Search

Objectives: We describe a patient suffering from Covid19-related acute respiratory distress syndrome (ARDS), highlighting the diagnostic role of the EEG in ICU. History: A Covid-19 patient undergoing mechanical ventilation due to related acute respiratory distress syndrome (ARDS), presented altered mental status in the ICU. Video-EEG revealed a focal monomorphic theta slowing in bilateral frontal-central regions. Concordant with the EEG localization, MRI showed abundant microbleeds located in bilateral white matter junction, various regions of corpus callosum and internal capsule, suggestive of Critical Illness-Associated Cerebral Microbleeds. CSF analysis excluded the presence of encephalitis, SARS-Cov2 RNA-PCR in CSF was negative. Clinical and biological picture was suggestive of cytokine release syndrome. Conclusion: This is the first reported case of Critical Illness-Associated Cerebral Microbleeds in the context of Covid-19. Knowledge of Covid-19 is still partial and acute neurological complications should be explored systematically. In our case, EEG helped to rule out non-convulsive status epilepticus, but revealed focal dysfunction, justifying further investigations.EEG plays a crucial role in these patients, allowing investigating the presence of focal or diffuse cerebral dysfunction. This is particularly helpful for Covid-19 patients in the ICU, where the neurological examination is challenging by the severity of the respiratory illness.

Abstract Objective Depersonalization refers to the sensation of being detached from one’s body, often associated with feelings of loss of control over one’s own body, actions, or thoughts. Derealization refers to the altered perception of one’s surroundings that is experienced as unreal. Although usually reported by psychiatric patients suffering from depression or anxiety, single case reports and small case series have described depersonalization‐ and derealization‐like symptoms in the context of epilepsy. Methods We investigated the brain mechanisms of ictal depersonalization– and derealization like symptoms by analyzing clinical and neuropsychological data as well as the epileptogenic zone based on a multimodal approach in a group of patients reporting depersonalization‐ (n = 9) and derealization‐like symptoms (n = 7), from a single presurgical epilepsy center with focal epilepsy. We compared them with a group of control patients with experiential phenomena due to temporal lobe epilepsy (n = 28). Results We show that all patients with ictal depersonalization‐like symptoms report altered self‐identification with their body and mostly suffer from frontal lobe epilepsy with the epileptogenic zone in the dorsal premotor cortex, while patients with derealization‐like symptoms suffer from temporal lobe epilepsy. This finding is supported by post‐ictal neuropsychological deficits, showing that depersonalization‐like symptoms were significantly more often associated with frontal lobe dysfunction as compared to the control patients and patients with derealization‐like symptoms. Conclusion We argue that depersonalization of epileptic origin constitutes a distinct disorder due to frontal lobe epilepsy. We discuss these findings with respect to earlier accounts of depersonalization and the recent concept of bodily self‐consciousness.

Summary Objective Electrical source imaging (ESI) is used increasingly to estimate the epileptogenic zone (EZ) in patients with epilepsy. Directed functional connectivity (DFC) coupled to ESI helps to better characterize epileptic networks, but studies on interictal activity have relied on high‐density recordings. We investigated the accuracy of ESI and DFC for localizing the EZ, based on low‐density clinical electroencephalography (EEG). Methods We selected patients with the following: (a) focal epilepsy, (b) interictal spikes on standard EEG, (c) either a focal structural lesion concordant with the electroclinical semiology or good postoperative outcome. In 34 patients (20 temporal lobe epilepsy [TLE], 14 extra‐TLE [ETLE]), we marked interictal spikes and estimated the cortical activity during each spike in 82 cortical regions using a patient‐specific head model and distributed linear inverse solution. DFC between brain regions was computed using Granger‐causal modeling followed by network topologic measures. The concordance with the presumed EZ at the sublobar level was computed using the epileptogenic lesion or the resected area in postoperative seizure‐free patients. Results ESI, summed outflow, and efficiency were concordant with the presumed EZ in 76% of the patients, whereas the clustering coefficient and betweenness centrality were concordant in 70% of patients. There was no significant difference between ESI and connectivity measures. In all measures, patients with TLE had a significantly higher (P

Epilepsy is regarded as a structural and functional network disorder, affecting around 50 million people worldwide. A correct disease diagnosis can lead to quicker medical action, preventing adverse effects. This paper reports the design of a classifier for epilepsy diagnosis in patients after a first ictal episode, using electroencephalogram (EEG) recordings. The dataset consists of resting-state EEG from 629 patients, of which 504 were retained for the study. The patient’s cohort exists out of 291 patients with epilepsy and 213 patients with other pathologies. The data were split into two sets: 80% training set and 20% test set. The extracted features from EEG included functional connectivity measures, graph measures, band powers and brain asymmetry ratios. Feature reduction was performed, and the models were trained using Machine Learning (ML) techniques. The models’ evaluation was performed with the area under the receiver operating characteristic curve (AUC). When focusing specifically on focal lesional epileptic patients, better results were obtained. This classification task was optimized using a 5-fold cross-validation, where SVM using PCA for feature reduction achieved an AUC of 0.730 ± 0.030. In the test set, the same model achieved 0.649 of AUC. The verified decrease is justified by the considerable diversity of pathologies in the cohort. An analysis of the selected features across tested models shows that functional connectivity and its graph measures have the most considerable predictive power, along with full-spectrum frequency-based features. To conclude, the proposed algorithms, with some refinement, can be of added value for doctors diagnosing epilepsy from EEG recordings after a suspected first seizure.

The article in the Annals of Neurology discusses a unique case of a patient developing a strong craving for Swiss chocolate following neurosurgery that resulted in a lesion in the orbito-frontal cortex. The patient's craving dissipated over time as the lesion resolved, with no recurrence of seizures or other neurological issues. The study highlights the role of the orbito-frontal cortex in craving and addiction, offering insights into potential treatment options for compulsive behaviors. The findings underscore the need for further research to better understand the neural correlates of cravings and addictions in humans. [Extracted from the article]

Diagnosis of epilepsy after a first unprovoked seizure is possible according to the guidelines by the International League Against Epilepsy, if the risk recurrence of a second unprovoked seizure is exceeding 60%. However, this cutoff constitutes only a proxy depending on the patients’ history, magnetic resonance imaging (MRI), and electroencephalography (EEG) findings but nevertheless also from the treating neurologists’ individual experience. In a Switzerland-wide observational study, we aim to recruit patients that were admitted to the emergency department with the referral diagnosis of a first and unprovoked seizure. We make use of optimized MRI protocols to identify potential structural epileptogenic lesions, introduce new imaging-based markers of epileptogenecity, and use most recent postprocessing methods as automatic morphometry, spike map analysis, and functional connectivity. With these diagnostic tools, we aim to segregate patients that present with epileptic seizures versus mimicks and non-epileptic seizures and stratify for every finding in MRI and EEG its predictive value for a second unprovoked seizure. These findings shall support neurologists to calculate and not only estimate the seizure recurrence rate in future.

This study aims to revitalise the concept of relational vulnerability in advancing the theory of managerial identity work. Drawing on 35 semi-structured interviews and 12 podcast interviews with top managers in Finland, we identify two entwined themes through which top managers practise identity work by negotiating their vulnerabilities in the workplace. Our study illustrates the embodied subtlety of relational vulnerabilities in top managers' identity negotiations by showing they can function as a tool for the managers' professional development. Our study contributes to the broader discussion on a more humane working life by investigating the ways in which top managers can foster workplaces in which vulnerabilities are used as a starting point for improvement rather than as a tool for disparaging the self and the others. This is an aspect of managerial identity work that deserves to be more profoundly considered in both academic debate and managerial practice. [ABSTRACT FROM AUTHOR]

This article provides an overview of surface sensitive X-ray techniques, explaining how scientists use X-rays to study the atomic and electronic structure of matter. It discusses the concept of surface sensitivity and the methods used to achieve it in X-ray scattering experiments. The article also introduces a new method called surface sensitive measurement of the Pair Distribution Function (sPDF) for studying the atomic structure of surface layers. It discusses mathematical representations of sample surfaces, the use of crystals in extracting surface scattering information, and the technique of X-ray reflectivity. The article outlines the requirements and preconditions for conducting surface sensitive X-ray experiments and discusses different setups and advancements in the field. It concludes by discussing future directions for surface sensitive X-ray scattering methods. [Extracted from the article]

Background: Electric and magnetic source imaging methods (ESI, MSI) estimate the location in the brain of the sources generating the interictal epileptiform discharges (II-ESI, II-MSI) and the ictal activity (IC-ESI, IC-MSI). These methods provide potentially valuable clinical information in the presurgical evaluation of patients with drug-resistant focal epilepsy, evaluated for surgical therapy. In spite of the significant technical advances in this field, and the numerous papers published on clinical validation of these methods, ESI and MSI are still underutilized in most epilepsy centers performing a presurgical evaluation. Our goal was to review and summarize the published evidence on the diagnostic accuracy of interictal and ictal ESI and MSI in epilepsy surgery.Methods: We searched the literature for papers on ESI and MSI that specified the diagnostic reference standard as the site of resection and the postoperative outcome (seizure-freedom). We extracted data from the selected studies, to calculate the diagnostic accuracy measures.Results: Our search resulted in 797 studies; 48 studies fulfilled the selection criteria (25 ESI and 23 MSI studies), providing data from 1,152 operated patients (515 for II-ESI, 440 for II-MSI, 159 for IC-ESI, and 38 for IC-MSI). The sensitivity of source imaging methods was between 74 and 90% (highest for IC-ESI). The specificity of the source imaging methods was between 20 and 54% (highest for II-MSI). The overall accuracy was between 50 and 75% (highest for IC-ESI). Diagnostic Odds Ratio was between 0.8 (IC-MSI) and 4.02–7.9 (II-ESI < II-MSI < IC-ESI).Conclusions: Our systematic review and meta-analysis provides evidence for the accuracy of source imaging in presurgical evaluation of patients with drug-resistant focal epilepsy. These methods have high sensitivity (up to 90%) and diagnostic odds ratio (up to 7.9), but the specificity is lower (up to 54%). ESI and MSI should be included in the multimodal presurgical evaluation.