of functional brain regions.