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@ARTICLE{Dinkel:141386,
author = {Dinkel, P. H. and Willmes, Klaus and Krinzinger, Helga and
Konrad, Kerstin and Koten Jr, Jan Willem},
title = {{D}iagnosing {D}evelopmental {D}yscalculia on the {B}asis
of {R}eliable {S}ingle {C}ase {FMRI} {M}ethods: {P}romises
and {L}imitations},
journal = {PLoS one},
volume = {8},
number = {12},
issn = {1932-6203},
address = {Lawrence, Kan.},
publisher = {PLoS},
reportid = {FZJ-2013-06566},
pages = {e83722 -},
year = {2013},
abstract = {FMRI-studies are mostly based on a group study approach,
either analyzing one group or comparing multiple groups, or
on approaches that correlate brain activation with
clinically relevant criteria or behavioral measures. In this
study we investigate the potential of fMRI-techniques
focusing on individual differences in brain activation
within a test-retest reliability context. We employ a
single-case analysis approach, which contrasts dyscalculic
children with a control group of typically developing
children. In a second step, a support-vector machine
analysis and cluster analysis techniques served to
investigate similarities in multivariate brain activation
patterns. Children were confronted with a non-symbolic
number comparison and a non-symbolic exact calculation task
during fMRI acquisition. Conventional second level group
comparison analysis only showed small differences around the
angular gyrus bilaterally and the left parieto-occipital
sulcus. Analyses based on single-case statistical procedures
revealed that developmental dyscalculia is characterized by
individual differences predominantly in visual processing
areas. Dyscalculic children seemed to compensate for
relative under-activation in the primary visual cortex
through an upregulation in higher visual areas. However,
overlap in deviant activation was low for the dyscalculic
children, indicating that developmental dyscalculia is a
disorder characterized by heterogeneous brain activation
differences. Using support vector machine analysis and
cluster analysis, we tried to group dyscalculic and
typically developing children according to brain activation.
Fronto-parietal systems seem to qualify for a distinction
between the two groups. However, this was only effective
when reliable brain activations of both tasks were employed
simultaneously. Results suggest that deficits in number
representation in the visual-parietal cortex get compensated
for through finger related aspects of number representation
in fronto-parietal cortex. We conclude that dyscalculic
children show large individual differences in brain
activation patterns. Nonetheless, the majority of
dyscalculic children can be differentiated from controls
employing brain activation patterns when appropriate methods
are used.},
cin = {INM-3},
ddc = {500},
cid = {I:(DE-Juel1)INM-3-20090406},
pnm = {333 - Pathophysiological Mechanisms of Neurological and
Psychiatric Diseases (POF2-333)},
pid = {G:(DE-HGF)POF2-333},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000328705200135},
pubmed = {pmid:24349547},
doi = {10.1371/journal.pone.0083722},
url = {https://juser.fz-juelich.de/record/141386},
}