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Title: Verbal fluency as a prefrontal activation probe: a validation study using 99mTc-ECD brain SPET
Authors: Audenaert, Koenraad ×
Brans, B
Van Laere, Koen
Lahorte, P
Versijpt, J
van Heeringen, K
Dierckx, R #
Issue Date: Dec-2000
Publisher: Springer-verlag
Series Title: European journal of nuclear medicine vol:27 issue:12 pages:1800-8
Abstract: This study aimed to investigate the feasibility of brain single-photon emission tomography (SPET) in the letter and category fluency paradigm of the Controlled Oral Word Association (COWA) test in healthy volunteers. Two groups each comprising ten right-handed healthy volunteers were injected twice with 370 MBq technetium-99m ethyl cysteinate dimer following a split-dose paradigm (resting and activation condition). Statistical parametric mapping (SPM96) was used to determine voxelwise significant changes. The letter fluency and the category fluency activation paradigm had a differential brain activation pattern. The posterior part of the left inferior prefrontal cortex (LIPC) was activated in both paradigms, with the category fluency task having an extra activation in the anterior LIPC. In the category fluency task, but not the letter fluency task, an activation in the right inferior prefrontal cortex was found. These findings confirm to a large extent the results of previous functional magnetic resonance imaging and positron emission tomography studies in semantic and phonological activation paradigms. The choice and validity of various methodological characteristics of the experimental design leading to these results are critically discussed. It is concluded that brain SPET activation with the letter fluency and category fluency paradigm under standard neuropsychological conditions in healthy volunteers is both technically and practically feasible.
URI: 
ISSN: 0340-6997
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Nuclear Medicine & Molecular Imaging
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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