Oscillation Quenching in Stuart-Landau Oscillators via Dissimilar Repulsive Coupling

Quenching of oscillations, namely amplitude and oscillations death, is an emerging phenomenon exhibited by many real-world complex systems. Here, we introduce a scheme that combines dissimilar couplings and repulsive feedback links for the interactions of Stuart Landau oscillators and analytically derives the conditions required for the amplitude death. Importantly, this analysis is independent of the network size, presents a generalized approach to calculate the stability conditions for various different coupling schemes, and befits for non-identical oscillators as well. Last, we discuss the similarities of the quenching of oscillations phenomenon with the postictal generalized EEG suppression in convulsive seizures

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies.

BACKGROUND Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure. MATERIAL AND METHODS A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS). RESULTS After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left>right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=-0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=-0.357; p=0.103) and left posterior limb of the internal capsule (R=-0.319; p=0.148). CONCLUSIONS Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity

An enhanced cerebral recovery index for coma prognostication following cardiac arrest

Prognostication of coma outcomes following cardiac arrest is both qualitative and poorly understood in current practice. Existing quantitative metrics are powerful, but lack rigorous approaches to classification. This is due, in part, to a lack of available data on the population of interest. In this paper we describe a novel retrospective data set of 167 cardiac arrest patients (spanning three institutions) who received electroencephalography (EEG) monitoring. We utilized a subset of the collected data to generate features that measured the connectivity, complexity and category of EEG activity. A subset of these features was included in a logistic regression model to estimate a dichotomized cerebral performance category score at discharge. We compared the predictive performance of our method against an established EEG-based alternative, the Cerebral Recovery Index (CRI) and show that our approach more reliably classifies patient outcomes, with an average increase in AUC of 0.27

Chaos or randomness? Effect of vagus nerve stimulation during sleep on heart-rate variability

Loss of complexity and chaos of heart rate variability (HRV) of an individual increases the risk of mortality from cardiovascular diseases. Abnormalities in HRV associated with intractable epilepsy may even lead to “sudden death in epilepsy” (SUDEP). By activating the parasympathetic division of the autonomic nervous system, Vagus Nerve Stimulation (VNS) has the potential to restore the natural chaotic behavior of the heart which can be measured by the increase in complexity of HRV as indicated by complexity measures such as Effort-To-Compress (ETC) and Lempel-Ziv Complexity (LZC). In this study, we formulate and test two hypothesis – (A) chaotic time series exhibit lower temporal correlation of complexity measures such as LZ and ETC than uniformly random time series, and (B) Vagus Nerve Stimulation (VNS ON) results in chaotic cardiovascular dynamics. Hypothesis-A is verified by a simulated study on chaotic time series from the Logistic map where we see a clear decrease in temporal correlation between ETC and LZC values as the degree of chaos increases. Hypothesis-B is supported by an experimental study on a VNS implanted patient and not implanted controls. A temporal correlation analysis between complexity measures (ETC and LZC) on HRV data samples shows that VNS during sleep increases chaotic behavior in contrast to lack of VNS and in control subjects. Surrogate analysis further confirmed that VNS activation led to deterministic chaos and not stochastic randomness. Our approach proposes a clear methodology to determine the efficacy of VNS intervention in restoring the chaoticity of cardiovascular dynamics

Neurostimulation, neuromodulation, and the treatment of epilepsies

Introduction. Neurostimulation and neuromodulation are techniques that may be able to affect the course of epilepsy. In the last 20 years, since the approval of VNS, we have observed a surge of studies assessing the potential of other devices and techniques for the treatment of pharmacoresistant epilepsies including deep brain stimulation (DBS), responsive neurostimulation (RNS), trigeminal nerve stimulation (TNS), transcranial direct current stimulation (tDCS), and repetitive transcranial magnetic stimulation (rTMS). Are these devices and techniques simply another treatment option that can be offered to patients with epilepsy or do they offer specific advantages when compared to the standard antiepileptic drugs (AEDs)

Predictability and Resetting in a Case of Convulsive Status Epilepticus

In this case study, we present evidence of resetting of brain dynamics following convulsive status epilepticus (SE) that was treated successfully with antiepileptic medications (AEDs). The measure of effective inflow (EI), a novel measure of network connectivity, was applied to the continuously recorded multichannel intracranial stereoelectroencephalographic (SEEG) signals before, during and after SE. Results from this analysis indicate trends of progressive reduction of EI over hours up to the onset of SE, mainly at sites of the epileptogenic focus with reversal of those trends upon successful treatment of SE by AEDs. The proposed analytical framework is promising for elucidation of the pathology of neuronal network dynamics that could lead to SE, evaluation of the efficacy of SE treatment strategies, as well as the development of biomarkers for susceptibility to SE