Resting-State Networks as Simultaneously Measured with Functional MRI and PET

Abstract

Functional MRI (fMRI) studies reported disruption of resting-state networks (RSNs) in several neuropsychiatric disorders. PET with 18 F-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 18 F-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.

Vulnerability of multiple large‐scale brain networks in dementia with Lewy bodies

“…Here, we adopted another validated [18F]FDG–PET connectivity approach, addressing multiple RSNs and network‐level alterations. Notably, this approach allows to reliably estimate topographies of large‐scale brain networks using [18F]FDG–PET data, at difference from data‐driven approaches, such as independent component analysis, for which problems emerged in the analysis of some RSNs (Di et al, ; Savio et al, ). For example, it was reported, with [18F]FDG–PET data, a less accurate identification of anteroposterior RSNs in comparison with fMRI data (Di et al, ).…”

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy

“…MCNs measure the covariant relationship of brain metabolism through a multivariate method, which enables the exploration of complex interactions among multiple brain regions with metabolic connectivity. Metabolic connectivity is a valuable concept in the fast‐developing field of brain connectivity, which less dependent on neurovascular coupling as in fMRI and are indicative of a presumed steady state of neuronal activity during the recording interval . Growing evidence indicates that metabolic connectivity may serve a marker of normal and pathological cognitive function .…”

Genetic interaction is associated with lower metabolic connectivity and memory impairment in clinically mild Alzheimer's disease

“…The neuronal connectivity in the DMN as observed in functional magnetic resonance imaging (fMRI) and FDG‐PET enables the detection of functional connectivity and metabolic connectivity, respectively. Despite recording different aspects of neuronal connectivity, both imaging modalities identify similar brain networks . Compared with fMRI, FDG‐PET captures neuronal activity and connectivity that is independent of vascular coupling and is in a steady state for a longer time span .…”

“…Despite recording different aspects of neuronal connectivity, both imaging modalities identify similar brain networks. 8 Compared with fMRI, FDG-PET captures neuronal activity and connectivity that is independent of vascular coupling and is in a steady state for a longer time span. 9 Brain networks observed in FDG-PET have been shown to progressively disintegrate as AD progresses.…”