Data di Pubblicazione:
2011
Abstract:
The cingulate cortex is a structurally heterogeneous brain region involved in emotional, cognitive and motor tasks. With the aim of identifying which behavioral domains are associated with the activation of the cingulate cortex, we performed a structure based-meta-analysis using the activation likelihood estimation (ALE), which assesses statistical significant convergence of neuroimaging studies using the BrainMap database. To map the meta-analytic coactivation maps of the cingulate cortex (MACM), we subdivided the parenchyma along the rostro-caudal axis in 12 bilateral equispaced ROIs. ROIs were not chosen according to previously suggested subdivisions, as to obtain a completely data-driven result. Studies were included with one or more activation coordinates in at least one of the 12 pre-defined ROIs. The meta-analytic connectivity profile and behavioral domains profiles were identified for each ROI. Cluster analysis was then performed on the MACM and behavioral domains to group together ROIs with similar profiles. The results showed that the cingulate cortex can be divided in three clusters according to the MACM parcellation and in four according to the behavioral domain-based parcellation. In addition, a behavioral-domain based meta-analysis was conducted and the spatial consistency of functional connectivity patterns across different domain-related ALE results was evaluated by computing probabilistic maps. These maps identified some portions of the cingulate cortex as involved in several tasks. Our results showed the existence of a more specific functional characterization of some portions of the cingulate cortex but also a great multifunctionality of others. By analyzing a large number of studies, structure based meta-analysis can greatly contribute to new insights in the functional significance of brain activations and in the role of specific brain areas in behavior.
Tipologia CRIS:
03A-Articolo su Rivista
Keywords:
Functional magnetic resonance imaging; fMRI; Cingulate cortex; Activation likelihood estimation; Meta-analytic connectivity modeling
Elenco autori:
Torta DM; Cauda F
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