Searchlight Goes GPU: Fast Multi-Voxel Pattern Analysis of fMRI Data

Eklund, A; Björnsdotter, M; Stelzer, J; LaConte, S

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Searchlight Goes GPU: Fast Multi-Voxel Pattern Analysis of fMRI Data

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https://www.ismrm.org/13/tp14.htm
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Eklund, A., Björnsdotter, M., Stelzer, J., & LaConte, S. (2013). Searchlight Goes GPU: Fast Multi-Voxel Pattern Analysis of fMRI Data. Poster presented at 21st Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2013), Salt Lake City, UT, USA.

Cite as: https://hdl.handle.net/21.11116/0000-0001-5593-9

Abstract

The searchlight algorithm is a popular choice for locally-multivariate decoding of fMRI data. A substantial drawback of searchlight is the increase in computational complexity, compared to the univariate general linear model. This is especially true for large searchlight spheres, non-linear classifiers, cross validation schemes and statistical permutation testing. Here we therefore present a graphics processing unit (GPU) implementation of the searchlight algorithm, to enable fast locally-multivariate fMRI analysis. The GPU implementation is 21 times faster than a multithreaded Matlab implementation. This makes it possible to apply 10 000 permutations with leave-one-out cross-validation in about 19 minutes.