Intercorrelations of Glucose Metabolic Rates between Brain Regions: Application to Healthy Males in a State of Reduced Sensory Input

Abstract

Summary:We use a correlational analysis of regional metabolic rates to characterize relations among different brain regions . Starting with rates of local glucose metab olism (rCMRglc) obtained by positron emission tomog raphy using [18F]fluorodeoxyglucose, we propose that pairs of brain regions whose rCMRglc values are signif icantly correlated are functionally associated, and that the strength of the association is proportional to the mag nitude of the correlation coefficient. Partial correlation coefficients, controlling for whole brain glucose metab olism, are used in the analysis . We also introduce a graph ical technique to display simultaneously all the correla tions, allowing us to examine patterns of relations among them . The method was applied to 40 very healthy males under conditions of reduced auditory and visual inputs (the "resting state") . Dividing the brain into 59 regions, and keeping only those partial correlation coefficients sig nificant to p < 0.01, we found the following: (a) All re gions were significantly correlated with their contralateral homologues. For the most part, the largest partial cor relation coefficients were between homologous brain re gions. (b) Generally, the pattern of significant correlations An important development in neuroscience has been the use of the 2-deoxY-D-glucose (2DG) tech nique to examine regional brain metabolism (So koloff et al., 1977). The coupling between nervous system function and oxidative metabolism or cere bral blood flow has been demonstrated repeatedly (Roy and Sherrington, 1890; Raichle et aI., 1976; Sokoloff, 198 1). The 2DG technique allows one to relate the regional cerebral metabolic rate for glu- 484between any two lobes in the left hemisphere did not differ statistically from the corresponding pattern in the right hemisphere. (c) Strong correlations were observed between primary somatosensory areas and premotor as sociation areas. Correlations between these association areas and primary visual and auditory regions were not statistically significant . (d) Significant correlations be tween inferior occipital and temporal areas were found. Metabolic rates in the superior part of the occipital lobe were not correlated significantly with metabolic rates in regions of the temporal lobe, nor with metabolism in the parietal lobe. (e) As a whole, there were numerous cor relations among frontal and parietal lobe regions, on the one hand, and among temporal and occipital lobe regions, on the other, but few statistically significant correlations between these two domains. We relate our results to var ious aspects of known brain anatomy, physiology, and cognitive functioning.

Glutamatergic Function in the Resting Awake Human Brain is Supported by Uniformly High Oxidative Energy

“…[31][32][33][34][35] The meta-analysis was composed of CMR O2 and CMR glc values from as few as 23 and as many as 46 distinct brain areas in 109 subjects. BioImage Suite (www.…”

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

“…This neuroimaging tool may hence be well suitable for exploring the baseline integrity of neuronal networks (Rocher et al, 2003) such as the DMN (Lee et al, 2008;Rilling et al, 2007). Although proposed more than 25 years ago (Clark et al, 1984;Horwitz et al, 1984;Metter et al, 1984), the method of interregional correlations has been validated for whole brain voxel-wise analyses only recently (Lee et al, 2008). In addition to the seed-based approaches as those mentioned above, covariance patterns in FDG-PET data can also be examined using multivariate analyses (Salmon et al, 2009;Zuendorf et al, 2003).…”

The elusive concept of brain connectivity

“…Prior to positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), the nontomographic xenon-133 inhalation technique was used to image functional brain activity in humans, and correlations between pairs of surface detectors (usually just the homologous left-right detectors) were evaluated (Prohovnik et al, 1980). Once PET studies of glucose metabolism began to be performed, several groups used region of interest methods to examine interregional correlations (across subjects) (Bartlett et al, 1987;Clark et al, 1984;Horwitz et al, 1984;Metter et al, 1984). Similar analyses were performed on autoradiographic data (usually 14 C-deoxyglucose) in nonhuman mammals (usually rats; e.g., Soncrant et al, 1992).…”