Consensus on diagnosis and management of JME: From founder's observations to current trends.

An international workshop on juvenile myoclonic epilepsy (JME) was conducted in Avignon, France in May 2011. During that workshop, a group of 45 experts on JME, together with one of the founding fathers of the syndrome of JME ("Janz syndrome"), Prof. Dr. Dieter Janz from Berlin, reached a consensus on diagnostic criteria and management of JME. The international experts on JME proposed two sets of criteria, which will be helpful for both clinical and scientific purposes. Class I criteria encompass myoclonic jerks without loss of consciousness exclusively occurring on or after awakening and associated with typical generalized epileptiform EEG abnormalities, with an age of onset between 10 and 25. Class II criteria allow the inclusion of myoclonic jerks predominantly occurring after awakening, generalized epileptiform EEG abnormalities with or without concomitant myoclonic jerks, and a greater time window for age at onset (6-25years). For both sets of criteria, patients should have a clear history of myoclonic jerks predominantly occurring after awakening and an EEG with generalized epileptiform discharges supporting a diagnosis of idiopathic generalized epilepsy. Patients with JME require special management because their epilepsy starts in the vulnerable period of adolescence and, accordingly, they have lifestyle issues that typically increase the likelihood of seizures (sleep deprivation, exposure to stroboscopic flashes in discos, alcohol intake, etc.) with poor adherence to antiepileptic drugs (AEDs). Results of an inventory of the different clinical management strategies are given. This article is part of a supplemental special issue entitled Juvenile Myoclonic Epilepsy: What is it Really?

Juvenile myoclonic epilepsy has hyper dynamic functional connectivity in the dorsolateral frontal cortex.

PURPOSE: Characterize the static and dynamic functional connectivity for subjects with juvenile myoclonic epilepsy (JME) using a quantitative data-driven analysis approach. METHODS: Whole-brain resting-state functional MRI data were acquired on a 3 T whole-body clinical MRI scanner from 18 subjects clinically diagnosed with JME and 25 healthy control subjects. 2-min sliding-window approach was incorporated in the quantitative data-driven data analysis framework to assess both the dynamic and static functional connectivity in the resting brains. Two-sample t-tests were performed voxel-wise to detect the differences in functional connectivity metrics based on connectivity strength and density. RESULTS: The static functional connectivity metrics based on quantitative data-driven analysis of the entire 10-min acquisition window of resting-state functional MRI data revealed significantly enhanced functional connectivity in JME patients in bilateral dorsolateral prefrontal cortex, dorsal striatum, precentral and middle temporal gyri. The dynamic functional connectivity metrics derived by incorporating a 2-min sliding window into quantitative data-driven analysis demonstrated significant hyper dynamic functional connectivity in the dorsolateral prefrontal cortex, middle temporal gyrus and dorsal striatum. Connectivity strength metrics (both static and dynamic) can detect more extensive functional connectivity abnormalities in the resting-state functional networks (RFNs) and depict also larger overlap between static and dynamic functional connectivity results. CONCLUSION: Incorporating a 2-min sliding window into quantitative data-driven analysis of resting-state functional MRI data can reveal additional information on the temporally fluctuating RFNs of the human brain, which indicate that RFNs involving dorsolateral prefrontal cortex have temporal varying hyper dynamic characteristics in JME patients. Assessing dynamic along with static functional connectivity may provide further insights into the abnormal function connectivity underlying the pathological brain functioning in JME.