Resampling as a cluster validation technique in fMRI
| Autor: | Randy Summers, R. L. Somorjai, Lawrence Ryner, Richard Baumgartner, Mark Jarmasz, Wolfgang Richter |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
Brain Mapping
Artificial neural network Computer science business.industry Alternative hypothesis Brain Pattern recognition computer.software_genre Independent component analysis Magnetic Resonance Imaging Voxel Resampling Principal component analysis Cluster Analysis Humans Radiology Nuclear Medicine and imaging Artificial intelligence Null hypothesis business computer Photic Stimulation Parametric statistics |
| Popis: | Exploratory, data-driven analysis approaches such as cluster analysis, principal component analysis, independent component analysis, or neural network-based techniques are complementary to hypothesis-led methods. They may be considered as hypothesis generating methods. The representative time courses they produce may be viewed as alternative hypotheses to the null hypothesis, ie, “no activation.” We present here a resampling technique to validate the results of exploratory fuzzy clustering analysis. In this case an alternative hypothesis is represented by a cluster centroid. For both simulated and in vivo functional magnetic resonance imaging data, we show that by permutation-based resampling, statistical significance may be computed for each voxel belonging to a cluster of interest without parametric distributional assumptions. J. Magn. Reson. Imaging 2000;11:228–231. © 2000 Wiley-Liss, Inc. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|