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The paper argues that, the third generation of neural networksthe spiking neural networks (SNN), can be used to model dynamic, spatio-temporal, cognitive brain processes measured as functional magnetic resonance imaging (fMRI) data. The paper proposes a novel method based on the NeuCube SNN architecture for which the following new algorithms are introduced: fMRI data encoding into spike sequences; deep unsupervised learning of fMRI data in a 3D SNN reservoir; classification of cognitive states;doi:10.1109/tcds.2016.2636291 fatcat:d65yarmtwvcltkktgawoxm7kvy