TITLE: On clustering fMRI time series
AUTHOR:
Cyril Goutte,
Peter Toft,
Egill Rostrup*,
Finn Årup Nielsen and
Lars Kai Hansen
Department of Mathematical Modelling,
Technical University of Denmark, Lyngby, Denmark
cg,pto,fn,lkhansen@imm.dtu.dk
http://eivind.imm.dtu.dk
*The Danish Research Centre for Magnetic Resonance,
Hvidovre, Denmark,
egillr@magnet.drcmr.dk
ABSTRACT:
Analysis of fMRI time series is often performed by extracting one or
more parameters for the individual voxel. Methods based e.g.\ on
various statistical tests are then used to yield parameters
corresponding to probability of activation or activation
strength. However, these methods do not indicate whether sets of voxels
are activated in a similar way, or activated in different ways.
Typically, delays between two activated signals are not identified. In
this article, we use clustering methods to detect similarities in
activation between voxels. We employ a novel metric which measures the
similarity between the activation stimulus and the fMRI signal. We
present two different clustering algorithms and use them to identify
regions of similar activations in an fMRI experiment involving a
visual stimulus.
IMM technical report IMM-REP-1998-11
A slightly different version will appear in NeuroImage.
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