Joint EEG/fMRI state space model for the detection of directed interactions in human brains--a simulation study

An often addressed challenge in neuroscience research is the assignment of different tasks to specific brain regions. In many cases several brain regions are activated during a single task. Therefore, one is also interested in the temporal evolution of brain activity to infer causal relations between activated brain regions. These causal relations may be described by a directed, task specific network which consists of activated brain regions as vertices and directed edges. The edges describe the causal relations. Inference of the task specific brain network from measurements like electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) is challenging, due to the low spatial resolution of the former and the low temporal resolution of the latter. Here, we present a simulation study investigating a possible combined analysis of simultaneously measured EEG and fMRI data to address the challenge specified above. A nonlinear state space model is used to distinguish between the underlying brain states and the (simulated) EEG/fMRI measurements. We make use of a modified unscented Kalman filter and a corresponding unscented smoother for the estimation of the underlying neural activity. Model parameters are estimated using an expectation-maximization algorithm, which exploits the partial linearity of our model. Inference of the brain network structure is then achieved using directed partial correlation, a measure for Granger causality. The results indicate that the convolution effect of the fMRI forward model imposes a big challenge for the parameter estimation and reduces the influence of the fMRI in combined EEG-fMRI models. It remains to be investigated whether other models or similar combinations of other modalities such as, e.g., EEG and magnetoencephalography can increase the profit of the promising idea of combining various modalities.     

Anticipating the unobserved: prediction of subclinical seizures

Subclinical seizures (SCS) have rarely been considered in the diagnosis and therapy of epilepsy and have not been systematically analyzed in studies on seizure prediction. Here, we investigate whether predictions of subclinical seizures are feasible and how their occurrence may affect the performance of prediction algorithms. Using the European database of long-term recordings of surface and invasive electroencephalography data, we analyzed the data from 21 patients with SCS, including in total 413 clinically manifest seizures (CS) and 3341 SCS. Based on the mean phase coherence we investigated the predictive performance of CS and SCS. The two types of seizures had similar prediction sensitivities. Significant performance was found considerably more often for SCS than for CS, especially for patients with invasive recordings. When analyzing false alarms triggered by predicting CS, a significant number of these false predictions were followed by SCS for 9 of 21 patients. Although currently observed prediction performance may not be deemed sufficient for clinical applications for the majority of the patients, it can be concluded that the prediction of SCS is feasible on a similar level as for CS and allows a prediction of more of the seizures impairing patients, possibly also reducing the number of false alarms that were in fact correct predictions of CS. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.     

Joining the benefits: Combining epileptic seizure prediction methods

Purpose: In recent years, a variety of methods developed in the field of linear and nonlinear time series analysis have been used to obtain reliable predictions of epileptic seizures. Because individual methods for seizure prediction so far have shown statistical significance but insufficient performance for clinical applications, we investigated possible improvements by combining algorithms capturing different aspects of electroencephalogram (EEG) dynamics. Methods: We applied the mean phase coherence and the dynamic similarity index to long‐term continuous intracranial EEG data. The predictive performance of both methods was assessed and statistically evaluated separately, as well as by using logical “AND” and “OR” combinations. Results: Used independently, either method resulted in a statistically significant prediction performance in only a few patients. Particularly the “AND” combination led to improved prediction performances, leading to an increase in sensitivity and/or specificity. For a maximum false prediction rate of 0.15/h, the mean sensitivity improved from about 25% for the individual methods to 43.2% for the “AND” and to 35.2% for the “OR” combination. Discussion: This study shows that combinations of prediction methods are promising new approaches to enhance seizure prediction performance considerably. It allows merging the individual benefits of prediction methods in a complementary manner. Because either sensitivity or specificity of seizure prediction methods can be improved depending on the needs of the desired clinical application, the combination opens a new window for future use in a clinical setting.     

Fatal illness associated with pulmonary hypertension in a neonate caused by intrauterine echovirus 11 infection

Nonpolio enterovirus (NPEV) infections are known to cause a wide range of illnesses in the neonatal period. In most cases, NPEV is presumed to be contracted during birth. Intrauterine NPEV infections occur infrequently. A case of intrauterine echovirus 11 infection with pneumonia, persistent pulmonary hypertension of the newborn, and purpura fulminans is presented.     

Potential of [<Superscript>11</Superscript>C]acetate for measuring myocardial blood flow: Studies in normal subjects and patients with hypertrophic cardiomyopathy

Background  

Measuring the rate of clearance of carbon-11 labelled acetate from myocardium using positron emission tomography (PET) is an accepted technique for noninvasively assessing myocardial oxygen consumption. Initial myocardial uptake of [¹¹C]acetate, however, is related to myocardial blood flow (MBF) and several tracer kinetic models for quantifying MBF using [¹¹C]acetate have been proposed. The objective of this study was to assess these models.     

Altered expression of immune-associated genes in first-trimester human decidua of pregnancies later complicated with hypertension or foetal growth restriction

During pregnancy the maternal immune system has to coordinate uterine spiral-artery remodelling, trophoblast invasion, and acceptance of the semi-allogenic fetus simultaneously. As dysregulation of the immune system is associated with adverse pregnancy outcomes, we analysed first-trimester deciduas of pregnancies for immune parameters in later complicated pregnancies. Higher IL6 and macrophage mRNA expression, and lower ratios of regulatory macrophages were found in first-trimester deciduas of pregnancies later complicated with pregnancy-induced hypertension. Lower Gata3 (Th2) mRNA expression was found in deciduas of pregnancies with later foetal growth restriction. Our results suggest that adverse pregnancy outcomes are associated with immunological disturbances in first-trimester deciduas.