Recovering spatially localised sources from fMRI data

NemoImage

13, Number

6, 2001,

Part 2 of 2 Parts 1 D E .C;L@

METHODS

- ANALYSIS

Recovering Spatially Localised Sources from fMR1 Data J Porrill*, J V Stone*, N R Porter*, N M Hunkin? *Department of Psychology, University of Shefield TDepartment of Clinical Neurology, University of Shefield Canonical variate analysis (CVA) can been used to identify the statistically significant modes of variation in imaging data sets for a given temporal design matrix (Friston et al. 1996). In cases where more than one significant mode is recovered the results can be difficult to interpret. We have described elsewhere (Ponill et al. 2000) a modified spatial independent component analysis (McKeown 1998) algorithm which recovers spatially localised sources by maximising histogram skewness rather than kurtosis. Skew ICA has robustness properties which make it particularly suitable for application to the spatial response maps associated with the significant canonical temporal modes. Here we present a test data set for which CVA followed by skew ICA leads to spatially localised sources with plausible temporal response functions. (The results of this analysis can be viewed at http://www.sheffield. act&/-pcljvsl). The data was obtained from a 1.5T Eclipse (Marconi Medical Systems, Ohio) using a gradient recalled, single shot echo planar imaging (EPI) sequence (TE = 40ms; TR = 3s). 96 T2* brain volumes (10 contiguous slices, thickness = 5mm; matrix = 128x 128; FOV = 240mm) were used in the analysis. The stimuli were 4Hz phase changing chequer boards alternating between left and right visual fields with a central fixation cross. Each hemifield stimulus was presented for 2s with a 10s interval before the next presentation (protocol based on Burock et al. 1998). Analysis using SPM99 (http://www.fil.ion.ucl.ac.uk/spm/) found broad areas of significant (corrected p
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