Intersubject variability in functional neuroanatomy of silent verb
generation: assessment by a new activation detection algorithm based on
amplitude and size information
Abstract:
We present an experimental evaluation of a new algorithm for the
detection of activated areas in brain functional maps. The new
algorithm, named HMSD, is based on a hierarchical multiscale description
of the difference image in terms of connected objects. Size and
magnitude of each object are simultaneously tested with respect to a
bidimensional frequency distribution derived using Monte-Carlo
simulations under the null hypothesis. In the present work. HMSD was
applied to the analysis of a silent verb generation PET activation
protocol conducted in six right-handed subjects. Applied to single-
subject data. HMSD reveals activation located in the left inferior
frontal gyrus in three subjects (two in the pars opercularis, one in the
pars triangularis), and in the pars opercularis of the right inferior
frontal gyrus in one case, the latter being combined to a crossed
cerebellar activation. Overall, single-case results were consistent with
the analyses of stereotactically averaged data. Despite a 2D
implentation. HMSD detection performances of averaged data were better
than that obtained with the 2D version of statistical parametric mapping
(SPM) and comparable to that of the 3D version of SPM