Functional MRI (fMRI) studies reported disruption of resting-state networks (RSNs) in several neuropsychiatric disorders. PET with 18F-FDG captures neuronal activity that is in steady state at a longer time span and is less dependent on neurovascular coupling. Methods: In the present study, we aimed to identify RSNs in 18F-FDG PET data and compare their spatial pattern with those obtained from simultaneously acquired resting-state fMRI data in 22 middle-aged healthy subjects. Results: Thirteen and 17 meaningful RSNs could be identified in PET and fMRI data, respectively. Spatial overlap was fair to moderate for the default mode, left central executive, primary and secondary visual, sensorimotor, cerebellar, and auditory networks. Despite recording different aspects of neural activity, similar RSNs were detected by both imaging modalities. Conclusion: The results argue for the common neural substrate of RSNs and encourage testing of the clinical utility of resting-state connectivity in PET data.
Keywords: brain connectivity; glucose metabolism; independent component analysis; multimodal imaging; positron emission tomography.
© 2017 by the Society of Nuclear Medicine and Molecular Imaging.