The Relationship between Glucose Metabolism, Resting-State fMRI BOLD Signal, and GABA_A-Binding Potential: A Preliminary Study in Healthy Subjects and Those with Temporal Lobe Epilepsy

Abstract

Glucose metabolism has been associated with magnitude of blood oxygen level-dependent (BOLD) signal and connectivity across subjects within the default mode and dorsal attention networks. Similar correlations within subjects across the entire brain remain unexplored. [18 F]-fluorodeoxyglucose positron emission tomography ([ 18 F]-FDG PET), [ 11 C]-flumazenil PET, and resting-state functional magnetic resonance imaging (fMRI) scans were acquired in eight healthy individuals and nine with temporal lobe epilepsy (TLE). Regional metabolic rate of glucose (rMRGlu) was correlated with amplitude of low frequency fluctuations (ALFFs) in the fMRI signal, global fMRI connectivity (GC), regional homogeneity (ReHo), and gamma-aminobutyric acid A-binding potential (GABA A BP ND ) across the brain. Partial correlations for ALFFs, GC, and ReHo with GABA A BP ND were calculated, controlling for rMRGlu. In healthy subjects, significant positive correlations were observed across the brain between rMRGlu and ALFF, ReHo and GABA A BP ND , and between ALFFs and GABA A BP ND , controlling for rMRGlu. Brain-wide correlations between rMRGlu and ALFFs were significantly lower in TLE patients, and correlations between rMRGlu and GC were significantly greater in TLE than healthy subjects. These results indicate that the glutamatergic and GABAergic systems are coupled across the healthy human brain, and that ALFF is related to glutamate use throughout the healthy human brain. TLE may be a disorder of altered long-range connectivity in association with glutamate function.

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

“…For instance, glutamate levels in the posterior cingulate measured via magnetic resonance spectroscopy (MRS) were shown to strongly correlate with DMN connectivity (Kapogiannis et al, 2013), and glucose metabolism is related to connectivity within both the DMN and the dorsal attention network (Tomasi et al, 2013). Nevertheless, this correlation may be confined to these specific networks rather than reflect a general relationship across the brain within subjects, at least in healthy individuals (Nugent et al, 2015a). The specificity of the relationship between glutamate and connectivity to the DMN is consistent with our finding of a relationship between glutamate and connectivity in the sgACC (sometimes included as a DMN region), but not in the amygdala.…”

Evidence for Thalamocortical Circuit Abnormalities and Associated Cognitive Dysfunctions in Underweight Individuals with Anorexia Nervosa

“…To address this issue, we performed two sensitivity analyses in which (a) we examined the potential impact of malnutrition on our resting-state connectivity findings by assessing group differences in the ALFF in blood-oxygen-level dependent (BOLD) signal, a proxy measure of glucose metabolism in the brain (Nugent et al, 2015;Tomasi et al, 2013), within the thalamus, AntPFC, and DLPFC and (b) we assessed the extent to which current BMI, one index of malnutrition, correlated with our main study findings in the AN group. We found no group differences in ALFF within any of the examined thalamofrontal regions, suggesting that the AN group did not exhibit alterations in BOLD signal that may have confounded the results of our resting-state connectivity analyses.…”

The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

“…Nugent et al (2015) compared ALFF, whole-brain correlation, and glucose consumption in individuals with temporal lobe epilepsy and healthy controls using spatial correlation. They found ALFF more similar to glucose consumption in healthy controls, but whole-brain correlation more similar in patients (Nugent et al, 2015). It is difficult to compare these results to our study, however, as spatial correlation is independent of spatial mean, which were shifted between states (Fig.…”

“…Changes in these networks occur under various diseases, and can closely match changes in brain metabolism due to that disease, for example, in Alzheimer's (Perrotin et al, 2015). This has created much interest in better understanding the metabolic basis of R-fMRI networks (Duncan et al, 2013;Hyder et al, 2013;Nugent et al, 2015;Tomasi et al, 2013;Vaishnavi et al, 2010). R-fMRI is noninvasive and, compared to other methods (e.g., positron emission tomography, PET), easy to acquire.…”