PURPOSE: Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. MATERIALS AND METHODS: Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n = 70) or as population-based cytoarchitectonic Brodmann areas (BA; n = 28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. RESULTS: In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. CONCLUSIONS: These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain.
PURPOSE: Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. MATERIALS AND METHODS: Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n = 70) or as population-based cytoarchitectonic Brodmann areas (BA; n = 28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. RESULTS: In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. CONCLUSIONS: These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain.
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