A hierarchical density-based clustering analysis of auditory fMRI activation data

被引：3

作者：

Deleus, FF ^{[1
]}

De Mazière, PA ^{[1
]}

Gautama, T ^{[1
]}

Van Hulle, MM ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Neuro & Psychofysiol Lab, B-3000 Louvain, Belgium

来源：

NEURAL NETWORKS FOR SIGNAL PROCESSING XI | 2001年

关键词：

D O I：

10.1109/NNSP.2001.943106

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new tool for analysing functional Magnetic Resonance Imaging (fMRI) data is introduced. The tool is based on the hierarchical clustering of the Fourier-transformed regression coefficients obtained by regressing the known task sequence with the individual fMRI signals. The clustering analysis is density-based and performed with topographic maps. The tool is tested on a standard data set and the results are compared with those obtained by Statistical Parametric Mapping (SPM), the most widely used tool in the field.

引用

页码：13 / 22

页数：10

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