Epilepsy-related brain networks in ring chromosome 20 syndrome : an EEG-fMRI study

Objective To identify the brain networks that are involved in the different electroencephalography (EEG) abnormalities in patients with ring chromosome 20 [r(20)] syndrome. We hypothesize the existence of both distinctive and common brain circuits for the paroxysmal high voltage sharp waves (hSWs), the seizures, and the slow-wave 3–7 Hz rhythm that characterize this condition. Methods Thirteen patients with [r(20)] syndrome were studied by means of EEG simultaneously recorded with functional magnetic resonance imaging (EEG-fMRI). EEG traces were reviewed in order to detect the pathologic interictal (hSWs) and ictal activities; the 3–7 Hz theta-delta power was derived using a fast Fourier transform. A group-level analysis was performed for each type of EEG abnormality separately using a fixed-effect model and a conjunction analysis. Finally, a second-level random-effect model was applied considering together the different EEG abnormalities, without distinction between hSW, seizures, or theta-delta rhythms. Results Subcontinuous theta-delta rhythm was recorded in seven patients, seizures in two, and hSWs in three patients. The main results are the following: (1) the slow-wave rhythm was related to blood oxygen level–dependent (BOLD) increases in the premotor, sensory-motor, and temporoparietal cortex, and to BOLD decrements involving the default mode (DMN) and the dorsal attention networks (DANs); (2) the ictal-related BOLD changes showed an early involvement of the prefrontal lobe; (3) increases in BOLD signal over the basal ganglia, either for interictal and ictal activities, were observed; (4) a common pattern of positive BOLD changes in the bilateral perisylvian regions was found across the different EEG abnormalities. Significance The BOLD increment in the perisylvian network and the decrease of the DMN and DAN could be the expression of the [r(20)] syndrome–related cognitive and behavioral deficits. The observed BOLD patterns are similar to the ones detected in other epileptic encephalopathies, suggesting that different epileptic disorders characterized by neurobehavioral regression are associated with dysfunction in similar brain networks.