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Brain Decoding via Clustering Ensemble and Graph Representation

Acronym: 
BDCeG

The general objective is the development of new brain decoding methods that use the spatial relation information in fRMI signals: (1) the development of a new feature selection method for brain decoding based on clustering ensemble algorithms that preserve the spatial relation among voxels and yield a consensus parcelation of the brain image; (2) the design of a graph representation of the brain image that captures all the information in a given parcelation; (3) the design of graph kernels able to measure the semantics inherit in the graph structure and with a low computational cost in its evaluation process.

Partners: 

RESTATE

Funding: 
EU Marie Curie
Research topics: