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Spatial and Temporal Feature Extraction for Brain Decoding using CUDA

Brain decoding is the process of predicting cognitive states from medical data which consists of thousands of voxels and hundreds of samples. Features representing spatial and temporal relationships among neighboring voxels are discriminative and these relationships are estimated by solving regression for all samples of all voxels. Finding the nearest neighbors of all voxels and computing regression that includes matrix multiplication, addition and inverse with GPU implementation has a high speedup over CPU implementation.