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On clustering fMRI time series.

Abstract：

:Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. 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 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 that 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.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Goutte C,Toft P,Rostrup E,Nielsen F,Hansen LK

doi

10.1006/nimg.1998.0391

keywords:

subject

Has Abstract

pub_date

1999-03-01 00:00:00

pages

298-310

issue

3

eissn

1053-8119

issn

1095-9572

pii

S1053811998903913

journal_volume

9

pub_type

杂志文章

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