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These results are not a replication of the original study. They do, however, support the hypothesis that this polymorphism influences the clinical use of phenytoin. They also demonstrate the utility of using multiple phenotypes in pharmacogenetics studies, particularly when attempting to separate pharmacokinetic and pharmacodynamic effects. As the SCN1A polymorphism affects phenytoin pharmacodynamics, it is particularly useful to obtain data on serum levels in addition to dose because association of a pharmacodynamic variant may be stronger with serum levels than dose as the serum level may eliminate or reduce pharmacokinetic variability.

Febrile infection-related epilepsy syndrome (FIRES) is a severe epilepsy disorder that affects previously healthy children. It carries high likelihood of unfavourable outcome and putative aetiology relates to an auto-inflammatory process. Standard antiepileptic drug therapies including intravenous anaesthetic agents are largely ineffective in controlling status epilepticus in FIRES. Deep brain stimulation of the centromedian thalamic nuclei (CMN-DBS) has been previously used in refractory status epilepticus in only a few cases. The use of Anakinra (a recombinant version of the human interleukin-1 receptor antagonist) has been reported in one case with FIRES with good outcome. Here we describe two male paediatric patients with FIRES unresponsive to multiple anti-epileptic drugs, first-line immune modulation, ketogenic diet and cannabidiol. They both received Anakinra and underwent CMN-DBS. The primary aim for CMN-DBS therapy was to reduce generalized seizures. CMN-DBS abolished generalized seizures in both cases and Anakinra had a positive effect in one.This patient had a favourable outcome whereas the other did not. These are the first reported cases of FIRES where CMN-DBS has been used.

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials (CCEP) at distant sites because of white matter connectivity. CCEPs provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the CCEPs recorded in a large multicentric database. Specifically, we considered each CCEP as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first CCEP component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with

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