Open AccessCluster analysis in individual functional brain images: Some new techniques to enhance the sensitivity of activation detection methods
Author(s) -
Poline JeanBaptiste,
Mazoyer Bernard
Publication year - 1994
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.460020110
Subject(s) - sensitivity (control systems) , voxel , pattern recognition (psychology) , computer science , artificial intelligence , selection (genetic algorithm) , signal (programming language) , decomposition , noise (video) , cluster (spacecraft) , biological system , chemistry , image (mathematics) , organic chemistry , electronic engineering , engineering , programming language , biology
Low signal‐to‐noise ratio is the fundamental limit of current voxel‐based strategies for detecting activations in functional brain maps. We propose some new techniques to enhance detection sensitivity in the analysis of brain activation maps. These new techniques are: (1) a multi‐filtering strategy; and (2) the use of a hierarchical decomposition. Multi‐filtering is used to optimize detection sensitivity when multiple signals of various sizes are present, while hierarchical decomposition allows selection of activation foci on the basis of their spatial extent and magnitude. Both techniques are combined within a single testing procedure that contrals the overall type I error. This approach shows significantly higher detectioin sensitivity on both simulated and experimental single‐subject datasets. ©1994 Wiley‐Liss, Inc.