During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an “EEG-element connectivity” methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence of EEG microstructural elements. Network characterization of specified physiological or pathological EEG microstructural elements can potentially be of great importance in the understanding, identification, and prediction of health and disease.

The role of heart rate reduction in the management of myocardial ischemia and chronic stable angina is pivotal. However, broad use and appropriate dosing of commonly used rate-slowing drugs is limited by their poor tolerability. Ivabradine is a selective inhibitor of the If currents of the sinoatrial node cells. If currents activity determines the slope of the depolarization curve towards the threshold level controlling heart rate in patients with sinus rhythm. Ivabradine, a compound of the benzocyclobutane (S 16257), exhibits a unique specificity for the If current and has a more favorable profile of adverse reactions compared to other If inhibitors. Accordingly, ivabradine has been used in the treatment of stable angina, where it presented anti-anginal and anti-ischemic effects equivalent to the effects of atenolol and amlodipine. Clinical studies proved the efficacy of ivabradine in patients with stable angina, while clinical data are awaited to verify its probable value in the treatment of atrial tachyarrhythmias and tachycardia due to ventricular dysfunction. Thus, the clinical value of ivabradine, which has completed clinical development for stable angina, is expected to exceed its role in the treatment of myocardial ischemia. In this context, ivabradine, promising efficacious and safe pharmacological management of heart rate, is a huge step in cardiovascular therapeutics.

SummaryWe studied slow (≤2.5 Hz) nonevolving generalized periodic epileptiform discharges (GPEDs) in the electroencephalogram (EEG) of comatose patients after cardiac arrest (CA) in search of evidence that could assist early diagnosis of possible hypoxic nonconvulsive status epilepticus (NCSE) and its differentiation from terminal brain anoxia (BA), which can present with a similar EEG pattern. We investigated the topography of the GPEDs in the first post‐CA EEGs of 13 patients, using voltage‐mapping, and compared findings between two patients with NCSE and GPEDs > 2.5 Hz (group 1), and 11 with GPEDs ≤ 2 Hz, of whom six had possible NCSE (group 2) and five had terminal BA (group 3). Voltage mapping showed frontal maximum for the negative phase of the GPEDs in all patients of groups 1 and 2, but not in any of the patients of group 3, who invariably showed maximization of the negative phase posteriorly. Morphology, amplitude, and duration of the GPEDs varied across the groups, without distinctive features for possible NCSE. These findings provide evidence that, in hypoxic coma after CA with slow GPEDs, anterior topography of the maximum GPED negativity on voltage mapping may be a distinctive biomarker for possible NCSE contributing to the coma.