ObjectiveTo investigate the neuronal correlates of spontaneous laughter in drug-naive pediatric patients with narcolepsy type I (NT1) compared to healthy controls by means of blood oxygen level-dependent (BOLD) MRI.MethodsTwenty-one children/adolescents with recent onset of NT1 and 21 age- and sex-matched healthy controls were studied with fMRI while viewing funny videos using a naturalistic paradigm. Whole-brain hemodynamic correlates of spontaneous laughter were investigated in each group and compared by use of appropriate second-level general linear model analyses. If recorded, cataplexy events were treated as the effect of no interest at the single-participant level. Correlations analyses between these contrasts and behavioral findings were performed.ResultsEmotion-induced laughter occurred in 16 patients (294 events) and 21 controls (357 events). In controls, laughter-related BOLD increases involved a widespread cortical and subcortical network including the bilateral motor and premotor areas, cingulated cortex, insula, and amygdala. In NT1, laughter induced BOLD signal increments in the motor cortex, right thalamus, and left subthalamic nucleus/zona incerta (STN/ZI). STN/ZI and thalamic changes were significantly higher during fMRI sessions with laughter without cataplexy compared to sessions in which laughter was associated with cataplexy.ConclusionLaughter expression in individuals with NT1 involves different brain circuits compared to controls by means of overactivation of cortical and subcortical regions belonging to the volitional control of laughter. The activation of the STN/ZI region observed predominantly in patients with NT1 during laugh episodes without cataplexy suggests that the ZI could act to prevent cataplexy.
Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies.However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated.Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
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