fmri.cluster function

Cluster thresholding.

Detection of activated regions using cluster thresholding.

fmri.cluster(spm, alpha = 0.05, ncmin = 2, ncmax=ncmin, 
             minimum.signal = 0, verbose = FALSE)

Arguments

• spm: fmrispm object
• alpha: multiple test (over volume and cluster sizes) adjusted significance level used for thresholds.
• ncmin: minimal cluster size used. An activation is detected if for any clustersize in nvmin:20 the size specific threshold is exceeded.
• ncmax: maximal cluster size used. An activation is detected if for any clustersize in ncmin:ncmax the size specific threshold is exceeded.
• minimum.signal: allows to specify a (positive) minimum value for detected signals. If minimum.signal >0 the thresholds are to conservative, this case needs further improvements.
• verbose: intermediate diagnostics

Details

Approximate thresholds for the existence of a cluster with spm-values exceeding a 1-beta threshold k_{nc,na:ne} for cluster size nc

are based on a simulation study under the hypothesis and adjusted for number of voxel in mask and spatial correlation. beta is chosen such that under the hypothesis the combined (over cluster sizes ncmin:ncmax) test has approximate significance level alpha.

Returns

Object with class attributes "fmripvalue" and "fmridata" - pvalue: cluster based p-values for voxel that were detected for any cluster size, a value of 1 otherwise.

• mask: mask of detected activations

• weights: voxelsize ratio

• dim: data dimension

• hrf: expected BOLD response for contrast (single stimulus only)

Author(s)

Joerg Polzehl polzehl@wias-berlin.de

See Also

fmri.lm, fmri.pvalue, fmri.searchlight

Examples

## Not run: fmri.cluster(fmrispmobj)