Aufruf zu einer rascheren Förderung der jüdischen Angelegenheiten im Vaterlande

(von Anton Rée)

Kurze Nachricht von dem falschen Messias Sabbathai Zebhi und den neulich seinetwegen in Hamburg und Altena entstandenen Bewegungen zu besserer Beurtheilung derer bisher in den Zeitungen und andern Schriften davon bekandt gewordenen Erzählungen

aufgesetzt von Carl Anton

Beziehungen auf Grundsätze des orthodoxen Judenthums : 2. Antwortschreiben an Salomon

von Ant. Theod. Harmann

Der Judenhaß und der Sozialismus

von Anton Fendrich

Seizure termination

A better understanding of the mechanisms by which most focal epileptic seizures stop spontaneously within a few minutes would be of highest importance, because they could potentially help to improve existing and develop novel therapeutic measures for seizure control. Studies devoted to unraveling mechanisms of seizure termination often take one of the two following approaches. The first approach focuses on metabolic mechanisms such as ionic concentrations, acidity, or neuromodulator release, studying how they are dependent on, and in turn affect changes of neuronal activity. The second approach uses quantitative tools to derive functional networks from electrophysiological recordings and analyzes these networks with mathematical methods, without focusing on actual details of cell biology. In this chapter, we summarize key results obtained by both of these approaches and attempt to show that they are complementary and equally necessary in our aim to gain a better understanding of seizure termination.

Improved Localization of Implanted Subdural Electrode Contacts on MRI Using an Elastic Image Fusion Algorithm in Invasive EEG Recording

BACKGROUND: Accurate projection of implanted subdural electrode contacts in presurgical evaluation of pharmacoresistant epilepsy cases by invasive EEG is highly relevant. Linear fusion of CT and MRI images may display the contacts in the wrong position due to brain shift effects. OBJECTIVE: A retrospective study in five patients with pharmacoresistant epilepsy was performed to evaluate whether an elastic image fusion algorithm can provide a more accurate projection of the electrode contacts on the pre-implantation MRI as compared to linear fusion. METHODS: An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF), and a standard linear fusion algorithm (LF) were used on preoperative MRI and post-implantation CT scans. Vertical correction of virtual contact positions, total virtual contact shift, corrections of midline shift and brain shifts due to pneumencephalus were measured. RESULTS: Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7mm (SD 1.25) was corrected to 0.4mm (SD 0.8) after AEF and to 0.0mm (SD 0) after GEF. Median virtual distances between contacts and cortical surface were corrected by a significant amount, from 2.3mm after LF to 0.0mm after AEF and GEF (p<.001). Mean total relative corrections of 3.1 mm (SD 1.85) after AEF and 3.0mm (SD 1.77) after GEF were achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumencephalus. CONCLUSION: The technique provided a clear improvement in fusion of pre- and post-implantation scans, although the accuracy is difficult to evaluate.

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.

Focal hemodynamic patterns of status epilepticus detected by susceptibility weighted imaging (SWI).

OBJECTIVE To investigate pathological findings in the susceptibility weighted imaging (SWI) of patients experiencing convulsive (CSE) or non-convulsive status epilepticus (NCSE) with focal hyperperfusion in the acute setting. METHODS Twelve patients (six with NCSE confirmed by electroencephalogram (EEG) and six patients with CSE with seizure event clinically diagnosed) underwent MRI in this acute setting (mean time between onset of symptoms and MRI was 3 h 8 min), including SWI, dynamic susceptibility contrast MR imaging (DSC) and diffusion-weighted imaging (DWI). MRI sequences were retrospectively evaluated and compared with EEG findings (10/12 patients), and clinical symptoms. RESULTS Twelve out of 12 (100 %) patients showed a focal parenchymal area with pseudo-narrowed cortical veins on SWI, associated with focal hyperperfused areas (increased cerebral blood flow (CBF) and mean transit time (MTT) shortening), and cortical DWI restriction in 6/12 patients (50 %). Additionally, these areas were associated with ictal or postical EEG patterns in 8/10 patients (80 %). Most frequent acute clinical findings were aphasia and/or hemiparesis in eight patients, and all of them showed pseudo-narrowed veins in those parenchymal areas responsible for these symptoms. CONCLUSION In this study series with CSE and NCSE patients, SWI showed focally pseudo-narrowed cortical veins in hyperperfused and ictal parenchymal areas. Therefore, SWI might have the potential to identify an ictal region in CSE/NCSE. KEY POINTS • The focal ictal brain regions show hyperperfusion in DSC MR-perfusion imaging. • SWI shows focally diminished cortical veins in hyperperfused ictal regions. • SWI has the potential to identify a focal ictal region in CSE/NCSE.

Juden und Deutsche : ein Resumé

von Anton Kuh

Das ‹Evangelium der Natur› oder: Was hat der Pelikan mit Christus zu tun?, Eine theologische Vortragsreihe. Begleitprogramm zu «Sprachen, Schriften, Zeichen»

Anhand einer über 1000 Jahre alten Berner Handschrift tauchen die Besucherinnen und Besucher sinnlich in die Welt christlicher Natursymbolik ein (Poster).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).