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

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.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-5593-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-5594-8
Genre: Poster

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https://www.ismrm.org/13/tp14.htm (Abstract)
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 Creators:
Eklund, A, Author
Björnsdotter, M, Author
Stelzer, J1, Author              
LaConte, S, Author
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1Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, ou_persistent22              

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 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.

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 Dates: 2013-04
 Publication Status: Published in print
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Title: 21st Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2013)
Place of Event: Salt Lake City, UT, USA
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Title: 21st Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2013)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 2291 Start / End Page: - Identifier: -