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. 2012 Sep;11(3):739-48.
doi: 10.1007/s12311-011-0333-7.

Metabolic changes of cerebrum by repetitive transcranial magnetic stimulation over lateral cerebellum: a study with FDG PET

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Metabolic changes of cerebrum by repetitive transcranial magnetic stimulation over lateral cerebellum: a study with FDG PET

Sang Soo Cho et al. Cerebellum. 2012 Sep.

Abstract

To better understand the functional role of cerebellum within the large-scale cerebellocerebral neural network, we investigated the changes of neuronal activity elicited by cerebellar repetitive transcranial magnetic stimulation (rTMS) using (18)F-fluorodeoxyglucose (FDG) and positron emission tomography (PET). Twelve right-handed healthy volunteers were studied with brain FDG PET under two conditions: active rTMS of 1 Hz frequency over the left lateral cerebellum and sham stimulation. Compared to the sham condition, active rTMS induced decreased glucose metabolism in the stimulated left lateral cerebellum, the areas known to be involved in voluntary motor movement (supplementary motor area and posterior parietal cortex) in the right cerebral hemisphere, and the areas known to be involved in cognition and emotion (orbitofrontal, medial frontal, and anterior cingulate gyri) in the left cerebral hemisphere. Increased metabolism was found in cognition- and language-related brain regions such as the left inferior frontal gyrus including Broca's area, bilateral superior temporal gyri including Wernicke's area, and bilateral middle temporal gyri. Left cerebellar rTMS also led to increased metabolism in the left cerebellar dentate nucleus and pons. These results demonstrate that rTMS over the left lateral cerebellum modulates not only the target region excitability but also excitability of remote, but interconnected, motor-, language-, cognition-, and emotion-related cerebral regions. They provide further evidence that the cerebellum is involved not only in motor-related functions but also in higher cognitive abilities and emotion through the large-scale cerebellocereberal neural network.

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