Gastric Electrical Slow Wave Functional MRI of the Human Brain

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Gastric Electrical Slow Wave Functional MRI of the Human Brain “Resting-state” fMRI (rsfMRI) is a noninvasive neuroimaging method that uses MRI acquisitions optimized for monitoring hemodynamic sequelae of task-evoked changes in brain activity (blood oxygenation level dependent or BOLD, task-fMRI) to observe activity in the brain “at rest”. The resulting MRI data manifest what are generally regarded as spontaneous fluctuations in intrinsic brain networks, allowing study of functional connectivity. Such phenomena may offer novel biomarkers for clinical populations, if they can be assessed without interference from other MRI effects and physiological phenomena. A recent report combining concurrent surface electrogastrography (EGG) and rsfMRI shows that the electrical slow wave (normogastric period of about 20 seconds), generated by interstitial cells of Cajal in the stomach, appears to drive activity in a brain “gastric network” including somato-motor cortices, dorsal precuneus, and the extrastriate body area. This observation that significant brain activity is not “spontaneous” in the sense of originating in the brain, but rather is driven by a “pacemaker” in the stomach, can be seen in two complementary ways: Either as a nuisance that confounds rsfMRI – suggesting the goal of modeling and reducing these effects – or as introducing a new technology for study of the embodied brain – suggesting the complementary goal of exploiting these effects. We will pursue three aims: 1. Estimate and reduce contributions of the slow gastric rhythm to established rsfMRI metrics. 2. Demonstrate whether controlling gastric state – fasted vs. fed – can reduce the impact of the gastric rhythm on established rsfMRI metrics. 3. Characterize the effects of gastric rhythm and state on the gastric network, and other brain regions. Accounting for brain activity driven by the basal gastric rhythm will enhance the ability to study spontaneous fluctuations in the brain's intrinsic networks, by allowing for the modeling of hitherto unexplained variability. Controlling gastric state has the potential to improve statistical power by reducing inter-session and inter-subject variance. Characterizing the effects of gastric rhythm and state on the brain will yield new measures of stomach/brain interactions, that could lead to novel studies in eating disorders ranging from anorexia to obesity.